State-of-health estimation for lithium-ion batteries based on Bi-LSTM-AM and LLE feature extraction

State-of-health estimation for lithium-ion batteries based on Bi-LSTM-AM and LLE feature extraction

With the increasing demands for battery safety management, data-driven method becomes a promising solution for highly accurate battery state of health (SOH) estimation. However, the data-driven method faces problems of poor interpretability and high dependence on input features. This paper proposes...

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Bibliographic Details
Main Authors: Wentao Wang, Gaoyuan Yang, Muxi Li, Zuoyi Yan, Lisheng Zhang, Hanqing Yu, Kaiyi Yang, Pengchang Jiang, Wei Hua, Yong Zhang, Bosong Zou, Kai Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Energy Research
Subjects:
state of health
deep learning
attention mechanism
differential thermal voltammetry
locally linear embedding
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2023.1205165/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2023.1205165/full

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