A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter
Qi Wang, Haitao Yu, Chen Li, Xiaoyu Lang, Seang Shen Yeoh, Tao Yang, Marco Rivera, Serhiy Bozhko, Patrick Wheeler
Abstract
Conventional finite control set model-predictive control (FCS-MPC) presents a high computational burden, especially in three-level neutral-point-clamped (NPC) converters. This article proposes a low-complexity optimal switching time-modulated model-predictive control (OST-M2PC) method for a three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared with the conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20-kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method.