Multiobjective design optimization of brushless permanent magnet motor using 3D equivalent magnetic circuit network method

Y. D. Chun, Shinji Wakao, T. H. Kim, K. B. Jang, J. Lee

    Research output: Contribution to journalArticle

    24 Citations (Scopus)

    Abstract

    In this paper, we discuss multiobjective design optimization of brushless permanent magnet motor (BLPMM) solved by genetic algorithm (GA) and 3D equivalent magnetic circuit network (EMCN) method. In the multiobjective optimization (MO) problem, we choose the decrease of cogging torque and the increase of torque as objectives. The airgap length, teeth width and magnetization angle of permanent magnet (PM) are also selected for the design variables respectively. From the results, our approach method enabled us to efficiently obtain diverse Pareto optimal (PO) solutions from the practical point of view. The experimental results are shown to confirm the validity of the optimization results.

    Original languageEnglish
    Pages (from-to)1910-1913
    Number of pages4
    JournalIEEE Transactions on Applied Superconductivity
    Volume14
    Issue number2
    DOIs
    Publication statusPublished - 2004 Jun

    Fingerprint

    magnetic circuits
    Magnetic circuits
    design optimization
    equivalent circuits
    permanent magnets
    Equivalent circuits
    Permanent magnets
    torque
    Torque
    optimization
    teeth
    Multiobjective optimization
    genetic algorithms
    Magnetization
    Genetic algorithms
    magnetization
    Design optimization

    Keywords

    • 3D equivalent magnetic circuit network method
    • Brushless permanent magnet motor
    • Genetic algorithm
    • Multiobjective design optimization

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Physics and Astronomy (miscellaneous)

    Cite this

    Multiobjective design optimization of brushless permanent magnet motor using 3D equivalent magnetic circuit network method. / Chun, Y. D.; Wakao, Shinji; Kim, T. H.; Jang, K. B.; Lee, J.

    In: IEEE Transactions on Applied Superconductivity, Vol. 14, No. 2, 06.2004, p. 1910-1913.

    Research output: Contribution to journalArticle

    @article{09cdcae1482a42c489df7497973516a8,
    title = "Multiobjective design optimization of brushless permanent magnet motor using 3D equivalent magnetic circuit network method",
    abstract = "In this paper, we discuss multiobjective design optimization of brushless permanent magnet motor (BLPMM) solved by genetic algorithm (GA) and 3D equivalent magnetic circuit network (EMCN) method. In the multiobjective optimization (MO) problem, we choose the decrease of cogging torque and the increase of torque as objectives. The airgap length, teeth width and magnetization angle of permanent magnet (PM) are also selected for the design variables respectively. From the results, our approach method enabled us to efficiently obtain diverse Pareto optimal (PO) solutions from the practical point of view. The experimental results are shown to confirm the validity of the optimization results.",
    keywords = "3D equivalent magnetic circuit network method, Brushless permanent magnet motor, Genetic algorithm, Multiobjective design optimization",
    author = "Chun, {Y. D.} and Shinji Wakao and Kim, {T. H.} and Jang, {K. B.} and J. Lee",
    year = "2004",
    month = "6",
    doi = "10.1109/TASC.2004.830928",
    language = "English",
    volume = "14",
    pages = "1910--1913",
    journal = "IEEE Transactions on Applied Superconductivity",
    issn = "1051-8223",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",
    number = "2",

    }

    TY - JOUR

    T1 - Multiobjective design optimization of brushless permanent magnet motor using 3D equivalent magnetic circuit network method

    AU - Chun, Y. D.

    AU - Wakao, Shinji

    AU - Kim, T. H.

    AU - Jang, K. B.

    AU - Lee, J.

    PY - 2004/6

    Y1 - 2004/6

    N2 - In this paper, we discuss multiobjective design optimization of brushless permanent magnet motor (BLPMM) solved by genetic algorithm (GA) and 3D equivalent magnetic circuit network (EMCN) method. In the multiobjective optimization (MO) problem, we choose the decrease of cogging torque and the increase of torque as objectives. The airgap length, teeth width and magnetization angle of permanent magnet (PM) are also selected for the design variables respectively. From the results, our approach method enabled us to efficiently obtain diverse Pareto optimal (PO) solutions from the practical point of view. The experimental results are shown to confirm the validity of the optimization results.

    AB - In this paper, we discuss multiobjective design optimization of brushless permanent magnet motor (BLPMM) solved by genetic algorithm (GA) and 3D equivalent magnetic circuit network (EMCN) method. In the multiobjective optimization (MO) problem, we choose the decrease of cogging torque and the increase of torque as objectives. The airgap length, teeth width and magnetization angle of permanent magnet (PM) are also selected for the design variables respectively. From the results, our approach method enabled us to efficiently obtain diverse Pareto optimal (PO) solutions from the practical point of view. The experimental results are shown to confirm the validity of the optimization results.

    KW - 3D equivalent magnetic circuit network method

    KW - Brushless permanent magnet motor

    KW - Genetic algorithm

    KW - Multiobjective design optimization

    UR - http://www.scopus.com/inward/record.url?scp=4344680357&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=4344680357&partnerID=8YFLogxK

    U2 - 10.1109/TASC.2004.830928

    DO - 10.1109/TASC.2004.830928

    M3 - Article

    VL - 14

    SP - 1910

    EP - 1913

    JO - IEEE Transactions on Applied Superconductivity

    JF - IEEE Transactions on Applied Superconductivity

    SN - 1051-8223

    IS - 2

    ER -