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Rapid prediction of the state of charge and health of retired power batteries based on electrochemical impedance spectroscopy

机译:基于电化学阻抗光谱的退休电池充电和健康状况的快速预测

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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.
机译:旨在在该阶段检测退休电池的健康状况的长时间,低精度和高能耗的问题,一种基于电化学阻抗的快速预测方法(SOC)的快速预测方法和健康状态(SOH)提出了光谱学(EIS)。首先,通过在不同SOC和不同温度下具有不同SOH的多个退出电力电池的电化学阻抗光谱测量,分析了阻抗幅度,相位角和通过拟合和SOC在不同温度下获得的等效电路模型参数之间的关系。然后,基于此,找到最稳定的阻抗参数来建立电池SOC估计算法,以实现退役电力电池的SOC的快速估计;最后,提出了两次测量方法,以快速预测充电状态和退役电力电池的健康,验证实验结果的最小误差小于1%。使用此方法可以大大降低测试时间,节省能源,并实现电池的未知充电状态的快速估计。

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