Online Identification of PMSM Q-Axis Apparent Inductance Using a PWM-Based Estimator

This paper introduces an estimator for the online identification of 𝐿 𝑞 that obviates both the integration stage and dependence on stator resistance. The proposed method is fundamentally a flux-based Model Reference Adaptive System (MRAS) but utilizes the natural excitation provided by a standard Space-Vector Pulse Width Modulation (SV-PWM) pattern. By oversampling the stator current within a single PWM switching period and leveraging the averaging properties of the applied voltage vectors, the estimator directly reconstructs the q-axis flux linkage without requiring explicit integration of terminal voltages. Consequently, the derived adaptation mechanism is rendered independent of stator resistance and immune to DC offset integration errors. A comprehensive comparative simulation study, implemented in MATLAB/Simulink, validates the estimator's performance against the classical fluxintegration-based MRAS across a rigorous set of operational scenarios. Results unequivocally demonstrate the superior accuracy, dynamic response, and parametric robustness of the proposed PWM-based method, particularly under stator resistance variation, speed sensor inaccuracy, and operating point transitions, including zero-speed crossing and regeneration modes.