Energy-Efficient Control of Bearingless Linear Motors

Reza Hosseinzadeh*, Floran Martin, Marko Hinkkanen

*Corresponding author for this work

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

Abstract

This paper presents a method to minimize the resistive losses in bearingless linear motors. A minimization algorithm is developed for calculating reference currents for a range of reference forces while the effect of spatial harmonics on force production is considered. The results from the algorithm are implemented in the form of lookup tables and artificial neural networks. A comparison between the two implementation methods is presented. Time-domain simulation results are given for motion control of a bearingless linear flux-switching permanent-magnet motor system while using optimal reference currents. Index Terms-Artificial neural networks, bearingless, energy efficiency, linear actuator, magnetic levitation, table lookup.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Conference on Mechatronics, ICM 2023
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-6654-6661-5
DOIs
Publication statusPublished - 17 Apr 2023
MoE publication typeA4 Conference publication
EventIEEE International Conference on Mechatronics - Leicestershire, United Kingdom
Duration: 15 Mar 202317 Mar 2023

Publication series

NameProceedings - 2023 IEEE International Conference on Mechatronics, ICM 2023

Conference

ConferenceIEEE International Conference on Mechatronics
Abbreviated titleICM
Country/TerritoryUnited Kingdom
CityLeicestershire
Period15/03/202317/03/2023

Keywords

  • Artificial neural networks
  • bearingless
  • energy efficiency
  • linear actuator
  • magnetic levitation
  • table lookup

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