Fault detection for lithium-ion batteries of electric vehicles with spatio-temporal autoencoder

Fault detection of lithium-ion battery packs is crucial for the safe operation of electric vehicles. Autoencoder, as an advanced machine learning method, has significant potential for improving anomaly detection accuracy. However, the autoencoders that just use temporal features in the reconstructio...

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Veröffentlicht in:	Applied energy Jg. 392; S. 125933
Hauptverfasser:	Li, Heng, Liu, Zhijun, Bin Kaleem, Muaaz, Duan, Lijun, Ruan, Siqi, Liu, Weirong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.08.2025
Schlagworte:	Battery pack energy Inconsistency lithium batteries spatial data Spatio-temporal autoencoder time series analysis Two-stage fault detection method Battery pack Inconsistency Two-stage fault detection method Spatio-temporal autoencoder
ISSN:	0306-2619
Online-Zugang:	Volltext
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