基于充电曲线特征的退役动力电池快速分选方法

A fast sorting method for retired power batteries based on charging curve characteristics

准确快速分选对退役动力电池梯次利用具有重要意义。通过充放电试验获取退役动力电池充电曲线和容量,运用灰色关联分析方法确定与容量相关性最优的电压区间,基于电池老化机理提取最优电压区间对应的充电容量ΔQ、充电时长T、主峰中心电压V 1、充电容量与区间电压比值K作为表征电池不一致性的特征参数。运用局部异常因子算法筛选异常老化电池,利用K-means聚类算法完成退役电池分选,提出静态与动态双维度指标体系评价分选一致性,采用2组退役电池充放电数据进行验证。结果表明:分选后电池的静态一致性和动态一致性最大分别提升55%、82%,且单个电池测试时间平均缩短至30 min。与K-means聚类算法相比,融合局部异常因子算法(local outlier factor,LOF)后,静态一致性和动态一致性最大分别提升50%、33%;与容量增量方法和静态参数方法相比,该方法的静态一致性最大分别提升28%、5%,动态一致性最大分别提升76%、61%。

Accurate and rapid sorting is crucialin the echelon utilization of retired power batteries.The charging curve and capacity of retired power batteries are obtained by charging and discharging test.The grey correlation analysis method is employed to determine the voltage interval with the best capacity correlation.Based on the battery aging mechanism,the charging capacityΔQ,charging time T,main peak center voltage V 1 and the ratio of charging capacity to interval voltage K corresponding to the optimal voltage interval are extracted as the characteristic parameters to characterize the inconsistency of the battery.The local outlier factor algorithm is employed to screen the abnormal aging batteries while the K-means clustering algorithm is adopted to complete the sorting of retired batteries.Meanwhile,a static and dynamic two-dimensional index system is proposed to evaluate the sorting consistency,and two sets of charge and discharge data of decommissioned batteries are used for verification.Our experimental results show the battery’s static consistency is increased by 55%and its dynamic consistency by 82%after sorting,and the average test time of a single battery is reduced to 30 minutes.Compared with the K-means clustering algorithm,the static and dynamic consistency of sorting is increased by 50%and 33%respectively after fusing the local outlier factor algorithm.Compared with the capacity increment method and the static parameter sorting method,the static consistency of our method is up by 28%and 5%respectively,and the dynamic consistency jumps by 76%and 61%respectively.