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Current decoupling model predictive control of a leakage flux controllable PM motor in virtual flux reference frame

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posted on 2025-07-22, 11:01 authored by Xiaoyong Zhu, Lei Xu, Lei Li, Wen-Hua ChenWen-Hua Chen, Wenjie Fan, Zhiwei Jin, Li Quan
The leakage flux controllable permanent magnet (LFC-PM) motor, which uses intentional magnet leakage flux paths cross-coupled with the q-axis flux paths to realize flux regulation, has been proposed recently and has received widespread attention for traction applications. Yet, the dual function of q-axis current, including flux regulation and torque generation, along with the resulting parameter variation caused by the controllable leakage flux, is one of the main barriers to its control and widespread application. To overcome this barrier, based on the model predictive current control, this article proposes a current decoupling control for the LFC-PM motor. The contribution of this paper is developing a virtual flux reference frame concept where the mathematic model and the optimal current assignment are deduced. On this basis, the predicted parameters can be obtained more accurately, which can suppress the disturbances and low efficiency caused by the mismatched parameters in the process of flux regulation. The proposed decoupling control is validated and compared with the traditional maximum torque per ampere methods. The effectiveness of the proposed control strategy is validated by means of experimental results on a test rig with a 3-kW leakage flux controllable PM motor.<p></p>

Funding

National Natural Science Foundation of China [grant no. 52320105009]

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Industrial Electronics

Volume

71

Issue

8

Pages

8471 - 8481

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2023-09-01

Publication date

2023-10-03

Copyright date

2023

ISSN

0278-0046

eISSN

1557-9948

Language

  • en

Depositor

Prof Wen-Hua Chen. Deposit date: 26 June 2024

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