State of health estimation of lithium-ion battery with automatic feature extraction and self-attention learning mechanism

Accurate state of health (SOH) estimation is significantly important to ensure the safe and reliable operation of lithium-ion battery. Most existing data-driven estimation methods are based on feature engineering and rely heavily on expert experience and manual operation. However, manually extractin...

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Veröffentlicht in:	Journal of power sources Jg. 556; S. 232466
Hauptverfasser:	Jiang, Yiyue, Chen, Yuan, Yang, Fangfang, Peng, Weiwen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.02.2023
Schlagworte:	Automatic feature extraction Convolutional autoencoder Lithium-ion battery Self-attention mechanism State of health estimation State of health estimation Lithium-ion battery Self-attention mechanism Automatic feature extraction Convolutional autoencoder
ISSN:	0378-7753
Online-Zugang:	Volltext
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