Local Demagnetization Fault Detection in PMASynRM based on Finite Element Modeling and Characterisation - Université de Lorraine Access content directly
Conference Papers Year : 2022

Local Demagnetization Fault Detection in PMASynRM based on Finite Element Modeling and Characterisation

Abstract

Good overall performances and efficiency of Permanent Magnet Synchronous Machines (PMSMs) are highly impacted by irreversible demagnetization faults. This paper proposes to analyze the electromagnetic behavior of a faulty Permanent Magnet Assisted Synchronous Reluctance Motor (PMASynRM) with neodymium-iron-boron (NdFeB) rare-earth magnets, in order to identify fault signatures and develop an efficient fault indicator. Finite Element Analysis (FEA) is used to model different demagnetization defects and evaluate precisely post-demagnetization characteristics of the baseline machine. The study focuses on flux and back-emf time and frequency analysis for its high potential to identify low severity fault signatures. The results show that the frequency spectrum of the Zero-Sequence Back-Emf Component (ZSBEC) calculated using fast Fourier transform (FFT) can be used to develop a fault detection index which allows quantifying, with high sensitivity, the severity of irreversible demagnetization faults in PMASynRMs.
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Dates and versions

hal-04210169 , version 1 (18-09-2023)

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Jeremy Creux, Najla Haje Obeid, Thierry Boileau, Farid Meibody-Tabar. Local Demagnetization Fault Detection in PMASynRM based on Finite Element Modeling and Characterisation. IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Oct 2022, Brussels, Belgium. pp.1-6, ⟨10.1109/IECON49645.2022.9968829⟩. ⟨hal-04210169⟩
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