Switched Reluctance Motor Design for an EV Propulsion Application

Omar Zayed; Mohamed Omar; Mohamed Bakr; Mehdi Narimani; Ali Emadi; Berker Bilgin

doi:10.1109/IECON48115.2021.9589953

Switched Reluctance Motor Design for an EV Propulsion Application

Omar Zayed
, Mohamed Omar
, Mohamed Bakr
, Mehdi Narimani
, Ali Emadi
, Berker Bilgin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

This paper introduces a design methodology for a Switched Reluctance Motor (SRM) for an 80 kW Battery Electric Vehicle (BEV) propulsion application. The methodology aims to satisfy the high power density requirement targeted for an electric motor for a BEV application, while maintaining improved efficiency and torque quality. Iterative modeling effort has been employed for the design, including finite element analysis for the electromagnetic characteristics of the motor and dynamic modeling for performance analyses. The design approach starts with determining the motor geometry followed by sensitivity analysis for the motor performance considering various motor parameters. Then the SRM conduction angles are optimized with multi-objective genetic algorithm to improve the torque density and reduce torque ripple. The performance is further analyzed and compared to the target motor.

Original language	English
Title of host publication	IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665435543
DOIs	https://doi.org/10.1109/IECON48115.2021.9589953
State	Published - 13 Oct 2021
Externally published	Yes

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2021-October

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Electric vehicle
genetic algorithm
motor design
multi-objective optimization
switched reluctance motor

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IECON48115.2021.9589953

Cite this

Zayed, O., Omar, M., Bakr, M., Narimani, M., Emadi, A., & Bilgin, B. (2021). Switched Reluctance Motor Design for an EV Propulsion Application. In IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October). IEEE Computer Society. https://doi.org/10.1109/IECON48115.2021.9589953

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title = "Switched Reluctance Motor Design for an EV Propulsion Application",

abstract = "This paper introduces a design methodology for a Switched Reluctance Motor (SRM) for an 80 kW Battery Electric Vehicle (BEV) propulsion application. The methodology aims to satisfy the high power density requirement targeted for an electric motor for a BEV application, while maintaining improved efficiency and torque quality. Iterative modeling effort has been employed for the design, including finite element analysis for the electromagnetic characteristics of the motor and dynamic modeling for performance analyses. The design approach starts with determining the motor geometry followed by sensitivity analysis for the motor performance considering various motor parameters. Then the SRM conduction angles are optimized with multi-objective genetic algorithm to improve the torque density and reduce torque ripple. The performance is further analyzed and compared to the target motor.",

keywords = "Electric vehicle, genetic algorithm, motor design, multi-objective optimization, switched reluctance motor",

author = "Omar Zayed and Mohamed Omar and Mohamed Bakr and Mehdi Narimani and Ali Emadi and Berker Bilgin",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.",

year = "2021",

month = oct,

day = "13",

doi = "10.1109/IECON48115.2021.9589953",

language = "English",

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Switched Reluctance Motor Design for an EV Propulsion Application. / Zayed, Omar; Omar, Mohamed; Bakr, Mohamed et al.
IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2021. (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Switched Reluctance Motor Design for an EV Propulsion Application

AU - Zayed, Omar

AU - Omar, Mohamed

AU - Bakr, Mohamed

AU - Narimani, Mehdi

AU - Emadi, Ali

AU - Bilgin, Berker

PY - 2021/10/13

Y1 - 2021/10/13

N2 - This paper introduces a design methodology for a Switched Reluctance Motor (SRM) for an 80 kW Battery Electric Vehicle (BEV) propulsion application. The methodology aims to satisfy the high power density requirement targeted for an electric motor for a BEV application, while maintaining improved efficiency and torque quality. Iterative modeling effort has been employed for the design, including finite element analysis for the electromagnetic characteristics of the motor and dynamic modeling for performance analyses. The design approach starts with determining the motor geometry followed by sensitivity analysis for the motor performance considering various motor parameters. Then the SRM conduction angles are optimized with multi-objective genetic algorithm to improve the torque density and reduce torque ripple. The performance is further analyzed and compared to the target motor.

AB - This paper introduces a design methodology for a Switched Reluctance Motor (SRM) for an 80 kW Battery Electric Vehicle (BEV) propulsion application. The methodology aims to satisfy the high power density requirement targeted for an electric motor for a BEV application, while maintaining improved efficiency and torque quality. Iterative modeling effort has been employed for the design, including finite element analysis for the electromagnetic characteristics of the motor and dynamic modeling for performance analyses. The design approach starts with determining the motor geometry followed by sensitivity analysis for the motor performance considering various motor parameters. Then the SRM conduction angles are optimized with multi-objective genetic algorithm to improve the torque density and reduce torque ripple. The performance is further analyzed and compared to the target motor.

KW - Electric vehicle

KW - genetic algorithm

KW - motor design

KW - multi-objective optimization

KW - switched reluctance motor

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DO - 10.1109/IECON48115.2021.9589953

M3 - Conference contribution

AN - SCOPUS:85119511408

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Computer Society

ER -

Switched Reluctance Motor Design for an EV Propulsion Application

Abstract

Publication series

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this