A Lithium-ion Battery State-of-Health Prediction Model Combining Convolutional Neural Network and Masked Multi-Head Attention Mechanism

The existing data-driven methods for the state of health (SOH) prediction of lithium-ion battery are limited by the data quantity, resulting in insufficient generalization performance, prediction accuracy and prediction stability. To tackle this challenge, this paper proposes a novel model, namely t...

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Veröffentlicht in:	IEEE transactions on energy conversion 2024-08, p.1-14
Hauptverfasser:	Xiao, Haipeng, Fu, Lijun, Shang, Chengya, Fan, Yaxiang, Bao, Xianqiang, Xu, Xinghua
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy CNN CNN-MMHA Convolutional neural networks Data models Data-driven methods Lithium-ion batteries Lithium-ion battery Long short term memory Mask mechanisms Multi-head attention Predictive models SOH Time series analysis
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