Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses

Euan MacRae; Ali Abdel-Aziz; Khaled Ahmed; Richard Pollock; Barry W. Williams

doi:10.1109/IEMDC55163.2023.10239015

Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses

Euan MacRae, Ali Abdel-Aziz, Khaled Ahmed, Richard Pollock, Barry W. Williams

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

2 Citations (Scopus)

23 Downloads (Pure)

Abstract

This paper presents a novel approach to current profiling for switched reluctance machines that eliminates torque ripple while inherently guaranteeing minimum copper losses, along with linear torque control. Minimization of copper losses increases machine efficiency, while eliminating torque ripple is the pre requisite for SRM use in applications such as traction vehicles. This paper presents theoretical optimal current profiles, initially without consideration of DC link voltage limitations. Utilizing a Genetic Algorithm in conjunction with current profiling limit envelopes, an optimized set of current profiles across the torque ripple free speed range of an exemplary 8/6 SRM is then created. The profiles characteristics are analyzed and compared with commonly used torque sharing function control to confirm the merits of the proposed method.

Original language	English
Title of host publication	2023 IEEE International Electric Machines & Drives Conference (IEMDC)
Place of Publication	Piscataway, NJ
Publisher	IEEE
Number of pages	7
ISBN (Electronic)	9798350398991
ISBN (Print)	9798350399004
DOIs	https://doi.org/10.1109/IEMDC55163.2023.10239015
Publication status	Published - 6 Sept 2023
Event	International Electric Machines and Drives Conference 2023 - San Francisco, United States Duration: 15 May 2023 → 18 May 2023

Conference

Conference	International Electric Machines and Drives Conference 2023
Abbreviated title	IEMDC 2023
Country/Territory	United States
City	San Francisco
Period	15/05/23 → 18/05/23

Keywords

current profiling
electric vehicles
genetic algorithm
switched reluctance machine

Access to Document

10.1109/IEMDC55163.2023.10239015

MacRae-etal-IEMDC-2023-Genetic-algorithm-based-approach-of-SRM-current-profilingAccepted author manuscript, 1.09 MBLicence: Strath_1

Cite this

@inproceedings{886b33b1e8a3455681fb88e0d0a611a8,

title = "Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses",

abstract = "This paper presents a novel approach to current profiling for switched reluctance machines that eliminates torque ripple while inherently guaranteeing minimum copper losses, along with linear torque control. Minimization of copper losses increases machine efficiency, while eliminating torque ripple is the pre requisite for SRM use in applications such as traction vehicles. This paper presents theoretical optimal current profiles, initially without consideration of DC link voltage limitations. Utilizing a Genetic Algorithm in conjunction with current profiling limit envelopes, an optimized set of current profiles across the torque ripple free speed range of an exemplary 8/6 SRM is then created. The profiles characteristics are analyzed and compared with commonly used torque sharing function control to confirm the merits of the proposed method.",

keywords = "current profiling, electric vehicles, genetic algorithm, switched reluctance machine",

author = "Euan MacRae and Ali Abdel-Aziz and Khaled Ahmed and Richard Pollock and Williams, {Barry W.}",

note = "Copyright {\textcopyright} 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; International Electric Machines and Drives Conference 2023, IEMDC 2023 ; Conference date: 15-05-2023 Through 18-05-2023",

year = "2023",

month = sep,

day = "6",

doi = "10.1109/IEMDC55163.2023.10239015",

language = "English",

isbn = "9798350399004",

booktitle = "2023 IEEE International Electric Machines & Drives Conference (IEMDC)",

publisher = "IEEE",

}

MacRae, E, Abdel-Aziz, A, Ahmed, K, Pollock, R & Williams, BW 2023, Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses. in 2023 IEEE International Electric Machines & Drives Conference (IEMDC). IEEE, Piscataway, NJ, International Electric Machines and Drives Conference 2023, San Francisco, California, United States, 15/05/23. https://doi.org/10.1109/IEMDC55163.2023.10239015

TY - GEN

T1 - Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses

AU - MacRae, Euan

AU - Abdel-Aziz, Ali

AU - Ahmed, Khaled

AU - Pollock, Richard

AU - Williams, Barry W.

N1 - Copyright © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2023/9/6

Y1 - 2023/9/6

N2 - This paper presents a novel approach to current profiling for switched reluctance machines that eliminates torque ripple while inherently guaranteeing minimum copper losses, along with linear torque control. Minimization of copper losses increases machine efficiency, while eliminating torque ripple is the pre requisite for SRM use in applications such as traction vehicles. This paper presents theoretical optimal current profiles, initially without consideration of DC link voltage limitations. Utilizing a Genetic Algorithm in conjunction with current profiling limit envelopes, an optimized set of current profiles across the torque ripple free speed range of an exemplary 8/6 SRM is then created. The profiles characteristics are analyzed and compared with commonly used torque sharing function control to confirm the merits of the proposed method.

AB - This paper presents a novel approach to current profiling for switched reluctance machines that eliminates torque ripple while inherently guaranteeing minimum copper losses, along with linear torque control. Minimization of copper losses increases machine efficiency, while eliminating torque ripple is the pre requisite for SRM use in applications such as traction vehicles. This paper presents theoretical optimal current profiles, initially without consideration of DC link voltage limitations. Utilizing a Genetic Algorithm in conjunction with current profiling limit envelopes, an optimized set of current profiles across the torque ripple free speed range of an exemplary 8/6 SRM is then created. The profiles characteristics are analyzed and compared with commonly used torque sharing function control to confirm the merits of the proposed method.

KW - current profiling

KW - electric vehicles

KW - genetic algorithm

KW - switched reluctance machine

U2 - 10.1109/IEMDC55163.2023.10239015

DO - 10.1109/IEMDC55163.2023.10239015

M3 - Conference contribution book

SN - 9798350399004

BT - 2023 IEEE International Electric Machines & Drives Conference (IEMDC)

PB - IEEE

CY - Piscataway, NJ

T2 - International Electric Machines and Drives Conference 2023

Y2 - 15 May 2023 through 18 May 2023

ER -

Genetic algorithm based approach of SRM current profiling for torque control and minimal copper losses

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