EconPapers    
Economics at your fingertips  
 

Comparison of an Off-Line Optimized Firing Angle Modulation and Torque Sharing Functions for Switched Reluctance Motor Control

Peter Bober and Želmíra Ferková
Additional contact information
Peter Bober: Faculty of Electrical Engineering and Informatics, Technical University of Kosice, 04200 Kosice, Slovakia
Želmíra Ferková: Faculty of Electrical Engineering and Informatics, Technical University of Kosice, 04200 Kosice, Slovakia

Energies, 2020, vol. 13, issue 10, 1-13

Abstract: In this paper, a comparison of the simple firing angle modulation method (FAM) and the more advanced torque sharing function (TSF)-based control of switched reluctance motor (SRM) is presented. The off-line procedure to tailor and optimize the parameters of chosen methods for off-the-shelf SRM is explained. Objective functions for optimization are motor efficiency, torque ripple, and integral square error. The off-line optimization uses a finite element method (FEM) model of the SRM. The model was verified by measurement on the SRM. Simulation results showed that FAM has comparable efficiency to TSF, but has a much higher value of torque ripple. The presented off-line procedure can be used for single or multi-objective optimization.

Keywords: switched reluctance motor; torque sharing functions; finite element method; firing angle modulation; torque ripple; efficiency; optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/10/2435/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/10/2435/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:10:p:2435-:d:357237

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2435-:d:357237