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A New Design Optimization Method for Permanent Magnet Synchronous Linear Motors

Author

Listed:
  • Juncai Song

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Fei Dong

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Jiwen Zhao

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Siliang Lu

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Le Li

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Zhenbao Pan

    (College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

Abstract

This study focused on the design optimization of permanent magnet synchronous linear motors (PMSLM) that are applied in microsecond laser cutting machines. A new design optimization method was introduced to enhance PMSLM performances in terms of motor thrust, thrust ripple, and inductive electromotive force (EMF). Based on accurate 3D finite element analysis (3D-FEA), a multiple support vector machine (multi-SVM) was proposed to build a non-parametric quick calculation model by mapping the relation between multivariate structure parameters and multivariate operation performances. The gravity center neighborhood algorithm (GCNA) was also applied to search the global optimal combination of the structure parameters by locating the gravity center of the multi-SVM model. The superiority and validity of this method are verified by experiments.

Suggested Citation

  • Juncai Song & Fei Dong & Jiwen Zhao & Siliang Lu & Le Li & Zhenbao Pan, 2016. "A New Design Optimization Method for Permanent Magnet Synchronous Linear Motors," Energies, MDPI, vol. 9(12), pages 1-15, November.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:12:p:992-:d:83792
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    References listed on IDEAS

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    1. Chun-Yu Hsiao & Sheng-Nian Yeh & Jonq-Chin Hwang, 2014. "Design of High Performance Permanent-Magnet Synchronous Wind Generators," Energies, MDPI, vol. 7(11), pages 1-20, November.
    2. Meng-Hui Wang & Mei-Ling Huang & Zi-Yi Zhan & Chong-Jie Huang, 2016. "Application of the Extension Taguchi Method to Optimal Capability Planning of a Stand-alone Power System," Energies, MDPI, vol. 9(3), pages 1-17, March.
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    Cited by:

    1. López, I. & Ibarra, E. & Matallana, A. & Andreu, J. & Kortabarria, I., 2019. "Next generation electric drives for HEV/EV propulsion systems: Technology, trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    2. Gang Lei & Jianguo Zhu & Youguang Guo & Chengcheng Liu & Bo Ma, 2017. "A Review of Design Optimization Methods for Electrical Machines," Energies, MDPI, vol. 10(12), pages 1-31, November.
    3. Dingfeng Dong & Wenxin Huang & Feifei Bu & Qi Wang & Wen Jiang & Xiaogang Lin, 2017. "Modeling and Static Analysis of Primary Consequent-Pole Tubular Transverse-Flux Flux-Reversal Linear Machine," Energies, MDPI, vol. 10(10), pages 1-16, September.
    4. Xinmei Wang & Yifei Wang & Tao Wu, 2022. "The Review of Electromagnetic Field Modeling Methods for Permanent-Magnet Linear Motors," Energies, MDPI, vol. 15(10), pages 1-18, May.
    5. Lijuan Yu & Shuyuan Chang & Jialong He & Huilu Sun & Jie Huang & Hailong Tian, 2022. "Electromagnetic Design and Analysis of Permanent Magnet Linear Synchronous Motor," Energies, MDPI, vol. 15(15), pages 1-17, July.

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