Genetic-Algorithm-based analytical method of SMPM motors

Libing Jing; Ronghai Qu; Wubin Kong; Dawei Li; Hailin Huang

doi:10.1109/IEMDC.2017.8002030

Genetic-Algorithm-based analytical method of SMPM motors

Libing Jing, Ronghai Qu, Wubin Kong, Dawei Li, Hailin Huang

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

8 Citations (Scopus)

Abstract

In this paper, an exact analytical method is developed to computer the air-gap magnetic field of surface-mounted permanent-magnet (SMPM) motors for valuating slotting effects accurately. In order to improve the flux density and reduce cogging torque, the genetic algorithm toolbox of Matlab is used to optimize the motor, in which the actual depth of slot, slot opening, the length of gap and pole-Arc to pole-pitch ratio are taken into account in the computation. Magnetic field distributions, induced back electromotive force (EMF) and optimized cogging torque computed from the proposed analytical method are compared with those issued from two-dimensional finite-element method (FEM), the comparison results are consistent and shows the correctness and effectiveness of the proposed analytical method.

Original language	English
Title of host publication	2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509042814
DOIs	https://doi.org/10.1109/IEMDC.2017.8002030
Publication status	Published - 3 Aug 2017
Externally published	Yes
Event	2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017 - Miami, United States Duration: 21 May 2017 → 24 May 2017

Publication series

Name	2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017

Conference

Conference	2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017
Country/Territory	United States
City	Miami
Period	21/05/17 → 24/05/17

Keywords

air-gap magnetic field
cogging torque
EMF
exact analytical method
FEM

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering

Access to Document

10.1109/IEMDC.2017.8002030

Cite this

Jing, L., Qu, R., Kong, W., Li, D., & Huang, H. (2017). Genetic-Algorithm-based analytical method of SMPM motors. In 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017 Article 8002030 (2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMDC.2017.8002030

@inproceedings{8bcd1640bce04c6d9f0abe53a411573a,

title = "Genetic-Algorithm-based analytical method of SMPM motors",

abstract = "In this paper, an exact analytical method is developed to computer the air-gap magnetic field of surface-mounted permanent-magnet (SMPM) motors for valuating slotting effects accurately. In order to improve the flux density and reduce cogging torque, the genetic algorithm toolbox of Matlab is used to optimize the motor, in which the actual depth of slot, slot opening, the length of gap and pole-Arc to pole-pitch ratio are taken into account in the computation. Magnetic field distributions, induced back electromotive force (EMF) and optimized cogging torque computed from the proposed analytical method are compared with those issued from two-dimensional finite-element method (FEM), the comparison results are consistent and shows the correctness and effectiveness of the proposed analytical method.",

keywords = "air-gap magnetic field, cogging torque, EMF, exact analytical method, FEM",

author = "Libing Jing and Ronghai Qu and Wubin Kong and Dawei Li and Hailin Huang",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017 ; Conference date: 21-05-2017 Through 24-05-2017",

year = "2017",

month = aug,

day = "3",

doi = "10.1109/IEMDC.2017.8002030",

language = "English",

series = "2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017",

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

booktitle = "2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017",

address = "United States",

}

Jing, L, Qu, R, Kong, W, Li, D & Huang, H 2017, Genetic-Algorithm-based analytical method of SMPM motors. in 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017., 8002030, 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017, Miami, United States, 21/05/17. https://doi.org/10.1109/IEMDC.2017.8002030

Genetic-Algorithm-based analytical method of SMPM motors. / Jing, Libing; Qu, Ronghai; Kong, Wubin et al.
2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8002030 (2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017).

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

TY - GEN

T1 - Genetic-Algorithm-based analytical method of SMPM motors

AU - Jing, Libing

AU - Qu, Ronghai

AU - Kong, Wubin

AU - Li, Dawei

AU - Huang, Hailin

PY - 2017/8/3

Y1 - 2017/8/3

N2 - In this paper, an exact analytical method is developed to computer the air-gap magnetic field of surface-mounted permanent-magnet (SMPM) motors for valuating slotting effects accurately. In order to improve the flux density and reduce cogging torque, the genetic algorithm toolbox of Matlab is used to optimize the motor, in which the actual depth of slot, slot opening, the length of gap and pole-Arc to pole-pitch ratio are taken into account in the computation. Magnetic field distributions, induced back electromotive force (EMF) and optimized cogging torque computed from the proposed analytical method are compared with those issued from two-dimensional finite-element method (FEM), the comparison results are consistent and shows the correctness and effectiveness of the proposed analytical method.

AB - In this paper, an exact analytical method is developed to computer the air-gap magnetic field of surface-mounted permanent-magnet (SMPM) motors for valuating slotting effects accurately. In order to improve the flux density and reduce cogging torque, the genetic algorithm toolbox of Matlab is used to optimize the motor, in which the actual depth of slot, slot opening, the length of gap and pole-Arc to pole-pitch ratio are taken into account in the computation. Magnetic field distributions, induced back electromotive force (EMF) and optimized cogging torque computed from the proposed analytical method are compared with those issued from two-dimensional finite-element method (FEM), the comparison results are consistent and shows the correctness and effectiveness of the proposed analytical method.

KW - air-gap magnetic field

KW - cogging torque

KW - EMF

KW - exact analytical method

KW - FEM

UR - https://www.scopus.com/pages/publications/85030308014

U2 - 10.1109/IEMDC.2017.8002030

DO - 10.1109/IEMDC.2017.8002030

M3 - Conference contribution

AN - SCOPUS:85030308014

T3 - 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017

BT - 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017

Y2 - 21 May 2017 through 24 May 2017

ER -

Genetic-Algorithm-based analytical method of SMPM motors

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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