Improved Model Predictive Current Control for PMSM Drives Based on Dynamic Reference Current

Model Predictive Current Control (MPCC) strategy is a high-performance control strategy for Permanent Magnet Synchronous Motor (PMSM), due to its fast response and simple computation. However, traditional MPCC methods often suffer from higher torque and current ripples. In this paper, an improved MPCC control scheme is proposed. Firstly, the control period is divided into n equal parts. Based on the reference current, the optimal voltage vector for the first part of the control period is determined. By utilizing the predicted current with the optimal voltage vector and the motor's electromagnetic torque equation, the estimated speed is obtained. Next, a Proportional-Integral (PI) controller matched with the speed loop is employed to determine the predicted reference current value for the next part of the sub-control period. Using the predicted reference current value, the optimal voltage vector for the next control period is re-selected. This process is repeated n times until the the control period concludes. Finally, through simulation verification, the proposed MPCC method is experimentally compared with the conventional MPCC approach. The results demonstrate the superiority of the proposed MPCC strategy and its effectiveness in reducing current and torque ripples.