Model Predictive Control With Autotuning Weighting Factors for Single-Phase Six-Level Hybrid-Clamped Converters
Yong Yang, Jianyu Pan, Huiqing Wen, Xinan Zhang, Yiwang Wang, Will Perdikakis
Abstract
Compared with the conventional multilevel converters, the hybrid-clamped converter (HCC) reduces the number of power devices, which brings down the converter cost while enhancing its reliability for medium-voltage high-power applications. As one of typical medium-voltage HCCs, the single-phase, six-level HCC (6L-HCC) faces the main technical challenge of the voltage balance among five inner capacitors. Most of the existing pulsewidth modulation techniques cannot solve this problem. Advanced control methods that directly apply a selected voltage vector, such as the classical model predictive control (MPC), may fail to balance the inner capacitor voltages during low output frequencies. In view of this situation, this article proposes an improved MPC approach with autotuning weighting factors. It contributes to ensure excellent performance of 6L-HCC under all operating conditions with well-balanced inner capacitor voltages. Simulation and experimental results are proposed to verify the effectiveness of the proposed approach.