Discrete Space Vector Modulation Based Model Predictive Flux Control With Reduced Switching Frequency for IM Drive

Abstract

This article presents an optimal model predictive flux control (MPFC) for a two-level inverter fed induction motor. Integrating discrete SVM into FCS-MPFC enhances the performance of the IM drive. However, conventional DSVM-MPFC requires to enumerate and evaluate a higher number of virtual vectors in the prediction loop. In this paper, a high-efficient and low complexity voltage selection method is proposed to reduce the number of candidate voltage vectors from 38 to 15 without any suboptimality. Both steady-state and transient performances of the proposed method remain the same as the 38-vector based conventional DSVM-MPFC, producing the same cost-function values in all operating conditions. Furthermore, an online switching frequency reduction technique is proposed to achieve a minimum commutation per inverter vector change within each sampling cycle and between adjacent cycles. By appropriately arranging the sequence of real voltage vectors in each sampling cycle, a lower average switching frequency is achieved. The proposed switching frequency reduction method decreases the switching losses without compromising the performance of DSVM-MPFC as only the applied sequences of the real voltage vectors are optimized. Experimental studies are conducted to verify the effectiveness of the proposed algorithm.