Fan-shape optimisation using CFD and genetic algorithms for increasing the efficiency of electric motors

被引：0
|
作者：
Leon-Rovira, Noel [1 ]
Uresti, Eduardo [2 ]
Arcos, Waldo [1 ]
机构：
[1] Ctr Innovat Design & Technol, Tecnol Monterrey, Campus Monterrey,Ave Eugenio Garza Sada 2501, Monterrey 64841, Mexico
[2] Ctr Artifitial Intelligence, Tecnol Monterrey, Monterrey 64841, Mexico
来源：
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY | 2007年 / 30卷 / 1-2期
关键词：
shape optimisation; genetic algorithms; shape parameterisation; CFD;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The electric motor efficiency represents the effectiveness with which the motor converts electrical energy into mechanical energy. As the energy losses are converted into heat, which is dissipated by the motor frame aided by internal and external fans, a better cooling system adds up to better efficiency. In recent years, improvements in motor efficiency have been achieved but at higher costs. By using Genetic Algorithms (GAs), changes are introduced to the fan shape looking for a better aerodynamic performance. The evaluation of the achieved fan efficiency with the modified shapes is performed with Computational Fluid Dynamics (CFD) simulation software.
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页码：47 / 58
页数：12
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