[{"data":1,"prerenderedAt":2984},["ShallowReactive",2],{"cell-json-zabt-gj9b-6wx3-06wj":3},{"@context":4,"@id":5,"@type":6,"schema:name":7,"schema:manufacturer":8,"hasPositiveElectrode":12,"hasCase":16,"hasProperty":19,"schema:subjectOf":87,"schema:creator":2980,"schema:version":2982,"schema:dateModified":2983},"https:\u002F\u002Fw3id.org\u002Femmo\u002Fdomain\u002Fbattery\u002Fcontext","https:\u002F\u002Fw3id.org\u002Fbattinfo\u002Fspec\u002Fzabt-gj9b-6wx3-06wj","BatteryCell","18650HG2",{"@type":9,"schema:name":10,"schema:sameAs":11},"schema:Organization","LG Chem","https:\u002F\u002Fwww.wikidata.org\u002Fentity\u002FQ486976",{"@type":13,"hasActiveMaterial":14},"PositiveElectrode",{"@type":15},"LithiumNickelManganeseCobaltOxide",[17],{"@type":18},"R18650",[20,28,33,39,44,49,55,60,66,71,76,82],{"@type":21,"hasNumericalPart":24,"hasMeasurementUnit":27},[22,23],"RatedCapacity","ConventionalProperty",{"@type":25,"hasNumericalValue":26},"RealData",3,"emmo:AmpereHour",{"@type":29,"hasNumericalPart":31},[30,23],"CycleLife",{"@type":25,"hasNumericalValue":32},60,{"@type":34,"hasNumericalPart":36,"hasMeasurementUnit":38},[35,23],"NominalVoltage",{"@type":25,"hasNumericalValue":37},3.6,"emmo:Volt",{"@type":40,"hasNumericalPart":42,"hasMeasurementUnit":38},[41,23],"UpperVoltageLimit",{"@type":25,"hasNumericalValue":43},4.2,{"@type":45,"hasNumericalPart":47,"hasMeasurementUnit":38},[46,23],"LowerVoltageLimit",{"@type":25,"hasNumericalValue":48},2,{"@type":50,"hasNumericalPart":52,"hasMeasurementUnit":54},[51,23],"DischargingCurrent",{"@type":25,"hasNumericalValue":53},0.6,"emmo:Ampere",{"@type":56,"hasNumericalPart":58,"hasMeasurementUnit":54},[57,23],"MaximumContinuousDischargingCurrent",{"@type":25,"hasNumericalValue":59},20,{"@type":61,"hasNumericalPart":63,"hasMeasurementUnit":65},[62,23],"Mass",{"@type":25,"hasNumericalValue":64},0.048,"emmo:Kilogram",{"@type":67,"hasNumericalPart":69,"hasMeasurementUnit":54},[68,23],"ChargingCurrent",{"@type":25,"hasNumericalValue":70},1.5,{"@type":72,"hasNumericalPart":74,"hasMeasurementUnit":54},[73,23],"MaximumContinuousChargingCurrent",{"@type":25,"hasNumericalValue":75},4,{"@type":77,"hasNumericalPart":79,"hasMeasurementUnit":81},[78,23],"Height",{"@type":25,"hasNumericalValue":80},0.065,"emmo:Metre",{"@type":83,"hasNumericalPart":85,"hasMeasurementUnit":81},[84,23],"Diameter",{"@type":25,"hasNumericalValue":86},0.0183,[88,102,111,123,135,147,157,168,178,186,194,201,209,216,227,234,243,251,260,267,283,295,303,313,322,330,338,344,354,363,372,380,390,399,411,419,425,435,445,460,472,490,503,509,518,528,535,544,551,560,566,575,581,587,597,607,620,631,641,648,660,671,677,687,694,702,709,718,724,732,742,753,760,767,776,784,793,802,809,820,831,844,850,861,867,872,880,885,892,902,908,914,920,928,936,946,954,962,967,975,987,992,998,1009,1016,1028,1037,1046,1059,1070,1076,1085,1092,1101,1111,1120,1132,1143,1153,1163,1179,1186,1193,1201,1210,1240,1248,1255,1261,1269,1276,1282,1287,1295,1303,1312,1317,1329,1337,1348,1353,1361,1369,1377,1384,1394,1402,1409,1421,1430,1438,1448,1458,1468,1481,1492,1500,1509,1517,1528,1539,1549,1559,1568,1579,1589,1602,1608,1617,1625,1632,1642,1648,1661,1672,1685,1694,1703,1716,1726,1732,1740,1752,1757,1767,1775,1785,1795,1803,1819,1832,1837,1844,1855,1865,1873,1881,1894,1903,1912,1919,1927,1935,1944,1957,1968,1978,1984,1993,2004,2015,2024,2033,2045,2056,2068,2077,2085,2093,2102,2110,2116,2123,2136,2147,2155,2165,2178,2185,2190,2196,2206,2212,2215,2224,2232,2243,2254,2262,2269,2278,2288,2296,2312,2325,2337,2346,2356,2368,2374,2384,2391,2402,2413,2423,2430,2441,2450,2463,2475,2481,2488,2497,2505,2513,2522,2527,2538,2548,2558,2569,2578,2584,2589,2594,2600,2604,2611,2615,2630,2638,2648,2659,2672,2681,2690,2701,2708,2714,2721,2726,2733,2739,2746,2753,2760,2770,2783,2791,2798,2810,2823,2831,2838,2843,2853,2860,2868,2875,2885,2891,2900,2906,2915,2924,2929,2939,2948,2957,2965,2971],{"@type":89,"@id":90,"schema:additionalType":91,"schema:identifier":92,"schema:headline":93,"schema:author":94,"schema:datePublished":100,"schema:isPartOf":101},"schema:ScholarlyArticle","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fcpe.70644","USED","10.1002\u002Fcpe.70644","SOC Prediction Model for Lithium‐Ion Batteries Based on Improved CEEMD With Adaptive Noise and Stacking Ensemble Learning",[95,96,97,98,99],"Song‐Bo Zhang","Si‐Wen Zhang","Jie‐Sheng Wang","Jun‐Yu Lu","Jia-Hui Zhao",2026,"Concurrency and Computation Practice and Experience",{"@type":89,"@id":103,"schema:additionalType":91,"schema:identifier":104,"schema:headline":105,"schema:author":106,"schema:datePublished":100,"schema:isPartOf":110},"https:\u002F\u002Fdoi.org\u002F10.1002\u002Fente.70530","10.1002\u002Fente.70530","A Hybrid Deep Learning Framework for Lithium‐Ion Battery State of Charge Estimation Combining an Attention‐Enhanced Gated Recurrent Unit with Residual Correction",[107,108,109],"Chaogui Deng","Zhiguo Lei","Kehao Li","Energy Technology",{"@type":89,"@id":112,"schema:additionalType":91,"schema:identifier":113,"schema:headline":114,"schema:author":115,"schema:datePublished":100,"schema:isPartOf":122},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compchemeng.2026.109720","10.1016\u002Fj.compchemeng.2026.109720","State of charge prediction for lithium-ion batteries under complex operating conditions and full temperature ranges via VMD-PatchTST",[116,117,118,119,120,121],"Jianwei Xu","Long Chen","Shujie Wu","Jinge Zheng","Hongliang Sun","Aziguli Wulamu","Computers & Chemical Engineering",{"@type":89,"@id":124,"schema:additionalType":91,"schema:identifier":125,"schema:headline":126,"schema:author":127,"schema:datePublished":100,"schema:isPartOf":134},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.csite.2026.108210","10.1016\u002Fj.csite.2026.108210","Intelligent architecture design and tuning of deep learning model for precise EV battery state-of-charge estimation",[128,129,130,131,132,133],"Hussein Shutari","M.H. Mohamed Hariri","Zaid Ahmed Shamsan","Abdullah S. Algamili","Yosef T. Aladadi","Sami Abdulla Mohsen Saleh","Case Studies in Thermal Engineering",{"@type":89,"@id":136,"schema:additionalType":91,"schema:identifier":137,"schema:headline":138,"schema:author":139,"schema:datePublished":100,"schema:isPartOf":146},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecmx.2026.101926","10.1016\u002Fj.ecmx.2026.101926","A unified disturbance rejection design framework for robust reduced-coupling state estimation in lithium-ion batteries",[140,141,142,143,144,145],"Shuo Zhang","Xijian Lin","Xinghao Wang","Shiyi Fu","Haoda Xi","Dianxun Xiao","Energy Conversion and Management X",{"@type":89,"@id":148,"schema:additionalType":91,"schema:identifier":149,"schema:headline":150,"schema:author":151,"schema:datePublished":100,"schema:isPartOf":156},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.egyr.2026.109544","10.1016\u002Fj.egyr.2026.109544","Adaptive battery SOC estimation: Temporal attention-enhanced BiLSTM and quantized model comparison for scalable edge solutions",[152,153,154,155],"Opy Das","Muhammad Hamza Zafar","Souman Rudra","Filippo Sanfilippo","Energy Reports",{"@type":89,"@id":158,"schema:additionalType":91,"schema:identifier":159,"schema:headline":160,"schema:author":161,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.119996","10.1016\u002Fj.est.2025.119996","An end-to-end dual-domain attention fusion network with evidential uncertainty for battery state of charge estimation",[162,163,164,165,166],"Zhou Ping Wu","Baile Xu","Fuguang Wen","Jian Ying Zhao","Furao Shen","Journal of Energy Storage",{"@type":89,"@id":169,"schema:additionalType":91,"schema:identifier":170,"schema:headline":171,"schema:author":172,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.120262","10.1016\u002Fj.est.2025.120262","How long could EV batteries last if their thermal management is optimized?",[173,174,175,176,177],"Mathis Boutrouelle","Rémy Panariello","Yvan Reynier","Eric Mayousse","Sébastien Martinet",{"@type":89,"@id":179,"schema:additionalType":91,"schema:identifier":180,"schema:headline":181,"schema:author":182,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.120618","10.1016\u002Fj.est.2026.120618","Real-time data reconstruction-based joint estimation of state-of-charge and state-of-health of lithium-ion batteries using quantitative feature informed deep learning framework",[183,184,185],"Md. Shoaib Akhter Rafi","Muhammad Anisuzzaman Talukder","Md. Kamrul Hasan",{"@type":89,"@id":187,"schema:additionalType":91,"schema:identifier":188,"schema:headline":189,"schema:author":190,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.120737","10.1016\u002Fj.est.2026.120737","A Beta-Gaussian deep state-space model for unsupervised multi-domain battery state-of-charge estimation",[191,192,193],"Rui Yang","Ángel F. García-Fernández","Che–Rung Lee",{"@type":89,"@id":195,"schema:additionalType":91,"schema:identifier":196,"schema:headline":197,"schema:author":198,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.121154","10.1016\u002Fj.est.2026.121154","Hybrid long short-term memory network and Bayesian adaptive extended Kalman filter approach for reliable lithium-ion battery state-of-charge estimation in electric vehicles",[199,200],"Sucharita Barik","B. Saravanan",{"@type":89,"@id":202,"schema:additionalType":91,"schema:identifier":203,"schema:headline":204,"schema:author":205,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.122235","10.1016\u002Fj.est.2026.122235","State-of-charge estimation of batteries using parameterized physics-informed neural networks",[206,207,208],"Yu Seok Jang","Y. T. Kim","Jinwoo Kim",{"@type":89,"@id":210,"schema:additionalType":91,"schema:identifier":211,"schema:headline":212,"schema:author":213,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.123296","10.1016\u002Fj.est.2026.123296","A hybrid open-circuit-voltage and coulomb-counting method for a battery management system with integrated hardware and firmware design for consumer electronics",[214,215],"Rohan Kumar","Kunwar Aditya",{"@type":89,"@id":217,"schema:additionalType":91,"schema:identifier":218,"schema:headline":219,"schema:author":220,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.123651","10.1016\u002Fj.est.2026.123651","Cross-chemistry state-of-health estimation for lithium-ion batteries via local temporal patches and global dependency modeling",[221,222,223,224,225,226],"Misheng Cai","Yuqi Li","Dapai Shi","Andrew F. Burke","Stephen J. Harris","Jingyuan Zhao",{"@type":89,"@id":228,"schema:additionalType":91,"schema:identifier":229,"schema:headline":230,"schema:author":231,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.124108","10.1016\u002Fj.est.2026.124108","State-of-charge estimation of lithium-ion batteries under low-temperature conditions using an extended Kalman-based particle filter with guided sampling",[232,233],"Mirghni Mohammed Mahmoud GAFFER","Hayri Arabacı",{"@type":89,"@id":235,"schema:additionalType":91,"schema:identifier":236,"schema:headline":237,"schema:author":238,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.124115","10.1016\u002Fj.est.2026.124115","Real-time state estimation of electric vehicle batteries using secretary bird optimization based unscented Kalman filter",[239,240,241,242],"Sathis Kumar Murugesan","Muhilan Paramasivam","Maheshwari Adaikkappan","Balamurugan Sankarapandian",{"@type":89,"@id":244,"schema:additionalType":91,"schema:identifier":245,"schema:headline":246,"schema:author":247,"schema:datePublished":100,"schema:isPartOf":250},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.fuel.2026.140727","10.1016\u002Fj.fuel.2026.140727","A hybrid extended kalman filter and feed-forward neural network architecture for robust state of charge estimation of lithium-ion batteries",[248,249],"Mansur Mustapha","Arunachalam Sundaram","Fuel",{"@type":89,"@id":252,"schema:additionalType":91,"schema:identifier":253,"schema:headline":254,"schema:author":255,"schema:datePublished":100,"schema:isPartOf":259},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jprocont.2026.103758","10.1016\u002Fj.jprocont.2026.103758","Electric vehicle range extension using nonlinear MPC based active battery cell balancing",[256,257,258],"Afaq Ahmed","Ali Arshad Uppal","Qadeer Ahmed","Journal of Process Control",{"@type":89,"@id":261,"schema:additionalType":91,"schema:identifier":262,"schema:headline":263,"schema:author":264,"schema:datePublished":100,"schema:isPartOf":266},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.nxmate.2026.101815","10.1016\u002Fj.nxmate.2026.101815","Data driven state of charge estimation for lithium ion batteries: Evaluating the influence of averaged input features using machine learning",[265],"Mohamed Abdul Basith Mydeen Pitchai","Next Materials",{"@type":89,"@id":268,"schema:additionalType":91,"schema:identifier":269,"schema:headline":270,"schema:author":271,"schema:datePublished":100,"schema:isPartOf":282},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.powera.2026.100210","10.1016\u002Fj.powera.2026.100210","Effects of high-temperature preconditioning on Li plating during low-temperature cycling of the COTS LG Chem HG2 cell",[272,273,274,275,276,277,278,279,280,281],"Lukas Lehnert","Keith B. Chin","Frederick C. Krause","John P. Ruiz","Simon Hein","John Bescup","Gil Garteiz","Arnulf Latz","Erik J. Brandon","Birger Horstmann","Journal of Power Sources Advances",{"@type":89,"@id":284,"schema:additionalType":91,"schema:identifier":285,"schema:headline":286,"schema:author":287,"schema:datePublished":100,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-49020-1","10.1038\u002Fs41598-026-49020-1","Generating imperceptible adversarial examples via low-frequency aware transfer attacks on battery management systems",[288,289,290,291,292,293],"Kyeongseo Min","Yeseo Joo","Jiho Hong","Hoki Kim","Sangho Lee","Youngdoo Son","Scientific Reports",{"@type":89,"@id":296,"schema:additionalType":91,"schema:identifier":297,"schema:headline":298,"schema:author":299,"schema:datePublished":100,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-52574-9","10.1038\u002Fs41598-026-52574-9","Optimal hidden layer size for Levenberg–Marquardt based neural network for SoC estimation under different temperature conditions",[300,301,302],"Nadia Chaker","Radhia Jebahi","Helmi Aloui",{"@type":89,"@id":304,"schema:additionalType":91,"schema:identifier":305,"schema:headline":306,"schema:author":307,"schema:datePublished":100,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2026.3695274","10.1109\u002Faccess.2026.3695274","Aging-Aware Hypernetwork LSTM With Multi-Constraint Physics-Informed Neural Network (AAH-LSTM-PINN) for Lithium-Ion Battery SOC Estimation",[308,309,310,311],"Awang Abdul Hadi Isa","Sheik Mohammed Sulthan","Muhammad Norfauzi Dani","Tan Soon Jiann","IEEE Access",{"@type":89,"@id":314,"schema:additionalType":91,"schema:identifier":315,"schema:headline":316,"schema:author":317,"schema:datePublished":100},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faide69088.2026.11544441","10.1109\u002Faide69088.2026.11544441","An accurate and computationally efficient SOC estimation in EV batteries using enhanced Deep Neural Networks",[318,319,320,321],"Tejaswini S","Chandrashekar M Patil","U Parvitha","Manya Ashvitha M",{"@type":89,"@id":323,"schema:additionalType":91,"schema:identifier":324,"schema:headline":325,"schema:author":326,"schema:datePublished":100},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Firaset68627.2026.11538536","10.1109\u002Firaset68627.2026.11538536","LSTM-based State of Charge Estimation for Electric Vehicle Battery Management Systems under Varying Temperature Conditions",[327,328,329],"Ayda BOUKHANCHA","Mohamed Bendaoud","Najib Essounbouli",{"@type":89,"@id":331,"schema:additionalType":91,"schema:identifier":332,"schema:headline":333,"schema:author":334,"schema:datePublished":100},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Freepe69046.2026.11481446","10.1109\u002Freepe69046.2026.11481446","Battling the Noise: Robust Machine Learning for Lithium-Ion Battery SoC Estimation",[335,336,337],"Alexei A. Druzhinin","Daniel Lisnovetski","Aleksei A. Matskevich",{"@type":89,"@id":339,"schema:additionalType":91,"schema:identifier":340,"schema:headline":341,"schema:author":342,"schema:datePublished":100,"schema:isPartOf":343},"https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-9057091\u002Fv1","10.21203\u002Frs.3.rs-9057091\u002Fv1","A Comparative Evaluation of Filters Applicable to Low-Complexity Processors in the Model-Based State-of-Charge Estimation of Lithium-Ion Batteries",[232,233],"Research Square",{"@type":89,"@id":345,"schema:additionalType":91,"schema:identifier":346,"schema:headline":347,"schema:author":348,"schema:datePublished":100,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries12010033","10.3390\u002Fbatteries12010033","Advanced Battery Modeling Framework for Enhanced Power and Energy State Estimation with Experimental Validation",[349,350,351,352],"Nemanja Mišljenović","Matej Žnidarec","Sanja Kelemen","Goran Knežević","Batteries",{"@type":89,"@id":355,"schema:additionalType":91,"schema:identifier":356,"schema:headline":357,"schema:author":358,"schema:datePublished":100,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries12020053","10.3390\u002Fbatteries12020053","Experimental Assessment of Multi-Domain Degradation-Based Risk in NMC Lithium-Ion Batteries Under Combined Thermal and Electrical Operating Conditions",[359,360,361,362],"Ziad M. Ali","Foad H. Gandoman","Faisal Aldawsari","Shady Abdel Aleem",{"@type":89,"@id":364,"schema:additionalType":91,"schema:identifier":365,"schema:headline":366,"schema:author":367,"schema:datePublished":100,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries12060185","10.3390\u002Fbatteries12060185","Toward Generalizable State-of-Charge Prediction of Lithium-Ion Batteries Using Deep Learning and Real-World Data",[368,369,370,371],"Montaha Khedhiri","Rim Slama","Eduardo Redondo-Iglesias","Rochdi Trigui",{"@type":89,"@id":373,"schema:additionalType":91,"schema:identifier":374,"schema:headline":375,"schema:author":376,"schema:datePublished":100,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries12080314","10.3390\u002Fbatteries12080314","Reconciling Manufacturer Claims with Measured Degradation in Commercial Lithium-Ion Cells: A Provenance-Aware Knowledge Graph with Coverage-Gated Abstention",[377,378,379],"Alexandru Lecu","Lezan Hawizy","Adrian Petru Groza",{"@type":89,"@id":381,"schema:additionalType":91,"schema:identifier":382,"schema:headline":383,"schema:author":384,"schema:datePublished":100,"schema:isPartOf":389},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectronics15030704","10.3390\u002Felectronics15030704","Lightweight 1D-CNN-Based Battery State-of-Charge Estimation and Hardware Development",[385,386,387,388],"Seungbum Kang","Yoonjae Lee","Gahyeon Jang","Seongsoo Lee","Electronics",{"@type":89,"@id":391,"schema:additionalType":91,"schema:identifier":392,"schema:headline":393,"schema:author":394,"schema:datePublished":397,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen18133436","10.3390\u002Fen18133436","Optimization and Estimation of the State of Charge of Lithium-Ion Batteries for Electric Vehicles",[395,396],"Luc Vivien Assiene Mouodo","Petros J. Axaopoulos",2025,"Energies",{"@type":89,"@id":400,"schema:additionalType":91,"schema:identifier":401,"schema:headline":402,"schema:author":403,"schema:datePublished":397,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-025-00482-9","10.1038\u002Fs41598-025-00482-9","A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation",[404,405,406,407,408,409,410],"Kaihua Yao","Xinyu Yan","Xiling Mao","Mengwei Li","Xiao Li","Ziyu Lian","Yuxiang Han",{"@type":89,"@id":412,"schema:additionalType":91,"schema:identifier":413,"schema:headline":414,"schema:author":415,"schema:datePublished":397,"schema:isPartOf":418},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40998-025-00872-9","10.1007\u002Fs40998-025-00872-9","Ensemble-Optimized Learning for Accurate Remaining Useful Life Estimation of Lithium-Ion Batteries in Electric Vehicles",[416,417],"J. Jeha","M. Shunmuga Priyan","Iranian Journal of Science and Technology Transactions of Electrical Engineering",{"@type":89,"@id":420,"schema:additionalType":91,"schema:identifier":421,"schema:headline":422,"schema:author":423,"schema:datePublished":397,"schema:isPartOf":424},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11581-025-06889-8","10.1007\u002Fs11581-025-06889-8","A comparative study of deep learning architectures for Li-ion battery SoC estimation under varying thermal conditions: Electric vehicle application",[301,300,302],"Ionics",{"@type":89,"@id":426,"schema:additionalType":91,"schema:identifier":427,"schema:headline":428,"schema:author":429,"schema:datePublished":397,"schema:isPartOf":434},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fwevj16030168","10.3390\u002Fwevj16030168","LSTM-Based State-of-Charge Estimation and User Interface Development for Lithium-Ion Battery Management",[430,431,432,433],"Abdellah Benallal","Nawal Cheggaga","Amine Hebib","Adrian Ilinca","World Electric Vehicle Journal",{"@type":89,"@id":436,"schema:additionalType":91,"schema:identifier":437,"schema:headline":438,"schema:author":439,"schema:datePublished":397,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fadf66f","10.1149\u002F1945-7111\u002Fadf66f","Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs",[440,441,442,443],"Surya Mitra Ayalasomayajula","Yuliya Preger","Jacob A. Mueller","Srikanth Allu","Journal of The Electrochemical Society",{"@type":89,"@id":446,"schema:additionalType":91,"schema:identifier":447,"schema:headline":448,"schema:author":449,"schema:datePublished":397,"schema:isPartOf":459},"https:\u002F\u002Fdoi.org\u002F10.1002\u002Feng2.70346","10.1002\u002Feng2.70346","Real‐Time Parameter Identification and State of Charge Estimation of Electric Vehicle Batteries",[450,451,452,453,454,455,456,457,458],"A. Maheshwari","S. Nageswari","R. Palanisamy","B. Ramaswamy Karthikeyan","Mohamed Metwally Mahmoud","Daniel Eutyche Mbadjoun Wapet","Ali M. El‐Rifaie","Ezzeddine Touti","Ahmed I. Omar","Engineering Reports",{"@type":89,"@id":461,"schema:additionalType":91,"schema:identifier":462,"schema:headline":463,"schema:author":464,"schema:datePublished":397,"schema:isPartOf":471},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.apenergy.2025.125736","10.1016\u002Fj.apenergy.2025.125736","Estimate state of charge in lithium-ion batteries with unknown data",[465,466,467,468,469,470],"Jingwei Hu","Xiaodong Li","Fang Zheng","Jun Cheng","Longqiang Yi","Zhihong Zhang","Applied Energy",{"@type":89,"@id":473,"schema:additionalType":91,"schema:identifier":474,"schema:headline":475,"schema:author":476,"schema:datePublished":397,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fadc50f","10.1149\u002F1945-7111\u002Fadc50f","Advanced Multi-Cell Housing Designs to Prevent Thermal Runaway Propagation in Lithium-Ion Batteries",[477,478,479,480,481,482,483,484,485,486,487,488,489],"Rengaswamy Srinivasan","Bliss G. Carkhuff","Hicham Alkandry","Avrami Rakovsky","David N. Owenby","Nathan J. Fairbanks","Daniel Ayoub","Brendan P. Croom","Jonathan Jones","Paul J. Biermann","Russell Paul Cain","Luke J. Currano","Plamen A. Demirev",{"@type":89,"@id":491,"schema:additionalType":91,"schema:identifier":492,"schema:headline":493,"schema:author":494,"schema:datePublished":397,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2025.139320","10.1016\u002Fj.energy.2025.139320","Bidirectional Mamba network with multi-scale feature fusion and sparse-channel mixture of experts for battery state of charge estimation",[495,496,497,498,499,500,501],"Yun Wang","Yuhao Li","Ziyang Zhang","Peihua Yu","Yifen Li","Bo Liu","Runmin Zou","Energy",{"@type":89,"@id":504,"schema:additionalType":91,"schema:identifier":505,"schema:headline":506,"schema:author":507,"schema:datePublished":397,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen18236192","10.3390\u002Fen18236192","Enhanced Lithium-Ion Battery State-of-Charge Estimation via Akima–Savitzky–Golay OCV-SOC Mapping Reconstruction and Bayesian-Optimized Adaptive Extended Kalman Filter",[308,309,310,508],"Soon Jiann Tan",{"@type":89,"@id":510,"schema:additionalType":91,"schema:identifier":511,"schema:headline":512,"schema:author":513,"schema:datePublished":397,"schema:isPartOf":517},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fpr13113559","10.3390\u002Fpr13113559","State of Charge Estimation for Lithium-Ion Batteries: An Online Method Combining Deep Neural Network and Adaptive Kalman Filter",[514,515,516],"Hongwen Xu","Feng Zhao","Yun Rui Guo","Processes",{"@type":89,"@id":519,"schema:additionalType":91,"schema:identifier":520,"schema:headline":521,"schema:author":522,"schema:datePublished":397,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen18102459","10.3390\u002Fen18102459","Robust Data-Driven State of Health Estimation of Lithium-Ion Batteries Based on Reconstructed Signals",[523,524,525,526,527],"Byron Alejandro Acuña Acurio","Diana Estefanía Chérrez Barragán","Juan Carlos Rodríguez","Felipe Grijalva","Luiz Carlos Pereira da Silva",{"@type":89,"@id":529,"schema:additionalType":91,"schema:identifier":530,"schema:headline":531,"schema:author":532,"schema:datePublished":397,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fadd777","10.1149\u002F1945-7111\u002Fadd777","Impact of Module Configuration on Lithium-Ion Battery Performance and Degradation: Part I. Energy Throughput, Voltage Spread, and Current Distribution",[441,442,533,443,534],"Armando Fresquez","Chaz Rich",{"@type":89,"@id":536,"schema:additionalType":91,"schema:identifier":537,"schema:headline":538,"schema:author":539,"schema:datePublished":397,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2025.139288","10.1016\u002Fj.energy.2025.139288","Cross-domain battery SOH and RUL estimation via Domain-Adaptive Transformer",[540,541,542,543],"Bo Zhu","Jia Li","Quan-Ke Pan","Hui Zhang",{"@type":89,"@id":545,"schema:additionalType":91,"schema:identifier":546,"schema:headline":547,"schema:author":548,"schema:datePublished":397,"schema:isPartOf":424},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11581-025-06846-5","10.1007\u002Fs11581-025-06846-5","Transfer learning for state of charge estimation across batteries and chemistries: a lightweight, physics-guided LSTM with regime-aware temporal attention and staged adaptation",[549,550],"Ebubekir Buğra Özarslan","Senem Kursun",{"@type":89,"@id":552,"schema:additionalType":91,"schema:identifier":553,"schema:headline":554,"schema:author":555,"schema:datePublished":397,"schema:isPartOf":559},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compeleceng.2025.110907","10.1016\u002Fj.compeleceng.2025.110907","Joint estimation of the state-of-charge and state-of-energy of lithium-ion batteries under diverse temperatures and discharging conditions using a data-driven model",[556,557,558],"B Chen","Jujin Pan","Yonggui Liu","Computers & Electrical Engineering",{"@type":89,"@id":561,"schema:additionalType":91,"schema:identifier":562,"schema:headline":563,"schema:author":564,"schema:datePublished":397,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2025.139524","10.1016\u002Fj.energy.2025.139524","Robust state-of-charge estimation for lithium-ion batteries: A high-order lumped disturbance compensation approach with a simple tuning strategy",[565,141,142,144,145],"S. F. Zhang",{"@type":89,"@id":567,"schema:additionalType":91,"schema:identifier":568,"schema:headline":569,"schema:author":570,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.115437","10.1016\u002Fj.est.2025.115437","BiLSTM-AKEF hybrid driven lithium-ion battery SOC prediction model based on CEEMD with different distributions noises",[571,97,572,497,573,574],"Xiaotian Wang","Songbo Zhang","Yi-Xuan Li","Xun Liu",{"@type":89,"@id":576,"schema:additionalType":91,"schema:identifier":577,"schema:headline":578,"schema:author":579,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.115833","10.1016\u002Fj.est.2025.115833","State of charge (SOC) estimation in electric vehicle (EV) battery management systems using ensemble methods and neural networks",[580],"Edward Ositadinma Ofoegbu",{"@type":89,"@id":582,"schema:additionalType":91,"schema:identifier":583,"schema:headline":584,"schema:author":585,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.116202","10.1016\u002Fj.est.2025.116202","Improving electric vehicle state of charge estimation with wavelet transform-integrated 1D-CNN pooling layers",[586],"Kürşad Uçar",{"@type":89,"@id":588,"schema:additionalType":91,"schema:identifier":589,"schema:headline":590,"schema:author":591,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.116636","10.1016\u002Fj.est.2025.116636","Multi-source transfer network for cross-domain state of charge estimation of lithium-ion batteries",[592,593,594,595,596],"Delong Mu","Wenliang Zhang","Bing C. Lin","Chenye Lin","Yu Dong Lu",{"@type":89,"@id":598,"schema:additionalType":91,"schema:identifier":599,"schema:headline":600,"schema:author":601,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.117325","10.1016\u002Fj.est.2025.117325","Capacity estimation of Lithium-ion batteries based on discharge rate compensation model under different discharge rates",[602,603,604,604,605,606],"Li Wang","Changpeng Tan","Ji Wu","Duo Yang","Muyao Wu",{"@type":89,"@id":608,"schema:additionalType":91,"schema:identifier":609,"schema:headline":610,"schema:author":611,"schema:datePublished":397,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2025.119451","10.1016\u002Fj.est.2025.119451","State of charge estimation of lithium-ion batteries using transfer dual-stream physics-informed network",[612,613,614,615,616,617,618,619],"Yuhang Zhou","Changdong Wang","Taochen Gu","Huamin Jie","Zhen Tao","Richard Xian‐Ke Gao","Kye Yak See","Zhenyu Zhao",{"@type":89,"@id":621,"schema:additionalType":91,"schema:identifier":622,"schema:headline":623,"schema:author":624,"schema:datePublished":397,"schema:isPartOf":630},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.fub.2025.100124","10.1016\u002Fj.fub.2025.100124","Predicting remaining useful life of lithium-ion batteries: A review of degradation mechanisms and open-source data availability",[625,626,627,628,629],"Kishan Patel","Vaidehi Gosala","M. Stender","Moritz Braun","Sören Ehlers","Future Batteries",{"@type":89,"@id":632,"schema:additionalType":91,"schema:identifier":633,"schema:headline":634,"schema:author":635,"schema:datePublished":397,"schema:isPartOf":640},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.mlwa.2025.100629","10.1016\u002Fj.mlwa.2025.100629","Machine learning-based state of charge estimation: A comparison between CatBoost model and C-BLSTM-AE model",[636,637,638,639],"Abderrahim Zilali","Mehdi Adda","Khaled Ziane","Maxime Berger","Machine Learning with Applications",{"@type":89,"@id":642,"schema:additionalType":91,"schema:identifier":643,"schema:headline":644,"schema:author":645,"schema:datePublished":397,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-025-29449-6","10.1038\u002Fs41598-025-29449-6","Dual-phase optimized deep learning framework for accurate, efficient, and robust battery SoC estimation",[646,647],"R. Sasikala","Geetha Mani",{"@type":89,"@id":649,"schema:additionalType":91,"schema:identifier":650,"schema:headline":651,"schema:author":652,"schema:datePublished":397,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-025-32347-6","10.1038\u002Fs41598-025-32347-6","Temporal-aware transformer networks for state of charge multi-output prediction in unmanned aerial vehicle lithium-ion batteries",[653,654,655,656,657,658,659],"Mingzhuang Hua","Miaokun Xu","Jinbo Li","Xiaopeng Zhao","Qin Wang","Xinyuan Ni","Yueqing Wu",{"@type":89,"@id":661,"schema:additionalType":91,"schema:identifier":662,"schema:headline":663,"schema:author":664,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3580552","10.1109\u002Faccess.2025.3580552","State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach",[665,666,667,668,669,670],"Sesidhar DVSR","Chandrashekhar Badachi","Chandrashekar Nagawaram","Panduranga Chary Kondoju","Chittathuru Dhanamjayulu","Innocent Kamwa",{"@type":89,"@id":672,"schema:additionalType":91,"schema:identifier":673,"schema:headline":674,"schema:author":675,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3583216","10.1109\u002Faccess.2025.3583216","Mixing High-Frequency Bands Based on Wavelet Decomposition for Long-Term State-of-Charge Forecasting of Lithium-Ion Batteries",[289,676,292,293],"Chihyeon Choi",{"@type":89,"@id":678,"schema:additionalType":91,"schema:identifier":679,"schema:headline":680,"schema:author":681,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3632340","10.1109\u002Faccess.2025.3632340","A Generative Adversarial Network and Feed-Forward Neural Network Approach to Predict Health of Electric Vehicle Lithium-Ion Batteries in Extreme Temperature",[682,683,684,685,686],"Pirunthavi Wijikumar","Biplob Ray","Jahan Hassan","Kianoush Emami","Vithusha Balachandran",{"@type":89,"@id":688,"schema:additionalType":91,"schema:identifier":689,"schema:headline":690,"schema:author":691,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3648252","10.1109\u002Faccess.2025.3648252","An Iterative Algorithm to Estimate State of Health in Li-Ion Batteries",[692,693],"Ana Caetano Bochini","Alain Segundo Potts",{"@type":89,"@id":695,"schema:additionalType":91,"schema:identifier":696,"schema:headline":697,"schema:author":698,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fadacis65663.2025.11437022","10.1109\u002Fadacis65663.2025.11437022","Comparative Study of CNN, LSTM, and Hybrid Models for Lithium-ion Battery State of Charge Estimation in Electric Vehicles",[699,700,701],"Abir Ben Ameur","Taoufik Ladhari","Salim Hadj Saïd",{"@type":89,"@id":703,"schema:additionalType":91,"schema:identifier":704,"schema:headline":705,"schema:author":706,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faiiot65859.2025.11105282","10.1109\u002Faiiot65859.2025.11105282","MoExSOC: A Mixture of Experts Approach for Enhanced Battery State of Charge Estimation",[707,708],"Itamar P. Ryan","Kundan Nepal",{"@type":89,"@id":710,"schema:additionalType":91,"schema:identifier":711,"schema:headline":712,"schema:author":713,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fccdc65474.2025.11090346","10.1109\u002Fccdc65474.2025.11090346","Estimation of Lithium Battery Soc Based on the Gwo-Cnn-Gru Hybrid Model",[714,715,716,717],"Shuo Meng","Hongyan Ma","Chengzhi Ren","Yanling Qin",{"@type":89,"@id":719,"schema:additionalType":91,"schema:identifier":720,"schema:headline":721,"schema:author":722,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcobep66423.2025.11231604","10.1109\u002Fcobep66423.2025.11231604","Electrothermal Models of Li-ion Battery Based on Neural Networks: A Comparison",[723,693],"Dayra Ivette Saurí Vázquez",{"@type":89,"@id":725,"schema:additionalType":91,"schema:identifier":726,"schema:headline":727,"schema:author":728,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fdelcon68055.2025.11400207","10.1109\u002Fdelcon68055.2025.11400207","State-of-Charge Estimation of Lithium-ion Batteries with BiLSTM Architecture",[729,730,731],"Asra Irfan","Majid Jamil","Sheeraz Kirmani",{"@type":89,"@id":733,"schema:additionalType":91,"schema:identifier":734,"schema:headline":735,"schema:author":736,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fecce58356.2025.11259835","10.1109\u002Fecce58356.2025.11259835","Explainable Hybrid Deep Learning Model for State of Charge Estimation in Real-World Driving Cycles",[737,738,739,740,741],"Anantha Padmanabhan N K","Ankit Kumar Pratihasta","Sanjay Kumar Singh","Rajeev Kumar Singh","Rakesh Misra",{"@type":89,"@id":743,"schema:additionalType":91,"schema:identifier":744,"schema:headline":745,"schema:author":746,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ffmlds67896.2025.00125","10.1109\u002Ffmlds67896.2025.00125","Battery State of Charge Estimation by Machine Learning",[747,748,749,750,751,752],"Shan Ehsan","Mohammad Hassanzadeh","Majid Ahmadi","Ardian Kelmendi","Nabih Jaber","George J. Pappas",{"@type":89,"@id":754,"schema:additionalType":91,"schema:identifier":755,"schema:headline":756,"schema:author":757,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fi-pact65952.2025.11307956","10.1109\u002Fi-pact65952.2025.11307956","State of Charge Estimation of Electric-Vehicle Batteries Using Machine Learning Algorithms",[758,759],"Lakshit Pardeshi","R. M. Brisilla",{"@type":89,"@id":761,"schema:additionalType":91,"schema:identifier":762,"schema:headline":763,"schema:author":764,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fic3ecsbhi63591.2025.10990906","10.1109\u002Fic3ecsbhi63591.2025.10990906","State-of-Charge Estimation of Li-Ion Battery in Electric Vehicles Using Deep Neural Network",[765,766,730,729],"Saif Ahmad Khan","Arslan Ahmad",{"@type":89,"@id":768,"schema:additionalType":91,"schema:identifier":769,"schema:headline":770,"schema:author":771,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficaaid68975.2025.11358288","10.1109\u002Ficaaid68975.2025.11358288","State-of-Charge Estimation of Lithium-Ion Batteries Using a Fuzzy C-Regression Model (FCRM) Approach",[772,773,774,775],"Nahed Ghanay","Moussa Boukhnifer","Abdelmoudjib Benterki","Achraf Jabeur Telmoudi",{"@type":89,"@id":777,"schema:additionalType":91,"schema:identifier":778,"schema:headline":779,"schema:author":780,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficcepe66357.2025.11193226","10.1109\u002Ficcepe66357.2025.11193226","State of Charge Estimation of Lithium-Ion Batteries Using Kalman Filter",[781,782,783],"Yaxi Wu","Yang Du","Hailin Feng",{"@type":89,"@id":785,"schema:additionalType":91,"schema:identifier":786,"schema:headline":787,"schema:author":788,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficec2nt65402.2025.11379939","10.1109\u002Ficec2nt65402.2025.11379939","State of Power Estimation of Lithium Ion Battery Using Machine Learning",[789,790,791,792],"Saniya Nadaf","Nidhi Agnihotri","Sindhu S Hurakadli","Anoopkumar Patil",{"@type":89,"@id":794,"schema:additionalType":91,"schema:identifier":795,"schema:headline":796,"schema:author":797,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficees67011.2025.11213431","10.1109\u002Ficees67011.2025.11213431","Long Short Term Memory (LSTM) Network for Efficient State of Charge (SoC) Estimation",[798,729,730,731,799,800,801],"Shovana Khan Yusufzai","Sohail Ahmad Parah","Manju Sharma","Huzaifa Naz",{"@type":89,"@id":803,"schema:additionalType":91,"schema:identifier":804,"schema:headline":805,"schema:author":806,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficepe65965.2025.11139794","10.1109\u002Ficepe65965.2025.11139794","Comparative Analysis of State of Charge Estimation Techniques for Electric Vehicle Batteries using various Artificial Neural Networks",[807,808],"Priya Makkar","S. B. Singh",{"@type":89,"@id":810,"schema:additionalType":91,"schema:identifier":811,"schema:headline":812,"schema:author":813,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficerect65215.2025.11376172","10.1109\u002Ficerect65215.2025.11376172","Prediction and Estimation of State of Charge (SoC) of EV Batteries Using Machine Learning Models",[814,815,816,817,818,819],"Amisha Andurkar","Kushal Masarkar","Akanksha. Sontakke","Prof. Kunal Sawalakhe","Ganesh Wakte","Ritesh Banpurkar",{"@type":89,"@id":821,"schema:additionalType":91,"schema:identifier":822,"schema:headline":823,"schema:author":824,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficit63637.2025.10965211","10.1109\u002Ficit63637.2025.10965211","State-of-Charge Estimation of the Battery Based on Improved Equivalent Circuit Model and Adaptive Extended Kalman Filter",[825,826,827,828,829,830],"Yu Ding","Tao Zhang","Boyuan Cheng","Yixi Yang","Dongpo Deng","Weilin Li",{"@type":89,"@id":832,"schema:additionalType":91,"schema:identifier":833,"schema:headline":834,"schema:author":835,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficmctc62214.2025.11196199","10.1109\u002Ficmctc62214.2025.11196199","Estimation of state of charge for electric vehicle lithium batteries based on neural networks",[836,837,838,839,840,841,842,843],"Yang Weimo","S. Kanaga Suba Raja","Sarerusaenye Binti Ismail","Saliyah Kahar","Panji Narputro","Marina Artiyasa","Mamoona Humayun","Naeem Ramzan",{"@type":89,"@id":845,"schema:additionalType":91,"schema:identifier":846,"schema:headline":847,"schema:author":848,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficmlca66850.2025.11336284","10.1109\u002Ficmlca66850.2025.11336284","Calculation of Battery State of Charge Based on Machine Leaning Methods and Comparison of Different Driving Conditions",[849],"Zuoquan Liu",{"@type":89,"@id":851,"schema:additionalType":91,"schema:identifier":852,"schema:headline":853,"schema:author":854,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fiecon58223.2025.11221627","10.1109\u002Fiecon58223.2025.11221627","SocGate: Physics-Gated Neural Network for Multi-Cycle Battery State-of-Charge Estimation",[855,856,857,858,859,860],"Xilin Dai","Ruidi Zhou","Jinhao Zhang","Fanfan Lin","Weifeng Zhang","Hao Ma",{"@type":89,"@id":862,"schema:additionalType":91,"schema:identifier":863,"schema:headline":864,"schema:author":865,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fiecon58223.2025.11221645","10.1109\u002Fiecon58223.2025.11221645","Noise-Resilient State Estimation of Lithium-Ion Batteries Based on the Decoupled Iterative Modelling",[565,141,866,145],"Zifeng Chen",{"@type":89,"@id":868,"schema:additionalType":91,"schema:identifier":869,"schema:headline":870,"schema:author":871,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Firaset64571.2025.11008079","10.1109\u002Firaset64571.2025.11008079","Arrhenius Equation-Based Temperature-Compensated Extended Kalman Filter for Improved Battery State-of-Charge Estimation",[308,309,310,311],{"@type":89,"@id":873,"schema:additionalType":91,"schema:identifier":874,"schema:headline":875,"schema:author":876,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisie62713.2025.11124741","10.1109\u002Fisie62713.2025.11124741","An Adaptive Kalman-Guided Soft Sensor Using Feedforward Neural Networks for SOC Estimation in Lithium-Ion Batteries",[877,878,879],"Mostafa Mahdi Yousef","Mohammad Shaterabadi","Houshang Karimi",{"@type":89,"@id":881,"schema:additionalType":91,"schema:identifier":882,"schema:headline":883,"schema:author":884,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisie62713.2025.11124816","10.1109\u002Fisie62713.2025.11124816","Enhancing Memory-Limited Feedforward Neural Networks for State of Charge Estimation through Temporal Feature Engineering",[877,878,879],{"@type":89,"@id":886,"schema:additionalType":91,"schema:identifier":887,"schema:headline":888,"schema:author":889,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec63604.2025.11097926","10.1109\u002Fitec63604.2025.11097926","Lightweight Feature-Based Attention Network for Li-Ion Battery SOC Estimation",[890,891],"Ahmed Abdulmaksoud","Ryan Ahmed",{"@type":89,"@id":893,"schema:additionalType":91,"schema:identifier":894,"schema:headline":895,"schema:author":896,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec63604.2025.11098056","10.1109\u002Fitec63604.2025.11098056","iTransformer Based Voltage Estimation of Lithium-Ion Batteries",[897,898,899,900,890,891,901],"Biswanath Dehury","Bridget Marfo","Jarin Tasnin Mou","Esi Afariwa Otoo","Phillip J. Kollmeyer",{"@type":89,"@id":903,"schema:additionalType":91,"schema:identifier":904,"schema:headline":905,"schema:author":906,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fiyce66046.2025.11155025","10.1109\u002Fiyce66046.2025.11155025","The Effect of Different Open-Circuit Voltage Curves on the Accuracy of Model-Based State Estimation in Lithium-Ion Batteries",[233,586,907],"Halil Çimen",{"@type":89,"@id":909,"schema:additionalType":91,"schema:identifier":910,"schema:headline":911,"schema:author":912,"schema:datePublished":397,"schema:isPartOf":913},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Flcsys.2025.3639370","10.1109\u002Flcsys.2025.3639370","Scalable and Modular Control Framework for Managing Active Cell Balancing Challenges",[256,257,258],"IEEE Control Systems Letters",{"@type":89,"@id":915,"schema:additionalType":91,"schema:identifier":916,"schema:headline":917,"schema:author":918,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fmeditcom64437.2025.11104472","10.1109\u002Fmeditcom64437.2025.11104472","The Temporal Feature Fusion Deep Transformer Network Algorithm for Battery SOC Prediction in UAV",[653,919,655,656,658,659],"Mengwei Xu",{"@type":89,"@id":921,"schema:additionalType":91,"schema:identifier":922,"schema:headline":923,"schema:author":924,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fmetroxraine66377.2025.11340475","10.1109\u002Fmetroxraine66377.2025.11340475","A Pipeline for Lithium-Ion Battery Data Integration and Remaining Useful Life Estimation",[925,926,927],"Luca Martiri","Andrea Moschetti","Loredana Cristaldi",{"@type":89,"@id":929,"schema:additionalType":91,"schema:identifier":930,"schema:headline":931,"schema:author":932,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fnesp65198.2025.11040526","10.1109\u002Fnesp65198.2025.11040526","Battery State of Charge Prediction Based on Conformer Architecture",[933,934,935],"Liqin Su","Zirun Jia","Chongwen Wang",{"@type":89,"@id":937,"schema:additionalType":91,"schema:identifier":938,"schema:headline":939,"schema:author":940,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpeds63958.2025.11144818","10.1109\u002Fpeds63958.2025.11144818","Active Cell Balancing Using Bidirectional DC-DC Converters with a Current-Mode Sliding Controller",[941,942,943,944,945],"Zi Jian Jarell Wong","Thanh Ha Tien","Yannick Guedon","Liter Siek","Daniel Puiu Poenar",{"@type":89,"@id":947,"schema:additionalType":91,"schema:identifier":948,"schema:headline":949,"schema:author":950,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fscc66964.2025.11424676","10.1109\u002Fscc66964.2025.11424676","Deep Learning-Based Estimation of Li-Ion Battery State of Charge: Comparative Analysis of CNN, LSTM, and GRU Approaches",[951,952,953],"Marwa Gaich","Sabeur Jemmali","Bilal Manaï",{"@type":89,"@id":955,"schema:additionalType":91,"schema:identifier":956,"schema:headline":957,"schema:author":958,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fsefet65155.2025.11255405","10.1109\u002Fsefet65155.2025.11255405","A Deep Learning Approach for State of Charge Prediction Using Time-Windowed Voltage and Current Features",[959,960,961,215],"Avinash Sinha","Ritesh Kumar","Binod Kumar",{"@type":89,"@id":963,"schema:additionalType":91,"schema:identifier":964,"schema:headline":965,"schema:author":966,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssd64182.2025.10989955","10.1109\u002Fssd64182.2025.10989955","State of Charge Estimation of Lithium-ion Batteries Using Long Short Term Memory Network in Electric Vehicle Applications",[951,952,953],{"@type":89,"@id":968,"schema:additionalType":91,"schema:identifier":969,"schema:headline":970,"schema:author":971,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fstpec66316.2025.11490662","10.1109\u002Fstpec66316.2025.11490662","Optimized Machine-Learning Approach for Estimation of State-Of-Charge of Lithium-Ion Batteries for Sustainable Transportation",[972,731,973,974],"ZEBA BAKHTIYAR ANJUM","Mohd Rizwan Khalid","Mohd Owais Khan",{"@type":89,"@id":976,"schema:additionalType":91,"schema:identifier":977,"schema:headline":978,"schema:author":979,"schema:datePublished":397,"schema:isPartOf":986},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftie.2025.3532722","10.1109\u002Ftie.2025.3532722","Data-Driven Modeling of Battery-Based Energy Storage Systems",[980,981,982,983,984,985],"Edgar D. Silva-Vera","Jesús E. Valdez-Reséndiz","Julio C. Rosas‐Caro","G. Escobar","Daniel Guillén","José M. Sosa","IEEE Transactions on Industrial Electronics",{"@type":89,"@id":988,"schema:additionalType":91,"schema:identifier":989,"schema:headline":990,"schema:author":991,"schema:datePublished":397,"schema:isPartOf":986},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftie.2025.3626581","10.1109\u002Ftie.2025.3626581","SocGate: Physics-Gated Neural Network for Stable Multicycle Estimation of Battery State-of-Charge",[855,856,857,858,859,860],{"@type":89,"@id":993,"schema:additionalType":91,"schema:identifier":994,"schema:headline":995,"schema:author":996,"schema:datePublished":397,"schema:isPartOf":997},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftii.2024.3520180","10.1109\u002Ftii.2024.3520180","Distribution, Scale, and Context Sensitive, Convolutional Neural Network-Based SOC Estimation for Li-ion Batteries",[907],"IEEE Transactions on Industrial Informatics",{"@type":89,"@id":999,"schema:additionalType":91,"schema:identifier":1000,"schema:headline":1001,"schema:author":1002,"schema:datePublished":397,"schema:isPartOf":1008},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftits.2025.3580152","10.1109\u002Ftits.2025.3580152","A Scalable Recurrent Structure With Fast Transfer Learning for Lithium-Ion Battery State of Charge Estimation at Different Ambient Temperatures",[1003,1004,1005,1006,1007],"Haonan Chen","Guangzhong Dong","Shaohua Xie","Yifei Wang","Yunjiang Lou","IEEE Transactions on Intelligent Transportation Systems",{"@type":89,"@id":1010,"schema:additionalType":91,"schema:identifier":1011,"schema:headline":1012,"schema:author":1013,"schema:datePublished":397,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2025.3573618","10.1109\u002Ftte.2025.3573618","SocNet: A Physics-Guided Neural Network for Battery State-of-Charge Estimation Robust to Temperature Variations and Sensor Noises",[855,856,857,1014,858,860],"Keyi He","IEEE Transactions on Transportation Electrification",{"@type":89,"@id":1017,"schema:additionalType":91,"schema:identifier":1018,"schema:headline":1019,"schema:author":1020,"schema:datePublished":397,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2025.3590916","10.1109\u002Ftte.2025.3590916","State-of-Charge and State-of-Energy Estimation for Lithium-Ion Batteries Based on Meta-Learning and Square-Root Unscented Kalman Filter",[1021,1022,1023,1024,1025,1026,1027],"Liping Chen","Hongli Ma","Yingjie Song","António Mendes Lopes","Xinyuan Bao","Lisheng Yin","Annuo Liu",{"@type":89,"@id":1029,"schema:additionalType":91,"schema:identifier":1030,"schema:headline":1031,"schema:author":1032,"schema:datePublished":397,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2025.3649812","10.1109\u002Ftte.2025.3649812","Robust Sensor Fault Diagnosis for Lithium-Ion Battery Systems Using an Electro-Thermal Model",[1033,1034,1035,1036,891],"Mohsen Seyyedhosseini","Azadeh Gholaminejad","Nikoo Manouchehri Naeini","Babak Nahid‐Mobarakeh",{"@type":89,"@id":1038,"schema:additionalType":91,"schema:identifier":1039,"schema:headline":1040,"schema:author":1041,"schema:datePublished":397,"schema:isPartOf":1045},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18010209","10.3390\u002Fsu18010209","Comparative Battery State of Charge (SoC) Estimation Using Shallow and Deep Machine Learning Models",[1042,1043,1044],"Mohammed Almubarak","Md Ismail Hossain","Md Shafiullah","Sustainability",{"@type":89,"@id":1047,"schema:additionalType":91,"schema:identifier":1048,"schema:headline":1049,"schema:author":1050,"schema:datePublished":1057,"schema:isPartOf":1058},"https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffenrg.2024.1424204","10.3389\u002Ffenrg.2024.1424204","A hybrid neural network based on KF-SA-Transformer for SOC prediction of lithium-ion battery energy storage systems",[1051,1052,1053,1054,1055,1056],"Yifei Xiong","Qinglian Shi","Lingxu Shen","Chen Chen","Lu Wu","Cong Xu",2024,"Frontiers in Energy Research",{"@type":89,"@id":1060,"schema:additionalType":91,"schema:identifier":1061,"schema:headline":1062,"schema:author":1063,"schema:datePublished":1057,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen17164132","10.3390\u002Fen17164132","Advanced Deep Learning Techniques for Battery Thermal Management in New Energy Vehicles",[1064,1065,1066,1067,1068,1069],"Shaotong Qi","Yubo Cheng","Zhiyuan Li","Jiaxin Wang","Huaiyi Li","Chunwei Zhang",{"@type":89,"@id":1071,"schema:additionalType":91,"schema:identifier":1072,"schema:headline":1073,"schema:author":1074,"schema:datePublished":1057,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen17143502","10.3390\u002Fen17143502","Transformer-Based Deep Learning Models for State of Charge and State of Health Estimation of Li-Ion Batteries: A Survey Study",[1075,891],"John K. Guirguis",{"@type":89,"@id":1077,"schema:additionalType":91,"schema:identifier":1078,"schema:headline":1079,"schema:author":1080,"schema:datePublished":1057,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2024.133467","10.1016\u002Fj.energy.2024.133467","A fusion algorithm of multidimensional element space mapping architecture for SOC estimation of lithium-ion batteries under dynamic operating conditions",[1081,1082,1083,1084],"Jiang Wu","Dong Lei","Zelong Liu","Yan Zhang",{"@type":89,"@id":1086,"schema:additionalType":91,"schema:identifier":1087,"schema:headline":1088,"schema:author":1089,"schema:datePublished":1057,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2024.131540","10.1016\u002Fj.energy.2024.131540","Deep machine learning approaches for battery health monitoring",[1090,1091],"Sanjeev Kumar Singh","P. R. Budarapu",{"@type":89,"@id":1093,"schema:additionalType":91,"schema:identifier":1094,"schema:headline":1095,"schema:author":1096,"schema:datePublished":1057,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2024.111877","10.1016\u002Fj.est.2024.111877","Improved deep learning based state of charge estimation of lithium ion battery for electrified transportation",[1097,731,1098,1099,1100],"Uzair Ijaz Khan","Yasser Rafat","Mohd Umar Rehman","Mohammad Saad Alam",{"@type":89,"@id":1102,"schema:additionalType":91,"schema:identifier":1103,"schema:headline":1104,"schema:author":1105,"schema:datePublished":1057,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2024.131856","10.1016\u002Fj.energy.2024.131856","Exploring large language model for generic and robust state-of-charge estimation of Li-ion batteries: A mixed prompt learning method",[1106,1107,1108,1109,1110],"Chong Bian","Zhiyu Duan","Yaqian Hao","Shunkun Yang","Junlan Feng",{"@type":89,"@id":1112,"schema:additionalType":91,"schema:identifier":1113,"schema:headline":1114,"schema:author":1115,"schema:datePublished":1057,"schema:isPartOf":1119},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs13369-024-09870-1","10.1007\u002Fs13369-024-09870-1","Precise State-of-Charge Estimation in Electric Vehicle Lithium-Ion Batteries Using a Deep Neural Network",[1116,1117,1118],"A. Mohamed Saleem","Canraş Batunlu","Cem Direkoğlu","Arabian Journal for Science and Engineering",{"@type":89,"@id":1121,"schema:additionalType":91,"schema:identifier":1122,"schema:headline":1123,"schema:author":1124,"schema:datePublished":1057,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2024.234189","10.1016\u002Fj.jpowsour.2024.234189","Deep neural network battery charging curve prediction incorporating external information",[1125,1126,1127,1128,1129,1129,1130],"Yupeng Lin","Qiuyang Liu","Yuanlong Chen","Chunyu Wang","Junjie Wang","Lingling Zhao","Journal of Power Sources",{"@type":89,"@id":1133,"schema:additionalType":91,"schema:identifier":1134,"schema:headline":1135,"schema:author":1136,"schema:datePublished":1057,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2024.133185","10.1016\u002Fj.energy.2024.133185","Improved whale optimization algorithm towards precise state-of-charge estimation of lithium-ion batteries via optimizing LSTM",[1137,1138,1139,1140,1141,1142],"Sicheng Wan","Haojing Yang","Jinwen Lin","Junhui Li","Yibo Wang","Xinman Chen",{"@type":89,"@id":1144,"schema:additionalType":91,"schema:identifier":1145,"schema:headline":1146,"schema:author":1147,"schema:datePublished":1057,"schema:isPartOf":389},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectronics14010097","10.3390\u002Felectronics14010097","The Joint Estimation of SOC-SOH for Lithium-Ion Batteries Based on BiLSTM-SA",[1148,1149,1150,1151,1152],"Lingling Wu","Chao Chen","Zhenhua Li","Zhuo Chen","Hao Li",{"@type":89,"@id":1154,"schema:additionalType":91,"schema:identifier":1155,"schema:headline":1156,"schema:author":1157,"schema:datePublished":1057,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fad5ef9","10.1149\u002F1945-7111\u002Fad5ef9","Full-, Half-, and Symmetrical Cell Analysis of Lithium-Ion Battery Using Impedance and Nonlinear Frequency Response",[1158,1159,1160,1161,1162],"Yan Ying Lee","Hoon Seng Chan","Julian Ulrich","André Weber","Ulrike Krewer",{"@type":89,"@id":1164,"schema:additionalType":91,"schema:identifier":1165,"schema:headline":1166,"schema:author":1167,"schema:datePublished":1057,"schema:isPartOf":1178},"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-031-61137-7_25","10.1007\u002F978-3-031-61137-7_25","Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions",[1168,1169,1170,1171,1172,1173,1174,1175,1176,1177],"Gabriel Matos Cardoso Leite","Jorge Pérez‐Aracil","Carolina G. Marcelino","Gabriel García-Gutiérrez","Milan Prodanović","Enrique García‐Quismondo","Sergio Pinilla","Jesús Palma","Silvia Jiménez-Fernández","Sancho Salcedo‐Sanz","Lecture notes in computer science",{"@type":89,"@id":1180,"schema:additionalType":91,"schema:identifier":1181,"schema:headline":1182,"schema:author":1183,"schema:datePublished":1057,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen17225582","10.3390\u002Fen17225582","Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments",[1097,1184,1185],"Mohd Tariq","Arif I. Sarwat",{"@type":89,"@id":1187,"schema:additionalType":91,"schema:identifier":1188,"schema:headline":1189,"schema:author":1190,"schema:datePublished":1057,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2024.111831","10.1016\u002Fj.est.2024.111831","A model for the prediction of thermal runaway in lithium–ion batteries",[1191,1192],"Bernardo J. Azuaje–Berbecí","Hayri Ertan",{"@type":89,"@id":1194,"schema:additionalType":91,"schema:identifier":1195,"schema:headline":1196,"schema:author":1197,"schema:datePublished":1057,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2024.235760","10.1016\u002Fj.jpowsour.2024.235760","State-of-charge estimation across battery chemistries: A novel regression-based method and insights from unsupervised domain adaptation",[1198,1199,1200],"Mohammad Badfar","Murat Yildirim","Ratna Babu Chinnam",{"@type":89,"@id":1202,"schema:additionalType":91,"schema:identifier":1203,"schema:headline":1204,"schema:author":1205,"schema:datePublished":1057,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2024.130584","10.1016\u002Fj.energy.2024.130584","A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature",[153,1206,1207,1208,1209,155],"Noman Mujeeb Khan","Mohamad Abou Houran","Majad Mansoor","Naureen Akhtar",{"@type":89,"@id":1211,"schema:additionalType":91,"schema:identifier":1212,"schema:headline":1213,"schema:author":1214,"schema:datePublished":1057,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2024.234106","10.1016\u002Fj.jpowsour.2024.234106","The battery failure databank: Insights from an open-access database of thermal runaway behaviors of Li-ion cells and a resource for benchmarking risks",[1215,1216,1217,1218,1219,1220,1221,1222,1223,1224,1225,1226,1227,1228,1229,1230,1231,1232,1233,1234,1235,1236,1237,1238,1239],"Donal P. Finegan","Julia Billman","John J. Darst","Peter J. Hughes","Jesus Trillo","Matt Sharp","Alex Benson","Martin Pham","Inez Kesuma","Mark Buckwell","Hamish Thomas Reid","Charlie Kirchner-Burles","Matilda Fransson","David Petrushenko","Thomas M. M. Heenan","Rhodri Jervis","Rhodri E. Owen","Drasti Patel","Ludovic Broche","Alexander Rack","Oxana V. Magdysyuk","Matthew A. Keyser","William Q. Walker","Paul Robert Shearing","Eric C. Darcy",{"@type":89,"@id":1241,"schema:additionalType":91,"schema:identifier":1242,"schema:headline":1243,"schema:author":1244,"schema:datePublished":1057,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2024.234619","10.1016\u002Fj.jpowsour.2024.234619","Battery capacity knee-onset identification and early prediction using degradation curvature",[1245,1246,1247],"Huang Zhang","Faisal Altaf","Torsten Wik",{"@type":89,"@id":1249,"schema:additionalType":91,"schema:identifier":1250,"schema:headline":1251,"schema:author":1252,"schema:datePublished":1057,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2024.3380188","10.1109\u002Faccess.2024.3380188","A Bayesian Optimized Deep Learning Approach for Accurate State of Charge Estimation of Lithium Ion Batteries Used for Electric Vehicle Application",[1253,1254],"Selvaraj Vedhanayaki","Vairavasundaram Indragandhi",{"@type":89,"@id":1256,"schema:additionalType":91,"schema:identifier":1257,"schema:headline":1258,"schema:author":1259,"schema:datePublished":1057,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2024.3495560","10.1109\u002Faccess.2024.3495560","Transformer-Based Deep Learning Strategies for Lithium-Ion Batteries SOX Estimation Using Regular and Inverted Embedding",[1075,890,1260,901,891],"Mohanad Ismail",{"@type":89,"@id":1262,"schema:additionalType":91,"schema:identifier":1263,"schema:headline":1264,"schema:author":1265,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faiccsa63423.2024.10912587","10.1109\u002Faiccsa63423.2024.10912587","Enhancing Li-Ion Battery State-of-Charge Prediction for Electric Vehicles Using Deep Learning Models",[1266,1267,1268],"Abdelaziz Sahbani","Kamel Cherif","Kamel Ben Saad",{"@type":89,"@id":1270,"schema:additionalType":91,"schema:identifier":1271,"schema:headline":1272,"schema:author":1273,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fapcit62007.2024.10673547","10.1109\u002Fapcit62007.2024.10673547","Long-Short-term Memory Neural Network to Predict State of Charge (SOC)",[1274,1275],"R.C. Mala","Samith Suvarna",{"@type":89,"@id":1277,"schema:additionalType":91,"schema:identifier":1278,"schema:headline":1279,"schema:author":1280,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fesars-itec60450.2024.10819804","10.1109\u002Fesars-itec60450.2024.10819804","Driving Conditions Leading to Thermal Runaway in Li-Ion Battery Ev's",[1281,1191],"Hulusi Bülent Ertan",{"@type":89,"@id":1283,"schema:additionalType":91,"schema:identifier":1284,"schema:headline":1285,"schema:author":1286,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficaige62696.2024.10776687","10.1109\u002Ficaige62696.2024.10776687","State of Charge Estimation of Lithium-Ion Batteries Using Convolutional Neural Networks in Electric Vehicle Applications",[951,952,953],{"@type":89,"@id":1288,"schema:additionalType":91,"schema:identifier":1289,"schema:headline":1290,"schema:author":1291,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficmica61068.2024.10732706","10.1109\u002Ficmica61068.2024.10732706","Uncertainty aware State-of-Charge estimation for Li-ion Batteries using Deep Learning",[1292,1293,1294],"Anshul Kumar Yadav","Anil Kumar Saini","Dhiraj",{"@type":89,"@id":1296,"schema:additionalType":91,"schema:identifier":1297,"schema:headline":1298,"schema:author":1299,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficsintesa62455.2024.10747939","10.1109\u002Ficsintesa62455.2024.10747939","State of Charge Estimation of Lithium Ion Battery Using Coulomb Counting Method Based on Raspberry Pi",[1300,1301,1302],"Julian Permana","Tri Eko Putra Manvi","Prawito Prajitno",{"@type":89,"@id":1304,"schema:additionalType":91,"schema:identifier":1305,"schema:headline":1306,"schema:author":1307,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fis61756.2024.10705192","10.1109\u002Fis61756.2024.10705192","Utilising Machine Learning for Precise State-of-Charge Prediction in Li-Ion Batteries",[1308,1309,1310,1311],"Avinash Khatri","Jaswinder Lota","Prasanna Nepal","Mohammad Hossein Amirhosseini",{"@type":89,"@id":1313,"schema:additionalType":91,"schema:identifier":1314,"schema:headline":1315,"schema:author":1316,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisas64331.2024.10845442","10.1109\u002Fisas64331.2024.10845442","Multi-Scale Self-Attention Convolutional Neural Network for Energy Storage State-of-Charge Estimation",[907],{"@type":89,"@id":1318,"schema:additionalType":91,"schema:identifier":1319,"schema:headline":1320,"schema:author":1321,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisocc62682.2024.10762752","10.1109\u002Fisocc62682.2024.10762752","State of Charge Estimation for Lithium-Ion Batteries Based on Informer-LSTM Hybrid Network",[1322,1323,1324,1325,1326,1327,1328],"Ningfei Song","Nanlin Jin","Jingchen Wang","Jie Zhang","Ka Lok Man","Jeremy S. Smith","Yutao Yue",{"@type":89,"@id":1330,"schema:additionalType":91,"schema:identifier":1331,"schema:headline":1332,"schema:author":1333,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec60657.2024.10598981","10.1109\u002Fitec60657.2024.10598981","Online State-of-Health and Capacity Fade Estimation Using Machine-Learning-, Deep-Learning-, and\u002For Neural-Network-Based Algorithms",[1334,1335,1336],"Dat Giang","Masood Shahverdi","Shiva Omidzadeh",{"@type":89,"@id":1338,"schema:additionalType":91,"schema:identifier":1339,"schema:headline":1340,"schema:author":1341,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpiicon63519.2024.10995078","10.1109\u002Fpiicon63519.2024.10995078","LSTM-Driven State of Charge Estimation for Battery Management",[1342,1343,1344,1345,1346,1347],"S Tharunkumar","G Thanuj","T Charuvarthan","Sai Karthikeya","Pradeesh Prem Kumar","Rahul Satheesh",{"@type":89,"@id":1349,"schema:additionalType":91,"schema:identifier":1350,"schema:headline":1351,"schema:author":1352,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpiicon63519.2024.10995220","10.1109\u002Fpiicon63519.2024.10995220","Deep Neural Network-Based State-of-Charge Estimation of Li-ion Batteries for Electrified Transportation",[729,730,731,799,801],{"@type":89,"@id":1354,"schema:additionalType":91,"schema:identifier":1355,"schema:headline":1356,"schema:author":1357,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fsege62220.2024.10739432","10.1109\u002Fsege62220.2024.10739432","Physics-Informed NN for Improving Electric Vehicles Lithium-Ion Battery State-of-Charge Estimation Robustness",[1358,1359,1360],"Abdullah Baraean","Mahmoud Kassas","M. A. Abido",{"@type":89,"@id":1362,"schema:additionalType":91,"schema:identifier":1363,"schema:headline":1364,"schema:author":1365,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fsustained63638.2024.11073999","10.1109\u002Fsustained63638.2024.11073999","Performance Enhancement of Li Ion Battery through SOC Prediction at Various Temperature: A Machine Learning-based Approach",[1366,1367,1368],"Akhilesh Mishra","Sachin Kumar","Vivek Verma",{"@type":89,"@id":1370,"schema:additionalType":91,"schema:identifier":1371,"schema:headline":1372,"schema:author":1373,"schema:datePublished":1057,"schema:isPartOf":1376},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftpel.2024.3505924","10.1109\u002Ftpel.2024.3505924","A Lumped Disturbance Compensation Scheme for Unbiased State-of-Charge Estimation of Lithium-ion Batteries",[144,141,565,1374,1375,145],"Xi Luo","Huayu Ji","IEEE Transactions on Power Electronics",{"@type":89,"@id":1378,"schema:additionalType":91,"schema:identifier":1379,"schema:headline":1380,"schema:author":1381,"schema:datePublished":1057,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2024.3391938","10.1109\u002Ftte.2024.3391938","Hybrid Prompt-Driven Large Language Model for Robust State-of-Charge Estimation of Multitype Li-ion Batteries",[1106,1382,1107,1383,1109,1110],"Xue Han","Chao Deng",{"@type":89,"@id":1385,"schema:additionalType":91,"schema:identifier":1386,"schema:headline":1387,"schema:author":1388,"schema:datePublished":1057,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2024.3483973","10.1109\u002Ftte.2024.3483973","An Unsupervised Domain Adaptation Framework for Cross-Conditions State of Charge Estimation of Lithium-Ion Batteries",[1389,1390,1391,1392,1393],"Yunpeng Liu","Moin Ahmed","Jiangtao Feng","Zhiyu Mao","Zhongwei Chen",{"@type":89,"@id":1395,"schema:additionalType":91,"schema:identifier":1396,"schema:headline":1397,"schema:author":1398,"schema:datePublished":1057,"schema:isPartOf":1401},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftvt.2024.3447228","10.1109\u002Ftvt.2024.3447228","An Interpretable Electric Vehicles Battery State of Charge Estimation Using MHDTCN-GRU",[737,1399,1400,739,740],"J Rithish","Aneesh G. Nath","IEEE Transactions on Vehicular Technology",{"@type":89,"@id":1403,"schema:additionalType":91,"schema:identifier":1404,"schema:headline":1405,"schema:author":1406,"schema:datePublished":1408,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2023.108268","10.1016\u002Fj.est.2023.108268","SoC estimation of lithium-ion batteries based on machine learning techniques: A filtered approach",[1407],"Mehmet Korkmaz",2023,{"@type":89,"@id":1410,"schema:additionalType":91,"schema:identifier":1411,"schema:headline":1412,"schema:author":1413,"schema:datePublished":1408,"schema:isPartOf":110},"https:\u002F\u002Fdoi.org\u002F10.1002\u002Fente.202201398","10.1002\u002Fente.202201398","Correlation of Health Indicators on Lithium‐Ion Batteries",[1414,1415,1416,1417,1418,1419,1420],"Philipp Dechent","Elias Barbers","Alexander Epp","Dominik Jöst","Weihan Li","Dirk Uwe Sauer","Susanne Lehner",{"@type":89,"@id":1422,"schema:additionalType":91,"schema:identifier":1423,"schema:headline":1424,"schema:author":1425,"schema:datePublished":1408,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen16073002","10.3390\u002Fen16073002","Multi-State Online Estimation of Lithium-Ion Batteries Based on Multi-Task Learning",[1426,1427,500,1428,1429],"Xiang Bao","Yuefeng Liu","Haofeng Liu","Yue Wang",{"@type":89,"@id":1431,"schema:additionalType":91,"schema:identifier":1432,"schema:headline":1433,"schema:author":1434,"schema:datePublished":1408,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries10010010","10.3390\u002Fbatteries10010010","Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods",[1435,1436,1437],"Joaquín de la Vega","Jordi‐Roger Riba","J. A. Ortega",{"@type":89,"@id":1439,"schema:additionalType":91,"schema:identifier":1440,"schema:headline":1441,"schema:author":1442,"schema:datePublished":1408,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2023.107159","10.1016\u002Fj.est.2023.107159","Review on technological advancement of lithium-ion battery states estimation methods for electric vehicle applications",[1443,1444,1445,1446,1447],"Prashant Shrivastava","P. Amritansh Naidu","Sakshi Sharma","Bijaya Ketan Panigrahi","Akhil Garg",{"@type":89,"@id":1449,"schema:additionalType":91,"schema:identifier":1450,"schema:headline":1451,"schema:author":1452,"schema:datePublished":1408,"schema:isPartOf":389},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectronics12030657","10.3390\u002Felectronics12030657","A Novel Fusion Approach Consisting of GAN and State-of-Charge Estimator for Synthetic Battery Operation Data Generation",[1453,1454,1455,1456,1457],"Kei Long Wong","Ka Seng Chou","Rita T. Tse","Su-Kit Tang","Giovanni Pau",{"@type":89,"@id":1459,"schema:additionalType":91,"schema:identifier":1460,"schema:headline":1461,"schema:author":1462,"schema:datePublished":1408,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2023.129503","10.1016\u002Fj.energy.2023.129503","Particle swarm optimization of Elman neural network applied to battery state of charge and state of health estimation",[1463,1464,1465,1466,1467],"Matheus Henrique Rodrigues Miranda","Fabrício Leonardo Silva","Maria Augusta de Menezes Lourenço","Jony Javorski Eckert","Ludmila C. A. Silva",{"@type":89,"@id":1469,"schema:additionalType":91,"schema:identifier":1470,"schema:headline":1471,"schema:author":1472,"schema:datePublished":1408,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2023.108915","10.1016\u002Fj.est.2023.108915","Physics-informed ensemble deep learning framework for improving state of charge estimation of lithium-ion batteries",[1473,1474,1475,1476,1477,1478,1479,1480],"Hanqing Yu","Zhengjie Zhang","Kaiyi Yang","Lisheng Zhang","Wentao Wang","Shichun Yang","Junfu Li","Xinhua Liu",{"@type":89,"@id":1482,"schema:additionalType":91,"schema:identifier":1483,"schema:headline":1484,"schema:author":1485,"schema:datePublished":1408,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2023.233472","10.1016\u002Fj.jpowsour.2023.233472","A time-series Wasserstein GAN method for state-of-charge estimation of lithium-ion batteries",[1486,1487,1488,1489,1490,1491],"Xinyu Gu","Khay Wai See","Yanbin Liu","Bilal Arshad","Liang Zhao","Yunpeng Wang",{"@type":89,"@id":1493,"schema:additionalType":91,"schema:identifier":1494,"schema:headline":1495,"schema:author":1496,"schema:datePublished":1408,"schema:isPartOf":1499},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.trpro.2023.11.804","10.1016\u002Fj.trpro.2023.11.804","Obtaining performance-based aging models through multidimensional fitting of Li-ion cell testing data",[1497,1498],"Gian Luca Patrone","Elena Paffumi","Transportation research procedia",{"@type":89,"@id":1501,"schema:additionalType":91,"schema:identifier":1502,"schema:headline":1503,"schema:author":1504,"schema:datePublished":1408,"schema:isPartOf":1508},"https:\u002F\u002Fdoi.org\u002F10.1049\u002Fcps2.12053","10.1049\u002Fcps2.12053","Variational mode decomposition enabled temporal convolutional network model for state of charge estimation",[1505,1506,1507],"Zhaocheng Zhang","Tao Cai","Aote Yuan","IET Cyber-Physical Systems Theory & Applications",{"@type":89,"@id":1510,"schema:additionalType":91,"schema:identifier":1511,"schema:headline":1512,"schema:author":1513,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fc358072.2023.10436317","10.1109\u002Fc358072.2023.10436317","Estimation of discharge voltage in lithium-ion batteries (LIB)",[1514,1515,1516],"Víctor Olivero-Ortíz","Ingrid Oliveros","Carlos Robles-Algarín",{"@type":89,"@id":1518,"schema:additionalType":91,"schema:identifier":1519,"schema:headline":1520,"schema:author":1521,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fccpis59145.2023.10291676","10.1109\u002Fccpis59145.2023.10291676","Robust Estimation of State of Charge for Electric Vehicular Application",[1522,1523,1524,1525,1526,1527],"Anuja Barge","Vaishnavi Bhagwat","Harshwardhan Barge","Ganesh Naik","Vaishali Katkar","Nikhil B Sardar",{"@type":89,"@id":1529,"schema:additionalType":91,"schema:identifier":1530,"schema:headline":1531,"schema:author":1532,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcodit58514.2023.10284143","10.1109\u002Fcodit58514.2023.10284143","A Temporal Convolution Network to Electric vehicle Battery State-of-Charge Estimation",[1533,1534,1535,1536,1537,1538],"Dedjani Yahia","Laid Degaa","Sara Daas","Nasri Seif Allah","Lafifi M. Mourad","Nassim Rizoug",{"@type":89,"@id":1540,"schema:additionalType":91,"schema:identifier":1541,"schema:headline":1542,"schema:author":1543,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fecai58194.2023.10194122","10.1109\u002Fecai58194.2023.10194122","Investigation of Deep Learning Based Techniques for Prognostic and Health Management of Lithium-Ion Battery",[1544,830,1545,1546,1547,1548],"Umar Saleem","Weinjie Liu","Ibtihaj Ahmad","Muhammad Mobeen Aslam","Hafiz Umair Lateef",{"@type":89,"@id":1550,"schema:additionalType":91,"schema:identifier":1551,"schema:headline":1552,"schema:author":1553,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fi-pact58649.2023.10434507","10.1109\u002Fi-pact58649.2023.10434507","State of Charge Estimation Using Deeplearning",[1554,1555,1556,1557,1558],"Adwyck Gupta","S Siddharth","Harshit Sharan","R. Thirumalaivasan","M. Janaki",{"@type":89,"@id":1560,"schema:additionalType":91,"schema:identifier":1561,"schema:headline":1562,"schema:author":1563,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficcasit58768.2023.10351674","10.1109\u002Ficcasit58768.2023.10351674","Improved State-of-Charge and State-of- Health Estimation of Lithium Batterie with Adaptive Square-Root Unscented Kalman Filter",[1564,1565,1566,1567],"Weipu Zou","Chun-Yang Zhang","Xiang Jia","Xuyang Shi",{"@type":89,"@id":1569,"schema:additionalType":91,"schema:identifier":1570,"schema:headline":1571,"schema:author":1572,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficdcece57866.2023.10150795","10.1109\u002Ficdcece57866.2023.10150795","Recurrent Neural Network based Data-Driven SOC Estimation in Lithium-Ion Battery",[1573,1574,1575,1576,1577,1578],"Ashwini Kumari P","Pradeep Kumar S","K A Manohar","B S Sagar","Bidare Divakarachari Parameshachari","K R Deepa",{"@type":89,"@id":1580,"schema:additionalType":91,"schema:identifier":1581,"schema:headline":1582,"schema:author":1583,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Findicon59947.2023.10440780","10.1109\u002Findicon59947.2023.10440780","Estimation of State of Charge for Li-ion Batteries using Data Driven Technique",[1584,1585,1586,1587,1588],"Brijendra Kumar Verma","Devansh Khanna","Subhash Kumar Ram","Anand Abhishek","Sarvesh Bhagtani",{"@type":89,"@id":1590,"schema:additionalType":91,"schema:identifier":1591,"schema:headline":1592,"schema:author":1593,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fispa-bdcloud-socialcom-sustaincom59178.2023.00146","10.1109\u002Fispa-bdcloud-socialcom-sustaincom59178.2023.00146","A Physics-Informed Integrated Modeling Method for Lithium-ion Batteries",[1594,1595,1596,1597,1598,1599,1600,1601],"Yunsheng Fan","Zhiwu Huang","Kaifu Guan","Boyu Shu","Yongjie Liu","Zeyu Zhu","Peinan He","Shuo Li",{"@type":89,"@id":1603,"schema:additionalType":91,"schema:identifier":1604,"schema:headline":1605,"schema:author":1606,"schema:datePublished":1408,"schema:isPartOf":913},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Flcsys.2023.3342550","10.1109\u002Flcsys.2023.3342550","Power Losses Aware Nonlinear Model Predictive Control Design for Active Cell Balancing",[257,1607,258],"Syed Bilal Javed",{"@type":89,"@id":1609,"schema:additionalType":91,"schema:identifier":1610,"schema:headline":1611,"schema:author":1612,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fnpec57805.2023.10384901","10.1109\u002Fnpec57805.2023.10384901","Hardware-in-loop setup for SoC estimation of Lithium-ion batteries using Simulink Desktop Real Time",[1613,1614,1615,1616],"N Jesica","Pooja Rani","C Rajesh Kannan","Vasudevan Gandhi",{"@type":89,"@id":1618,"schema:additionalType":91,"schema:identifier":1619,"schema:headline":1620,"schema:author":1621,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fnpec57805.2023.10384964","10.1109\u002Fnpec57805.2023.10384964","SOC Estimation of a Li-ion Battery using Deep Learning Method: A comparative Study of LSTM and GRU Architecture",[1622,1623,1624],"Aditya C. Gole","Prashant K. Aher","Sanjaykumar L. Patil",{"@type":89,"@id":1626,"schema:additionalType":91,"schema:identifier":1627,"schema:headline":1628,"schema:author":1629,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpcems58491.2023.10136079","10.1109\u002Fpcems58491.2023.10136079","Comparative Study of Data Driven Methods for State of Charge Estimation of Li-ion Battery",[1630,1631],"Abhilash Sreekumar","R. R. Lekshmi",{"@type":89,"@id":1633,"schema:additionalType":91,"schema:identifier":1634,"schema:headline":1635,"schema:author":1636,"schema:datePublished":1408,"schema:isPartOf":1376},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftpel.2023.3251568","10.1109\u002Ftpel.2023.3251568","Source-Free Cross-Domain State of Charge Estimation of Lithium-Ion Batteries at Different Ambient Temperatures",[1637,1638,1639,1640,1641],"Liyuan Shen","Jingjing Li","Lin Zuo","Lei Zhu","Heng Tao Shen",{"@type":89,"@id":1643,"schema:additionalType":91,"schema:identifier":1644,"schema:headline":1645,"schema:author":1646,"schema:datePublished":1408,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2023.3293551","10.1109\u002Ftte.2023.3293551","Transfer Learning-Based State of Charge and State of Health Estimation for Li-Ion Batteries: A Review",[1637,1638,1647,1640,1641],"Lichao Meng",{"@type":89,"@id":1649,"schema:additionalType":91,"schema:identifier":1650,"schema:headline":1651,"schema:author":1652,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fupec57427.2023.10294352","10.1109\u002Fupec57427.2023.10294352","A Comprehensive Exploration on Different Machine Learning Techniques for State of Charge Estimation of EV Battery",[1653,1654,1655,1656,1657,1658,1659,1660],"Mithul Raaj A T","Justin Ratnam","Niranjan Kumar S","Tanya Gupta","Keerthi Balaji","Rani Chinnappa Naidu","Rajesh Kumar M","Mohamed Emad Farrag",{"@type":89,"@id":1662,"schema:additionalType":91,"schema:identifier":1663,"schema:headline":1664,"schema:author":1665,"schema:datePublished":1408,"schema:isPartOf":343},"https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-2943579\u002Fv1","10.21203\u002Frs.3.rs-2943579\u002Fv1","TFDSUNet: Time-Frequency Dual-Stream Uncertainty Network for Battery SOH\u002FSOC Prediction",[1666,1599,1667,1668,1669,1670,1671],"Wenzhe Xiao","Qizhou Wang","Li Pang","Chengyong Shu","Deyu Meng","Xiangyong Cao",{"@type":89,"@id":1673,"schema:additionalType":91,"schema:identifier":1674,"schema:headline":1675,"schema:author":1676,"schema:datePublished":1408,"schema:isPartOf":1684},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectricity4030014","10.3390\u002Felectricity4030014","Multi-Agent Reinforcement Learning-Based Decentralized Controller for Battery Modular Multilevel Inverter Systems",[1677,1678,1679,1680,1681,1682,1683],"Ali Mashayekh","Sebastian Pohlmann","Julian Estaller","Manuel Kuder","Anton Lesnicar","Richard Eckerle","Thomas Weyh","Electricity",{"@type":89,"@id":1686,"schema:additionalType":91,"schema:identifier":1687,"schema:headline":1688,"schema:author":1689,"schema:datePublished":1408,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen16083565","10.3390\u002Fen16083565","High Degree of Electrification in Heavy-Duty Vehicles",[1690,1691,1692,1693],"Santiago Martínez-Boggio","Javier Monsalve Serrano","Antonio García","Pedro Curto-Risso",{"@type":89,"@id":1695,"schema:additionalType":91,"schema:identifier":1696,"schema:headline":1697,"schema:author":1698,"schema:datePublished":1408,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen16207165","10.3390\u002Fen16207165","Modeling of the Battery Pack and Battery Management System towards an Integrated Electric Vehicle Application",[1699,1700,1701,1702],"Nadya Novarizka Mawuntu","Bao-Qi Mu","Oualid Doukhi","Deok Jin Lee",{"@type":89,"@id":1704,"schema:additionalType":91,"schema:identifier":1705,"schema:headline":1706,"schema:author":1707,"schema:datePublished":1408,"schema:isPartOf":1715},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fmath11224635","10.3390\u002Fmath11224635","DLPformer: A Hybrid Mathematical Model for State of Charge Prediction in Electric Vehicles Using Machine Learning Approaches",[1708,1709,1710,1711,1712,1713,1714],"Yaoyidi Wang","Niansheng Chen","Guangyu Fan","Dingyu Yang","Lei Rao","Songlin Cheng","Xiaoyong Song","Mathematics",{"@type":89,"@id":1717,"schema:additionalType":91,"schema:identifier":1718,"schema:headline":1719,"schema:author":1720,"schema:datePublished":1408,"schema:isPartOf":1725},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs23187737","10.3390\u002Fs23187737","A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles",[1721,1722,1723,1724],"Tianyu Lan","Zhi-Wei Gao","Haishuang Yin","Yuanhong Liu","Sensors",{"@type":89,"@id":1727,"schema:additionalType":91,"schema:identifier":1728,"schema:headline":1729,"schema:author":1730,"schema:datePublished":1408,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2304.11671","10.48550\u002Farxiv.2304.11671","Battery Capacity Knee-Onset Identification and Early Prediction Using Degradation Curvature",[1245,1246,1247],"arXiv (Cornell University)",{"@type":89,"@id":1733,"schema:additionalType":91,"schema:identifier":1734,"schema:headline":1735,"schema:author":1736,"schema:datePublished":1408,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2307.13907","10.48550\u002Farxiv.2307.13907","Robustness Verification of Deep Neural Networks using Star-Based Reachability Analysis with Variable-Length Time Series Input",[1737,1738,1739],"Neelanjana Pal","Diego Manzanas Lopez","Taylor Thomas Johnson",{"@type":89,"@id":1741,"schema:additionalType":91,"schema:identifier":1742,"schema:headline":1743,"schema:author":1744,"schema:datePublished":1750,"schema:isPartOf":1751},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ensm.2022.06.007","10.1016\u002Fj.ensm.2022.06.007","Battery state-of-charge estimation amid dynamic usage with physics-informed deep learning",[1745,1746,1747,1748,1749],"Jinpeng Tian","Rui Xiong","Jiahuan Lu","Cheng Chen","Weixiang Shen",2022,"Energy storage materials",{"@type":89,"@id":1753,"schema:additionalType":91,"schema:identifier":1754,"schema:headline":1755,"schema:author":1756,"schema:datePublished":1750,"schema:isPartOf":502},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.energy.2022.124328","10.1016\u002Fj.energy.2022.124328","Real-time state of charge estimation for electric vehicle power batteries using optimized filter",[450,451],{"@type":89,"@id":1758,"schema:additionalType":91,"schema:identifier":1759,"schema:headline":1760,"schema:author":1761,"schema:datePublished":1750,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2022.105343","10.1016\u002Fj.est.2022.105343","Impact of micro-cycles on the lifetime of lithium-ion batteries: An experimental study",[1762,1763,1764,1765,1766],"Adrian Soto","Alberto Berrueta","Miren Mateos","Pablo Sanchis","Alfredo Ursúa",{"@type":89,"@id":1768,"schema:additionalType":91,"schema:identifier":1769,"schema:headline":1770,"schema:author":1771,"schema:datePublished":1750,"schema:isPartOf":424},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11581-022-04751-9","10.1007\u002Fs11581-022-04751-9","GA-ELM-based adaptive Kalman estimator for SOC of lithium-ion batteries",[1772,1773,1774],"Yitong Ren","Jie Ding","Tianyun Hao",{"@type":89,"@id":1776,"schema:additionalType":91,"schema:identifier":1777,"schema:headline":1778,"schema:author":1779,"schema:datePublished":1750,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen15218003","10.3390\u002Fen15218003","State of Charge Estimation for Electric Vehicle Battery Management Systems Using the Hybrid Recurrent Learning Approach with Explainable Artificial Intelligence",[1780,1781,1782,1783,1784],"Saleh Mohammed Shahriar","Erphan Ahmmad Bhuiyan","Md. Nahiduzzaman","Mominul Ahsan","Julfikar Haider",{"@type":89,"@id":1786,"schema:additionalType":91,"schema:identifier":1787,"schema:headline":1788,"schema:author":1789,"schema:datePublished":1750,"schema:isPartOf":1794},"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-19-3379-0_39","10.1007\u002F978-981-19-3379-0_39","Comparison Between Ultra-High-Temperature Thermal Battery and Li-Ion Battery",[1790,1791,1792,1793],"Alok Kumar Ray","Sagar Vashisht","Jibin M. Joy","Dibakar Rakshit","Lecture notes in mechanical engineering",{"@type":89,"@id":1796,"schema:additionalType":91,"schema:identifier":1797,"schema:headline":1798,"schema:author":1799,"schema:datePublished":1750,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen15103798","10.3390\u002Fen15103798","The Distribution and Detection Issues of Counterfeit Lithium-Ion Batteries",[1800,1801,1802],"Lingxi Kong","Diganta Das","MICHAEL G. PECHT",{"@type":89,"@id":1804,"schema:additionalType":91,"schema:identifier":1805,"schema:headline":1806,"schema:author":1807,"schema:datePublished":1750,"schema:isPartOf":1818},"https:\u002F\u002Fdoi.org\u002F10.1039\u002Fd2ee01676a","10.1039\u002Fd2ee01676a","Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning",[1808,1809,1810,1811,1812,1813,1814,1815,1816,1817],"Guijun Ma","Songpei Xu","Benben Jiang","Cheng Cheng","Xin Ping Ou Yang","Yue Shen","Tao Yang","Yunhui Huang","Han Ding","Ye Yuan","Energy & Environmental Science",{"@type":89,"@id":1820,"schema:additionalType":91,"schema:identifier":1821,"schema:headline":1822,"schema:author":1823,"schema:datePublished":1750,"schema:isPartOf":1831},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00170-022-09775-z","10.1007\u002Fs00170-022-09775-z","In-depth evaluation of micro-resistance spot welding for connecting tab to 18,650 Li-ion cells for electric vehicle battery application",[1824,1825,1826,1827,1828,1829,1830],"Nikhil Kumar","Sugumaran Minda Ramakrishnan","Kailasanathan Panchapakesan","Devarajan Subramaniam","Iain Masters","Martin N. Dowson","Abhishek Das","The International Journal of Advanced Manufacturing Technology",{"@type":89,"@id":1833,"schema:additionalType":91,"schema:identifier":1834,"schema:headline":1835,"schema:author":1836,"schema:datePublished":1750,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fac4ea4","10.1149\u002F1945-7111\u002Fac4ea4","Early-Stage Heat- And Discharge-Induced Transformations in a Lithium-Ion Cell Monitored by an Advanced Battery Management System",[477,489,478],{"@type":89,"@id":1838,"schema:additionalType":91,"schema:identifier":1839,"schema:headline":1840,"schema:author":1841,"schema:datePublished":1750,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2022.232238","10.1016\u002Fj.jpowsour.2022.232238","Estimating battery state-of-charge with a few target training data by meta-learning",[1842,1843],"Daeung Jeong","Sungwoo Bae",{"@type":89,"@id":1845,"schema:additionalType":91,"schema:identifier":1846,"schema:headline":1847,"schema:author":1848,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcistem55808.2022.10043957","10.1109\u002Fcistem55808.2022.10043957","State of Charge Estimation for Lithium-Ion Batteries Using Machine Learning Algorithms",[1849,1850,1851,1852,1853,1854],"Hamza Mediouni","Soumia El Hani","Amal Ezzouhri","Amina Daghouri","Imad Aboudrar","Nisrine Naseri",{"@type":89,"@id":1856,"schema:additionalType":91,"schema:identifier":1857,"schema:headline":1858,"schema:author":1859,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficevt55516.2022.9924793","10.1109\u002Ficevt55516.2022.9924793","Pack-to-Multicell Equalization of Lithium Battery String Based on Series-Parallel Topology of Switched-Capacitor Circuit",[1860,1861,1862,1863,1864],"Paul Lawrence","Trendy Prima Wijaya","Edi Leksono","Justin Pradipta","Irsyad Nashirul Haq",{"@type":89,"@id":1866,"schema:additionalType":91,"schema:identifier":1867,"schema:headline":1868,"schema:author":1869,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficps55917.2022.00021","10.1109\u002Ficps55917.2022.00021","State-of-Charge Estimation Algorithm for Li-ion Batteries using Long Short-Term Memory Network with Bayesian Optimization",[1870,1871,1872],"Akshat Dubey","Ayaan Zaidi","Ayush Kulshreshtha",{"@type":89,"@id":1874,"schema:additionalType":91,"schema:identifier":1875,"schema:headline":1876,"schema:author":1877,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpiicon56320.2022.10045116","10.1109\u002Fpiicon56320.2022.10045116","Artificial Neural Network-based State of Charge (SOC) Estimation of a Lithium-Ion Battery under Different Temperatures Conditions",[1878,1879,1880],"Swapnil Tiwari","Bhavnesh Kumar","Arjun Tyagi",{"@type":89,"@id":1882,"schema:additionalType":91,"schema:identifier":1883,"schema:headline":1884,"schema:author":1885,"schema:datePublished":1750,"schema:isPartOf":1893},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftia.2022.3180282","10.1109\u002Ftia.2022.3180282","SOC Estimation Using Deep Bidirectional Gated Recurrent Units With Tree Parzen Estimator Hyperparameter Optimization",[1886,1887,1888,1889,1890,1891,1892],"Dickson N. T. How","M. A. Hannan","Molla Shahadat Hossain Lipu","Pin Jern Ker","Muhamad Mansor","Khairul Salleh Mohamed Sahari","Kashem Mohammad Muttaqi","IEEE Transactions on Industry Applications",{"@type":89,"@id":1895,"schema:additionalType":91,"schema:identifier":1896,"schema:headline":1897,"schema:author":1898,"schema:datePublished":1750,"schema:isPartOf":1376},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftpel.2022.3205437","10.1109\u002Ftpel.2022.3205437","Adaptive Neural Network-Based Prescribed-Time Observer for Battery State-of-Charge Estimation",[1899,1900,1478,1901,1902],"Chenyang Pan","Zhaoxia Peng","Guoguang Wen","Tingwen Huang",{"@type":89,"@id":1904,"schema:additionalType":91,"schema:identifier":1905,"schema:headline":1906,"schema:author":1907,"schema:datePublished":1750,"schema:isPartOf":1401},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftvt.2022.3216337","10.1109\u002Ftvt.2022.3216337","Variational Bayesian-Based Maximum Correntropy Cubature Kalman Filter Method for State-of-Charge Estimation of Li-Ion Battery Cells",[1908,1909,1910,1911],"Ishaq Hafez","Ali Wadi","Mamoun F. Abdel–Hafez","Ala Al-Haj Hussein",{"@type":89,"@id":1913,"schema:additionalType":91,"schema:identifier":1914,"schema:headline":1915,"schema:author":1916,"schema:datePublished":1750,"schema:isPartOf":1918},"https:\u002F\u002Fdoi.org\u002F10.23919\u002Fccc55666.2022.9901537","10.23919\u002Fccc55666.2022.9901537","A hybrid Kalman filter for SOC estimation of lithium-ion batteries",[1774,1773,1917],"Taotao Tu","2022 41st Chinese Control Conference (CCC)",{"@type":89,"@id":1920,"schema:additionalType":91,"schema:identifier":1921,"schema:headline":1922,"schema:author":1923,"schema:datePublished":1926,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2021.229690","10.1016\u002Fj.jpowsour.2021.229690","Understanding the limitations of lithium ion batteries at high rates",[1924,1925],"Michael J. Lain","Emma Kendrick",2021,{"@type":89,"@id":1928,"schema:additionalType":91,"schema:identifier":1929,"schema:headline":1930,"schema:author":1931,"schema:datePublished":1926,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2021.102440","10.1016\u002Fj.est.2021.102440","State of Charge and State of Energy Estimation for Lithium-Ion Batteries Based on a Long Short-Term Memory Neural Network",[1932,1933,1934],"Liang Ma","Chao Hu","Fangjuan Cheng",{"@type":89,"@id":1936,"schema:additionalType":91,"schema:identifier":1937,"schema:headline":1938,"schema:author":1939,"schema:datePublished":1926,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fabf05f","10.1149\u002F1945-7111\u002Fabf05f","Performance of Commercial Li-Ion Cells for Future NASA Missions and Aerospace Applications",[274,1940,1941,280,1239,1942,1943],"Juan P. Ruiz","Simon C. Jones","Christopher J. Iannello","Ratnakumar V. Bugga",{"@type":89,"@id":1945,"schema:additionalType":91,"schema:identifier":1946,"schema:headline":1947,"schema:author":1948,"schema:datePublished":1926,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2021.3049944","10.1109\u002Faccess.2021.3049944","An Improved Bidirectional Gated Recurrent Unit Method for Accurate State-of-Charge Estimation",[1949,1950,1951,1952,1953,1954,1955,1956],"Zhaowei Zhang","Zhekang Dong","Huipin Lin","Zhiwei He","Minghao Wang","Yufei He","Xiang Gao","Mingyu Gao",{"@type":89,"@id":1958,"schema:additionalType":91,"schema:identifier":1959,"schema:headline":1960,"schema:author":1961,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcpe-powereng50821.2021.9501189","10.1109\u002Fcpe-powereng50821.2021.9501189","A Hybrid Storage Systems for All Electric Aircraft",[1962,1963,1964,1965,1966,1967],"Giuseppe Bossi","Alfonso Damiano","Nicola Campagna","Vincenzo Castiglia","Rosario Miceli","Antonino Oscar Di Tommaso",{"@type":89,"@id":1969,"schema:additionalType":91,"schema:identifier":1970,"schema:headline":1971,"schema:author":1972,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficit46573.2021.9453530","10.1109\u002Ficit46573.2021.9453530","Bidirectional Partial Power DC-DC Configuration for HESS interface in EV Powertrains",[1973,1974,1975,1976,1977],"Hector J. Ferreira","Samir Kouro","Christian A. Rojas","Nicolás Müller","Sebastian Rivera",{"@type":89,"@id":1979,"schema:additionalType":91,"schema:identifier":1980,"schema:headline":1981,"schema:author":1982,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fiecon48115.2021.9589130","10.1109\u002Fiecon48115.2021.9589130","A Hybrid Energy Storage Sizing for a Vertical Take-off and Landing Electric Aircraft",[1964,1965,1963,1983,1966,1967],"Luigi Pio Di Noia",{"@type":89,"@id":1985,"schema:additionalType":91,"schema:identifier":1986,"schema:headline":1987,"schema:author":1988,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisie45552.2021.9576403","10.1109\u002Fisie45552.2021.9576403","Trade-off Analysis of Energy Storage Systems for Helicopter Landing Gear Electromechanical Actuator",[1989,1990,1991,1992],"Milos Lukic","Paolo Giangrande","Christian Klumpner","Michael Galea",{"@type":89,"@id":1994,"schema:additionalType":91,"schema:identifier":1995,"schema:headline":1996,"schema:author":1997,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fspies52282.2021.9633780","10.1109\u002Fspies52282.2021.9633780","LISA: A Transferable Light-weight Multi-Head Self-Attention Neural Network Model for Lithium-Ion Batteries State-of-Charge Estimation",[1998,1999,2000,2001,2002,2003],"Ruizhi Hun","Song Zhang","Gurjeet Singh","Jian Qing Qian","Yun Chen","Patrick Yin Chiang",{"@type":89,"@id":2005,"schema:additionalType":91,"schema:identifier":2006,"schema:headline":2007,"schema:author":2008,"schema:datePublished":1926,"schema:isPartOf":2014},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftcst.2021.3103483","10.1109\u002Ftcst.2021.3103483","qTSL: A Multilayer Control Framework for Managing Capacity, Temperature, Stress, and Losses in Hybrid Balancing Systems",[2009,2010,2011,2012,2013],"Ricardo Pinto de Castro","H. Pereira","Rui Esteves Araújo","Jorge Varela Barreras","Herschel C. Pangborn","IEEE Transactions on Control Systems Technology",{"@type":89,"@id":2016,"schema:additionalType":91,"schema:identifier":2017,"schema:headline":2018,"schema:author":2019,"schema:datePublished":1926,"schema:isPartOf":1401},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftvt.2021.3064287","10.1109\u002Ftvt.2021.3064287","Estimating State of Charge for xEV Batteries Using 1D Convolutional Neural Networks and Transfer Learning",[2020,2021,2022,2023],"Arnab Bhattacharjee","Ashu Kumar Verma","Sukumar Mishra","Tapan Kumar Saha",{"@type":89,"@id":2025,"schema:additionalType":91,"schema:identifier":2026,"schema:headline":2027,"schema:author":2028,"schema:datePublished":1926,"schema:isPartOf":2032},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fvppc53923.2021.9699201","10.1109\u002Fvppc53923.2021.9699201","Li-ion battery State-of-Charge estimation using computationally efficient neural network models",[2029,2011,2030,2031],"Pedro Monteiro","Cláudio Lúcio Lopes Pinto","Stephan Matz","2021 IEEE Vehicle Power and Propulsion Conference (VPPC)",{"@type":89,"@id":2034,"schema:additionalType":91,"schema:identifier":2035,"schema:headline":2036,"schema:author":2037,"schema:datePublished":2044,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen13236366","10.3390\u002Fen13236366","An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery",[2038,2039,2040,2041,2042,2043],"Wenxian Duan","Chuanxue Song","Silun Peng","Feng Li Xiao","Yulong Shao","Shixin Song",2020,{"@type":89,"@id":2046,"schema:additionalType":91,"schema:identifier":2047,"schema:headline":2048,"schema:author":2049,"schema:datePublished":2044,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fabae37","10.1149\u002F1945-7111\u002Fabae37","Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling Conditions",[441,2050,533,2051,2052,2053,2054,2055],"Heather Marie Barkholtz","Daniel L. Campbell","Benjamin W. Juba","Jessica Kustas","Summer Rhodes Ferreira","Babu R. Chalamala",{"@type":89,"@id":2057,"schema:additionalType":91,"schema:identifier":2058,"schema:headline":2059,"schema:author":2060,"schema:datePublished":2044,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fab6ff0","10.1149\u002F1945-7111\u002Fab6ff0","Preventing Cell-to-Cell Propagation of Thermal Runaway in Lithium-Ion Batteries",[477,2061,2062,478,2063,479,2064,2065,2066,2067,488,489],"Michael E. Thomas","Marc B. Airola","L. J. Frizzell-Makowski","James Reuster","Hasan N. Oğuz","Peter W Green","J. La Favors",{"@type":89,"@id":2069,"schema:additionalType":91,"schema:identifier":2070,"schema:headline":2071,"schema:author":2072,"schema:datePublished":2044,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen13164085","10.3390\u002Fen13164085","Battery Models for Battery Powered Applications: A Comparative Study",[1964,1965,1966,2073,2074,2075,2076],"Rosa Anna Mastromauro","Ciro Spataro","Marco Trapanese","Fabio Viola",{"@type":89,"@id":2078,"schema:additionalType":91,"schema:identifier":2079,"schema:headline":2080,"schema:author":2081,"schema:datePublished":2044,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fab6448","10.1149\u002F1945-7111\u002Fab6448","Analysis of Generalized Peukert’s Equations for Capacity Calculation of Lithium-Ion Cells",[2082,2083,2084],"Nikolay E. Galushkin","Nataliya N. Yazvinskaya","Dmitriy N. Galushkin",{"@type":89,"@id":2086,"schema:additionalType":91,"schema:identifier":2087,"schema:headline":2088,"schema:author":2089,"schema:datePublished":2044,"schema:isPartOf":444},"https:\u002F\u002Fdoi.org\u002F10.1149\u002F1945-7111\u002Fabc0a5","10.1149\u002F1945-7111\u002Fabc0a5","Review—Thermal Safety Management in Li-Ion Batteries: Current Issues and Perspectives",[477,489,478,2090,2091,2092],"Shriram Santhanagopalan","Judith A. Jeevarajan","Thomas P. Barrera",{"@type":89,"@id":2094,"schema:additionalType":91,"schema:identifier":2095,"schema:headline":2096,"schema:author":2097,"schema:datePublished":2044},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fenergycon48941.2020.9236517","10.1109\u002Fenergycon48941.2020.9236517","Estimation of State of Charge and Terminal Voltage of Li-ion Battery using Extended Kalman Filter",[2098,2099,2100,2101],"Mintu Kumar","Thumpiri Reddy Manasa","Balakrishnan Raja","K. Selvajyothi",{"@type":89,"@id":2103,"schema:additionalType":91,"schema:identifier":2104,"schema:headline":2105,"schema:author":2106,"schema:datePublished":2044},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficecocs50124.2020.9314577","10.1109\u002Ficecocs50124.2020.9314577","Online Parameter Estimation of an Electric Vehicle Lithium-Ion Battery Using AFFRLS",[2107,2108,2109],"Elmarghichi Mouncef","Mostafa Bouzi","Naoufl Ettalabi",{"@type":89,"@id":2111,"schema:additionalType":91,"schema:identifier":2112,"schema:headline":2113,"schema:author":2114,"schema:datePublished":2044,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2011.00841","10.48550\u002Farxiv.2011.00841","Estimating State of Charge for xEV batteries using 1D Convolutional\\n Neural Networks and Transfer Learning",[2020,2115,2022,2023],"Ashu Verma",{"@type":89,"@id":2117,"schema:additionalType":91,"schema:identifier":2118,"schema:headline":2119,"schema:author":2120,"schema:datePublished":2122,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries5040064","10.3390\u002Fbatteries5040064","Design Strategies for High Power vs. High Energy Lithium Ion Cells",[1924,2121,1925],"James Brandon",2019,{"@type":89,"@id":2124,"schema:additionalType":91,"schema:identifier":2125,"schema:headline":2126,"schema:author":2127,"schema:datePublished":2122,"schema:isPartOf":434},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fwevj10040079","10.3390\u002Fwevj10040079","Understanding the Thermal Runaway of Ni-Rich Lithium-Ion Batteries",[2128,2129,2130,2131,2132,2133,2134,2135],"Thi Thu Dieu Nguyen","Sara Abada","Amandine Lecocq","Julien Bernard","Martin Petit","Guy Marlair","Sylvie Grugeon","Stéphane Laruelle",{"@type":89,"@id":2137,"schema:additionalType":91,"schema:identifier":2138,"schema:headline":2139,"schema:author":2140,"schema:datePublished":2122},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fecce.2019.8912966","10.1109\u002Fecce.2019.8912966","High Performance Active Battery Management System with Multi-Winding Transformer",[2141,2142,2143,2144,2145,2146],"Umberto Abronzini","Mauro Di Monaco","Francesco Porpora","G. Tomasso","Matilde D’Arpino","Ciro Attaianese",{"@type":89,"@id":2148,"schema:additionalType":91,"schema:identifier":2149,"schema:headline":2150,"schema:author":2151,"schema:datePublished":2122},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec.2019.8790543","10.1109\u002Fitec.2019.8790543","Li-ion Battery State of Charge Estimation Using Long Short-Term Memory Recurrent Neural Network with Transfer Learning",[2152,901,2153,2154],"Carlos Vidal","Ephrem Chemali","Ali Emadi",{"@type":89,"@id":2156,"schema:additionalType":91,"schema:identifier":2157,"schema:headline":2158,"schema:author":2159,"schema:datePublished":2122},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Frtsi.2019.8895554","10.1109\u002Frtsi.2019.8895554","Modelling, simulation and characterization of Li-Ion battery cell",[1965,1966,2160,2161,2076,2162,2163,2164],"Guido Ala","Pietro Romano","Graziella Giglia","Antonino Imburgia","Giuseppe Schettino",{"@type":89,"@id":2166,"schema:additionalType":91,"schema:identifier":2167,"schema:headline":2168,"schema:author":2169,"schema:datePublished":2122,"schema:isPartOf":1893},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftia.2019.2911057","10.1109\u002Ftia.2019.2911057","Real-Time Control of a Full Scale Li-ion Battery and Li-ion Capacitor Hybrid Energy Storage System for a Plug-in Hybrid Vehicle",[901,2170,2171,2172,2173,2174,2175,2176,2153,2177,2154],"Mackenzie Wootton","John Reimers","Daniel F. Opila","Himesh Kurera","Mrudang Kadakia","Ran Gu","Tyler Stiene","Megan Wood",{"@type":89,"@id":2179,"schema:additionalType":91,"schema:identifier":2180,"schema:headline":2181,"schema:author":2182,"schema:datePublished":2122,"schema:isPartOf":1401},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftvt.2019.2929653","10.1109\u002Ftvt.2019.2929653","Smart and Hybrid Balancing System: Design, Modeling, and Experimental Demonstration",[2009,2183,2012,2011,2184],"Cláudio Pinto","David A. Howey",{"@type":89,"@id":2186,"schema:additionalType":91,"schema:identifier":2187,"schema:headline":2188,"schema:author":2189,"schema:datePublished":2122},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fvppc46532.2019.8952557","10.1109\u002Fvppc46532.2019.8952557","Model Predictive Power Allocation for Hybrid Battery Balancing Systems",[2009,2011],{"@type":89,"@id":2191,"schema:additionalType":91,"schema:identifier":2192,"schema:headline":2193,"schema:author":2194,"schema:datePublished":2195,"schema:isPartOf":1131},"https:\u002F\u002Fdoi.org\u002F10.1016\u002FJ.JPOWSOUR.2018.10.014","10.1016\u002Fj.jpowsour.2018.10.014","Rapid monitoring of impedance phase shifts in lithium-ion batteries for hazard prevention",[477,489,478],2018,{"@type":89,"@id":2197,"schema:additionalType":91,"schema:identifier":2198,"schema:headline":2199,"schema:author":2200,"schema:datePublished":2195},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fvppc.2018.8604956","10.1109\u002Fvppc.2018.8604956","Design of a High Performance Battery Pack as a Constraint Satisfaction Problem",[2201,2202,2203,2204,2205],"Louis Pelletier","Félix-Antoine LeBel","Ruben Gonzalez Rubio","M.-A. Roux","João Pedro F. Trovão",{"@type":89,"@id":2207,"schema:additionalType":91,"schema:identifier":2208,"schema:headline":2209,"schema:author":2210,"schema:datePublished":2211},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fecce.2017.8095834","10.1109\u002Fecce.2017.8095834","Optimal performance of a full scale li-ion battery and li-ion capacitor hybrid energy storage system for a plug-in hybrid vehicle",[901,2170,2171,2176,2153,2177,2154],2017,{"@type":89,"@id":2213,"schema:additionalType":91,"schema:identifier":2214},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpowsour.2025.238357","10.1016\u002Fj.jpowsour.2025.238357",{"@type":89,"@id":2216,"schema:additionalType":2217,"schema:identifier":2218,"schema:headline":2219,"schema:author":2220,"schema:datePublished":100,"schema:isPartOf":2223},"https:\u002F\u002Fdoi.org\u002F10.1002\u002Fbte2.70149","REFERENCED","10.1002\u002Fbte2.70149","Prognostic Approaches for Early Detection of Thermal Runaway in Lithium‐Ion Batteries",[2221,2222,2091,1802],"Sahithi Maddipatla","Byoungchul Kwon","Battery energy",{"@type":89,"@id":2225,"schema:additionalType":2217,"schema:identifier":2226,"schema:headline":2227,"schema:author":2228,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.120909","10.1016\u002Fj.est.2026.120909","State of charge estimation for parallel-series battery packs based on the representative cells",[2229,2230,2231],"Reyhane Mohammadrezaee","Jafar Ghaisari","Alireza Bakhshai",{"@type":89,"@id":2233,"schema:additionalType":2217,"schema:identifier":2234,"schema:headline":2235,"schema:author":2236,"schema:datePublished":100,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2026.121006","10.1016\u002Fj.est.2026.121006","Generative data augmentation for improving state estimation and prognostics in lithium-ion batteries: Advances, Challenges, and Future directions",[2237,2238,2239,2240,2241,2242],"Md.  Sulyman Islam Sifat","Ummy Sawda","Md Alamgir Kabir","Mobyen Uddin Ahmed","M. S. Hossain Lipu","M.M. Manjurul Islam",{"@type":89,"@id":2244,"schema:additionalType":2217,"schema:identifier":2245,"schema:headline":2246,"schema:author":2247,"schema:datePublished":100,"schema:isPartOf":294},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-53543-y","10.1038\u002Fs41598-026-53543-y","Hybrid multi-scale CNN-Residual-LSTM approach for robust state-of-charge estimation in lithium-ion batteries",[2248,2249,2250,2251,2252,2253],"Saadin Oyucu","Onur Polat","Muammer Türkoğlu","Faruk Kürker","Ahmet Aksöz","Emre Biçer",{"@type":89,"@id":2255,"schema:additionalType":2217,"schema:identifier":2256,"schema:headline":2257,"schema:author":2258,"schema:datePublished":100,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2026.3677263","10.1109\u002Faccess.2026.3677263","An Improved Robust H ∞ Observer Framework for State-of-Charge Estimation of Lithium-Ion Batteries in Electric Vehicles",[2259,2260,2261],"K. Vinothini","R. Manivannan","Chala Merga Abdissa",{"@type":89,"@id":2263,"schema:additionalType":2217,"schema:identifier":2264,"schema:headline":2265,"schema:author":2266,"schema:datePublished":100},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Feesat65054.2026.11404093","10.1109\u002Feesat65054.2026.11404093","A SPICE-compatible Equivalent Circuit Model for Li-ion Batteries Incorporating Diffusion and Current-Dependent Dynamics",[2267,2268],"Aryan Chollera","Byunghoo Jung",{"@type":89,"@id":2270,"schema:additionalType":2217,"schema:identifier":2271,"schema:headline":2272,"schema:author":2273,"schema:datePublished":100,"schema:isPartOf":2277},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fieeedata.2026.3697177","10.1109\u002Fieeedata.2026.3697177","Descriptor: University of Rhode Island Photovoltaic Battery Energy Storage SOC Tracking Dataset (URI-PBEST)",[2274,2275,2276],"Showrov Rahman","Kaushallya Adhikari","Kaan Icer","IEEE data descriptions.",{"@type":89,"@id":2279,"schema:additionalType":2217,"schema:identifier":2280,"schema:headline":2281,"schema:author":2282,"schema:datePublished":100,"schema:isPartOf":2287},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fapp16020618","10.3390\u002Fapp16020618","A Systematic Review of Computational and Data-Driven Approaches for Energy-Efficient Battery Management in Electrified Vehicles",[2283,2284,2285,2286],"Milos Poliak","Damian Paweł Frej","Piotr Łagowski","Justyna J. Jaskiewicz","Applied Sciences",{"@type":89,"@id":2289,"schema:additionalType":2217,"schema:identifier":2290,"schema:headline":2291,"schema:author":2292,"schema:datePublished":397,"schema:isPartOf":424},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11581-025-06714-2","10.1007\u002Fs11581-025-06714-2","A dual-scale deep learning model for estimating lithium-ion battery SOC by data denoising",[2293,1773,2294,2295],"Sai Wang","Dezhi Shen","Huibo Chen",{"@type":89,"@id":2297,"schema:additionalType":2217,"schema:identifier":2298,"schema:headline":2299,"schema:author":2300,"schema:datePublished":397,"schema:isPartOf":2311},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12633-025-03447-9","10.1007\u002Fs12633-025-03447-9","Towards Sustainable Lithium-Ion Batteries: A State-of-the-Art Review on Silicon Anodes, Economics, and Recycling",[2301,2302,2303,2304,2305,2306,2307,2308,2309,2310],"Maria Lucia Protopapa","Emiliano Burresi","Angela Fiore","L. Mirenghi","Barbara Palazzo","Monica Schioppa","M.A. Tagliente","Vitantonio Valenzano","Nicola Taurisano","Giovanni Battista Appetecchi","Silicon",{"@type":89,"@id":2313,"schema:additionalType":2217,"schema:identifier":2314,"schema:headline":2315,"schema:author":2316,"schema:datePublished":397,"schema:isPartOf":2287},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fapp15095078","10.3390\u002Fapp15095078","Explainable Artificial Intelligence for State of Charge Estimation of Lithium-Ion Batteries",[2317,2318,2319,2320,2321,2322,2323,2324],"Ho Tung Jeremy Chan","Jelena Rubeša-Zrim","Franz Pichler","Amil Salihi","Adam Mourad","Ilija Šimić","Kristina Časni","Eduardo Enrique Veas",{"@type":89,"@id":2326,"schema:additionalType":2217,"schema:identifier":2327,"schema:headline":2328,"schema:author":2329,"schema:datePublished":397,"schema:isPartOf":471},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.apenergy.2025.127266","10.1016\u002Fj.apenergy.2025.127266","Lithium-ion batteries for space applications in low earth orbits: Promising Technologies and testing methods",[2330,2331,2332,2333,2334,2335,2336],"Elizaveta Yu. Evshchik","A.V. Shikhovtseva","Valery G. Kolmakov","V. I. Bugaev","R.L. Valeev","V. S. Voropaev","A.V. Levchenko",{"@type":89,"@id":2338,"schema:additionalType":2217,"schema:identifier":2339,"schema:headline":2340,"schema:author":2341,"schema:datePublished":397,"schema:isPartOf":2345},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ifacol.2025.12.331","10.1016\u002Fj.ifacol.2025.12.331","Uncertainty-Aware State of Charge Estimation for Lithium-Ion Batteries with Gated Recurrent Unit and Deep Evidential Regression",[2342,2343,2344],"Ashik E Rasul","Humaira Tasnim","Hyung-Jin Yoon","IFAC-PapersOnLine",{"@type":89,"@id":2347,"schema:additionalType":2217,"schema:identifier":2348,"schema:headline":2349,"schema:author":2350,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Facait67930.2025.11522121","10.1109\u002Facait67930.2025.11522121","SOC Estimation for Lithium-Ion Batteries Based on Fusion of Basisformer and Wavelet Transforms",[2351,1427,2352,2353,2354,2355],"Ziyu Yang","Qiyan Zhao","Yanmei Li","Qiao Zuo","Mengyuan Tian",{"@type":89,"@id":2357,"schema:additionalType":2217,"schema:identifier":2358,"schema:headline":2359,"schema:author":2360,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3539528","10.1109\u002Faccess.2025.3539528","Data-Driven Approaches for Estimation of EV Battery SoC and SoH: A Review",[2361,2362,2363,2364,2365,2366,2367],"Shahid Gulzar Padder","Jayesh Ambulkar","Atul Banotra","Sudhakar Modem","Sidharth Maheshwari","Kolleboyina Jayaramulu","Chinmoy Kundu",{"@type":89,"@id":2369,"schema:additionalType":2217,"schema:identifier":2370,"schema:headline":2371,"schema:author":2372,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3594129","10.1109\u002Faccess.2025.3594129","NMPC-Based Performance Evaluation of Active Balancing Networks of Li-ion Batteries for Overnight EV Charging",[2373,256,257,258],"Muhammad Azmat Ullah",{"@type":89,"@id":2375,"schema:additionalType":2217,"schema:identifier":2376,"schema:headline":2377,"schema:author":2378,"schema:datePublished":397,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2025.3600641","10.1109\u002Faccess.2025.3600641","A Novel Method for Estimating the State of Charge of Lithium Batteries Adopts a Bidirectional Gated Recurrent Unit With Attention Mechanism and Piecewise Estimation",[2379,2380,2381,2382,2383],"Weida Cheng","Shuo Sun","Hang Yin","Zongliang Wang","Wei Ju Cai",{"@type":89,"@id":2385,"schema:additionalType":2217,"schema:identifier":2386,"schema:headline":2387,"schema:author":2388,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fecce58356.2025.11260295","10.1109\u002Fecce58356.2025.11260295","Enhancing Energy Intelligence: Transfer-Learning-Enabled Transformer Models for Onboard SOC Estimation Using EV CAN Data",[1335,2389,2390],"David H. Robertson","Geoffrey Chavez",{"@type":89,"@id":2392,"schema:additionalType":2217,"schema:identifier":2393,"schema:headline":2394,"schema:author":2395,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fgpecom65896.2025.11061982","10.1109\u002Fgpecom65896.2025.11061982","Enchancing SOC Estimation Hybrid RNN Models for Li-Ion Batteries Under Various Temperatures",[2396,2397,2398,2399,2400,2401],"Ertuğrul Sert","Bera Küçükkurt","Atalay Bektaş","Umut Baran Ekinci","Fatih Ekinci","Koray Açıcı",{"@type":89,"@id":2403,"schema:additionalType":2217,"schema:identifier":2404,"schema:headline":2405,"schema:author":2406,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fi-pact65952.2025.11307833","10.1109\u002Fi-pact65952.2025.11307833","ACO-LSTM Driven Prediction of Lithium-Ion Battery State-of-Charge: a Hybrid Approach",[2407,2408,2409,2410,2411,2412],"Reshma Gopi Remabhai Amma","Chitra Annamalai","Maher Al‐Greer","Razia Sultana .W","Indra Gandhi V","Pujari Harish Kumar",{"@type":89,"@id":2414,"schema:additionalType":2217,"schema:identifier":2415,"schema:headline":2416,"schema:author":2417,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficeccc65144.2025.11063996","10.1109\u002Ficeccc65144.2025.11063996","A Comparative Analysis of DNN Architectures for State of Charge Estimation Using Deep Neural Networks in Electric Vehicles",[319,2418,2419,2420,2421,2422],"S Tejaswini","B S Manasvi","V Meghana","N Pragathi","S Neha",{"@type":89,"@id":2424,"schema:additionalType":2217,"schema:identifier":2425,"schema:headline":2426,"schema:author":2427,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.2172\u002F3363952","10.2172\u002F3363952","Impact of Aging on the Safety of Lithium-Ion Batteries and Implications for Diagnostics",[2428,441,2429],"Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)","Energy Storage Division (OE-30)",{"@type":89,"@id":2431,"schema:additionalType":2217,"schema:identifier":2432,"schema:headline":2433,"schema:author":2434,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.23919\u002Fdate64628.2025.10993233","10.23919\u002Fdate64628.2025.10993233","Coupling Neural Networks and Physics Equations For Li-Ion Battery State-of-Charge Prediction",[2435,2436,2437,2438,2439,2440],"Giovanni Pollo","Alessio Burrello","Enrico Macii","Massimo Poncino","Sara Vinco","Daniele Jahier Pagliari",{"@type":89,"@id":2442,"schema:additionalType":2217,"schema:identifier":2443,"schema:headline":2444,"schema:author":2445,"schema:datePublished":397,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries11010032","10.3390\u002Fbatteries11010032","State of Charge and State of Health Estimation in Electric Vehicles: Challenges, Approaches and Future Directions",[2446,2447,2448,2449],"Babatunde Soyoye","Indranil Bhattacharya","Mary Vinolisha Antony Dhason","Trapa Banik",{"@type":89,"@id":2451,"schema:additionalType":2217,"schema:identifier":2452,"schema:headline":2453,"schema:author":2454,"schema:datePublished":397,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2510.27369","10.48550\u002Farxiv.2510.27369","From the Rock Floor to the Cloud: A Systematic Survey of State-of-the-Art NLP in Battery Life Cycle",[2455,2456,2457,2458,2459,2460,2461,2462],"Tosin Adewumi","Martin H. Karlsson","Marcus Liwicki","Mikael Sjödahl","Lama Alkhaled","Rihab Gargouri","Nudrat Habib","Franz Hennie",{"@type":89,"@id":2464,"schema:additionalType":2217,"schema:identifier":2465,"schema:headline":2466,"schema:author":2467,"schema:datePublished":1057,"schema:isPartOf":2474},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41597-024-03859-z","10.1038\u002Fs41597-024-03859-z","A multi-stage lithium-ion battery aging dataset using various experimental design methodologies",[2468,2469,2470,2471,2472,2473],"Florian Stroebl","Ronny Petersohn","Barbara Schricker","Florian Schaeufl","Oliver S. Bohlen","Herbert Palm","Scientific Data",{"@type":89,"@id":2476,"schema:additionalType":2217,"schema:identifier":2477,"schema:headline":2478,"schema:author":2479,"schema:datePublished":1057,"schema:isPartOf":434},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fwevj15040131","10.3390\u002Fwevj15040131","A Review of Lithium-Ion Battery State of Charge Estimation Methods Based on Machine Learning",[515,516,2480],"Baoming Chen",{"@type":89,"@id":2482,"schema:additionalType":2217,"schema:identifier":2483,"schema:headline":2484,"schema:author":2485,"schema:datePublished":1057,"schema:isPartOf":2474},"https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41597-024-03831-x","10.1038\u002Fs41597-024-03831-x","Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC\u002FC-SiO cell",[2486,2487],"Matthias Luh","Thomas Blank",{"@type":89,"@id":2489,"schema:additionalType":2217,"schema:identifier":2490,"schema:headline":2491,"schema:author":2492,"schema:datePublished":1057,"schema:isPartOf":434},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fwevj15120562","10.3390\u002Fwevj15120562","An RNN-CNN-Based Parallel Hybrid Approach for Battery State of Charge (SoC) Estimation Under Various Temperatures and Discharging Cycle Considering Noisy Conditions",[2493,2494,2495,2496],"Md Shahriar Nazim","Md. Minhazur Rahman","Md. Ibne Joha","Yeong Min Jang",{"@type":89,"@id":2498,"schema:additionalType":2217,"schema:identifier":2499,"schema:headline":2500,"schema:author":2501,"schema:datePublished":1057,"schema:isPartOf":2504},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11431-024-2765-2","10.1007\u002Fs11431-024-2765-2","Prior-based patch-level representation learning for electric vehicle battery state-of-charge estimation across a wide temperature scope",[2502,2503],"SongTao Ye","Dou An","Science China Technological Sciences",{"@type":89,"@id":2506,"schema:additionalType":2217,"schema:identifier":2507,"schema:headline":2508,"schema:author":2509,"schema:datePublished":1057,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2024.112107","10.1016\u002Fj.est.2024.112107","Hybrid and combined states estimation approaches for lithium-ion battery management system: Advancement, challenges and future directions",[1888,2510,1890,2511,2512,1887],"M. S. Abd Rahman","Shaheer Ansari","Sheikh Tanzim Meraj",{"@type":89,"@id":2514,"schema:additionalType":2217,"schema:identifier":2515,"schema:headline":2516,"schema:author":2517,"schema:datePublished":1057,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen17225746","10.3390\u002Fen17225746","Lithium-Ion Battery Health Management and State of Charge (SOC) Estimation Using Adaptive Modelling Techniques",[2518,2519,2520,2521],"Houda Bouchareb","Khadija Saqli","N.K. M’Sirdi","Mohammed Oudghiri Bentaie",{"@type":89,"@id":2523,"schema:additionalType":2217,"schema:identifier":2524,"schema:headline":2525,"schema:author":2526,"schema:datePublished":1057,"schema:isPartOf":434},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fwevj15110532","10.3390\u002Fwevj15110532","Adaptive Joint Sigma-Point Kalman Filtering for Lithium-Ion Battery Parameters and State-of-Charge Estimation",[2518,2519,2520,2521],{"@type":89,"@id":2528,"schema:additionalType":2217,"schema:identifier":2529,"schema:headline":2530,"schema:author":2531,"schema:datePublished":1057,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2024.3441517","10.1109\u002Faccess.2024.3441517","Toward an Intelligent Diagnosis and Prognostic Health Management System for Autonomous Electric Vehicle Powertrains: A Novel Distributed Intelligent Digital Twin-Based Architecture",[2532,2533,2534,2535,2536,2537],"Hicham El Hadraoui","Nada Ouahabi","Nabil El Bazi","Oussama Laayati","Mourad Zegrari","Ahmed Chebak",{"@type":89,"@id":2539,"schema:additionalType":2217,"schema:identifier":2540,"schema:headline":2541,"schema:author":2542,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Facdsa59508.2024.10467375","10.1109\u002Facdsa59508.2024.10467375","State-of-Charge assessment of Li-ion battery using Genetic Algorithm-Neural Network (GANN)",[2543,2544,2545,2546,2547],"Ermanno Cardelli","Fabio Crescimbini","Francesco Riganti Fulginei","Michele Quercio","Lorenzo Sabino",{"@type":89,"@id":2549,"schema:additionalType":2217,"schema:identifier":2550,"schema:headline":2551,"schema:author":2552,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficccnt61001.2024.10725170","10.1109\u002Ficccnt61001.2024.10725170","Lithium-Ion Battery SoC Prediction Using Deep Learning",[2553,2554,2555,2556,2557],"Mouleshwar Saravanan","Jujare AjayKumar","K.S. Arun","S P Sibhiecharan","T. V. Ananthan",{"@type":89,"@id":2559,"schema:additionalType":2217,"schema:identifier":2560,"schema:headline":2561,"schema:author":2562,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficces63552.2024.10859757","10.1109\u002Ficces63552.2024.10859757","Next-Gen EV Battery State Prediction",[2563,2564,2565,2566,2567,2568],"R. Tamilkodi","N. Santha Raju","Vajjala Omkar","K. Giridhar Sai","Kunche Prasanth","Nallabothula Chandra",{"@type":89,"@id":2570,"schema:additionalType":2217,"schema:identifier":2571,"schema:headline":2572,"schema:author":2573,"schema:datePublished":1057,"schema:isPartOf":2577},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fojia.2024.3354899","10.1109\u002Fojia.2024.3354899","Advancing Lithium-Ion Battery Health Prognostics With Deep Learning: A Review and Case Study",[2574,2575,2576],"Mohamed Massaoudi","Haitham Abu‐Rub","Ali Ghrayeb","IEEE Open Journal of Industry Applications",{"@type":89,"@id":2579,"schema:additionalType":2217,"schema:identifier":2580,"schema:headline":2581,"schema:author":2582,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fsefet61574.2024.10718061","10.1109\u002Fsefet61574.2024.10718061","Impact of Activation Functions in Deep Learning Based State of Charge Estimation for Batteries",[1346,1347,2583],"Hassan Haes Alhelou",{"@type":89,"@id":2585,"schema:additionalType":2217,"schema:identifier":2586,"schema:headline":2587,"schema:author":2588,"schema:datePublished":1057,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2024.3354551","10.1109\u002Ftte.2024.3354551","Decentralized Deep-Learning Approach for Lithium-Ion Batteries State of Health Forecasting Using Federated Learning",[1453,1455,1456,1457],{"@type":89,"@id":2590,"schema:additionalType":2217,"schema:identifier":2591,"schema:headline":2592,"schema:author":2593,"schema:datePublished":1057,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2024.3430540","10.1109\u002Ftte.2024.3430540","Antidisturbance State-of-Charge Estimation for Lithium-Ion Batteries Using Nonlinear Extended State Observers",[565,142,866,145],{"@type":89,"@id":2595,"schema:additionalType":2217,"schema:identifier":2596,"schema:headline":2597,"schema:author":2598,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.2172\u002F2585186","10.2172\u002F2585186","Impact of Aging on the Safety of Lithium-ion Batteries",[2428,441,2599],"Other (DOE)",{"@type":89,"@id":2601,"schema:additionalType":2217,"schema:identifier":2602,"schema:headline":2597,"schema:author":2603,"schema:datePublished":1057},"https:\u002F\u002Fdoi.org\u002F10.2172\u002F2585848","10.2172\u002F2585848",[2428,441,2429],{"@type":89,"@id":2605,"schema:additionalType":2217,"schema:identifier":2606,"schema:headline":2607,"schema:author":2608,"schema:datePublished":1057,"schema:isPartOf":2287},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fapp14146240","10.3390\u002Fapp14146240","Tiny Machine Learning Battery State-of-Charge Estimation Hardware Accelerated",[2609,2610],"Danilo Pietro Pau","Alberto Aniballi",{"@type":89,"@id":2612,"schema:additionalType":2217,"schema:identifier":2613,"schema:headline":2433,"schema:author":2614,"schema:datePublished":1057,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2412.16724","10.48550\u002Farxiv.2412.16724",[2435,2436,2437,2438,2439,2440],{"@type":89,"@id":2616,"schema:additionalType":2217,"schema:identifier":2617,"schema:headline":2618,"schema:author":2619,"schema:datePublished":1408,"schema:isPartOf":2629},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12541-023-00832-5","10.1007\u002Fs12541-023-00832-5","Data-Driven Methods for Predicting the State of Health, State of Charge, and Remaining Useful Life of Li-Ion Batteries: A Comprehensive Review",[2620,2621,2622,2623,2624,2625,2626,2627,2628],"Eunsong Kim","Minseon Kim","Juo Kim","Joonchul Kim","Junghwan Park","Kyoung‐Tak Kim","Joung‐Hu Park","Taesic Kim","Kyoungmin Min","International Journal of Precision Engineering and Manufacturing",{"@type":89,"@id":2631,"schema:additionalType":2217,"schema:identifier":2632,"schema:headline":2633,"schema:author":2634,"schema:datePublished":1408,"schema:isPartOf":389},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Felectronics12061478","10.3390\u002Felectronics12061478","Parameter Identification of Li-ion Batteries: A Comparative Study",[2635,2636,2637],"Shahenda M. Abdelhafiz","Mohammed E. Fouda","Ahmed Gomaa Radwan",{"@type":89,"@id":2639,"schema:additionalType":2217,"schema:identifier":2640,"schema:headline":2641,"schema:author":2642,"schema:datePublished":1408,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen16031194","10.3390\u002Fen16031194","Improved Digital Twin of Li-Ion Battery Based on Generic MATLAB Model",[2643,2644,2645,2646,2647],"Juraj Biľanský","Milan Lacko","Marek Pástor","Adrián Marcinek","František Ďurovský",{"@type":89,"@id":2649,"schema:additionalType":2217,"schema:identifier":2650,"schema:headline":2651,"schema:author":2652,"schema:datePublished":1408,"schema:isPartOf":2658},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fvehicles5020030","10.3390\u002Fvehicles5020030","Intelligent Deep Learning Estimators of a Lithium-Ion Battery State of Charge Design and MATLAB Implementation—A Case Study",[2653,2654,2655,2656,2657],"Nicolae Tudoroiu","Mohammed Zaheeruddin","Roxana-Elena Tudoroiu","Mihai Sorin Radu","Hana Chammas","Vehicles",{"@type":89,"@id":2660,"schema:additionalType":2217,"schema:identifier":2661,"schema:headline":2662,"schema:author":2663,"schema:datePublished":1408,"schema:isPartOf":2671},"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11708-023-0891-7","10.1007\u002Fs11708-023-0891-7","Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery",[2664,2665,2666,2667,2668,2669,2670],"Nan Qi","Kang Yan","Yajuan Yu","Rui Li","Rong Huang","Lai Chen","Yuefeng Su","Frontiers in Energy",{"@type":89,"@id":2673,"schema:additionalType":2217,"schema:identifier":2674,"schema:headline":2675,"schema:author":2676,"schema:datePublished":1408,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2023.3301989","10.1109\u002Faccess.2023.3301989","A Comprehensive Review of Research Hotspots on Battery Management Systems for UAVs",[2677,2678,2679,2680],"Shiqin Jiao","Guiyang Zhang","Mei Zhou","Guoqi Li",{"@type":89,"@id":2682,"schema:additionalType":2217,"schema:identifier":2683,"schema:headline":2684,"schema:author":2685,"schema:datePublished":1408,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2023.3337215","10.1109\u002Faccess.2023.3337215","Transfer Learning Techniques for the Lithium-Ion Battery State of Charge Estimation",[2686,2687,2688,2689],"Panagiotis Eleftheriadis","Spyridon Giazitzis","Sonia Leva","Emanuèle Ogliari",{"@type":89,"@id":2691,"schema:additionalType":2217,"schema:identifier":2692,"schema:headline":2693,"schema:author":2694,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fapet59977.2023.10489281","10.1109\u002Fapet59977.2023.10489281","SOC Estimation for Lithium-Ion Battery Charging and Discharging Based on AMLRLS and MIAEKF Algorithm",[2695,2696,2697,2698,2699,2700],"Huang Xiaohua","Guodong Li","Chong Xu","Shengzhong Liu","Xiaokang Wu","Wei Bin",{"@type":89,"@id":2702,"schema:additionalType":2217,"schema:identifier":2703,"schema:headline":2704,"schema:author":2705,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcodit58514.2023.10284459","10.1109\u002Fcodit58514.2023.10284459","State of Health Prediction of Lithium-Ion Battery Using Machine Learning Algorithms",[2706,1534,1538,2707],"Jamila Hemdani","Abdelkader Châari",{"@type":89,"@id":2709,"schema:additionalType":2217,"schema:identifier":2710,"schema:headline":2711,"schema:author":2712,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fiecon51785.2023.10311754","10.1109\u002Fiecon51785.2023.10311754","Robust State of Charge Estimation for Battery with Self-Adaptive Super Twisting Sliding Mode Observer",[565,142,2713,145],"Chengrui Li",{"@type":89,"@id":2715,"schema:additionalType":2217,"schema:identifier":2716,"schema:headline":2717,"schema:author":2718,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fpowertech55446.2023.10202982","10.1109\u002Fpowertech55446.2023.10202982","State of Charge Estimation Using a Nonlinear Autoregressive with Exogenous Input Neural Network",[2686,2719,2720,2689,2688],"Filippo Lodigiani","Jacopo Bruneri",{"@type":89,"@id":2722,"schema:additionalType":2217,"schema:identifier":2723,"schema:headline":2724,"schema:author":2725,"schema:datePublished":1408,"schema:isPartOf":1015},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftte.2023.3310159","10.1109\u002Ftte.2023.3310159","Predicting State-of-Charge Using Gradient-Boosted SVR Ensemble Technique for Lithium Ion Battery Used in EVs",[1445,1447,1446],{"@type":89,"@id":2727,"schema:additionalType":2217,"schema:identifier":2728,"schema:headline":2729,"schema:author":2730,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.23919\u002Fccc58697.2023.10239712","10.23919\u002Fccc58697.2023.10239712","An Improved Whale Optimization Algorithm Based on Nonlinear Convergence Factors and Differential Evolution",[2293,1773,2731,2732],"Xubin Qin","Jing Yan",{"@type":89,"@id":2734,"schema:additionalType":2217,"schema:identifier":2735,"schema:headline":2736,"schema:author":2737,"schema:datePublished":1408},"https:\u002F\u002Fdoi.org\u002F10.23919\u002Fccc58697.2023.10241021","10.23919\u002Fccc58697.2023.10241021","State of Charge Estimation Based on SMA-RELM and Kalman Filter",[2738,1773,1774,2294],"Shimeng Huang",{"@type":89,"@id":2740,"schema:additionalType":2217,"schema:identifier":2741,"schema:headline":2742,"schema:author":2743,"schema:datePublished":1408,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries9070364","10.3390\u002Fbatteries9070364","Model-Based State-of-Charge and State-of-Health Estimation Algorithms Utilizing a New Free Lithium-Ion Battery Cell Dataset for Benchmarking Purposes",[2744,2745],"Steven Neupert","Julia Kowal",{"@type":89,"@id":2747,"schema:additionalType":2217,"schema:identifier":2748,"schema:headline":2749,"schema:author":2750,"schema:datePublished":1408,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries9070385","10.3390\u002Fbatteries9070385","Lithium–Ion Battery Data: From Production to Prediction",[2751,370,2752],"Marwan Hassini","Pascal Venet",{"@type":89,"@id":2754,"schema:additionalType":2217,"schema:identifier":2755,"schema:headline":2756,"schema:author":2757,"schema:datePublished":1408,"schema:isPartOf":1731},"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2309.03607","10.48550\u002Farxiv.2309.03607","Your Battery Is a Blast! Safeguarding Against Counterfeit Batteries with Authentication",[2758,2759],"Francesco Marchiori","Mauro Conti",{"@type":89,"@id":2761,"schema:additionalType":2217,"schema:identifier":2762,"schema:headline":2763,"schema:author":2764,"schema:datePublished":1750,"schema:isPartOf":2769},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fmachines10100912","10.3390\u002Fmachines10100912","Deep Learning in the State of Charge Estimation for Li-Ion Batteries of Electric Vehicles: A Review",[2765,2766,2767,2768],"Dawei Zhang","Chen Zhong","Peijuan Xu","Yiyang Tian","Machines",{"@type":89,"@id":2771,"schema:additionalType":2217,"schema:identifier":2772,"schema:headline":2773,"schema:author":2774,"schema:datePublished":1750,"schema:isPartOf":353},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbatteries8110219","10.3390\u002Fbatteries8110219","Smart Battery Management Technology in Electric Vehicle Applications: Analytical and Technical Assessment toward Emerging Future Directions",[1888,2775,2511,2776,2777,2778,1367,2779,2780,2781,2782],"Md. Sazal Miah","Safat B. Wali","Taskin Jamal","Rajvikram Madurai Elavarasan","Musaab Mohammed Ali","Mahidur R. Sarker","Ahmed Aljanad","Nadia M. L. Tan",{"@type":89,"@id":2784,"schema:additionalType":2217,"schema:identifier":2785,"schema:headline":2786,"schema:author":2787,"schema:datePublished":1750,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2022.105752","10.1016\u002Fj.est.2022.105752","Deep learning enabled state of charge, state of health and remaining useful life estimation for smart battery management system: Methods, implementations, issues and prospects",[1888,2511,2775,2512,2788,2789,1887,1892,2790],"Kamrul Hasan","ASM Shihavuddin","Aini Hussain",{"@type":89,"@id":2792,"schema:additionalType":2217,"schema:identifier":2793,"schema:headline":2794,"schema:author":2795,"schema:datePublished":1750,"schema:isPartOf":2797},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcodit55151.2022.9804048","10.1109\u002Fcodit55151.2022.9804048","Prediction of aging electric vehicle battery by multi-physics modeling and deep learning method",[2706,1534,2796,1538,775,2707],"Moêz Soltani","2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)",{"@type":89,"@id":2799,"schema:additionalType":2217,"schema:identifier":2800,"schema:headline":2801,"schema:author":2802,"schema:datePublished":1750,"schema:isPartOf":2809},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fi-smac55078.2022.9987282","10.1109\u002Fi-smac55078.2022.9987282","AI and IoT-based Electric Vehicle Monitoring System",[2803,2804,2805,2806,2807,2808],"M. Bharathi","K. Geetha","P. K Mani.","G. Nixon Samuel Vijayakumar","Karthick Srinivasan","Kallakunta Ravi Kumar","2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)",{"@type":89,"@id":2811,"schema:additionalType":2217,"schema:identifier":2812,"schema:headline":2813,"schema:author":2814,"schema:datePublished":1750,"schema:isPartOf":2822},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficosec54921.2022.9952044","10.1109\u002Ficosec54921.2022.9952044","IoT-based Battery Management System by Deploying an Machine Learning Model",[2815,2816,2817,2818,2819,2820,2821],"Abhijith Prabha","S. Saravanan","S. Balaji","K V Malini","Kaushalya Thopate","T. Sivakami","M. Siva Ramkumar","2022 3rd International Conference on Smart Electronics and Communication (ICOSEC)",{"@type":89,"@id":2824,"schema:additionalType":2217,"schema:identifier":2825,"schema:headline":2826,"schema:author":2827,"schema:datePublished":1750,"schema:isPartOf":2830},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fmysurucon55714.2022.9972355","10.1109\u002Fmysurucon55714.2022.9972355","Comparative Analysis on Deep Learning Methods to Estimate the State of Charge in Li-ion Battery",[2828,2829],"Vijay Vignesh S","A. Suyampulingam","2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon)",{"@type":89,"@id":2832,"schema:additionalType":2217,"schema:identifier":2833,"schema:headline":2834,"schema:author":2835,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Foncon56984.2022.10127051","10.1109\u002Foncon56984.2022.10127051","Development of a Machine Learning Technique to Accurately Estimate Battery State of Charge",[2836,2837],"Varsha Pendyala","Nishanth Gadiyar",{"@type":89,"@id":2839,"schema:additionalType":2217,"schema:identifier":2840,"schema:headline":2841,"schema:author":2842,"schema:datePublished":1750},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fsynergymed55767.2022.9941407","10.1109\u002Fsynergymed55767.2022.9941407","Bayesian Hyperparameter Optimization of Stacked Long Short-Term Memory Neural Network for the State of Charge Estimation",[2686,2688,2689],{"@type":89,"@id":2844,"schema:additionalType":2217,"schema:identifier":2845,"schema:headline":2846,"schema:author":2847,"schema:datePublished":1926,"schema:isPartOf":2852},"https:\u002F\u002Fdoi.org\u002F10.1016\u002FJ.EGYAI.2021.100081","10.1016\u002Fj.egyai.2021.100081","Lithium-ion battery data and where to find it",[2848,2849,2850,2851],"Gonçalo dos Reis","Calum Strange","Mohit Yadav","Xiang Li","Energy and AI",{"@type":89,"@id":2854,"schema:additionalType":2217,"schema:identifier":2855,"schema:headline":2856,"schema:author":2857,"schema:datePublished":1926,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002FEN14092371","10.3390\u002Fen14092371","Analysis of Synthetic Voltage vs. Capacity Datasets for Big Data Li-ion Diagnosis and Prognosis",[2858,2859],"Matthieu Dubarry","David Beck",{"@type":89,"@id":2861,"schema:additionalType":2217,"schema:identifier":2862,"schema:headline":2863,"schema:author":2864,"schema:datePublished":1926,"schema:isPartOf":398},"https:\u002F\u002Fdoi.org\u002F10.3390\u002Fen14217064","10.3390\u002Fen14217064","FPGA Implementation of an Ant Colony Optimization Based SVM Algorithm for State of Charge Estimation in Li-Ion Batteries",[2865,2866,2867],"Mattia Stighezza","Valentina Bianchi","Ilaria De Munari",{"@type":89,"@id":2869,"schema:additionalType":2217,"schema:identifier":2870,"schema:headline":2871,"schema:author":2872,"schema:datePublished":1926,"schema:isPartOf":2874},"https:\u002F\u002Fdoi.org\u002F10.1021\u002Facsenergylett.1c00743","10.1021\u002Facsenergylett.1c00743","ENPOLITE: Comparing Lithium-Ion Cells across Energy, Power, Lifetime, and Temperature",[1414,1416,1417,441,2873,1418,1419],"Peter M. Attia","ACS Energy Letters",{"@type":89,"@id":2876,"schema:additionalType":2217,"schema:identifier":2877,"schema:headline":2878,"schema:author":2879,"schema:datePublished":1926,"schema:isPartOf":2884},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Feptc53413.2021.9663884","10.1109\u002Feptc53413.2021.9663884","Investigation of Thermoelectric Cooling for a Competition Electric Vehicle",[2880,2881,2882,2883],"Mark Takehana","Kunlachat Kangkorn","Jonggyu Lee","Yoonjin Won","2021 IEEE 23rd Electronics Packaging Technology Conference (EPTC)",{"@type":89,"@id":2886,"schema:additionalType":2217,"schema:identifier":2887,"schema:headline":2888,"schema:author":2889,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec51675.2021.9490043","10.1109\u002Fitec51675.2021.9490043","Accurate Surface Temperature Estimation of Lithium-Ion Batteries Using Feedforward and Recurrent Artificial Neural Networks",[2890,901,2152,2154],"Mina Naguib",{"@type":89,"@id":2892,"schema:additionalType":2217,"schema:identifier":2893,"schema:headline":2894,"schema:author":2895,"schema:datePublished":1926},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec51675.2021.9490163","10.1109\u002Fitec51675.2021.9490163","A Kalman Filter Based Battery State of Charge Estimation MATLAB Function",[2896,2897,2898,2899,901,2154],"Fauzia Khanum","Eduardo Louback","Federico Duperly","Colleen Jenkins",{"@type":89,"@id":2901,"schema:additionalType":2217,"schema:identifier":2902,"schema:headline":2903,"schema:author":2904,"schema:datePublished":2044,"schema:isPartOf":312},"https:\u002F\u002Fdoi.org\u002F10.1109\u002FACCESS.2020.2980961","10.1109\u002Faccess.2020.2980961","Machine Learning Applied to Electrified Vehicle Battery State of Charge and State of Health Estimation: State-of-the-Art",[2152,2905,901,2154],"Pawel Malysz",{"@type":89,"@id":2907,"schema:additionalType":2217,"schema:identifier":2908,"schema:headline":2909,"schema:author":2910,"schema:datePublished":2044,"schema:isPartOf":2914},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jclepro.2020.124110","10.1016\u002Fj.jclepro.2020.124110","Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends",[1888,1887,2790,2911,2912,2913,1886],"Afida Ayob","Mohamad Hanif Md Saad","Tahia Fahrin Karim","Journal of Cleaner Production",{"@type":89,"@id":2916,"schema:additionalType":2217,"schema:identifier":2917,"schema:headline":2918,"schema:author":2919,"schema:datePublished":2044,"schema:isPartOf":2923},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.firesaf.2020.103119","10.1016\u002Fj.firesaf.2020.103119","Progress on the research of fire behavior and fire protection of lithium ion battery",[2920,2921,2922],"Jinhua Sun","Binbin Mao","Qingsong Wang","Fire Safety Journal",{"@type":89,"@id":2925,"schema:additionalType":2217,"schema:identifier":2926,"schema:headline":2927,"schema:author":2928,"schema:datePublished":2122},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Feeeic.2019.8783862","10.1109\u002Feeeic.2019.8783862","Analysis of the main battery characterization techniques and experimental comparison of commercial 18650 Li-ion cells",[1762,1763,1765,1766],{"@type":89,"@id":2930,"schema:additionalType":2217,"schema:identifier":2931,"schema:headline":2932,"schema:author":2933,"schema:datePublished":2195,"schema:isPartOf":2938},"https:\u002F\u002Fdoi.org\u002F10.1016\u002FJ.RSER.2018.03.002","10.1016\u002Fj.rser.2018.03.002","The lithium-ion battery: State of the art and future perspectives",[2934,2935,2936,2937],"Ghassan Zubi","Rodolfo Dufo‐López","Mónica Carvalho","Güzay Paşaoğlu","Renewable and Sustainable Energy Reviews",{"@type":89,"@id":2940,"schema:additionalType":2217,"schema:identifier":2941,"schema:headline":2942,"schema:author":2943,"schema:datePublished":2195,"schema:isPartOf":2947},"https:\u002F\u002Fdoi.org\u002F10.1088\u002F1742-6596\u002F1124\u002F4\u002F041007","10.1088\u002F1742-6596\u002F1124\u002F4\u002F041007","Spectral Approach to Li–ion Batteries Degradation Rate Estimation",[2944,2945,2946],"E A Yusupova","Vladislav Gennadievich Malyshkin","Vadim Vladimirovich Davydov","Journal of Physics Conference Series",{"@type":89,"@id":2949,"schema:additionalType":2217,"schema:identifier":2950,"schema:headline":2951,"schema:author":2952,"schema:datePublished":2195,"schema:isPartOf":2956},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fjproc.2018.2793158","10.1109\u002Fjproc.2018.2793158","Energy Storage Technologies for Small Satellite Applications",[273,280,1943,2953,1941,274,2954,2955],"Marshall C. Smart","William Clark West","Gary S. Bolotin","Proceedings of the IEEE",{"@type":89,"@id":2958,"schema:additionalType":2217,"schema:identifier":2959,"schema:headline":2960,"schema:author":2961,"schema:datePublished":2211,"schema:isPartOf":2964},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitec-india.2017.8333899","10.1109\u002Fitec-india.2017.8333899","An electric circuit based EV battery model for runtime prediction and state of charge tracking",[2962,2963,1892],"Kaveh Sarrafan","Danny Sutanto","2017 IEEE Transportation Electrification Conference (ITEC-India)",{"@type":89,"@id":2966,"schema:additionalType":2967,"schema:identifier":2968,"schema:headline":2969,"schema:author":2970,"schema:datePublished":397},"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcodit66093.2025.11321681","UNCLEAR","10.1109\u002Fcodit66093.2025.11321681","Estimation of Lithium-Ion Battery State of Charge and Health Using LSTM Networks",[772,774,773,775],{"@type":89,"@id":2972,"schema:additionalType":2967,"schema:identifier":2973,"schema:headline":2974,"schema:author":2975,"schema:datePublished":1057,"schema:isPartOf":167},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.est.2024.110560","10.1016\u002Fj.est.2024.110560","Aging datasets of commercial lithium-ion batteries: A review",[2976,2977,2978,2979,2752],"Quentin Mayemba","Rémy Mingant","An Li","Gabriel Ducret",{"@type":2981,"schema:name":1414},"schema:Person","1.0","2026-09-27",1790617783759]