Double-Vector-Based Finite Control Set Model Predictive Control for Five-Phase PMSMs With High Tracking Accuracy and DC-Link Voltage Utilization

Finite control set (FCS) model predictive control (MPC) has been widely emerged for the double-subspace control problem of five-phase permanent magnet synchronous motor (PMSM) drives thanks to the principles of the virtual voltage vectors (V3s), which improve the steady-state performance with low computational burden. However, the V3s are designed offline to include one-subspace components, which is not considered as an optimized solution. Therefore, this article presents an improved double-vector-based FCS-MPC scheme for five-phase PMSM drives, considering the control objectives of the two subspaces. The proposed scheme remedies the limitations of the conventional V3s using online selection of the two vectors combination and duty ratio calculation. To keep low computational burden, ten possible double-vector combinations are examined during every sampling interval for each fundamental α–β sector, which is defined using the deadbeat calculations. Compared with the standard FCS-MPC and the traditional FCS-MPC with V3s schemes, the proposed double-vector-based FCS-MPC scheme can achieve improved tracking accuracy and high dc-link voltage utilization. The potentials of the proposed scheme over these existing FCS-MPC schemes are verified by simulation analysis and experimental test on a five-phase PMSM drive prototype.