Modeling and Hierarchical Structure Based Model Predictive Control of Cascaded Flying Capacitor Bridge Multilevel Converter for Active Front-End Rectifier in Solid-State Transformer

This paper introduces modeling and control of a cascaded flying capacitor bridge (CFCB) multilevel converter for a solid-state transformer. The finite control set-model predictive control (FCS-MPC) is easy and simple to implement for many applications. However, the computational complexity increases with the increase in the number of switches. Furthermore, as the number of control variables increases, the weighting factors also increase. Thus, it is difficult to apply to a system with a large number of switches and variables to be controlled similar to a CFCB multilevel converter. In this paper, the proposed method divides variables such as current, dc-link voltage, and flying capacitor voltage into layers. The proposed method reduces the number of states to be considered in the control, which shortens the computational time and simplifies expansion of the flying capacitor bridge. In addition, since weighting factors are not used, there is no tradeoff between current quality and voltage quality, and there is no difficulty in selecting weighting factors. Algorithms that include a method for compensating for the distortion caused by the delay of the digital control system are also described. The effectiveness of the proposed method is verified via experiments using a two-cell CFCB multilevel converter.