Direct Torque Control for a Bearingless Induction Motor Based on Model prediction
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Published:2021-08-19
Issue:ahead-of-print
Volume:ahead-of-print
Page:
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ISSN:0332-1649
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Container-title:COMPEL - The international journal for computation and mathematics in electrical and electronic engineering
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language:en
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Short-container-title:COMPEL
Author:
Wang Ding,Yang Zebin,Sun Xiaodong,Sun Weiming,Mei Haitao
Abstract
Purpose
The purpose of this paper is to address the large stator flux linkage ripple and electromagnetic torque ripple caused by the hysteresis comparator in traditional direct torque control for a bearingless induction motor (BIM).
Design/methodology/approach
Model predictive direct torque control (MPDTC) strategy is adopted. On the basis of the mathematical model of BIM, the stator current and stator flux observational values are obtained, and the electromagnetic torque and stator flux at the next moment are predicted. Then, based on the relationship between the stator flux and the electromagnetic torque, the predicted stator flux can be transformed into an equivalent flux linkage vector, which eliminates the weighting coefficients problem among multiple variables in traditional objective functions. The objective function and torque PI controller will output the optimal stator flux linkage and the increments of the torque phase angle. Through the phase angle increments, the space voltage vector can be obtained by the reference flux linkage controller instead of the stator flux linkage and the torque hysteresis controller.
Findings
The proposed MPDTC method can effectively improve the stator flux linkage and the torque ripple. It can implement the stable suspension of the rotor and improve the dynamic performance and steady-state accuracy of the BIM system.
Originality/value
A MPDTC strategy is proposed to reduce the ripple of stator flux and electromagnetic torque. The phase angle increment angle of stator flux linkage and electromagnetic torque is optimized by model prediction, and the optimal space voltage vector is obtained by designing the reference flux controller.
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computational Theory and Mathematics,Computer Science Applications
Reference24 articles.
1. New modelling approach for micro energy harvesting systems based on model order reduction enabling truly system-level simulation,2012
2. Dimension reduction of large-scale second-order dynamical system via a second-order Arnoldi method;SIAM Journal on Scientific Computing,2005
3. Index-aware model order reduction methods for DAEs;Technische Universiteit Eindhoven,2014
4. Model reduction by rational interpolation,2017