Hybrid Multi-Vector Modulated Model Predictive Control Strategy for Voltage Source Inverters Based on a New Visualization Analysis Method

Abstract

Conventional model predictive control (MPC) strategy for voltage source inverters has large current ripple since only one voltage vector is applied in each control cycle. Although the multi-vector modulated MPC strategy can reduce the current ripple, its lack of theoretical basis makes its optimality questionable. To solve this problem, a new visualization analysis method is proposed in this article to evaluate the effectiveness of the conventional multi-vector modulated MPC strategy, based on which a new hybrid multi-vector modulated MPC strategy is further presented to improve the current control performance. First, the principle of the proposed visualization analysis method is introduced, based on which it is verified that the conventional multi-vector modulated MPC has better control performance than the single-vector MPC. Second, based on the proposed visualization analysis method, it is also found that both the conventional double-vector and triple-vector modulated MPC strategies cannot achieve optimal control. Thus, a new hybrid multi-vector modulated MPC strategy is further proposed. By selecting an optimal voltage vector from 18 alternative voltage vector combinations, the current control performance is improved. Detailed comparative experimental results based on experimental platform and StarSim hardware-in-the-loop platform validate the effectiveness of the proposed hybrid multi-vector modulated MPC strategy.