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 (V(3)s), which improve the steady-state performance with low computational burden. However, the V(3)s 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 sub-spaces. The proposed scheme remedies the limitations of the conventional V(3)s 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 alpha-beta sector, which is defined using the deadbeat calculations. Compared with the standard FCS-MPC and the traditional FCS-MPC with V(3)s 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.