基于K-means聚类的退役动力电池梯次利用成组方法

Reutilization grouping of retired electric vehicle battery based on K-means clustering

针对退役动力电池梯次利用过程中选配成组问题,采用基于安时积分法的检测方法对退役动力电池进行批量检测。根据检测过程中的充放电数据以及电池的荷电状态(SOC),将待测电池与同型号标准电池的充放电曲线进行比较,计算两者间的动态时间弯曲(DTW)距离。结合特征参量法检测所得电池的开路电压和内阻共同作为电池的健康因子,对各个健康因子做归一化处理后,运用K-means聚类算法对退役动力电池进行重新成组。该方法改进了企业梯次利用选配成组技术,改善了成组后电池模组在容量和一致性方面的表现。

The grouping problems in the reutilization of retired electric vehicle battery were investigated,batch measurement of retired electric vehicle battery was carried out using detection equipment and detection methods based on the ampere-hour integration method.According to the charge and discharge data during the test and the state of charge(SOC)of the battery,the curve of each battery was compared with the curve of the standard battery of the same model,and the dynamic time warping(DTW)distance between the two was calculated.Combined with the open circuit voltage and internal resistance of the battery detected by the characteristic parameter method as the health factors of the battery,after normalizing each health factor,the K-means clustering algorithm was used to regroup retired electric vehicle battery.The reutilization grouping technology was improved,and the performance of the battery modules in terms of capacity and consistency after the group was improved.