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Power Control Strategies of On-Road Charging for Electric Vehicles

Author

Listed:
  • Linlin Tan

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

  • Jinpeng Guo

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

  • Xueliang Huang

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

  • Han Liu

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

  • Changxin Yan

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

  • Wei Wang

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu, China
    Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Zhenjiang 212009, Jiangsu, China)

Abstract

On-road charging systems for electric vehicles (EVs) have shown revolutionary potential in extending driving range and reducing battery capacities. The optimal equivalent load resistances to maximize receiving power of each EV according to different EV amounts are investigated. This paper introduces a typical on-road charging system with a single transmitting coil and multiple receiving coils. The equivalent circuit models according to different numbers of EVs are built. Power control strategies with regard to a varying number of EVs are then presented. Specifically, self-adaptive source voltage based on primary current detection is utilized to charge EVs, while the source can support enough EVs by providing the rated power. Otherwise, the source voltage is regulated to its maximum value and the charging energy of each EV is suggested to be controlled by adjusting the individual driving speed. A remarkable feature of the power control strategies is that the charging power for each EV is stable and can compensate for energy losses efficiently. As for urgent power demand from a particular EV with a low battery capacity, the adjustment of the corresponding load resistance is applied to alter the power distribution. The proposed technique has been verified in an experimental prototype.

Suggested Citation

  • Linlin Tan & Jinpeng Guo & Xueliang Huang & Han Liu & Changxin Yan & Wei Wang, 2016. "Power Control Strategies of On-Road Charging for Electric Vehicles," Energies, MDPI, vol. 9(7), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:7:p:531-:d:73705
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    References listed on IDEAS

    as
    1. Yabiao Gao & Kathleen Blair Farley & Zion Tsz Ho Tse, 2015. "A Uniform Voltage Gain Control for Alignment Robustness in Wireless EV Charging," Energies, MDPI, vol. 8(8), pages 1-16, August.
    2. Thuc Phi Duong & Jong-Wook Lee, 2015. "A Dynamically Adaptable Impedance-Matching System for Midrange Wireless Power Transfer with Misalignment," Energies, MDPI, vol. 8(8), pages 1-25, July.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Kamal Eldin Idris Elnail & Xueliang Huang & Chen Xiao & Linlin Tan & Xu Haozhe, 2018. "Core Structure and Electromagnetic Field Evaluation in WPT Systems for Charging Electric Vehicles," Energies, MDPI, vol. 11(7), pages 1-17, July.
    2. Young Jin Hwang & Jae Young Jang, 2020. "Design and Analysis of a Novel Magnetic Coupler of an In-Wheel Wireless Power Transfer System for Electric Vehicles," Energies, MDPI, vol. 13(2), pages 1-22, January.
    3. Linlin Tan & Ming Zhang & Songcen Wang & Shulei Pan & Zhenxing Zhang & Jiacheng Li & Xueliang Huang, 2019. "The Design and Optimization of a Wireless Power Transfer System Allowing Random Access for Multiple Loads," Energies, MDPI, vol. 12(6), pages 1-19, March.
    4. Hyukjoon Lee & Dongjin Ji & Dong-Ho Cho, 2019. "Optimal Design of Wireless Charging Electric Bus System Based on Reinforcement Learning," Energies, MDPI, vol. 12(7), pages 1-20, March.
    5. Konstantina Anastasiadou & Nikolaos Gavanas & Magda Pitsiava-Latinopoulou & Evangelos Bekiaris, 2021. "Infrastructure Planning for Autonomous Electric Vehicles, Integrating Safety and Sustainability Aspects: A Multi-Criteria Analysis Approach," Energies, MDPI, vol. 14(17), pages 1-19, August.

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