Current and Position Sensor Fault Diagnosis Algorithm for PMSM Drives Based on Robust State Observer
Kyunghwan Choi, Yonghun Kim, Seok‐Kyoon Kim, Kyung-Soo Kim
Abstract
This study proposes an advanced current and position sensor fault diagnosis mechanism for permanent magnet synchronous motor (PMSM) applications. Machine nonlinear dynamics as well as parameter and load uncertainties are addressed. The features of the results of this study are summarized as follows: 1) a proportional-type full-state observer is combined with a disturbance observer to deal with the model uncertainties, 2) a partial optimal process is introduced for determining the observer gain, 3) the concept of normalized residuals is introduced for fault diagnosis criteria, and 4) a closed-loop analysis of the convergence, performance recovery, and offset-free guarantee is provided. The performance recovery property makes the proposed algorithm robust to parameter uncertainties and load variations, and sensitive only to sensor faults. In addition, the location and type of sensor faults can be identified by the fault diagnosis criteria using the normalized residuals. The performance of the sensor fault diagnosis algorithm was experimentally verified under several credible scenarios using a 7.5-kW PMSM.