Multi-Vector Model Predictive Control for NPC Inverter-Fed PMSM Drives Based on Fast Vector Selection

Model predictive control (MPC) has recently been considered for permanent magnet synchronous motor (PMSM) drive applications. However, the traditional finite-set MPC suffers from such defects as large algorithmic computation and a single vector acting on the whole cycle. Those problems will directly affect the application of MPC in three-level inverters. To address the above issues, a multi-vector MPC algorithm based on fast vector selection is proposed in this work. The algorithm adopts vector synthesis and new optimization strategies to enhance the control performance. As a result, the self-balance of the NP voltage is realized for the NPC inverter with reduced common-mode voltage (CMV). Moreover, the new control strategy performs well in current harmonics minimization with reduced computational burden. Simulation results verify the effectiveness of the proposed three-vector MPC strategy.