Diagnosis of ITSC fault in the electrical vehicle powertrain system through signal processing analysis

Q3 Engineering Diagnostyka Pub Date : 2023-02-20 DOI:10.29354/diag/161309
Dehbia Ouamara, M. Boukhnifer, A. Chaibet, A. Maidi
{"title":"Diagnosis of ITSC fault in the electrical vehicle powertrain system through signal processing analysis","authors":"Dehbia Ouamara, M. Boukhnifer, A. Chaibet, A. Maidi","doi":"10.29354/diag/161309","DOIUrl":null,"url":null,"abstract":"The three-phase induction motor is well suited for a wide range of mobile drives, specifically for electric vehicle powertrain. During the entire life cycle of the electric motor, some types of failures can occur, with stator winding failure being the most common. The impact of this failure must be considered from the incipient as it can affect the performance of the motor, especially for electrically powered vehicle application. In this paper, the intern turn short circuit of the stator winding was studied using Fast Fourier transform (FFT) and Shor-Time Fourier transform (STFT) approaches. The residuals current between the estimated currents provided by the extended Kalman filter (EKF) and the actual ones are used for fault diagnosis and identification. Through FFT, the residual spectrum is sensitive to faults and gives the extraction of inter-turn short circuit (ITSC) related frequencies in the phase winding. In addition, the FFT is used to obtain information about when and where the ITSC appears in the phase winding. Indeed, the results allow to know the faulty phase, to estimate the fault rate and the fault occurrence frequency as well as their appearance time","PeriodicalId":52164,"journal":{"name":"Diagnostyka","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnostyka","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29354/diag/161309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 3

Abstract

The three-phase induction motor is well suited for a wide range of mobile drives, specifically for electric vehicle powertrain. During the entire life cycle of the electric motor, some types of failures can occur, with stator winding failure being the most common. The impact of this failure must be considered from the incipient as it can affect the performance of the motor, especially for electrically powered vehicle application. In this paper, the intern turn short circuit of the stator winding was studied using Fast Fourier transform (FFT) and Shor-Time Fourier transform (STFT) approaches. The residuals current between the estimated currents provided by the extended Kalman filter (EKF) and the actual ones are used for fault diagnosis and identification. Through FFT, the residual spectrum is sensitive to faults and gives the extraction of inter-turn short circuit (ITSC) related frequencies in the phase winding. In addition, the FFT is used to obtain information about when and where the ITSC appears in the phase winding. Indeed, the results allow to know the faulty phase, to estimate the fault rate and the fault occurrence frequency as well as their appearance time
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信号处理分析的电动汽车动力总成系统ITSC故障诊断
三相感应电动机非常适合各种移动驱动器,特别是电动汽车动力总成。在电动机的整个生命周期中,可能会发生一些类型的故障,其中定子绕组故障是最常见的。这种故障的影响必须从一开始就考虑,因为它会影响电机的性能,特别是对于电动汽车应用。本文采用快速傅立叶变换(FFT)和短时傅立叶变换(STFT)方法对定子绕组内匝短路进行了研究。扩展卡尔曼滤波(EKF)给出的估计电流与实际电流之间的残差电流用于故障诊断和识别。通过快速傅里叶变换,残差频谱对故障敏感,提取出相绕组匝间短路(ITSC)相关频率。此外,FFT用于获取有关ITSC在相位绕组中出现的时间和位置的信息。实际上,这些结果可以让我们知道故障的阶段,从而估计出故障的发生率和发生频率以及它们的出现时间
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Diagnostyka
Diagnostyka Engineering-Mechanical Engineering
CiteScore
2.20
自引率
0.00%
发文量
41
期刊介绍: Diagnostyka – is a quarterly published by the Polish Society of Technical Diagnostics (PSTD). The journal “Diagnostyka” was established by the decision of the Presidium of Main Board of the Polish Society of Technical Diagnostics on August, 21st 2000 and replaced published since 1990 reference book of the PSTD named “Diagnosta”. In the years 2000-2003 there were issued annually two numbers of the journal, since 2004 “Diagnostyka” is issued as a quarterly. Research areas covered include: -theory of the technical diagnostics, -experimental diagnostic research of processes, objects and systems, -analytical, symptom and simulation models of technical objects, -algorithms, methods and devices for diagnosing, prognosis and genesis of condition of technical objects, -methods for detection, localization and identification of damages of technical objects, -artificial intelligence in diagnostics, neural nets, fuzzy systems, genetic algorithms, expert systems, -application of technical diagnostics, -diagnostic issues in mechanical and civil engineering, -medical and biological diagnostics with signal processing application, -structural health monitoring, -machines, -noise and vibration, -analysis of technical and civil systems.
期刊最新文献
Construction and application of a bearing fault diagnosis model based on improved GWO algorithm Failure identification and isolation of DC-DC boost converter using a sliding mode controller and adaptive threshold Diagnosis of voltage unbalance state in a system with power converter Diagnostics of production processes using selected Lean Manufacturing tools Enhancing the performance of solar boost converter using Gray Wolf optimizer
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1