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Accurate Modeling of CCS Combo Type 1 Cable and Its Communication Performance Analysis for High-Speed EV-EVSE Charging System

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Listed:
  • Sanghwa Park

    (School of Electric and Electronic Enginnering, Yonsei University, Seoul 03722, Republic of Korea
    These authors contributed equally to this work.)

  • Euibum Lee

    (School of Electric and Electronic Enginnering, Yonsei University, Seoul 03722, Republic of Korea
    These authors contributed equally to this work.)

  • Yeong-Hoon Noh

    (School of Electric and Electronic Enginnering, Yonsei University, Seoul 03722, Republic of Korea)

  • Dong-Hoon Choi

    (School of Electric and Electronic Enginnering, Yonsei University, Seoul 03722, Republic of Korea)

  • Jong-gwan Yook

    (School of Electric and Electronic Enginnering, Yonsei University, Seoul 03722, Republic of Korea)

Abstract

This paper addresses the issue of electromagnetic interference (EMI) in electric vehicle supply equipment (EVSE) charging cables, which can disrupt the communication signal for the real-time monitoring of the charging status, leading to the termination of charging. We propose a dedicated measurement jig for the Combined Charging System Combo Type 1 (CCS-CT1) cable structure and models its electrical characteristics of the jig using the impedance peeling technique for de-embedding. The obtained pure S-parameters of CCS-CT1 are then used to conduct a simulation of the signal integrity problem caused by Gaussian noise, which is the worst-case scenario that can occur in a typical charging system. This paper suggests that the root cause of this problem may be related to the high-power AC/DC conversion device included in the EVSE, which uses a switch-mode power conversion (SMPC) method that involves nonlinear operation and can result in increased harmonic noise and a more complex signal protocol for precise control. Finally, this study provides insights into the challenges of implementing high-speed charging systems and offers a solution for obtaining the accurate electromagnetic characteristics of charging cables.

Suggested Citation

  • Sanghwa Park & Euibum Lee & Yeong-Hoon Noh & Dong-Hoon Choi & Jong-gwan Yook, 2023. "Accurate Modeling of CCS Combo Type 1 Cable and Its Communication Performance Analysis for High-Speed EV-EVSE Charging System," Energies, MDPI, vol. 16(16), pages 1-16, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:5947-:d:1215613
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    References listed on IDEAS

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    1. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    2. Haifeng Dai & Bo Jiang & Xuezhe Wei, 2018. "Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient," Energies, MDPI, vol. 11(1), pages 1-18, January.
    3. Dima Alame & Maher Azzouz & Narayan Kar, 2020. "Assessing and Mitigating Impacts of Electric Vehicle Harmonic Currents on Distribution Systems," Energies, MDPI, vol. 13(12), pages 1-17, June.
    4. Naireeta Deb & Rajendra Singh & Richard R. Brooks & Kevin Bai, 2021. "A Review of Extremely Fast Charging Stations for Electric Vehicles," Energies, MDPI, vol. 14(22), pages 1-27, November.
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