Prognostics of battery cycle life in the early-cycle stage based on hybrid model
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DOI: 10.1016/j.energy.2021.119901
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- Zhang, Meng & Hu, Tao & Wu, Lifeng & Kang, Guoqing & Guan, Yong, 2021. "A method for capacity estimation of lithium-ion batteries based on adaptive time-shifting broad learning system," Energy, Elsevier, vol. 231(C).
- Cheng, Gong & Wang, Xinzhi & He, Yurong, 2021. "Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network," Energy, Elsevier, vol. 232(C).
- Zhang, Meng & Kang, Guoqing & Wu, Lifeng & Guan, Yong, 2022. "A method for capacity prediction of lithium-ion batteries under small sample conditions," Energy, Elsevier, vol. 238(PC).
- Fei, Zicheng & Yang, Fangfang & Tsui, Kwok-Leung & Li, Lishuai & Zhang, Zijun, 2021. "Early prediction of battery lifetime via a machine learning based framework," Energy, Elsevier, vol. 225(C).
- Chen, Dinghong & Zhang, Weige & Zhang, Caiping & Sun, Bingxiang & Cong, XinWei & Wei, Shaoyuan & Jiang, Jiuchun, 2022. "A novel deep learning-based life prediction method for lithium-ion batteries with strong generalization capability under multiple cycle profiles," Applied Energy, Elsevier, vol. 327(C).
- Fan, Xinyuan & Zhang, Weige & Sun, Bingxiang & Zhang, Junwei & He, Xitian, 2022. "Battery pack consistency modeling based on generative adversarial networks," Energy, Elsevier, vol. 239(PE).
- Yao, Fang & He, Wenxuan & Wu, Youxi & Ding, Fei & Meng, Defang, 2022. "Remaining useful life prediction of lithium-ion batteries using a hybrid model," Energy, Elsevier, vol. 248(C).
- He, Jiabei & Wu, Lifeng, 2023. "Cross-conditions capacity estimation of lithium-ion battery with constrained adversarial domain adaptation," Energy, Elsevier, vol. 277(C).
- Park, Jinhyeong & Kim, Kunwoo & Park, Seongyun & Baek, Jongbok & Kim, Jonghoon, 2021. "Complementary cooperative SOC/capacity estimator based on the discrete variational derivative combined with the DEKF for electric power applications," Energy, Elsevier, vol. 232(C).
- Zhang, Chen & Wang, Hongmin & Wu, Lifeng, 2023. "Life prediction model for lithium-ion battery considering fast-charging protocol," Energy, Elsevier, vol. 263(PE).
- Zhang, Jiusi & Jiang, Yuchen & Li, Xiang & Huo, Mingyi & Luo, Hao & Yin, Shen, 2022. "An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Yan, Lisen & Peng, Jun & Gao, Dianzhu & Wu, Yue & Liu, Yongjie & Li, Heng & Liu, Weirong & Huang, Zhiwu, 2022. "A hybrid method with cascaded structure for early-stage remaining useful life prediction of lithium-ion battery," Energy, Elsevier, vol. 243(C).
- Wu, Lifeng & Zhang, Yu, 2023. "Attention-based encoder-decoder networks for state of charge estimation of lithium-ion battery," Energy, Elsevier, vol. 268(C).
- Ma, Yan & Shan, Ce & Gao, Jinwu & Chen, Hong, 2022. "A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction," Energy, Elsevier, vol. 251(C).
- Seo, Minhwan & Song, Youngbin & Kim, Jake & Paek, Sung Wook & Kim, Gi-Heon & Kim, Sang Woo, 2021. "Innovative lumped-battery model for state of charge estimation of lithium-ion batteries under various ambient temperatures," Energy, Elsevier, vol. 226(C).
- Wang, Yixiu & Zhu, Jiangong & Cao, Liang & Gopaluni, Bhushan & Cao, Yankai, 2023. "Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction," Applied Energy, Elsevier, vol. 350(C).
- Dai, Houde & Wang, Jiaxin & Huang, Yiyang & Lai, Yuan & Zhu, Liqi, 2024. "Lightweight state-of-health estimation of lithium-ion batteries based on statistical feature optimization," Renewable Energy, Elsevier, vol. 222(C).
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Keywords
Lithium-ion battery; Remaining useful life; Early-cycle stage; Random forest; Artificial bee colony; General regression neural network;All these keywords.
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