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Low-Complexity Three-Vector Based Model Predictive Flux Control for Induction Motors
ID：44 View Protection：PRIVATE Updated Time：2023-06-14 10:47:54 Hits：1019 Oral Presentation

Start Time：2023-06-18 14:40（Asia/Shanghai）

Duration：20min

Session：S Oral Session » S6Oral Session 9 & Oral Session 12

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Abstract
In this paper, a low-complexity model predictive flux control (MPFC) with a fixed switching frequency is proposed for induction motors (IMs) fed by a two-level voltage source inverter. The appropriate active voltage vectors (AVVs) are determined according to estimated torque derivation. The generalized discrete space vector is used for improving the controller performance, and the computation time is mitigated by derivation of the extremum of the flux control objective. To ensure the controller switching frequency is fixed, the synthesized control voltage vector is implemented using a symmetrical three-vector method. The proposed controller is evaluated at 5 kHz sampling frequency and the achieved results validate the effectiveness of the strategy for improving the steady-state performance while maintaining a constant switching frequency around 5 kHz over a wide range of operating conditions.
Keywords
Model predictive flux control (MPFC), active voltage vector (AVV), induction motors (IMs), steady-state performance, switching frequency (SF).
Speaker
Huiqing Song

Tao Jin
Fuzhou University

Ipoum-Ngome Paul Gistain

Jinquan Tang

Mon-Nzongo Daniel Legrand

Jose Rodriguez
Universidad San Sebastian

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Important Date

  • Conference Date

    Jun 16

    2023

    to

    Jun 19

    2023

  • Jun 15 2023

    Contribution Submission Deadline

  • Jul 02 2023

    Registration deadline

Sponsored By
Huazhong University of Science and Technology, China
(IEEE PELS)
IEEE
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