Model Predictive Control with Novel Preliminary Voltage Vectors Selection for PMSM Drive

Abstract

The increasing demand for electric drives in the context of electrification requires the development of advanced, efficient control systems. Modern electric drives require high dynamic response and robustness to varying operating conditions. In this paper, the authors propose a Model Predictive Current Control with Preliminary Voltage Vector Selection (PVVS-MPCC). In this novel concept, the squared difference between the reference and measured current values is used, along with an analytical method to determine optimal scaling factors. The proposed solution was evaluated and compared with Continuous Control Set MPCC (CCS-MPCC), deadbeat duty-cycle MPCC (DB-MPCC), and a preliminary voltage vector selection based on low-pass filtering. Experimental results demonstrate that the developed control scheme achieves lower current ripple and higher robustness against drive-parameter variations while maintaining high dynamic performance, compared to reference methods.