Performance improvement of PMSM with Particle Swarm Optimized Field-Oriented Control

The accelerating global transition toward sustainable electrification has established Permanent Magnet Synchronous Motors (PMSMs) as a key propulsion technology for electric vehicles and advanced industrial applications. However, the inherent nonlinear dynamics and parameter sensitivities of these systems pose significant control challenges, where conventional Proportional-Integral (PI) controllers often fail to maintain stability under varying operating conditions. To address this limitation, this study proposes a robust Field-Oriented Control (FOC) framework in which Particle Swarm Optimization (PSO) is employed for offline optimal tuning of controller gains. The optimization process is formulated based on multiple performance indices, including the Integral Absolute Error (IAE), Integral Square Error (ISE), and Integral Time-Absolute Error (ITAE), to ensure improved dynamic and steady-state performance. The obtained results demonstrate that the proposed FOC-PSO strategy significantly outperforms conventional controllers. In particular, the overshoot is completely eliminated (0%) compared to 4.8% in standard PID controllers, while achieving a faster rise time of 0.0053 s and reduced settling time. Moreover, the proposed approach effectively minimizes torque ripple and current ripple, and maintains robust performance under varying load conditions and parameter uncertainties. Consequently, this work provides a reliable and efficient control solution for enhancing the performance and robustness of PMSM-based electric drive systems.