Reduced Vector Model Predictive Control of ANPC Inverter for PMSM Drives With Optimized Commutation

In this work, a new reduced vector model predictive control (RV-MPC) method is proposed for full silicon-carbide (SiC)-MOSFET modules-based three-level active neutral-point-clamped (3L-ANPC) inverter fed permanent magnet synchronous motor (PMSM) drives. The main purpose of this approach is to reduce the computational burden of conventional MPC for ANPC inverters while optimizing the current commutation paths. To reduce the computational burden, the proposed algorithm is implemented by two steps. In the first step, the expected dq -axis voltages are predicted, and then, the positive and negative half cycles are determined through a hysteresis sign calculation algorithm. In the second step, only eight switching states need to be enumerated under the defined half period, which is remarkably reduced from 27 to 8. The neutral point potential balance and switching effort penalization are also considered in the proposed method. Moreover, the ANPC inverter can achieve more even loss distribution and better thermal characteristics with the optimized commutation, which is profitable for the high-power drive applications. The effectiveness of the proposed approach is evaluated by simulations and experimentally verified on a platform of 11-kW PMSM drives.