基于电化学阻抗谱的退役动力电池充电状态和健康状况快速预测

Fan Luo, Haihong Huang
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引用次数: 1

摘要

针对现阶段退役动力电池健康状态检测时间长、精度低、能耗高等问题,提出了一种基于电化学阻抗谱(EIS)的电池荷电状态(SOC)和健康状态(SOH)快速预测方法。首先,通过对多个不同SOHs的退役动力电池在不同SOC和不同温度下的电化学阻抗谱测量,分析拟合得到的阻抗幅值、相角和等效电路模型参数与不同温度下SOC的关系。然后,在此基础上,寻找最稳定的阻抗参数建立电池荷电状态估计算法,实现对退役动力电池荷电状态的快速估计;最后,提出EIS二次测量方法,快速预测退役动力电池的充电状态和健康状况,验证实验结果的最小误差小于1%。使用该方法可以大大缩短测试时间,节省能量,实现对电池未知充电状态和健康状态的快速估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid prediction of the state of charge and health of retired power batteries based on electrochemical impedance spectroscopy
Aiming at the problems of long time, low accuracy and high energy consumption in detecting the health status of retired power batteries at this stage, a rapid prediction method of battery state of charge (SOC) and state of health (SOH) based on electrochemical impedance spectroscopy (EIS) is proposed. First, through electrochemical impedance spectroscopy measurements of multiple retired power batteries with different SOHs at different SOCs and different temperatures, the relationship between impedance amplitude, phase angle and the equivalent circuit model parameters obtained by fitting and SOC at different temperatures are analyzed. Then, based on this, find the most stable impedance parameter to establish the battery SOC estimation algorithm to realize the rapid estimation of the SOC of the retired power battery;Finally, the EIS twice measurement method is proposed to quickly predict the state of charge and health of the retired power battery, and the minimum error of the verification experimental results is less than 1%. Using this method can greatly reduce test time, save energy, and achieve rapid estimation of unknown state of charge and health of the battery.
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