Permanent magnet synchronous motor parameter identification considering nonlinearities based on harmonic suppression and an improved black-winged kite algorithm

Abstract

Aiming at the loss of accuracy and stability in permanent magnet synchronous motor (PMSM) parameter identification under voltage source inverter (VSI) nonlinearities, this study develops an improved black-winged kite algorithm with PIR harmonic suppression. First, a PIR controller is used to suppress the sixth-order harmonics of the d - q axis currents. This reduces the adverse effect of VSI nonlinearities on the quality of identification data. Second, a snowmelt factor is introduced to adaptively adjust the position update step in the attack phase, which improves both exploration and exploitation. Finally, a cooperative migration strategy based on Bezier curves is designed to enhance convergence stability and speed. Experimental results demonstrate that the proposed method maintains reliable identification performance under the tested operating conditions.