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<p>This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of V2I communications. Moreover, a heuristic solution is developed to reduce the computational complexity. The results confirm the efficiency of the proposed solutions in mitigating overloading and reducing the total time cost in EV networks with hybrid traffic flows.</p>

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Efficient charging scheduling through coordination of electric vehicle platoons and charging stations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月13日

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  • Liwan Qi,
  • Bochun Wu,
  • Shoubo Li,
  • Yi Gong,
  • Wei Ni

摘要

This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of V2I communications. Moreover, a heuristic solution is developed to reduce the computational complexity. The results confirm the efficiency of the proposed solutions in mitigating overloading and reducing the total time cost in EV networks with hybrid traffic flows.