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

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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.
Czasopismo
Rocznik
Strony
art. no. 2023113
Opis fizyczny
Bibliogr. 33 poz., rys.
Twórcy
  • Department of Electrotechnics, Mouloud Mammeri University of Tizi Ouzou, Algeria
  • University of Lorraine, LCOMS, F-57000 Metz, France
  • ISAT, University of Burgundy, France
autor
  • L2CSP Laboratory, Mouloud Mammeri University of Tizi Ouzou, Algeria
Bibliografia
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  • 19. Khayam Hoseini SR, Farjah E, Ghanbari T, Givi H. Extended Kalman filter-based method for inter-turn fault detection of the switched reluctance motors. IET Electric Power Applications. 2016; 10(8): 714-722. https://doi.org/10.1049/iet-epa.2015.0602.
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-72059a15-98be-4ab1-b744-219b49beb133
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