Open-Circuit Fault Detection in PMSM Drives Using Model Predictive Control and Cost Function Error

This article proposes a cost function error-based approach to diagnose open-circuit faults (OCFs) in permanent magnet synchronous machine drives with model predictive current control. The intrinsic relations of motor currents and cost functions under fault conditions are investigated. The residuals of the dq -axis currents are utilized to detect the fault type associated with the number of faulty devices. Instead of deriving the explicit values of cost functions, an estimation model is built according to the analytical expressions of currents and the optimal voltage vector. The error between the estimated cost function and the actual one is analyzed for fault localization. The faulty switch is finally diagnosed by assessing the minimum average absolute value of the cost function error. Simulated and experimental results confirm that the developed approach can achieve a fast diagnosis of single and multiple OCFs with good robustness to the motor parameter and operating power variations.