DocumentCode :
40583
Title :
Robust Optimization Considering Probabilistic Magnetic Degradation
Author :
Hidaka, Yuki ; Furui, Shintaro ; Igarashi, Hajime
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
Volume :
51
Issue :
3
fYear :
2015
fDate :
Mar-15
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents robust topology optimization of electromagnetic machines by considering the magnetic degradation caused by mechanical and thermal stresses in punching, shrinking fitting, and other manufacturing processes. The topology optimization is performed using two methods: one is the robust genetic algorithm in which random noises are added to the magnetic characteristic parameters and the other takes the deviations in the objective and constraint functions due to the degradation into account. These methods are applied to optimization of the flux barrier shapes in an interior permanent magnetic motor to find that one can successfully realize robust design.
Keywords :
genetic algorithms; permanent magnet motors; thermal stresses; wear; constraint functions; electromagnetic machines; flux barrier shapes optimization; interior permanent magnetic motor; magnetic characteristic parameters; manufacturing processes; mechanical stresses; objective functions; probabilistic magnetic degradation; punching; random noises; robust genetic algorithm; robust topology optimization; shrinking fitting; thermal stresses; Degradation; Genetic algorithms; Magnetomechanical effects; Magnetostatic waves; Magnetostatics; Optimization; Robustness; Finite element method (FEM); magnetic degradation; robust optimization; topology optimization;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2014.2353653
Filename :
7093444
Link To Document :
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