From Modeling to Failure Prognosis of Permanent Magnet Synchronous Machine

Abstract

Due to the accelerating pace of environmental concerns and fear of the depletion of conventional sources of energy, researchers are working on finding renewable energy sources of power for different axes of life. The transportation sector has intervened in this field and introduced hybrid electric vehicles. Many complaints have been mentioned concerning fault detection and identification in the vehicle to ensure its safety, reliability and availability. Diagnosis has not been able to overcome all these concerns, and research has shifted toward prognosis, where the manufacturing sector is urged to integrate fault prognosis in the vehicle’s electrical powertrain. In this article, prognosis of the vehicle’s electrical machine is treated using a hidden Markov model after modeling the electrical machine using the finite element method. Permanent magnet machines are preferable in this application. The modeling of the machine is a combination of the electromagnetic, thermal and vibration finite element models. The considered faults are demagnetization, turn-to-turn short circuit and eccentricity. A strategy for the calculation of the remaining useful life (RUL) is suggested when a turn-to-turn short circuit fault occurs.