计量学报2024，Vol.45Issue(6)：890-898,9.DOI:10.3969/j.issn.1000-1158.2024.06.15
基于自适应LTTB与DTW-DBA-Means的动力电池组不一致性评估方法
An Inconsistency Assessment Method for Power Battery Pack Based on Adaptive LTTB and DTW-DBA-Means
摘要
Abstract
Aiming at the problem that the inconsistency of electric vehicle power battery pack is difficult to be effectively evaluated through external parameters,when analyzing the battery pack voltage data,the Silhouette Coefficient is introduced as the inconsistency evaluation index,and a new inconsistency evaluation method for power battery pack is proposed by integrating adaptive down-sampling(LTTB)and time-series clustering(DTW-DBA-Means)algorithms.Adaptive LTTB can adaptively adjust the compression ratio and sample point allocation in compression intervals according to the characteristics of the battery pack voltage sequence,which can improve the DTW-DBA-Means operation efficiency and ensure the clustering effect.Experiments is conducted based on the real vehicle data running for nine months,the results show that the adaptive LTTB down-sampling effect is better than dynamic LTTB and LTTB,and the DTW-DBA-Means time-series clustering effect is better than k-Shape,and the proposed method can save about 96.7％operation time while ensuring the accuracy of evaluation.关键词
电学计量/动力电池组/不一致性评估/轮廓系数/降采样/时序数据聚类Key words
electrical metrology/power battery pack/inconsistency assessment/silhouette coefficient/down-sampling/time-series clustering分类
通用工业技术引用本文复制引用
吴凤和,柴海宁,章正柱,张宁,王正明,蒋展鹏,郭保苏..基于自适应LTTB与DTW-DBA-Means的动力电池组不一致性评估方法[J].计量学报,2024,45(6):890-898,9.基金项目
国家重点研发计划(2020YFB1711803) （2020YFB1711803）
国家自然科学基金(92266203) （92266203）
河北省高等学校科学技术研究重点项目(ZD2020156) （ZD2020156）
