Prediction of Lithium Battery Voltage and State of Charge Using Multi-Head Attention BiLSTM Neural Network

Prediction of Lithium Battery Voltage and State of Charge Using Multi-Head Attention BiLSTM Neural Network

Predicting battery states such as the voltage and state of charge (SOC) can help us monitor lithium batteries more efficiently during usage. This study proposed a predictive model for the lithium battery voltage and SOC by combining a second-order RC equivalent circuit model with a multi-head attent...

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Bibliographic Details
Main Authors: Haiwen Xi, Taolin Lv, Jincheng Qin, Mingsheng Ma, Jingying Xie, Shigang Lu, Zhifu Liu
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
lithium battery prediction
equivalent circuit model
multi-head attention
bi-directional long short-term memory
Online Access:https://www.mdpi.com/2076-3417/15/6/3011
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