锂电池联合状态估计与故障诊断方法研究

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Abstract The running state of lithium batteries has the problems of insufficient accuracy of ontology state estimation and high difficulty of battery pack fault state diagnosis. A joint state estimation method based on electrothermal coupling model considering the influence of multiple factors is proposed, and a multi-sensor fault diagnosis method based on detection window and correlation coefficient is designed. For the state of lithium battery, firstly, the electrothermal coupling model of lithium battery is constructed based on the equivalent circuit model method. Secondly, the mechanism of joint estimation of state of charge (SOC) and state of health (SOH) is analyzed. Using extended Kalman filter (EKF) and particle filter (PF), combined with online parameter identification method, an online joint estimation model covering the whole life cycle of lithium battery is constructed to achieve accurate joint state estimation. For the battery pack fault state, the multi-sensor fault diagnosis method based on detection window and correlation coefficient realizes the accurate diagnosis and location of short circuit and open circuit faults. The experimental results verify the effectiveness of the proposed method, which can accurately reflect the operation state of the battery, and has certain engineering application value.

Key words： lithium battery health management electro-thermal coupling model joint state estimation multi-sensor fault diagnosis

Received: 23 December 2024

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	Articles by authors
	WANG Bangting
	WANG Li
	ZHENG Cong
	YANG Shanshui
	GE Binxin

Cite this article:

WANG Bangting,WANG Li,ZHENG Cong等. Research on joint state estimation and fault diagnosis method for lithium battery[J]. Electrical Engineering, 2025, 26(7): 1-12.

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https://dqjs.cesmedia.cn/EN/Y2025/V26/I7/1

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