A Novel Split Space-Vector-Based Model Predictive Control With DC Power Balancing Strategy for Cascaded H-Bridge Inverter-Fed PMSM Drives

In this work, a novel split-space-vector-based finite control set model predictive control (MPC) for an interior permanent magnet synchronous motor drive fed by a three-phase five-level cascaded H-bridge multilevel inverter is proposed. The key novelty of this work is related to the ability of the proposed algorithm to guarantee the inverter submodules (SMs) dc power balancing by introducing some switching constraints aimed to emulate the phase-shifted pulsewidth modulation switching pattern, which naturally guarantees the SMs dc power balancing. Then, the main contribution of this work is guaranteeing the SMs dc power balancing without resorting to an explicit modulation stage or to a devoted term into the cost function. Indeed, the former reduces the system dynamic, the latter imposes measuring the dc voltages and tuning the cost function weighting factors. Moreover, the adopted switching constraints and an offline optimization process allow for guaranteeing the minimum computational burden. The proposed control algorithm's effectiveness is proven by experimental tests both in steady-state and dynamic working conditions and by comparison with a very-low computational burden voltage-vector-based finite control set MPC.