基于SOC-OCV曲线特征的SOH估计方法研究

doi:10.19562/j.chinasae.qcgc.2019.010.008

摘要/Abstract

摘要： 电池的健康状态估计(state of health, SOH)是锂离子电池管理系统中的状态参数之一,影响电池荷电状态估计(state of charge, SOC)和峰值功率估计(state of power, SOF)的精度。本文中通过追踪SOC-OCV(open circuit of voltage, OCV)曲线特征的衍变规律,从热力学的角度提出了全新的SOH估计方法。利用三元锰酸锂复合材料为正极的锂离子电池循环寿命实验数据构建SOH与SOC-OCV曲线特征参数之间的关系,并验证所提SOH估计方法的精度。实验结果表明:SOH从100%衰退到50%,SOH估计精度在±1.5%以内。

关键词: 锂离子电池, SOH估计, 电池老化, SOC-OCV建模

Abstract: State of health (SOH) is one of the state parameters in lithium-ion battery management system, which affects the accuracy of state of charge (SOC) and state of power (SOF) . In this paper, a new SOH estimation method is proposed from the thermodynamic perspective by tracing the evolution law of the SOC-OCV curve characteristics. In this paper, the relationship between SOH and SOC-OCV curve characteristic parameters is constructed and the accuracy of the proposed SOH estimation method is verified using the experimental data of the cycle life of the lithium ion battery with ternary lithium manganate composite as the positive electrode. The experimental results show that the SOH estimation accuracy is within ±1.5% while SOH declines from 100% to 50%

Key words: lithium-ion battery; SOH estimation; battery degradation; SOC-OCV modeling

刘轶鑫,张頔,李雪,韩智强. 基于SOC-OCV曲线特征的SOH估计方法研究[J]. 汽车工程, 2019, 41(10): 1158-1163.

Liu Yixin, Zhang Di, Li Xue & Han Zhiqiang. A Research on SOH Estimation Method Based on SOC-OCV Curve Characteristics[J]. Automotive Engineering, 2019, 41(10): 1158-1163.

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