Maximum Torque Per Ampere Control of MPC-Driven PMSM Motors Considering Iron Loss

This paper proposes an enhanced Model Predictive Control (MPC) strategy for Permanent Magnet Synchronous Motors (PMSM), aimed at improving dynamic performance, minimizing current and torque ripples, and increasing overall system efficiency. Initially, a conventional MPC framework integrated with the Maximum Torque Per Ampere (MTPA) strategy is implemented to evaluate its effectiveness under various static and dynamic load conditions. While the MTPA-enhanced approach demonstrates improved current utilization, especially under high-load scenarios, it also presents limitations such as speed and torque overshoot, steady-state ripples, and increased computational complexity. To address these issues, a modified MPC algorithm is developed that limits the control action to only two optimal voltage vectors per sampling period, significantly reducing computational burden. Additionally, the improved controller incorporates iron loss modeling, enabling more accurate current reference generation and loss-aware control. Simulation results show that the proposed strategy achieves a substantial reduction in current ripple, improved torque stability, faster settling times, and enhanced transient response during both speed and load changes.