[1] Zhuang Yingchao, Yu Haitao, Xia Jun, Hu Minqiang, et al. Optimization of linear induction machinesbased on a novel adaptive genetic algorithm [J]. Journal of Southeast University (English Edition), 2009, 25 (2): 203-207. [doi:10.3969/j.issn.1003-7985.2009.02.013]

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Optimization of linear induction machinesbased on a novel adaptive genetic algorithm()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

25

Issue:

2009 2

Page:

203-207

Research Field:

Electrical Engineering

Publishing date:

2009-06-30

Info

Title:

Optimization of linear induction machinesbased on a novel adaptive genetic algorithm

Author(s):

Zhuang Yingchao¹;  Yu Haitao¹;  Xia Jun²;  Hu Minqiang¹

¹School of Electrical Engineering, Southeast University, Nanjing 210096, China
² Jiangsu Science and Technology Museum, Nanjing 210013, China

Keywords:

adaptive genetic algorithm;  linear induction machine;  uniform design

PACS:

TM359.4

DOI:

10.3969/j.issn.1003-7985.2009.02.013

Abstract:

In order to improve the thrust-power ratio index of the linear induction motor(LIM), a novel adaptive genetic algorithm(NAGA)is proposed for the design optimization of the LIM.A good-point set theory that helps to produce a uniform initial population is used to enhance the optimization efficiency of the genetic algorithm.The crossover and mutation probabilities are improved by using the function of sigmoid and they can be adjusted nonlinearly between average fitness and maximal fitness with individual fitness.Based on the analyses of different structures between the LIM and the rotary induction motor(RIM)and referring to the analysis method of the RIM, the steady-state characteristics of the LIM that considers the end effects of the LIM is calculated and the optimal design model of the thrust-power ratio index is also presented.Through the comparison between the optimal scheme and the old scheme, the thrust-power ratio index of the LIM is obviously increased and the validity of the NAGA is proved.

References:

[1] Wang Liqiang, Ji Qi. Optimum design of linear induction motor based on genetic algorithms [J].Small and Special Electrical Machines, 2008, 36(3):14-16.(in Chinese)
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[4] Ye Yunyue.The theory and application of linear machines[M].Beijing:China Machine Press, 2000:51-89.(in Chinese)
[5] Guo Huihao, Fan Yu, Shao Li. Application of adaptive genetic algorithm for parameter optimization of linear induction motor [J].Explosion-Proof Electric Machine, 2005, 40(3):16-18.(in Chinese)
[6] Wang Ruiming, Shi Haijun, Yang Qiong.Optimum design of power transformer based on an improved adaptive genetic algorithm [J].Jiangsu Electrical Engineering, 2005, 24(4):46-48.(in Chinese)
[7] Jin Jing, Su Yong.An improved adaptive genetic algorithm [J].Computer Engineering and Applications, 2005, 41(18):64-69.(in Chinese)
[8] Li Zhijun, Cheng Jiaxing.Uniform design of initial population of genetic algorithm based on good point set [J].Computer and Information Technology, 2007, 15(4):29-32.(in Chinese)
[9] Hassanpour Isfahani A, Ebrahimi B M, Lesani H.Design optimization of a low-speed single-sided linear induction motor for improved efficiency and power factor [J].IEEE Transactions on Magnetics, 2008, 44(2):46-51.

Memo

Memo:

Biographies: Zhuang Yingchao(1983—), male, gradate;Yu Haitao(corresponding author), male, doctor, professor, htyu@seu.edu.cn.
Citation: Zhuang Yingchao, Yu Haitao, Xia Jun, et al.Optimization of linear induction machines based on a novel adaptive genetic algorithm[J].Journal of Southeast University(English Edition), 2009, 25(2):203-207.

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