为解决低采样频率下SOH(电池健康状态)评估不准确的问题,提出一种基于PDF(概率密度函数法)的区域频率法.采用不同倍率下三元锂电池的充放电电压数据进行分析,采样频率为1/60 Hz,分别提取PDF峰高和区域频率作为健康因子,并建立与SOH的关系.结果表明:随着电池充放电电流倍率的增加,PDF峰高作为健康因子与SOH的拟合度降低,尤其在放电阶段,1C倍率下拟合度R2仅为0.097 1.当区域频率作为健康因子时,电池在不同倍率下充放电阶段SOH模型的拟合度R2均在0.95以上.当区域电压从100 mV增加到400 mV,模型的拟合度可达0.98以上.最后,使用1/2C倍率下电池老化数据对该方法进行验证,SOH评估误差在2%以内,结果表明该方法可提高低采样频率下的电池SOH评估的准确性.
A probability density function(PDF)based area frequency method was proposed to solve the problem of inaccurate battery health state SOH assessment at low sampling frequency.The charging and discharging voltage data of ternary lithium batteries at different multiplicities were used for analysis with a sampling frequency of 1/60 Hz,and the PDF peak height and area frequency were extracted as health factors,respectively,and the relationship with SOH was established.The results show that the fit of PDF peak height as a health factor with SOH decreases as the charge/discharge current multiplier increases,especially in the discharge phase,the fit R2 is only 0.097 1 at 1C.When the regional frequency is used as the health factor,the R2 of the fit of the SOH model is above 0.95 at different multipliers of the charge/discharge phase.When the regional voltage increases from 100 mV to 400 mV,the fit of the model is above 0.98.Finally,the method is validated using battery aging data at 1/2C magnification,and the SOH evaluation error is within 2%,which shows that the method could improve the accuracy of SOH evaluation of batteries at low sampling frequency.