Connected and automated vehicles (CAVs) provide enormous opportunities for improving fuel economy, safety, and capacity of the transportation system. In this article, an eco-driving control scheme for electric vehicle (EV) platoons is proposed by taking regenerative braking and braking torque distribution into account. An efficient Poly-Eco speed planning method is first presented to improve computational efficiency. A control scheme comprising a splitting/merging decision-making and a modified intelligent driver model (MIDM) vehicle-following controller is established to verify the effectiveness of the proposed Poly-Eco speed advisory in mixed traffic scenarios. Comprehensive hardware-in-the-loop (HIL) tests are conducted to examine the proposed Poly-Eco control scheme in terms of energy consumption, traffic efficiency, and ride comfort. The rule-based (RB) and sequential programming (SP) methods are used for comparison. The comparison results show that the proposed Poly-Eco method can reduce the energy consumption by 4.71% while guaranteeing lower jerk and less arrival time compared with the commonly used SP method. The lapse time per period for the proposed Poly-Eco method is only 2.3% of that for the SP method. In addition, the proposed Poly-Eco method stages superior performance under typical mixed traffic scenarios.


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    Titel :

    Efficient Eco-Driving Control for EV Platoons in Mixed Urban Traffic Scenarios Considering Regenerative Braking


    Beteiligte:
    Liu, Jizheng (Autor:in) / Wang, Zhenpo (Autor:in) / Zhang, Lei (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.06.2024


    Format / Umfang :

    3116356 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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