Current Sensor Incipient Fault Diagnosis in PMSM Drive Systems Using Novel Interval Sliding Mode Observer

This article presents a novel method for timely and accurate detection of incipient faults in current sensors of permanent magnet synchronous motor (PMSM) drive systems by utilizing an interval sliding mode observer (SMO). Initially, a hybrid logic dynamic model is developed to incorporate current sensor incipient faults, system parameter perturbation, and unknown disturbances. The current sensor incipient faults are then reconstructed using state augmentation and nonsingular coordinate transformation techniques. Subsequently, an adaptive interval SMO with a fast convergence rate and the ability to suppress high-frequency chattering is designed to estimate the reconstructed state accurately. The residual between the actual value and the observed value of the reconstructed state is employed as the detection variable, and adaptive upper and lower thresholds are designed for incipient fault diagnosis of the current sensor. The proposed method is capable of diagnosing both incipient faults and significant faults in current sensors. Experimental results validate the accuracy and robustness of the diagnostic method.