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Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM
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  • Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM
  • Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM
저자명
Kim. Min-Jae,Lim. Jae-Won,Seo. Jang-Ho,Jung. Hyun-Kyo
간행물명
Journal of electrical engineering & technology
권/호정보
2011년|6권 2호|pp.202-207 (6 pages)
발행정보
대한전기학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Numerous methodologies have been developed in an effort to reduce cogging torque. However, most of these methodologies have side effects that limit their applications. One approach is the optimization methodology that determines an optimized design variable within confined conditions. The response surface methodology (RSM) and the genetic algorithm (GA) are powerful instruments for such optimizations and are matters of common interest. However, they have some weaknesses. Generally, the RSM cannot accurately describe an object function, whereas the GA is time consuming. The current paper describes a novel GA and RSM hybrid algorithm that overcomes these limitations. The validity of the proposed algorithm was verified by three test functions. Its application was performed on a surface-mounted permanent magnet.