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基于扩充虚拟矢量的永磁同步电动机模型预测直接转矩控制

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author:

Zheng, W. (Zheng, W..) [1] | Zhou, Y. (Zhou, Y..) [2] (Scholars:周扬忠) | Zhong, T. (Zhong, T..) [3] (Scholars:钟天云) | Unfold

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Scopus PKU CSCD

Abstract:

To address the problems of traditional model predictive direct torque control strategy, such as low computational efficiency, high voltage jump and poor steady-state characteristics, an improved model predictive direct torque control strategy is proposed. To improve the steady-state characteristics of the motor, 36 virtual voltage vectors are constructed based on the principle of the nearest three vectors. The action time of redundant vectors in the virtual voltage vector is adjusted by combining the principle of no beat. To prevent excessive voltage jump in the output line of the inverter from causing adverse effects on the motor, only voltage vectors with voltage jump not exceeding Udc / 2 are selected as alternative voltage vectors. Meanwhile, the reference voltage vector is predicted by combining the model with the deadbeat principle, and the voltage vector located in the same sector as the reference voltage vector is selected as the final candidate vector set. Compared with traditional control strategies under rated operating conditions, the experimental results show that the improved control strategy reduces the electromagnetic torque, stator flux amplitude error, and current harmonic distortion rate by 37. 42%, 32. 00%, and 44. 52%, respectively. The program execution time is reduced by approximately 11. 52% . © 2023 Science Press. All rights reserved.

Keyword:

computing efficiency jump of voltage model predictive direct torque control permanent magnet synchronous motor steady state performance T-type three-level inverter

Community:

  • [ 1 ] [Zheng W.]Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Zhou Y.]Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Zhong T.]Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Qu A.]Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou, 350116, China

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Source :

仪器仪表学报

ISSN: 0254-3087

CN: 11-2179/TH

Year: 2023

Issue: 7

Volume: 44

Page: 296-304

Cited Count:

WoS CC Cited Count:

30 Days PV: 0

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