<p>With the development of the electric vehicle industry, Vienna rectifiers have been widely studied for their control strategies due to their high power density and low harmonic content. Traditional finite control set - model predictive control (FCS-MPC) has poor control performance at low switching frequency and is difficult in achieving multi-objective control when used in Vienna rectifier. Therefore, a hierarchical model predictive control strategy based on virtual vector and optimal switching sequence is proposed in this paper (VV-OSS-MPC). Firstly, an extended space vector set containing 157 vectors (including 138 virtual vectors) is constructed to improve the control accuracy. Secondly, a sector localization algorithm based on feature vectors is used to reduce the number of candidate vectors to 8–10, which greatly reduces the computational burden. Finally, the current tracking is realized through the outer MPC, and the inner MPC selects the optimal switch sequence according to the neutral point voltage state to achieve voltage balance, thus completely avoiding the setting of the weight factor. Compared with the traditional FCS-MPC method, the calculation time is shortened from 17.9µs to 12.3µs. The experimental results confirm that the proposed scheme can reduce the total harmonic distortion of the current to 2.9%, the voltage fluctuation does not exceed 4&#xa0;V, and the computational complexity can be reduced.</p>