Comparison of stochastic optimization methods for design optimization of permanent magnet synchronous motor
Küçük Resim Yok
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER LONDON LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents design optimization of permanent magnet synchronous motor by using different artificial intelligence methods. For this purpose, three stochastic optimization methods-genetic algorithm, simulated annealing, and differential evolution-were used. Motor design parameters and efficiency results obtained by the artificial intelligence methods were compared with each other. The results were later checked by finite element analysis. Consequently, the motor efficiencies obtained from the algorithms have high accuracy. Approaches strategies of the artificial intelligence algorithms are quite sufficient and remarkable for design optimization of permanent magnet synchronous motor. The differential evolution is better and more reliable optimization method nevertheless.
Açıklama
Anahtar Kelimeler
Permanent magnet synchronous motor, Design optimization, Genetic algorithm, Simulated annealing, Differential evolution
Kaynak
NEURAL COMPUTING & APPLICATIONS
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
21
Sayı
8
