Adaptive Zero‐Crossing Distortion Suppression Strategy for Vienna Rectifier Based on Vector Error Modeling

ABSTRACT To address the issue of input current zero‐crossing distortion in Vienna rectifiers, this paper proposes an adaptive zero‐crossing distortion suppression strategy based on vector error modeling. First, the phenomenon of input current zero‐crossing distortion in Vienna rectifiers is analyzed, revealing that sector misjudgments caused by ripple and sampling errors near the current zero‐crossing, as well as vector errors generated by the use of shared switch states during these misjudgments, are the fundamental causes of the distortion. Based on this analysis, a quantitative mathematical model of the sector misjudgment conditions and vector errors is developed. On this basis, an adaptive zero‐crossing distortion suppression strategy is designed by constructing a multi‐objective model predictive error function incorporating vector errors, optimizing the use of shared switch states, and dynamically compensating vector errors to suppress input current zero‐crossing distortion. Finally, the proposed method is validated through simulation and physical platform experiments. Experimental results demonstrate that the method can effectively suppress input current zero‐crossing distortion, significantly improve input current quality, and provide a new approach for zero‐crossing distortion suppression in Vienna rectifiers.