Stator Fault Diagnostics in Asymmetrical Six-phase Induction Motor Drives With Model Predictive Control under Transient Regimes

Speed variations and motor start-ups have been pointed out as a critical challenge in the framework of fault diagnostics in induction motor drives, namely interturn short circuit faults. Speed variations influence the usual symptoms of the fault, and consequently, the fault detection becomes inaccurate, reducing a timely response. To overcome this issue, this paper proposes a transient regime inter-turn short-circuit fault diagnostics technique for asymmetrical six-phase induction motor drives with model predictive control. A time-frequency domain spectrogram of the AC component extracted from the q-axis reference current signal serves as a reliable fault indicator. As this reference current is a control variable accessible in the model predictive control algorithm, the diagnostics of the fault can be done without resorting to both voltage and current sensors. Experimental tests involving various load torques and fault severities, in transient regimes, were performed to validate the proposed methodology's effectiveness thoroughly.