Application of vector optimization employing modified genetic algorithm to permanent magnet motor design

Author

Sim, Dong-Joon ; Jung, Hyun-Kyo ; Hahn, Song-Yop ; Won, Jon-Soo

Author_Institution

Steel Process Div., RIST, Pohang, South Korea

Volume

33

Issue

2

fYear

1997

fDate

3/1/1997 12:00:00 AM

Firstpage

1888

Lastpage

1891

Abstract

This paper presents a method to solve the vector optimization problem that determines both the noninferior solution set and the best compromise solution employing a modified genetic algorithm. The algorithm differs from the conventional one in the definition of fitness value and convergence criterion. Some parameters of the algorithm are adjusted to the vector optimization. The algorithm also contains the additional routine for searching the best compromise solution. This method is applied to the optimal design of the permanent magnet synchronous motor for which two objective functions regarding motor efficiency and weight are used

Keywords

design engineering; genetic algorithms; machine theory; permanent magnet motors; synchronous motors; best compromise solution; convergence criterion; efficiency; fitness value; modified genetic algorithm; noninferior solution set; objective functions; optimal design; permanent magnet synchronous motor design; vector optimization; weight; Algorithm design and analysis; Design optimization; Electric machines; Genetic algorithms; Induction motors; Magnetic flux; Optimization methods; Permanent magnet motors; Steel; Synchronous motors;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/20.582654

Filename

582654