温度和老化影响下的锂离子电池荷电状态和健康状态联合估计方法研究

doi:10.3901/JME.2024.18.266

摘要/Abstract

摘要： 锂离子电池被广泛应用于电动汽车、储能电站和电子产品，精确的荷电状态(State of charge, SOC)和健康状态(State of health, SOH)是其安全和高效应用的基础。然而，由于温度和老化状态变化引起的电池非线性动力学特性严重影响了状态估计的准确性。以三元锂离子电池为例开展研究：① 分析电池在不同老化阶段、温度和SOC区间下的开路电压行为特性，提出一种考虑老化、温度和SOC的开路电压模型；② 建立等效电路模型，提出一种基于多时间尺度扩展卡尔曼滤波算法(Multi-scale extended Kalman filter, MEKF)和衰减记忆的近似加权总体最小二乘算法(Fading memory approximate weighted total least squares, FMAWTLS)的电池SOC和SOH联合估计方法，其中，使用MEKF的宏观尺度估计模型参数、微观尺度估计SOC，使用FMAWTLS估计SOH；③ 应用不同老化状态和温度的电池数据开展算法验证，结果表明SOC和SOH的最大估计误差均小于3%。建立的开路电压模型和联合估计方法为温度和老化影响下的SOC和SOH估计提供了新的思路。

关键词: 锂离子电池, 荷电状态, 健康状态, 扩展卡尔曼滤波, 最小二乘法

Abstract: Lithium-ion batteries are widely used in electric vehicles, energy storage power stations and electronic products. Accurate state of charge(SOC) and state of health(SOH) are the basis for its safe and efficient application. However, the nonlinear dynamics of batteries due to temperature and aging state changes severely affect the accuracy of state estimation. Taking the nickel manganese cobalt lithium-ion battery as an example to carry out research: ① The open circuit voltage behavior characteristics of the battery at different aging stages, temperature and SOC ranges are analyzed, and an open circuit voltage model considering aging, temperature and SOC is proposed; ② The equivalent circuit model is established, and a joint estimation method of SOC and SOH of the battery based on multi-scale extended Kalman filter algorithm(MEKF) and fading memory approximate weighted total least squares algorithm(FMAWTLS) is proposed. Among them, MEKF is used to estimate model parameters at the macro scale, SOC is estimated at the micro scale, and FMAWTLS is used to estimated SOH; ③ The algorithm is verified by using battery data of different aging states and temperatures, and the results show that the maximum errors of SOC and SOH are both less than 3 %. The established open circuit voltage model and joint estimation method provide new ideas for SOC and SOH estimation under the influence of temperature and aging.

Key words: lithium-ion batteries, state of charge, state of health, extended Kalman filter, least squares method

中图分类号:

TM912

蒋帅, 陈铖, 段砚州, 熊瑞. 温度和老化影响下的锂离子电池荷电状态和健康状态联合估计方法研究[J]. 机械工程学报, 2024, 60(18): 266-275.

JIANG Shuai, CHEN Cheng, DUAN Yanzhou, XIONG Rui. Joint Estimation of State-of-charge and State-of-health for Lithium-ion Batteries under the Influence of Temperature and Aging[J]. Journal of Mechanical Engineering, 2024, 60(18): 266-275.

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