A comparative performance evaluation of evolutionary algorithms for optimal design of three-phase induction motor

被引：0

作者：

Ranjan, Soumya ^{[1
]}

Mishra, Sudhansu Kumar ^{[1
]}

Behera, Subhendu Ku. ^{[2
]}

机构：

[1] Birla Inst Technol, Dept Elect & Elect Engn, Ranchi, Bihar, India

[2] DRIEMS, Dept Elect &Commun Engn, Cuttack, Orissa, India

来源：

2013 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS AND NETWORKING TECHNOLOGIES (ICCCNT) | 2013年

关键词：

MOEA; SOEA; Multiobjective optimization; induction motors; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The attribute of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In this paper a multi-objective problem is considered in which three phase squirrel cage induction motor (SCIM) has been designed in such a way that the efficiency is maximized while power density to be minimized simultaneously keeping various constraints in mind. Three well-known single objective methods such as tabu search (TS), simulated annealing (SA) and Genetic algorithm (GA) for comparing Pareto solutions has also been applied. Performance comparison carried out in this paper by performing different numerical experiments. The result shows that NSGA-II outperforms other three for the considered test cases.

引用

页数：5

共 19 条

[1] OPTIMIZATION OF 3-PHASE INDUCTION-MOTOR DESIGN .1. FORMULATION OF THE OPTIMIZATION TECHNIQUE [J].

APPELBAUM, J ;

FUCHS, EF ;

WHITE, JC .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 1987, 2 (03) :407-414

[2]

Appelbaum J., 1984, Proceedings of the International Conference on Electrical Machines, P639

[3] Handling multiple objectives with particle swarm optimization [J].

Coello, CAC ;

Pulido, GT ;

Lechuga, MS .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2004, 8 (03) :256-279

[4] A computationally efficient evolutionary algorithm for real-parameter optimization [J].

Deb, K ;

Anand, A ;

Joshi, D .

EVOLUTIONARY COMPUTATION, 2002, 10 (04) :371-395

[5] A fast and elitist multiobjective genetic algorithm: NSGA-II [J].

Deb, K ;

Pratap, A ;

Agarwal, S ;

Meyarivan, T .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197

[6] INDUCTION-MOTOR OPTIMUM DESIGN, INCLUDING ACTIVE POWER LOSS EFFECT [J].

FETIH, NH ;

ELSHEWY, HM .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 1986, 1 (03) :155-160

[7]

Fuchs E.F., 1985, EPRIEL4152CCM

[8] A general approach to sizing and power density equations for comparison of electrical machines [J].

Huang, SR ;

Luo, J ;

Leonardi, F ;

Lipo, TA .

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 1998, 34 (01) :92-97

[9] Multiobjective optimal design of three-phase induction motor using improved evolution strategy [J].

Kim, MK ;

Lee, CG ;

Jung, HK .

IEEE TRANSACTIONS ON MAGNETICS, 1998, 34 (05) :2980-2983

[10]

Madescu G., 1996, IEEE IAS ANN M SAN D, V1, P556

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