Computationally Efficient Cascaded Predictive Control for Hybrid-Inverter Fed Open-Winding PMSM Drive With Fast Partial Preselection

In this article, a computationally efficient cascaded model predictive control (CMPC) is put forward for the hybrid-inverter fed open-winding permanent magnet synchronous motor (OW-PMSM) drive, which significantly reduces the computational burden and eliminates the weighting factors. The hybrid-inverter consists of a main inverter (MI) and a compensatory inverter (CI), which are respectively powered by a voltage source and a floating capacitor. Hence, an additional weighting factor is required to tradeoff the control of OW-PMSM and the floating capacitor. To avoid the tedious tuning work, a cascaded two-stage structure is designed to coordinate the multiobjective control. However, the weighting factor is eliminated at the cost of the increased number of evaluations. To this end, a fast partial preselection strategy is proposed, which evaluates only the voltage vectors (VVs) of CI in the first stage and then evaluates the VV combinations of both MI and CI in the second stage. With the proposed scheme, the number of VV combinations to be evaluated is decreased from 64 to 32, where the total computational burden is lowered by 48%. Finally, experiments are carried out on a 500 W OW-PMSM drive to prove the effectiveness of the proposed CMPC.