Robust three‐voltage‐vector‐based model‐free predictive current control for permanent magnet synchronous motor with ultra‐local model

Abstract

Abstract A large current ripple may arise in the finite control set model‐free predictive current control (FCS‐MFPCC) strategy because only one voltage vector can be applied during the whole control period. Therefore, an improved three‐vector‐based model‐free predictive current control (MFPCC) strategy to improve the current tracking performance is proposed by increasing the number of the applied voltage vector. Based on the extreme existence theorem for the function of two variables, the optimal voltage vector can be synthesized. Compared with the one‐vector‐based FCS‐model‐based predicted current control (FCS‐MBPCC) and two‐vector‐based FCS‐MBPCC in the time and frequency domains, the maximum tracking error is decreased by 42.17% and 48.58%, and the total harmonic distortion is decreased by 40.97% and 37.56%, respectively. Besides, compared with the previous three‐vector‐based strategy, the computational time of the proposed strategy is reduced from 57.6 to 45.89 μs, which is reduced by 20.33%. Furthermore, the switching frequency of the proposed method can be decreased by 70.3% compared with the deadbeat MFPCC. The experimental results in the time and frequency domains demonstrate that the proposed three‐vector‐based MFPCC can not only improve the current tracking performance but also improve robustness against parameter mismatches.

Keywords

• permanent magnet motors
• predictive control
• model‐free