A Novel Multi-Objective Finite Control Set Model Predictive Control for IPMSM drive fed by a Five-Level Cascaded H-Bridge Inverter

Abstract

In this work, a novel multi-objective voltage-vector-based finite control set model predictive control for a permanent magnet synchronous machine drive fed by a three-phase five-level cascaded H-bridge multilevel inverter is proposed. This algorithm aims to overcome the main issues relative to model predictive control implementation detected in the scientific literature for electric drives fed by cascaded H-bridge multilevel inverters. In detail, the goals are the minimization of computational cost by reducing the number of required predictions, the minimization of the switching devices state transitions, i.e. the switching losses minimization, and the common mode voltage reduction. These goals are fulfilled through an offline optimization process, thus, no additional terms and weighting factors to be tuned are required for the cost function. Experimental validations are presented to prove the effectiveness of the proposed approach. In detail, an accurate electric drive performance comparison, both in steady state and dynamic working conditions, is carried out when the proposed voltage-vector-based model predictive control and the cell-by-cell-based model predictive control are adopted. As comparison tools, current and voltage total harmonic distortion, apparent switching frequency, common mode voltage amplitude, and torque ripple are adopted.