Modeling and Detecting the Demagnetization Fault in the Permanent Magnet Synchronous Machine Using the Current Signature Analysis

Abstract

Various types of faults can occur in a Permanent Magnet Synchronous Machine (PMSM) system, including bearing faults, electrical short/open circuits, eccentricity faults, and demagnetization faults (DFs). A DF occurs when the magnetic strength of the PMSM's permanent magnets weakens, resulting in reduced output torque, which is undesirable in electric vehicles (EVs). This fault can be attributed to physical damage, high-temperature stress, reverse magnetic fields, and aging. Motor current signature snalysis (MCSA) is a traditional method for detecting motor faults, relying on the extraction of signal features from the stator current. In this study, a simulation model of the PMSM was developed to represent both partial and uniform DFs, allowing for the simulation of varying degrees of demagnetization. Harmonic analysis using fast Fourier transform (FFT) demonstrated that the fault diagnosis method based on harmonic wave analysis is effective only for partial DFs in PMSMs, and not applicable to uniform DFs.