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Optimal Design Methodology on Compensation Parameters of Inductive Power Transfer Converter for Electric Vehicles

Author

Listed:
  • Cheol-Hee Jo

    (Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

  • Dong-Hee Kim

    (Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

Abstract

Compensation topologies of the inductive power transfer (IPT) converter for electric vehicles (EVs) have been researched in previous works. However, a methodology for designing a compensation topology based on the efficiency of the IPT converter has been barely discussed. This paper proposes an optimal design methodology for compensation parameters to achieve optimal efficiency of the IPT converter with LCC-S. The optimal output voltage is derived using the losses analysis of the IPT converter, and the IPT converter is designed for the optimal output voltage to achieve the optimal efficiency. Furthermore, the battery management (BM) converter on the receiving side is designed based on the output voltage of the IPT converter, the fluctuation range of the coupling coefficient, and the battery charging voltage. The validity of the proposed IPT converter design methodology is verified by designing different compensation parameters and BM converters. The power rating of the three design cases is 3.3 kW with the same magnetic pads satisfying the SAE J2954 WPT 1 class.

Suggested Citation

  • Cheol-Hee Jo & Dong-Hee Kim, 2021. "Optimal Design Methodology on Compensation Parameters of Inductive Power Transfer Converter for Electric Vehicles," Energies, MDPI, vol. 14(24), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8269-:d:697852
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    References listed on IDEAS

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    1. Yafei Chen & Hailong Zhang & Sung-Jun Park & Dong-Hee Kim, 2019. "A Comparative Study of S-S and LCCL-S Compensation Topologies in Inductive Power Transfer Systems for Electric Vehicles," Energies, MDPI, vol. 12(10), pages 1-19, May.
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