基于放电曲线和模糊C均值法的退役电池一致性分选方法  

Research on the consistent sorting method of retired batteries based on discharge curves and improved fuzzy C-means algorithm

作　　者：赵光金 孟高军[2] 董锐锋 苏令 张正 ZHAO Guangjin;MENG Gaojun;DONG Ruifeng;SU Ling;ZHANG Zheng(State Grid Henan Electric Power Research Institute,Zhengzhou Henan 450052,China;School of Electric Power Engineering,Nanjing Institute of Technology,Nanjing Jiangsu 211167,China)

机构地区：[1]国网河南省电力公司电力科学研究院,河南郑州450052 [2]南京工程学院电力工程学院,江苏南京211167

出　　处：《电源技术》2024年第9期1769-1776,共8页Chinese Journal of Power Sources

基　　金：国网河南省电力公司科技项目(52170223000F)。

摘　　要：在电动汽车井喷式增长的背景下,巨量退役的动力电池如何回收成为当前电动汽车行业亟待解决的问题。考虑到退役电池容量、内阻等性能会出现较大的不一致性,在对退役电池梯次利用前,有必要根据其性能状况进行一致性分选,以实现退役电池的经济效益和利用率最大化。提出了一种基于放电曲线和改进模糊C均值算法的退役电池一致性分选方法。该方法以退役电池单体为研究对象,借助1 C充放电实验选取放电曲线,进行特征参数提取;在此基础上,结合改进的模糊C均值算法构建退役电池高精度分选模型,基于简化的特征点提取过程,在不同容量梯度的退役电池下对分选方法的可行性进行了验证。The recycling of the substantial volume of retired batteries has emerged as one of the most pressing issues facing the electric vehicle(EV)industry due to the exponential rise of EVs.In order to maximize their economic benefits and utilization rate,retired batteries must be sorted according to the consistency of their performance before being used at the echelons utilization due to the inconsistent performance of retired batteries in terms of their capacity,internal resistance and other properties.Therefore,this article proposes a consistency sorting method for retired batteries based on discharge curves and improved fuzzy C-means algorithm.With this method,retired battery cells are used as the research subject.Discharge curves are selected through 1 C rate charging and discharging experiments,and feature parameters are then extracted.This information is used to build a highprecision sorting model of retired batteries,which is integrated with the improved fuzzy C-means algorithm.Based on the streamlined feature point extraction process,the efficiency of the sorting method is confirmed using retired batteries with various gradients in capacity.

关 键 词：退役动力电池 放电曲线 一致性分选 特征参数 模糊C均值算法 

分 类 号：TM912[电气工程—电力电子与电力传动]