Robustness model prediction torque optimization control for permanent magnet synchronous motor

Beiheng Song; Haiyan Zhang; Junbo Xu; Te Liu

doi:10.1117/12.2686825

10 August 2023 Robustness model prediction torque optimization control for permanent magnet synchronous motor

Beiheng Song, Haiyan Zhang, Junbo Xu, Te Liu

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 1275929 (2023) https://doi.org/10.1117/12.2686825
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

To address the issue of large torque ripple in traditional model predictive torque control for permanent magnet synchronous motors, we propose a torque-flux hysteresis-based model predictive voltage control approach. Firstly, a mathematical model is formulated in a two-phase rotating reference frame, and the computation process for the suggested model predictive voltage regulation technique grounded on the torque-flux hysteresis is delineated. To reduce the switching frequency, a spatial vector modulation technique and a hysteresis-based predictive torque-flux control are combined. To minimize the impact of parameter variations on model predictions, the least squares method is used for motor parameter identification. The simulation results indicate that the proposed method is capable of efficiently decreasing both switching losses and torque ripple, while simultaneously ensuring satisfactory system performance.

Citation Download Citation

Beiheng Song, Haiyan Zhang, Junbo Xu, and Te Liu "Robustness model prediction torque optimization control for permanent magnet synchronous motor", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 1275929 (10 August 2023); https://doi.org/10.1117/12.2686825

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