Modeling and Optimal Design of a Short Primary Double-Sided Linear Induction Motor Considering Both Transverse and Longitudinal End Effects Using Improved Differential Evolution

被引:0
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作者
Hanming Wang
Jinghong Zhao
Guoqiang Guo
Hansi Chen
Yiyong Xiong
Sinian Yan
机构
[1] Naval university of engineering,Department of electrical engineering
关键词
Artificial intelligence; Double-sided linear induction motor; Design optimization; Electrical engineering; Meta-heuristics algorithm;
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学科分类号
摘要
Due to its simple structure, the linear induction motor provides a linear driving force without any intermediate conversion devices. Linear induction motors are gradually used in various applications, including rail transit and the national defense industry. However, linear induction motors are affected by the end-effect phenomenon and suffer from problems such as low efficiencies and low power factors. In this paper, to optimize the performance of short primary double-sided linear induction motors (SP-DLIMs), first, a new analytical model is established based on an equivalent circuit considering both transverse and longitudinal end effects. Second, to analyze the impact of main parameters on the output characteristics of SP-DLIMs, a simple iterative design method (IDM) is presented. Third, a multi-objective optimal design method is proposed to optimize the efficiency, power factor and tooth weight of SP-DLIMs, with proposed design constraints and four different optimization problems. Moreover, an improved differential evolutionary (IDE) algorithm is proposed to optimize the design. A comparison of the results proved that the IDE yielded a competitive performance to those of other advanced heuristic algorithms. Finally, a three-dimensional time-stepping finite-element method was utilized to verify the validity of the optimization results.
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页码:1065 / 1081
页数:16
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