Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine

Myung Ki Seo; Tae Yong Lee; Jong Wook Kim; Yong Jae Kim; Sang Yong Jung

doi:10.1109/CEFC.2016.7816308

Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine

Myung Ki Seo
, Tae Yong Lee
, Jong Wook Kim
, Yong Jae Kim
, Sang Yong Jung

Department of Electronic and Electrical Engineering

Sungkyunkwan University
Dong-A University
Chosun University

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

Abstract

Optimal design of Permanent Magnet Synchronous Machine (PMSM) based on Finite Element Analysis (FEA) calls for huge computational time for high accuracy. Therefore, it is essential to select appropriate optimization algorithm. This paper presents the principal component optimization based on principal component analysis with mesh adaptive direct search to improve computation time and reliability of convergence to global optimum. It is verified through a benchmark function and applied to optimal design of PMSM for minimization of torque ripple based on FEA.

Original language	English
Title of host publication	IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509010325
DOIs	https://doi.org/10.1109/CEFC.2016.7816308
State	Published - 12 Jan 2017
Event	17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016 - Miami, United States Duration: 13 Nov 2016 → 16 Nov 2016

Publication series

Name	IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation

Conference

Conference	17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016
Country/Territory	United States
City	Miami
Period	13/11/16 → 16/11/16

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

AC machines
Finite element analysis
Optimization methods
Permanent magnet machine

Access to Document

10.1109/CEFC.2016.7816308

Cite this

Seo, M. K., Lee, T. Y., Kim, J. W., Kim, Y. J., & Jung, S. Y. (2017). Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine. In IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation Article 7816308 (IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEFC.2016.7816308

Seo, Myung Ki ; Lee, Tae Yong ; Kim, Jong Wook et al. / Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine. IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation. Institute of Electrical and Electronics Engineers Inc., 2017. (IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation).

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title = "Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine",

abstract = "Optimal design of Permanent Magnet Synchronous Machine (PMSM) based on Finite Element Analysis (FEA) calls for huge computational time for high accuracy. Therefore, it is essential to select appropriate optimization algorithm. This paper presents the principal component optimization based on principal component analysis with mesh adaptive direct search to improve computation time and reliability of convergence to global optimum. It is verified through a benchmark function and applied to optimal design of PMSM for minimization of torque ripple based on FEA.",

keywords = "AC machines, Finite element analysis, Optimization methods, Permanent magnet machine",

author = "Seo, \{Myung Ki\} and Lee, \{Tae Yong\} and Kim, \{Jong Wook\} and Kim, \{Yong Jae\} and Jung, \{Sang Yong\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016 ; Conference date: 13-11-2016 Through 16-11-2016",

year = "2017",

month = jan,

day = "12",

doi = "10.1109/CEFC.2016.7816308",

language = "English",

series = "IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation",

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

booktitle = "IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation",

}

Seo, MK, Lee, TY, Kim, JW, Kim, YJ & Jung, SY 2017, Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine. in IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation., 7816308, IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation, Institute of Electrical and Electronics Engineers Inc., 17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016, Miami, United States, 13/11/16. https://doi.org/10.1109/CEFC.2016.7816308

Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine. / Seo, Myung Ki; Lee, Tae Yong; Kim, Jong Wook et al.
IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation. Institute of Electrical and Electronics Engineers Inc., 2017. 7816308 (IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation).

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

TY - GEN

T1 - Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine

AU - Seo, Myung Ki

AU - Lee, Tae Yong

AU - Kim, Jong Wook

AU - Kim, Yong Jae

AU - Jung, Sang Yong

PY - 2017/1/12

Y1 - 2017/1/12

N2 - Optimal design of Permanent Magnet Synchronous Machine (PMSM) based on Finite Element Analysis (FEA) calls for huge computational time for high accuracy. Therefore, it is essential to select appropriate optimization algorithm. This paper presents the principal component optimization based on principal component analysis with mesh adaptive direct search to improve computation time and reliability of convergence to global optimum. It is verified through a benchmark function and applied to optimal design of PMSM for minimization of torque ripple based on FEA.

AB - Optimal design of Permanent Magnet Synchronous Machine (PMSM) based on Finite Element Analysis (FEA) calls for huge computational time for high accuracy. Therefore, it is essential to select appropriate optimization algorithm. This paper presents the principal component optimization based on principal component analysis with mesh adaptive direct search to improve computation time and reliability of convergence to global optimum. It is verified through a benchmark function and applied to optimal design of PMSM for minimization of torque ripple based on FEA.

KW - AC machines

KW - Finite element analysis

KW - Optimization methods

KW - Permanent magnet machine

UR - https://www.scopus.com/pages/publications/85011982294

U2 - 10.1109/CEFC.2016.7816308

DO - 10.1109/CEFC.2016.7816308

M3 - Conference contribution

AN - SCOPUS:85011982294

T3 - IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation

BT - IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016

Y2 - 13 November 2016 through 16 November 2016

ER -

Seo MK, Lee TY, Kim JW, Kim YJ, Jung SY. Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine. In IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation. Institute of Electrical and Electronics Engineers Inc. 2017. 7816308. (IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation). doi: 10.1109/CEFC.2016.7816308

Principal component optimization with mesh adaptive direct search for optimal design of permanent magnet synchronous machine

Abstract

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UN SDGs

Keywords

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