An Improved Strategy Combining with MPC for IPMSM Flux-Weakening Control

Yu Luo, Zheng Li, Dongliang Ke, S. Alireza Davari, Dongxiao Huang, Fengxiang Wang, Jose Rodriguez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper proposes a new hybrid flux-weakening strategy which combines look-up table algorithm, voltage feed-back and model predictive control method to realize the high speed control of interior permanent synchronous motor (IPMSM). In order to identify the current situation of the motor in the process of speed increase, a large number of experiments have been carried out. And by processing these data with Matlab fitting tools, two precise three-dimensional fitting planes are obtained. In the other place, for the stable control which aims to avoid voltage exceeding limit, feedback means is also taken. Most of all, model predictive control is integrated into this strategy, so that selecting the optimal control voltage vector for IPMSMs. The effectiveness of this strategy is verified by simulation.

Original languageEnglish
Title of host publication6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages190-195
Number of pages6
ISBN (Electronic)9781665425575
DOIs
Publication statusPublished - 2021
Event6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021 - Jinan, China
Duration: 20 Nov 202122 Nov 2021

Publication series

Name6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021

Conference

Conference6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2021
Country/TerritoryChina
CityJinan
Period20/11/2122/11/21

Keywords

  • hybrid flux-weakening control
  • IPMSM
  • model predictive control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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