[Oral Presentation]Low-Complexity Three-Vector Based Model Predictive Flux Control for Induction Motors

IMPORTANT DATES

Digest Submission Opens: Oct. 30, 2022
Digest Submission Deadline: Mar. 20, 2023
Acceptance Notification: Apr. 28, 2023
Full Paper Submission Deadline: May. 20, 2023

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：369 Oral Presentation

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

Duration：20min

Session：[S] Oral Session » [S6] Oral 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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