Predictive torque control with fixed switching frequency for induction motor drives

Jose A. Riveros, Marco Rivera, Consuelo Rodriguez, Michael Galea, Giampaolo Buticchi, Patrick Wheeler

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

5 Citations (Scopus)

Abstract

Predictive torque control is one of the most considered high-performance methods for variable-speed applications. This scheme is characterised by a flexible architecture that provides a fast torque/flux response, while its operation reports variable switching frequency as one of the main issues. This work presents a redesigned technique to overcome the described drawback. The strategy applies two active voltage space vectors with an appropriate sequence at every sampling period to produce a constant number of commutations. The dwell times are computed with the conventional cost function and a novel optimisation process to obtain the proper switching combination. Simulation tests at transient- and steady-state demonstrate the quick dynamic response of this proposal, whereas a performance comparison respect to the conventional implementation illustrates the achieved enhancements and mitigation trade-off.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Industrial Technology, ICIT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-216
Number of pages6
ISBN (Electronic)9781728157542
DOIs
Publication statusPublished - Feb 2020
Event21st IEEE International Conference on Industrial Technology, ICIT 2020 - Buenos Aires, Argentina
Duration: 26 Feb 202028 Feb 2020

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2020-February

Conference

Conference21st IEEE International Conference on Industrial Technology, ICIT 2020
Country/TerritoryArgentina
CityBuenos Aires
Period26/02/2028/02/20

Keywords

  • Predictive control
  • Torque control
  • Variable speed drives

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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