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State-of-health estimation for lithium-ion batteries based ..:
Wentao Wang
;
Gaoyuan Yang
;
Muxi Li
...
https://www.frontiersin.org/articles/10.3389/fenrg.2023.1205165/full. , 2023
Link:
https://doi.org/10.3389/fenrg.2023.1205165
RT Journal T1 <Title>State-of-health estimation for lithium-ion batteries based on Bi-LSTM-AM and LLE feature extraction</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:b414b1b30a324efe8e2bd9d6e52a5fe8&Exemplar=1&LAN=DE A1 Wentao Wang A1 Gaoyuan Yang A1 Muxi Li A1 Zuoyi Yan A1 Lisheng Zhang A1 Hanqing Yu A1 Kaiyi Yang A1 Pengchang Jiang A1 Wei Hua A1 Yong Zhang A1 Bosong Zou A1 Kai Yang PB Frontiers Media S.A. YR 2023 K1 state of health K1 deep learning K1 attention mechanism K1 differential thermal voltammetry K1 locally linear embedding K1 General Works K1 A JF https://www.frontiersin.org/articles/10.3389/fenrg.2023.1205165/full LK http://dx.doi.org/https://doi.org/10.3389/fenrg.2023.1205165 DO https://doi.org/10.3389/fenrg.2023.1205165 SF ELIB - SuUB Bremen
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