A hybrid deep learning approach for remaining useful life prediction of lithium-ion batteries based on discharging fragments
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DOI: 10.1016/j.apenergy.2023.122555
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- Chen, Guanxu & Yang, Fangfang & Peng, Weiwen & Fan, Yuqian & Lyu, Ximin, 2024. "State-of-health estimation for lithium-ion batteries based on Kullback–Leibler divergence and a retentive network," Applied Energy, Elsevier, vol. 376(PB).
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Keywords
Lithium-ion battery; Remaining useful life; Discharging fragment; Deep learning; Decomposition noise;All these keywords.
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