PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Author:

Romdhane Mabrouka12,Naoui Mohamed3ORCID,Mansouri Ali4

Affiliation:

1. Technology Energy and Innovation Materials Research Laboratory, Faculty of Sciences of Gafsa, University of Gafsa, Gafsa 2112, Tunisia

2. National Engineering School of Gabes, University of Gabes, Gabes 6029, Tunisia

3. Research Unit of Energy Processes Environment and Electrical Systems, National Engineering School of Gabes, University of Gabes, Gabes 6029, Tunisia

4. Higher School of Applied Sciences and Technology of Gafsa, University of Gafsa, Gafsa 2112, Tunisia

Abstract

To avoid damaging the motor and its surrounding equipment, detecting Inter-Turn Short Circuit (ITSC) faults in Permanent Magnet Synchronous Motors (PMSMs) applied in electric vehicles is a crucial task. In this paper, the detection of ITSC faults in stator winding for PMSMs is carried out by means of the Extended KALMAN Filter (EKF) algorithm combined with the Fuzzy Logic Estimator (FLE). To estimate the motor parameters, including the rotor position and speed, the EKF algorithm uses the measured stator currents and voltages beside the stator resistance, which is calculated in advance using fuzzy logic and fed to the EKF. The change behaviors of the estimated parameters were then used to detect short circuit faults in the PMSM. Using Matlab/Simulink, the proposed FL-EKF algorithm was implemented and tested on a faulty PMSM controlled by Field Oriented Control (FOC). The observation of a perfect estimation of the stator resistance through the simulation helps to precisely detect the failure, and that demonstrates the sensitivity and robustness of the proposed approach.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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