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Study on Line-Start Permanent Magnet Assistance Synchronous Reluctance Motor for Improving Efficiency and Power Factor

Author

Listed:
  • Hyunwoo Kim

    (Department of Electrical Engineering, Hanyang University, Seoul 04763, Korea)

  • Yeji Park

    (Department of Electrical Engineering, Hanyang University, Seoul 04763, Korea)

  • Huai-Cong Liu

    (Hyundai Transys, Hwaseong 18280, Korea)

  • Pil-Wan Han

    (Electric Machines and Drives Research Center, Korea Electrotechnology Research Institute, Changwon 51543, Korea)

  • Ju Lee

    (Department of Electrical Engineering, Hanyang University, Seoul 04763, Korea)

Abstract

In order to improve the efficiency, a line-start synchronous reluctance motor (LS-SynRM) is studied as an alternative to an induction motor (IM). However, because of the saliency characteristic of SynRM, LS-SynRM have a limited power factor. Therefore, to improve the efficiency and power factor of electric motors, we propose a line-start permanent magnet assistance synchronous reluctance motor (LS-PMA-SynRM) with permanent magnets inserted into LS-SynRM. IM and LS-SynRM are selected as reference models, whose performances are analyzed and compared with that of LS-PMA-SynRM using a finite element analysis. The performance of LS-PMA-SynRM is analyzed considering the position and length of its permanent magnet, as well as its manufacture. The final model of LS-PMA-SynRM is designed for improving the efficiency and power factor of electric motors compared with LS-SynRM. To verify the finite element analysis (FEA) result, the final model is manufactured, experiments are conducted, and the performance of LS-PMA-SynRM is verified.

Suggested Citation

  • Hyunwoo Kim & Yeji Park & Huai-Cong Liu & Pil-Wan Han & Ju Lee, 2020. "Study on Line-Start Permanent Magnet Assistance Synchronous Reluctance Motor for Improving Efficiency and Power Factor," Energies, MDPI, vol. 13(2), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:384-:d:308171
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    References listed on IDEAS

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    1. Jia, Mengda & Srinivasan, Ravi S. & Raheem, Adeeba A., 2017. "From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 525-540.
    2. Pavol Rafajdus & Valeria Hrabovcova & Pavel Lehocky & Pavol Makys & Filip Holub, 2018. "Effect of Saturation on Field Oriented Control of the New Designed Reluctance Synchronous Motor," Energies, MDPI, vol. 11(11), pages 1-10, November.
    3. Vojko Matko & Barbara Brezovec, 2018. "Improved Data Center Energy Efficiency and Availability with Multilayer Node Event Processing," Energies, MDPI, vol. 11(9), pages 1-17, September.
    4. Nezih Gokhan Ozcelik & Ugur Emre Dogru & Murat Imeryuz & Lale T. Ergene, 2019. "Synchronous Reluctance Motor vs. Induction Motor at Low-Power Industrial Applications: Design and Comparison," Energies, MDPI, vol. 12(11), pages 1-20, June.
    5. Ying Xie & Cheng Pi & Zhiwei Li, 2019. "Study on Design and Vibration Reduction Optimization of High Starting Torque Induction Motor," Energies, MDPI, vol. 12(7), pages 1-15, April.
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    Cited by:

    1. Vladimir Prakht & Mohamed N. Ibrahim & Vadim Kazakbaev, 2023. "Energy Efficiency Improvement of Electric Machines without Rare-Earth Magnets," Energies, MDPI, vol. 16(8), pages 1-3, April.
    2. Chang-Sung Jin & Chang-Min Kim & In-Jin Kim & Iksang Jang, 2021. "Proposed Commutation Method for Performance Improvement of Brushless DC Motor," Energies, MDPI, vol. 14(19), pages 1-16, September.
    3. Jonathan Muñoz Tabora & Maria Emília de Lima Tostes & Edson Ortiz de Matos & Thiago Mota Soares & Ubiratan Holanda Bezerra, 2020. "Voltage Harmonic Impacts on Electric Motors: A Comparison between IE2, IE3 and IE4 Induction Motor Classes," Energies, MDPI, vol. 13(13), pages 1-18, June.
    4. Hyunwoo Kim & Yeji Park & Seung-Taek Oh & Hyungkwan Jang & Sung-Hong Won & Yon-Do Chun & Ju Lee, 2020. "A Study on the Rotor Design of Line Start Synchronous Reluctance Motor for IE4 Efficiency and Improving Power Factor," Energies, MDPI, vol. 13(21), pages 1-15, November.

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