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Data-driven state-of-health estimation for lithium-ion battery based on aging features

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  1. Feng, Juqiang & Cai, Feng & Zhao, Yang & Zhang, Xing & Zhan, Xinju & Wang, Shunli, 2024. "A novel feature optimization and ensemble learning method for state-of-health prediction of mining lithium-ion batteries," Energy, Elsevier, vol. 299(C).
  2. Tao, Junjie & Wang, Shunli & Cao, Wen & Cui, Yixiu & Fernandez, Carlos & Guerrero, Josep M., 2024. "Innovative multiscale fusion – Antinoise extended long short-term memory neural network modeling for high precision state of health estimation of lithium-ion batteries," Energy, Elsevier, vol. 312(C).
  3. Chen, Junxiong & Hu, Yuanjiang & Zhu, Qiao & Rashid, Haroon & Li, Hongkun, 2023. "A novel battery health indicator and PSO-LSSVR for LiFePO4 battery SOH estimation during constant current charging," Energy, Elsevier, vol. 282(C).
  4. Zeng, Yi & Li, Yan & Zhou, Zhongkai & Zhao, Daduan & Yang, Tong & Ren, Pu & Zhang, Chenghui, 2025. "Joint estimation of state of charge and health utilizing fractional-order square-root cubature Kalman filtering with order scheduling strategy," Energy, Elsevier, vol. 320(C).
  5. Li, Xiaopeng & Zhao, Minghang & Zhong, Shisheng & Li, Junfu & Fu, Song & Yan, Zhiqi, 2024. "BMSFormer: An efficient deep learning model for online state-of-health estimation of lithium-ion batteries under high-frequency early SOC data with strong correlated single health indicator," Energy, Elsevier, vol. 313(C).
  6. Yao, Jiachi & Han, Te, 2023. "Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data," Energy, Elsevier, vol. 271(C).
  7. Giovane Ronei Sylvestrin & Joylan Nunes Maciel & Marcio Luís Munhoz Amorim & João Paulo Carmo & José A. Afonso & Sérgio F. Lopes & Oswaldo Hideo Ando Junior, 2025. "State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review," Energies, MDPI, vol. 18(3), pages 1-77, February.
  8. Tao, Junjie & Wang, Shunli & Cao, Wen & Fernandez, Carlos & Blaabjerg, Frede & Cheng, Liangwei, 2025. "An innovative multitask learning - Long short-term memory neural network for the online anti-aging state of charge estimation of lithium-ion batteries adaptive to varying temperature and current condi," Energy, Elsevier, vol. 314(C).
  9. Zhang, Wencan & He, Hancheng & Li, Taotao & Yuan, Jiangfeng & Xie, Yi & Long, Zhuoru, 2024. "Lithium-ion battery state of health prognostication employing multi-model fusion approach based on image coding of charging voltage and temperature data," Energy, Elsevier, vol. 296(C).
  10. Han, Xuewei & Yuan, Huimei & Wu, Lifeng, 2025. "Kalman filter anomaly values processing meta-model ensemble learning framework for Lithium-ion battery capacity prediction," Energy, Elsevier, vol. 322(C).
  11. Zhang, Jiarui & Mao, Lei & Liu, Zhongyong & Yu, Kun & Hu, Zhiyong, 2025. "A Bayesian transfer learning framework for assessing health status of Lithium-ion batteries considering individual battery operating states," Applied Energy, Elsevier, vol. 382(C).
  12. Ren, Fei & Cui, Naxin & Lu, Dong & Li, Changlong, 2025. "Temperature prediction of lithium-ion battery based on adaptive GRU transfer learning framework considering thermal effects decomposition characteristics," Energy, Elsevier, vol. 322(C).
  13. Yu He & Norasage Pattanadech & Kasiean Sukemoke & Minling Pan & Lin Chen, 2025. "The State of Health Estimation of Retired Lithium-Ion Batteries Using a Multi-Input Metabolic Gated Recurrent Unit," Energies, MDPI, vol. 18(5), pages 1-21, February.
  14. Zhang, Hao & Gao, Jingyi & Kang, Le & Zhang, Yi & Wang, Licheng & Wang, Kai, 2023. "State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network," Energy, Elsevier, vol. 283(C).
  15. Xue, Jingsong & Ma, Wentao & Feng, Xiaoyang & Guo, Peng & Guo, Yaosong & Hu, Xianzhi & Chen, Badong, 2023. "Stacking integrated learning model via ELM and GRU with mixture correntropy loss for robust state of health estimation of lithium-ion batteries," Energy, Elsevier, vol. 284(C).
  16. Chen, Si-Zhe & Liu, Jing & Yuan, Haoliang & Tao, Yibin & Xu, Fangyuan & Yang, Ling, 2025. "AM-MFF: A multi-feature fusion framework based on attention mechanism for robust and interpretable lithium-ion battery state of health estimation," Applied Energy, Elsevier, vol. 381(C).
  17. Li, Xiaoyu & Lyu, Mohan & Li, Kuo & Gao, Xiao & Liu, Caixia & Zhang, Zhaosheng, 2023. "Lithium-ion battery state of health estimation based on multi-source health indicators extraction and sparse Bayesian learning," Energy, Elsevier, vol. 282(C).
  18. Liu, Yanli & Wang, Junyi & Liu, Liqi, 2024. "Physics-informed reinforcement learning for probabilistic wind power forecasting under extreme events," Applied Energy, Elsevier, vol. 376(PA).
  19. Chang, Chun & Pan, Yaliang & Wang, Shaojin & Jiang, Jiuchun & Tian, Aina & Gao, Yang & Jiang, Yan & Wu, Tiezhou, 2024. "Fast EIS acquisition method based on SSA-DNN prediction model," Energy, Elsevier, vol. 288(C).
  20. Sun, Jinlei & Liu, Xinwei & Li, Xin & Chen, Siwen & Xing, Shiyou & Guo, Yilong, 2025. "State of health estimation of lithium-ion battery based on constant current charging time feature extraction and internal resistance compensation," Energy, Elsevier, vol. 315(C).
  21. Yu, Quanqing & Nie, Yuwei & Guo, Shanshan & Li, Junfu & Zhang, Chengming, 2024. "Machine learning enables rapid state of health estimation of each cell within battery pack," Applied Energy, Elsevier, vol. 375(C).
  22. Xia, Guangshu & Jia, Chenyu & Shi, Yuanhao & Jia, Jianfang & Pang, Xiaoqiong & Wen, Jie & Zeng, Jianchao, 2025. "Remaining useful life prediction of lithium-ion batteries by considering trend filtering segmentation under fuzzy information granulation," Energy, Elsevier, vol. 318(C).
  23. Zhu, Tao & Wang, Shunli & Fan, Yongcun & Hai, Nan & Huang, Qi & Fernandez, Carlos, 2024. "An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition," Energy, Elsevier, vol. 306(C).
  24. Xiong, Ran & Wang, Shunli & Huang, Qi & Yu, Chunmei & Fernandez, Carlos & Xiao, Wei & Jia, Jun & Guerrero, Josep M., 2024. "Improved cooperative competitive particle swarm optimization and nonlinear coefficient temperature decreasing simulated annealing-back propagation methods for state of health estimation of energy stor," Energy, Elsevier, vol. 292(C).
  25. Peng, Simin & Wang, Yujian & Tang, Aihua & Jiang, Yuxia & Kan, Jiarong & Pecht, Michael, 2025. "State of health estimation joint improved grey wolf optimization algorithm and LSTM using partial discharging health features for lithium-ion batteries," Energy, Elsevier, vol. 315(C).
  26. Zhang, Jiahao & Chen, Jiadui & Liu, Dan & He, Ling & Yang, Kai & Du, Feilong & Ye, Wen & Zhang, Xiaoxiang, 2025. "Multi-state joint prediction algorithm for lithium battery packs based on data-driven and physical models," Energy, Elsevier, vol. 322(C).
  27. Tang, Telu & Yang, Xiangguo & Li, Muheng & Li, Xin & Huang, Hai & Guan, Cong & Huang, Jiangfan & Wang, Yufan & Zhou, Chaobin, 2025. "Deep learning model-based real-time state-of-health estimation of lithium-ion batteries under dynamic operating conditions," Energy, Elsevier, vol. 317(C).
  28. Peng, Simin & Zhu, Junchao & Wu, Tiezhou & Tang, Aihua & Kan, Jiarong & Pecht, Michael, 2024. "SOH early prediction of lithium-ion batteries based on voltage interval selection and features fusion," Energy, Elsevier, vol. 308(C).
  29. Wang, Siwei & Xiao, Xinping & Ding, Qi, 2024. "A novel fractional system grey prediction model with dynamic delay effect for evaluating the state of health of lithium battery," Energy, Elsevier, vol. 290(C).
  30. Tang, Aihua & Xu, Yuchen & Hu, Yuanzhi & Tian, Jinpeng & Nie, Yuwei & Yan, Fuwu & Tan, Yong & Yu, Quanqing, 2024. "Battery state of health estimation under dynamic operations with physics-driven deep learning," Applied Energy, Elsevier, vol. 370(C).
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