Gradient-based design optimization of a switched reluctance motor for an HVAC application

Ehab Sayed; Mohamed H. Bakr; Berker Bilgin; Ali Emadi

doi:10.1109/ITEC48692.2020.9161741

Gradient-based design optimization of a switched reluctance motor for an HVAC application

Ehab Sayed
, Mohamed H. Bakr
, Berker Bilgin
, Ali Emadi

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

7 Scopus citations

Abstract

This work proposes a 6/14 SRM that achieves the performance specifications of a commercially available motor of a heating, ventilation, and air-conditioning (HVAC) system. The authors developed a MATLAB tool to automate the design process of the considered motor. The tool calculates the sensitivities/gradients of the considered objective function with respect to various design parameters. An interior-point algorithm uses the estimated gradients to simultaneously optimize the geometry and electric-circuit parameters of a 6/14 SRM to maximize the motor dynamic torque. The ON/OFF topology optimization technique then utilizes the obtained adjoint sensitivities with respect to material properties to optimize the ferromagnetic material distribution in the stator teeth of the previously optimized design to reduce the torque ripple.

Original language	English
Title of host publication	2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1031-1037
Number of pages	7
ISBN (Electronic)	9781728146294
DOIs	https://doi.org/10.1109/ITEC48692.2020.9161741
State	Published - Jun 2020
Externally published	Yes
Event	2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020 - Chicago, United States Duration: 23 Jun 2020 → 26 Jun 2020

Publication series

Name	2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020

Conference

Conference	2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020
Country/Territory	United States
City	Chicago
Period	23/06/20 → 26/06/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

AVM method
CFD Method
FEM analysis
geometry optimization
switched reluctance machine
topology optimization

ASJC Scopus subject areas

Energy Engineering and Power Technology
Automotive Engineering
Transportation

Access to Document

10.1109/ITEC48692.2020.9161741

Cite this

Sayed, E., Bakr, M. H., Bilgin, B., & Emadi, A. (2020). Gradient-based design optimization of a switched reluctance motor for an HVAC application. In 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020 (pp. 1031-1037). Article 9161741 (2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITEC48692.2020.9161741

Sayed, Ehab ; Bakr, Mohamed H. ; Bilgin, Berker et al. / Gradient-based design optimization of a switched reluctance motor for an HVAC application. 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 1031-1037 (2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020).

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title = "Gradient-based design optimization of a switched reluctance motor for an HVAC application",

abstract = "This work proposes a 6/14 SRM that achieves the performance specifications of a commercially available motor of a heating, ventilation, and air-conditioning (HVAC) system. The authors developed a MATLAB tool to automate the design process of the considered motor. The tool calculates the sensitivities/gradients of the considered objective function with respect to various design parameters. An interior-point algorithm uses the estimated gradients to simultaneously optimize the geometry and electric-circuit parameters of a 6/14 SRM to maximize the motor dynamic torque. The ON/OFF topology optimization technique then utilizes the obtained adjoint sensitivities with respect to material properties to optimize the ferromagnetic material distribution in the stator teeth of the previously optimized design to reduce the torque ripple.",

keywords = "AVM method, CFD Method, FEM analysis, geometry optimization, switched reluctance machine, topology optimization",

author = "Ehab Sayed and Bakr, \{Mohamed H.\} and Berker Bilgin and Ali Emadi",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020 ; Conference date: 23-06-2020 Through 26-06-2020",

year = "2020",

month = jun,

doi = "10.1109/ITEC48692.2020.9161741",

language = "English",

series = "2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Sayed, E, Bakr, MH, Bilgin, B & Emadi, A 2020, Gradient-based design optimization of a switched reluctance motor for an HVAC application. in 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020., 9161741, 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020, Institute of Electrical and Electronics Engineers Inc., pp. 1031-1037, 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020, Chicago, United States, 23/06/20. https://doi.org/10.1109/ITEC48692.2020.9161741

Gradient-based design optimization of a switched reluctance motor for an HVAC application. / Sayed, Ehab; Bakr, Mohamed H.; Bilgin, Berker et al.
2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1031-1037 9161741 (2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020).

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

TY - GEN

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AU - Sayed, Ehab

AU - Bakr, Mohamed H.

AU - Bilgin, Berker

AU - Emadi, Ali

PY - 2020/6

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N2 - This work proposes a 6/14 SRM that achieves the performance specifications of a commercially available motor of a heating, ventilation, and air-conditioning (HVAC) system. The authors developed a MATLAB tool to automate the design process of the considered motor. The tool calculates the sensitivities/gradients of the considered objective function with respect to various design parameters. An interior-point algorithm uses the estimated gradients to simultaneously optimize the geometry and electric-circuit parameters of a 6/14 SRM to maximize the motor dynamic torque. The ON/OFF topology optimization technique then utilizes the obtained adjoint sensitivities with respect to material properties to optimize the ferromagnetic material distribution in the stator teeth of the previously optimized design to reduce the torque ripple.

AB - This work proposes a 6/14 SRM that achieves the performance specifications of a commercially available motor of a heating, ventilation, and air-conditioning (HVAC) system. The authors developed a MATLAB tool to automate the design process of the considered motor. The tool calculates the sensitivities/gradients of the considered objective function with respect to various design parameters. An interior-point algorithm uses the estimated gradients to simultaneously optimize the geometry and electric-circuit parameters of a 6/14 SRM to maximize the motor dynamic torque. The ON/OFF topology optimization technique then utilizes the obtained adjoint sensitivities with respect to material properties to optimize the ferromagnetic material distribution in the stator teeth of the previously optimized design to reduce the torque ripple.

KW - AVM method

KW - CFD Method

KW - FEM analysis

KW - geometry optimization

KW - switched reluctance machine

KW - topology optimization

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M3 - Conference contribution

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BT - 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020

Y2 - 23 June 2020 through 26 June 2020

ER -

Sayed E, Bakr MH, Bilgin B, Emadi A. Gradient-based design optimization of a switched reluctance motor for an HVAC application. In 2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 1031-1037. 9161741. (2020 IEEE Transportation Electrification Conference and Expo, ITEC 2020). doi: 10.1109/ITEC48692.2020.9161741

Gradient-based design optimization of a switched reluctance motor for an HVAC application

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this