A static current error elimination algorithm for predictive current control in PMSM for electric vehicles

Permanent magnet synchronous motors (PMSM), especially interior PMSM, offer several benefits, including a compact design, light weight, simple construction, high efficiency, and versatile control capabilities, which make them ideal for use in electric vehicle drive systems. A robust predictive current control approach for PMSM drives is proposed. The finite control set-model predictive current control (FS-MPC) system's sensitivity to the PMSM model's parameters was initially examined, and the current response characteristics were assessed. On this basis, a static error elimination algorithm based on PI controller and particle swarm optimization (PSO) is proposed to compensate the parameter mismatches between actual parameters and model parameters adaptively. By combining the proposed algorithm to the FS-MPC, error elimination FS-MPC (FS-EEMPC) can significantly reduce the current static error. Simulation and experimental comparisons between the FS-MPC and FS-EEMPC approaches were conducted to confirm the parameter robustness of the proposed method. The results demonstrate that FS-EEMPC improves steady-state performance while maintaining the good dynamic performance of FS-MPC, with minimal additional computational load. • A novel FS-EEMPC method is proposed to eliminate static current errors in PMSM drives for EV applications. • FS-EEMPC integrates PI-based error elimination and uses offline PSO to optimize parameters under typical conditions. • The FS-EEMPC method enhances steady-state accuracy without sacrificing dynamic response, with minimal added computation. • Simulations and experiments show FS-EEMPC reduces steady-state errors and MSE under parameter mismatches.