An observer-based approach for sensors (position/speed, currents and DC-link voltage) fault detection and diagnosis in PMSM drive

Abstract

The paper describes a strategy for the mechanical, current and DC bus voltage sensor Fault Detection and Diagnosis (FDD) of a Permanent Magnet Synchronous Machine (PMSM) drive. The method is based on three observers. The Extended Kalman Filter (EKF) is designed to estimate the position in case of mechanical sensor fault. A Model Reference Adaptive System (MRAS) estimates the phase currents using the actual position and speed and a nonlinear observer computes the DC link voltage from the phase currents and the duty cycles. The computation and sort of the residuals (difference between measured and estimated values) allows the fault isolation. The method is evaluated on a test bench with mechanical, phase current and DC voltage sensor faults. The experimental results show the effectiveness and the capability of fault detection and diagnosis of the proposed strategy.