基于电压曲线诊断锂离子电池的故障  

Fault diagnosis method for Li-ion battery based on voltage curve

作　　者：廖力[1] 杨达 李勋波 姜久春 LIAO Li;YANG Da;LI Xunbo;JIANG Jiuchun(Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System,Hubei University of Technology,Wuhan,Hubei 430068,China)

机构地区：[1]湖北工业大学太阳能高效利用及储能运行控制湖北省重点实验室,湖北武汉430068

出　　处：《电池》2024年第5期655-659,共5页Battery Bimonthly

基　　金：中央引导地方科技发展专项基金(2022BGE230),国家自然科学基金(52177212),湖北省教育厅科学研究计划(T2021005)。

摘　　要：锂离子电池在电动汽车中应用广泛,电池的不一致性故障与内短路故障是电动汽车的严重安全隐患。采用绝对中位差方法来放大电池组故障电池的电压特性;再利用非局部均值滤波算法进行滤波,得到平滑的故障电压特征;最后,通过动态时间归整(DTW)算法计算特征值曲线之间的相似度距离,实现故障电池自动定位。使用运行车辆电压数据进行验证,发现该诊断方法对两类故障车辆均具有良好的检测效果:一是故障电池DTW距离长期偏离其他电池的不一致性故障车辆;二是故障电池DTW距离短期偏离其他电池的内部短路故障车辆。与余弦相似度进行对比,验证所提方法的准确性更高。Li-ion battery is widely used in electric vehicles,battery inconsistency faults and internal short-circuit faults are serious safety hazards for electric vehicles.The absolute mean difference method is used to amplify the voltage characteristics of faulty cells in a battery pack.Then,a nonlocal mean filtering algorithm is used to filter it to obtain a smooth fault voltage characteristic.Finally,the similarity distance between the eigenvalue curves is calculated by the dynamic time warping(DTW)algorithm to realize automatic localization of faulty batteries.Validation is carried out by using operating vehicle voltage data.The diagnostic method has a good detection effect on two types of faulty vehicles:one is the inconsistent faulty vehicle where the DTW distance of the faulty battery deviates from other batteries for a long period of time,the other is the faulty vehicle where the DTW distance of the faulty battery deviates from other batteries for a short period of time with an internal short-circuit.A comparison with the cosine similarity verifies that the proposed method is more accurate.

关 键 词：锂离子电池 不一致性故障 内短路故障 故障诊断 实车数据 动态时间归整(DTW)算法 

分 类 号：TM912.9[电气工程—电力电子与电力传动]