Efficiency determination of induction motors using multi-objective evolutionary algorithms

被引：24

作者：

Cunkas, Mehmet ^{[1
]}

Sag, Tahir ^{[1
]}

机构：

[1] Selcuk Univ, Dept Elect & Comp Educ, Fac Tech Educ, TR-42003 Konya, Turkey

来源：

ADVANCES IN ENGINEERING SOFTWARE | 2010年 / 41卷 / 02期

关键词：

Multi-objective evolutionary algorithms; Induction motor; In-situ efficiency determination; IN-SERVICE; GENETIC ALGORITHM;

D O I：

10.1016/j.advengsoft.2009.07.008

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper introduces a method based on multi-objective evolutionary algorithms for the determination of in-service induction motor efficiency. In general, the efficiency is determined by accumulating multiple objectives into one objective by a linear combination and optimizing the resulting single-objective problem. The approach has some drawbacks such that exact information about solution alternatives will not be readily visible. In this paper the multi-objective evolutionary optimization algorithms, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Strength Pareto Evolutionary Algorithm-2 (SPEA2), are successfully applied to the efficiency determination problem in induction motor. The performances of algorithms are compared on the basis of the obtained results. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：255 / 261

页数：7

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