An Efficient Multi-Vector-Based Model Predictive Current Control for PMSM Drive

To address the problems of high current harmonics, large torque ripples, and heavy computational burden in the finite control set model predictive control (FCS-MPC), this paper proposes an efficient multi-vector model predictive current control (MPCC) scheme for permanent magnet synchronous motor (PMSM) drive.Firstly, a simple pre-selection method based on the trace of the stator current increment is proposed to obtain the candidate optimal voltage vectors.This pre-selection method avoids the heavy computational burden of evaluating all voltage vectors and is easy to implement.Then, to further reduce the torque ripples and current harmonics, the dwelling time of each voltage vector is achieved in inverse proportion to its cost function.Compared to the standard means, the proposed scheme is able to obtain great performance while greatly decreasing the computational burden and complexity.And its effectiveness is experimentally validated through comparative assessments. Index Terms-Finite control set model predictive control (FCS-MPC), low complexity, multi-vector control, pre-selection, permanent magnet synchronous motor (PMSM). I. IntroductIonP ERMANENT magnet synchronous motor (PMSM) has been widely applied in electric vehicles and robot industries due to its high torque-to-inertia ratio, structural compactness, and high power density [1], [2].Especially for high-power traction system, the application of PMSM drives can obtain the benefits of energy saving, comfort, and safety [2].However, with the increasing requirements on the performance of PMSM drives, traditional control schemes like field-oriented control (FOC) and direct torque control (DTC) have shown limitations