Three-Layer Double-Vector Model Predictive Control Strategy for Current Harmonic Reduction and Neutral-Point Voltage Balance in Vienna Rectifier

Vienna rectifier, which is a nongenerative-boost-type rectifier, is widely employed in electric vehicle charging systems. Nevertheless, the Vienna rectifier faces the challenge of current distortion elimination, current ripple mitigation, and neutral-point (NP) voltage balance. As these problems are mutually coupled, the conventional finite control set model predictive control (FCS-MPC) methods cannot solve these problems properly. To address these issues, a three-layer double-vector FCS-MPC method is proposed. In the first layer of the proposed FCS-MPC method, the sectors are divided and the candidate vectors are selected to reduce the current distortion. In the second layer of the proposed FCS-MPC method, the double vectors with optimal duty cycles are adopted to reduce the current ripples. In the third layer of the proposed FCS-MPC method, the NP voltage is balanced by selecting the redundant p-type small vector or n-type small vector. Through the proposed method, the current distortion elimination, current ripple mitigation, and NP voltage balancing are realized at the same time. The effectiveness of the proposed method has been verified by simulation and experiment.

Automated summary

This paper proposes a three-layer double-vector FCS-MPC method to address the challenges of current distortion elimination, current ripple mitigation, and NP voltage balance in the Vienna rectifier. By dividing the sectors and selecting candidate vectors to reduce current distortion, adopting double vectors with optimal duty cycles to reduce current ripples, and balancing the NP voltage by selecting redundant p-type or n-type small vectors, the proposed method achieves simultaneous current distortion elimination, current ripple mitigation, and NP voltage balancing. The effectiveness of the method has been verified through simulation and experiment.