Title :
Optimal design of electric machine using genetic algorithms coupled with direct method
Author :
Oh, Yong-Hwan ; Tae-Kyung Chung ; Kim, Min-Kyu ; Jung, Hyun-Kyo
Author_Institution :
Dept. of Electr. Eng., Chung Ang Univ., Seoul, South Korea
fDate :
5/1/1999 12:00:00 AM
Abstract :
This paper discusses the development of a new optimization algorithm for DC motor design. In principle, the new algorithm utilizes a mixed method that consists of genetic algorithms in conjunction with direct search method. The genetic algorithms are used for locating the global optimum region while the direct search method is used to achieve objective function convergence. In order to validate the effectiveness, the new algorithm has been applied to an actual DC motor. Field and torque characteristics of the DC motor are computed using the finite element method and the principle of virtual work, respectively
Keywords :
DC motors; electromagnetic fields; finite element analysis; genetic algorithms; machine theory; search problems; torque; DC motor design; EM field characteristics; direct search method; finite element method; genetic algorithms; objective function convergence; optimization algorithm; torque characteristics; virtual work principle; Algorithm design and analysis; Convergence; Couplings; DC motors; Design optimization; Electric machines; Finite element methods; Genetic algorithms; Search methods; Torque;
Journal_Title :
Magnetics, IEEE Transactions on