Finite-Set Model Predictive Control With Virtual Medium Voltage Vectors and Eliminated Weighting Factors for 3L-NPC Inverters

Abstract

Discrete space vector modulation (DSVM) and weighting factor elimination have been investigated to improve the system performance of finite-set model predictive control (FS-MPC). However, the existing DSVM-based FS-MPC without weighting factors for three-level inverters suffers from high computational burden, low algorithm flexibility, and substantially narrowed operating range. To address these issues, this article proposes a novel DSVM-based FS-MPC with the virtual medium voltage vectors (MVVs), which greatly reduces the current harmonics and computational burden, realizes a flexibly adjustable number of time intervals in DSVM, and eliminates the weighting factor while ensuring balanced neutral-point voltage (NPV) over the full range of operating frequencies and load conditions. The introduced virtual MVVs allow the candidate set to be always narrowed down to the voltage vector closest to the reference vector. A simple judgment scheme is proposed to determine whether a real or virtual MVV should be used, which enables a flexible constraint on the maximum NPV error. Carrier-based implementation is also achieved. Experimental results validate the proposed algorithm.