Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture
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- 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).
- 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).
- Tao Zhang & Yang Wang & Rui Ma & Yi Zhao & Mengjiao Shi & Wen Qu, 2023. "Prediction of Lithium Battery Health State Based on Temperature Rate of Change and Incremental Capacity Change," Energies, MDPI, vol. 16(22), pages 1-17, November.
- Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Qin, Taichun, 2019. "State of health estimation of lithium-ion batteries based on the constant voltage charging curve," Energy, Elsevier, vol. 167(C), pages 661-669.
- Gong, Dongliang & Gao, Ying & Kou, Yalin & Wang, Yurang, 2022. "State of health estimation for lithium-ion battery based on energy features," Energy, Elsevier, vol. 257(C).
- Zhang, Xugang & Gao, Xiyuan & Duan, Linchao & Gong, Qingshan & Wang, Yan & Ao, Xiuyi, 2025. "A novel method for state of health estimation of lithium-ion batteries based on fractional-order differential voltage-capacity curve," Applied Energy, Elsevier, vol. 377(PA).
- Jiwei Wang & Hao Li & Chunling Wu & Yujun Shi & Linxuan Zhang & Yi An, 2024. "State of Health Estimations for Lithium-Ion Batteries Based on MSCNN," Energies, MDPI, vol. 17(17), pages 1-21, August.
- Emil Petkovski & Iacopo Marri & Loredana Cristaldi & Marco Faifer, 2023. "State of Health Estimation Procedure for Lithium-Ion Batteries Using Partial Discharge Data and Support Vector Regression," Energies, MDPI, vol. 17(1), pages 1-14, December.
- Yang, Yongsong & Xu, Yuchen & Nie, Yuwei & Li, Jianming & Liu, Shizhuo & Zhao, Lijun & Yu, Quanqing & Zhang, Chengming, 2024. "Deep transfer learning enables battery state of charge and state of health estimation," Energy, Elsevier, vol. 294(C).
- 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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Keywords
lithium-ion battery; state of health; feature reconstruction; data-driven; Transformer-GRU; parallel architecture;All these keywords.
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