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논문 기본 정보

자료유형
학술저널
저자정보
Il-Woo Kim (Hyosung corporation) Dong-Kyun Woo (Seoul National University) Dong-Kuk Lim (Seoul National University) Sang-Yong Jung (Sungkyunkwan University) Cheol-Gyun Lee (Dong Eui University) Jong-Suk Ro (Seoul National University) Hyun-Kyo Jung (Seoul National University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.9 No.3
발행연도
2014.5
수록면
859 - 865 (7page)

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초록· 키워드

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Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

목차

Abstract
1. Introduction
2. The Proposed Algorithm, KSM
3. Verification of the KSM
4. Conclusion
References

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