Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM

  • Kim, Min-Jae ;
  • Lim, Jae-Won ;
  • Seo, Jang-Ho ;
  • Jung, Hyun-Kyo
  • Received : 2010.03.14
  • Accepted : 2010.12.01
  • Published : 2011.03.01


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.


Response surface methodology;Genetic algorithm;Hybrid optimization


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