PMSM optimized predictive flux control based on three vectors

Zhi Li; Li Zhou; Yuqi Nie

doi:10.1117/12.3008921

27 October 2023 PMSM optimized predictive flux control based on three vectors

Zhi Li, Li Zhou, Yuqi Nie

Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 129220O (2023) https://doi.org/10.1117/12.3008921
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China

Abstract

In order to reduce torque ripple and current ripple of permanent magnet synchronous motor (PMSM) in traditional model predictive control, a improved predictive flux control scheme is proposed. First,synthesize 12 virtual voltage vectors. In order to simplify the vector selection, divide each vector into 12 sectors, quickly determine the vector range by calculating the voltage vector angle, reduce the optional 12 voltage vectors to 2, Simply calculate the cost function twice to select the first required vector. Secondly,Pairwise combine the first vector selected with the remaining 11 vectors, and the unwanted voltage vectors are filtered out through the designed flux linkage cost function to Select the two vectors with the best control effect. Flexibly add a zero voltage vector according to the switching characteristics of the inverter to adjusting the magnitude of voltage and vector angle, and a fuzzy controller is designed to improve the evaluation accuracy of speed loop. Finally, use the flux difference parameter to calculate the occupancy time of each voltage. The experimental results show that the proposed scheme reduces the torque current fluctuation and improves the stability of the system.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhi Li, Li Zhou, and Yuqi Nie "PMSM optimized predictive flux control based on three vectors", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 129220O (27 October 2023); https://doi.org/10.1117/12.3008921

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