摘要
电池制造过程的初始差异和实际使用时的动态差异,带来动力电池组中各单体电池的一致性差异,对电动汽车整体性能产生负面影响,并造成安全隐患。以某电动汽车动力电池组为研究对象,对云端源数据进行预处理,实现了充放电片段的有效分割;提出了放电工况下基于层次聚类分析电池组温度一致性和电压一致性的方法;以类间距极差作为不一致性评价指标,分析了温度和电压不一致性变化趋势。研究发现,可根据温度不一致性将云端数据分为5个阶段,电压不一致性受温度不一致性影响较大,电压不一致性具有一定的不可恢复性,总体呈上升趋势。
Due to the initial difference in manufacturing process and the dynamic difference in application of a battery pack,there exists battery inconsistency of the battery pack,which has a negative impact on the overall performance of the battery pack and cause safety risks of the electric vehicles.This paper takes the battery pack of an electric vehicle as the object to study the correlation of battery pack temperature consistency and voltage consistency.Firstly,the raw data is pre-processed to solve the problems of inconsistent raw data field format,data missing,and bad points.Moreover,according to the discharge and charge state of the battery pack,effective charge and discharge segments has been divided.All the raw data are divided into 1157 discharge and charge segments.Based on these effective segments,the characteristics of the total voltage and current under typical discharge conditions and the single battery cell voltage and temperature at different positions under the same discharge segment are then analyzed.It is found that multiple battery cells are detected with the same voltage at the same time,making it difficult to determine the single battery cell corresponding to the highest or lowest voltage.In addition,there are significant differences in the temperature at the different positions of the battery pack,and there is a certain correlation between temperature difference and discharge time.Thirdly,a method based on hierarchical clustering to analysis battery pack temperature inconsistency and voltage inconsistency under discharge condition is proposed.In the method,Euclidean distance of different temperature and voltage sampling points is used for the class division,and the average distance is used to calculate the center distance of each clustering.Fourthly,in order to quantitatively characterize the temperature consistency and voltage consistency of the battery pack,the dispersion of the whole battery pack is measured by the clustering center distance.The maximum and minimum clustering center distance are
作者
王丽梅
张迎
陆东
赵秀亮
李扬
孙洁洁
WANG Limei;ZHANG Ying;LU Dong;ZHAO Xiuliang;LI Yang;SUN Jiejie(Automotive Engineering Research Institute,Jiangsu University,Zhenjiang 212013,China;Jiangsu Yueda Special Vehicle Co.,Ltd.,Yancheng 224007,China;Beijing Electric Vehicle Co.,Ltd.,(BAIC BJEV),Beijing 100176,China)
出处
《重庆理工大学学报（自然科学）》
北大核心
2023年第9期13-22,共10页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(52072155)
盐城市“黄海明珠人才计划”领军人才项目。
关键词
动力电池组
云端数据
放电工况
温度一致性
电压一致性
battery pack
cloud data
discharge condition
temperature consistency
voltage consistency
