重庆理工大学学报2024，Vol.38Issue(11)：21-29,9.DOI:10.3969/j.issn.1674-8425(z).2024.06.003
基于局部离群点检测的动力电池组不一致早期故障预警
Early fault warning for inconsistent power battery pack based on local outlier detection
摘要
Abstract
With the rapid development of new energy vehicles,the safety of power batteries has gained growing public attention.On the new energy vehicle operation monitoring platform,the existing power battery safety detection function fails to provide early warnings of battery failures.A more suitable process for early warnings of battery inconsistency in power battery packs has been designed to address the battery inconsistency warnings.First,a dynamic gradient data cleaning strategy based on box graph method is designed to effectively eliminate abnormal data.Then,the data are divided into charging stages and inconsistent characteristics of individual voltage changes are extracted.Based on this,the outlier detection algorithm is employed to obtain the outlier values of each battery cell,conduct initial warning of inconsistent faults,and identify abnormal battery cells.Our retrospective analysis of actual vehicles with inconsistent battery faults demonstrates that the preexisting alarm mechanism of the monitoring platform for this process has no less than 7 charging cycles and accurately locates abnormal cells.关键词
动力电池/大数据/离群检测/电池不一致/故障预警Key words
power battery/big data/outlier detection/battery inconsistency/fault warning分类
交通工程引用本文复制引用
魏正新,吕晗珺,闵永军,张涌..基于局部离群点检测的动力电池组不一致早期故障预警[J].重庆理工大学学报,2024,38(11):21-29,9.基金项目
江苏省重点研发计划项目(BE2022053-2) （BE2022053-2）
