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State of health estimation of lithium-ion battery with improved radial basis function neural network

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  1. Li, Ziyang & Zhang, Xiangwen & Gao, Wei, 2024. "State of health estimation of lithium-ion battery during fast charging process based on BiLSTM-Transformer," Energy, Elsevier, vol. 311(C).
  2. 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).
  3. 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).
  4. Fang Guo & Guangshan Huang & Wencan Zhang & An Wen & Taotao Li & Hancheng He & Haolin Huang & Shanshan Zhu, 2023. "Lithium Battery State-of-Health Estimation Based on Sample Data Generation and Temporal Convolutional Neural Network," Energies, MDPI, vol. 16(24), pages 1-15, December.
  5. Liu, Xingtao & Tang, Qinbin & Feng, Yitian & Lin, Mingqiang & Meng, Jinhao & Wu, Ji, 2023. "Fast sorting method of retired batteries based on multi-feature extraction from partial charging segment," Applied Energy, Elsevier, vol. 351(C).
  6. 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.
  7. Hu, Dunan & Huang, Sheng & Wen, Zhen & Gu, Xiuquan & Lu, Jianguo, 2024. "A review on thermal runaway warning technology for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
  8. Farwah Ali Syed & Kwo-Ting Fang & Adiqa Kausar Kiani & Muhammad Shoaib & Muhammad Asif Zahoor Raja, 2025. "Design of Neuro-Stochastic Bayesian Networks for Nonlinear Chaotic Differential Systems in Financial Mathematics," Computational Economics, Springer;Society for Computational Economics, vol. 65(1), pages 241-270, January.
  9. Sun, Rongli & Chen, Junsheng & Li, Benchuan & Piao, Changhao, 2025. "State of health estimation for Lithium-ion batteries based on novel feature extraction and BiGRU-Attention model," Energy, Elsevier, vol. 319(C).
  10. Mouncef El Marghichi & Soufiane Dangoury & Younes zahrou & Azeddine Loulijat & Hamid Chojaa & Fahd A Banakhr & Mohamed I Mosaad, 2023. "Improving accuracy in state of health estimation for lithium batteries using gradient-based optimization: Case study in electric vehicle applications," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-24, November.
  11. 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).
  12. 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).
  13. Peng, Simin & Sun, Yunxiang & Liu, Dandan & Yu, Quanqing & Kan, Jiarong & Pecht, Michael, 2023. "State of health estimation of lithium-ion batteries based on multi-health features extraction and improved long short-term memory neural network," Energy, Elsevier, vol. 282(C).
  14. Gu, Xin & Li, Jinglun & Zhu, Yuhao & Wang, Yue & Mao, Ziheng & Shang, Yunlong, 2023. "A quick and intelligent screening method for large-scale retired batteries based on cloud-edge collaborative architecture," Energy, Elsevier, vol. 285(C).
  15. Wu, Ji & Wang, Jieming & Lin, Mingqiang & Meng, Jinhao, 2025. "Retired battery capacity screening based on deep learning with embedded feature smoothing under massive imbalanced data," Energy, Elsevier, vol. 318(C).
  16. Sun, Jing & Wang, Haitao, 2025. "State of health estimation for lithium-ion batteries based on optimal feature subset algorithm," Energy, Elsevier, vol. 322(C).
  17. Wang, Cong & Chen, Yunxia & Zhang, Qingyuan & Zhu, Jiaxiao, 2023. "Dynamic early recognition of abnormal lithium-ion batteries before capacity drops using self-adaptive quantum clustering," Applied Energy, Elsevier, vol. 336(C).
  18. 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).
  19. Lai, Xin & Yao, Yi & Tang, Xiaopeng & Zheng, Yuejiu & Zhou, Yuanqiang & Sun, Yuedong & Gao, Furong, 2023. "Voltage profile reconstruction and state of health estimation for lithium-ion batteries under dynamic working conditions," Energy, Elsevier, vol. 282(C).
  20. Lu, Zhenfeng & Fei, Zicheng & Wang, Benfei & Yang, Fangfang, 2024. "A feature fusion-based convolutional neural network for battery state-of-health estimation with mining of partial voltage curve," Energy, Elsevier, vol. 288(C).
  21. Chen, Liping & Xie, Siqiang & Lopes, António M. & Li, Huafeng & Bao, Xinyuan & Zhang, Chaolong & Li, Penghua, 2024. "A new SOH estimation method for Lithium-ion batteries based on model-data-fusion," Energy, Elsevier, vol. 286(C).
  22. 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).
  23. Pan, Rui & Liu, Tongshen & Huang, Wei & Wang, Yuxin & Yang, Duo & Chen, Jie, 2023. "State of health estimation for lithium-ion batteries based on two-stage features extraction and gradient boosting decision tree," Energy, Elsevier, vol. 285(C).
  24. Jun He & Xinyu Liu & Wentao Huang & Bohan Zhang & Zuoming Zhang & Zirui Shao & Zimu Mao, 2024. "Health State Assessment of Lithium-Ion Batteries Based on Multi-Health Feature Fusion and Improved Informer Modeling," Energies, MDPI, vol. 17(9), pages 1-18, April.
  25. 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).
  26. Bao, Zhengyi & Nie, Jiahao & Lin, Huipin & Jiang, Jiahao & He, Zhiwei & Gao, Mingyu, 2023. "A global–local context embedding learning based sequence-free framework for state of health estimation of lithium-ion battery," Energy, Elsevier, vol. 282(C).
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