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Study of a New Quick-Charging Strategy for Electric Vehicles in Highway Charging Stations

Author

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  • Lixing Chen

    (School of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, China)

  • Xueliang Huang

    (School of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, China)

  • Zhong Chen

    (School of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, China)

  • Long Jin

    (School of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, China)

Abstract

To solve the problem, because of which conventional quick-charging strategies (CQCS) cannot meet the requirements of quick-charging for multiple types of electric vehicles (EV) on highways where vehicle inflow is excessive, this paper proposed a new quick-charging strategy (NQCS) for EVs: on the premise of not affecting those EVs being charged, the remaining power of the quick-charging pile with multiple power output interfaces is used to provide a synchronous charging service for EVs waiting in the queue. To verify the effectiveness of this strategy, a power distribution model of charging pile and a queuing model of charging station (CS) were constructed. In addition, based on an actual highway service area where vehicle inflow is excessive during the simulation period (0:00–24:00), charging situations of CQCS and NQCS were respectively simulated in a charging station (CS), with different number of chargers, by basic queuing algorithm and an improved queuing algorithm. The simulation results showed that when the relative EV inflow is excessive, compared to CQCS, NQCS not only can reduce user waiting time, charging time, and stay time, but also can improve the utilisation rate of charging infrastructure and service capacity of CS and reduce the queue length of CS. At the same time, NQCS can reduce the impact on the power grid. In addition, in NQCS, the on-demand power distribution method is more efficient than the average power distribution method. Therefore, NQCS is more suitable for quick-charging for multiple types of EVs on highways where vehicle inflow is excessive.

Suggested Citation

  • Lixing Chen & Xueliang Huang & Zhong Chen & Long Jin, 2016. "Study of a New Quick-Charging Strategy for Electric Vehicles in Highway Charging Stations," Energies, MDPI, vol. 9(9), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:9:p:744-:d:78136
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    References listed on IDEAS

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    Cited by:

    1. Lixing Chen & Xueliang Huang & Hong Zhang, 2020. "Modeling the Charging Behaviors for Electric Vehicles Based on Ternary Symmetric Kernel Density Estimation," Energies, MDPI, vol. 13(7), pages 1-17, March.
    2. Tian Wu & Bohan Zeng & Yali He & Xin Tian & Xunmin Ou, 2017. "Sustainable Governance for the Opened Electric Vehicle Charging and Upgraded Facilities Market," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    3. Antonia Golab & Sebastian Zwickl-Bernhard & Hans Auer, 2022. "Minimum-Cost Fast-Charging Infrastructure Planning for Electric Vehicles along the Austrian High-Level Road Network," Energies, MDPI, vol. 15(6), pages 1-26, March.
    4. Lixing Chen & Xueliang Huang & Hong Zhang & Yinsheng Luo, 2018. "A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection," Energies, MDPI, vol. 11(6), pages 1-16, May.
    5. Alberto Romero-Ania & Lourdes Rivero Gutiérrez & María Auxiliadora De Vicente Oliva, 2021. "Multiple Criteria Decision Analysis of Sustainable Urban Public Transport Systems," Mathematics, MDPI, vol. 9(16), pages 1-30, August.
    6. Lourdes Rivero Gutiérrez & María Auxiliadora De Vicente Oliva & Alberto Romero-Ania, 2021. "Managing Sustainable Urban Public Transport Systems: An AHP Multicriteria Decision Model," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    7. Zhenxing Li & Yang Gong & Lu Wang & Hong Tan & Prominent Lovet Kativu & Pengfei Wang, 2018. "A Regional Protection Partition Strategy Considering Communication Constraints and Its Implementation Techniques," Energies, MDPI, vol. 11(10), pages 1-15, September.
    8. Su Su & Hao Li & David Wenzhong Gao, 2017. "Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits," Energies, MDPI, vol. 10(7), pages 1-15, July.
    9. Cuiyu Kong & Raka Jovanovic & Islam Safak Bayram & Michael Devetsikiotis, 2017. "A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations," Energies, MDPI, vol. 10(5), pages 1-20, May.

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