Direct model predictive torque control for permanent magnet synchronous motor with voltage vector parallel optimisation algorithm

The multi-vector-based direct model predictive torque control (DMPTC) inherits the high control precise of vector control and the fast dynamic response of model predictive control. However, the cascade optimisation mode is difficult to guarantee the global optimal performance of the voltage vector (VV) combination, and results in invalid VV time duration in some cases as well as high calculation complexity. In this paper, for the predictive control of permanent magnet synchronous motors widely used in electric propulsion aircraft, a parallel optimisation DMPTC method is proposed to ensure that the multi-vectors applied are all optimal in each control cycle. The optimal double vectors are directly chosen locating the sub-region of the sector of reference VV. With only the absolute value of stator VV error term, the time duration is always in the valid range and robust to motor parameters. In addition, a cost function with a single control objective is designed to control the torque and flux cooperatively, eliminating the stator flux weighting factor and reducing the computation burden. The proposed method is compared with the recent predictive torque control strategies. The experimental results confirm the effectiveness of the proposed method in improving the dynamic response and steady-state performance while reducing computation burden and complexity.