基于小波分解和Hilbert包络谱分析的电池故障诊断方法  

Battery fault diagnosis method based on wavelet decomposition and Hilbert envelope spectrum analysis

作　　者：常春[1] 王启悦 姜久春 高洋 吴铁洲[1] CHANG Chun;WANG Qiyue;JIANG Jiuchu;GAO Yang;WU Tiezhou(Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System,Hubei University of Technology,Wuhan Hubei 430068;Sunwoda Electronics Co.,Ltd.,Shenzhen Guangdong 518108;School of electric power,South China University of technology,Guangzhou Guangdong 510641,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 [2]欣旺达电子股份公司,广东深圳518108 [3]华南理工大学电力学院,广东广州510641

出　　处：《蓄电池》2021年第6期251-256,共6页Chinese LABAT Man

基　　金：湖北工业大学博士科研基金启动项目(批准号BSQD2019014);湖北省教育厅科学研究指导性项目(批准号B2020047)。

摘　　要：目前,电动汽车安全事故频繁发生,严重影响驾驶人员的生命和财产安全,因此在电池严重故障发生之前如果能够进行有效的诊断和预警,将确保电动汽车安全运行。提出一种基于小波分解和希尔伯特(Hilbert)包络谱分析的电池故障诊断方法。首先,利用小波分解得到合适的分解信号;其次,选取合适的细节分解信号进行希尔伯特变换得到包络谱;然后提取出有效故障特征,并利用离群点检测算法进行故障电池检测。实车试验结果表明,该方法能有效提取故障特征,并提前实现电池故障诊断。At present,electric vehicle safety accidents occur frequently,which seriously affect the life and property safety of drivers.Therefore,if effective diagnosis and early warning can be carried out before the occurrence of serious battery failure,the safe operation of electric vehicles will be ensured.A battery fault diagnosis method based on wavelet decomposition and Hilbert envelope spectrum analysis is proposed.Firstly,the proper decomposition signal is obtained by wavelet decomposition.Secondly,the envelope spectrum is obtained by Hilbert transform of appropriate detail decomposition signals.Then the effective fault features are extracted and the outlier detection algorithm is used to detect the faulty battery.The experimental results show that this method can extract fault features effectively and realize battery fault diagnosis in advance.

关 键 词：锂离子电池 小波分解 包络谱 故障诊断 希尔伯特变换 离群点 

分 类 号：TM912.9[电气工程—电力电子与电力传动]