锂电池联合状态估计与故障诊断方法研究

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摘要锂电池运行状态存在本体状态估计精度不足、电池组故障状态诊断难度较高的问题,因此本文提出一种考虑多因素影响的基于电热耦合模型的联合状态估计方法,并设计基于检测窗口和相关系数的多传感器故障诊断方法。针对锂电池本体状态,首先基于等效电路模型法构建锂电池的电热耦合模型;其次分析荷电状态（SOC）与健康状态（SOH）联合估计机理,采用扩展卡尔曼滤波算法（EKF）和粒子滤波算法（PF）,结合在线参数辨识方法,构建涵盖锂电池全生命周期的在线联合估计模型,实现精确联合状态估计。针对电池组故障状态,采用基于检测窗口和相关系数的多传感器故障诊断方法,实现了短路和开路故障的精准诊断与定位。实验结果验证了所提方法的有效性,所提方法能够准确反映电池运行状态,具有一定的工程应用价值。

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	王帮亭
	王莉
	郑聪
	杨善水
	葛彬欣

关键词 ：锂电池, 健康管理, 电热耦合模型, 联合状态估计, 多传感器故障诊断

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

收稿日期: 2024-12-23

基金资助:国家自然科学基金（U2341279）

作者简介: 王帮亭（1984—）,男,山西省晋中市人,博士,主要从事储能系统管理、电气系统电网设计和控制等方面的研究工作。

引用本文:

王帮亭, 王莉, 郑聪, 杨善水, 葛彬欣. 锂电池联合状态估计与故障诊断方法研究[J]. 电气技术, 2025, 26(7): 1-12. WANG Bangting, WANG Li, ZHENG Cong, YANG Shanshui, GE Binxin. Research on joint state estimation and fault diagnosis method for lithium battery. Electrical Engineering, 2025, 26(7): 1-12.

链接本文:

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

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