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A New Surrogate-assisted Robust Multi-objective Optimization Algorithm for an Electrical Machine Design

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Abstract

For a multi-objective optimization problem applied to the electric machine design, a new surrogate-assisted robust algorithm is proposed in this research. The proposed algorithm can find a robust and well-distributed Pareto front set rapidly and precisely for robust nondominated solutions using a surrogate model and an uncertainty consideration with a worst-case scenario. The outstanding performances of the proposed algorithm are verified by test functions. Furthermore, through the application of the optimal design process of a surface-mounted permanent magnet synchronous motor for an electric bicycle, the feasibility of this algorithm is verified.

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Acknowledgements

This work was supported by the 2017 Research Fund of University of Ulsan.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Ulsan, Ulsan, South Korea

    Dong-Kuk Lim

  2. Department of Electrical Engineering, Yeungnam University, Gyeongbuk, South Korea

    Dong-Kyun Woo

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  1. Dong-Kuk Lim
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  2. Dong-Kyun Woo
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Correspondence to Dong-Kyun Woo.

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Lim, DK., Woo, DK. A New Surrogate-assisted Robust Multi-objective Optimization Algorithm for an Electrical Machine Design. J. Electr. Eng. Technol. 14, 1247–1254 (2019). https://doi.org/10.1007/s42835-019-00120-1

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  • DOI: https://doi.org/10.1007/s42835-019-00120-1

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