This paper presents an automated vehicle speed planning system called the energy-optimal deceleration planning system (EDPS), which aims to maximize energy-recuperation of regenerative braking on connected and autonomous electrified vehicles. Based on the impending deceleration requirements resulting from speed reduction ahead of turning or stopping at a nearby intersection, a recuperation-energy-optimal speed profile is computed by maximizing the regenerative braking energy-efficiency while satisfying the physical limits of an electrified powertrain. Optimal deceleration commands are determined by a parameterized polynomial-based deceleration model that is obtained by regression analyses with real-world test data from human drivers. For the fast-tracking validation, the proposed speed planning algorithm is compared with human drivers and we show that EDPS-based autonomous driving results in improved energy recuperation and a shorter driving time.


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    Titel :

    Energy-Optimal Regenerative Braking Strategy for Connected and Autonomous Electrified Vehicles: A Practical Design and Implementation for Real-World Commercial PHEVs


    Beteiligte:
    Kim, Dohee (Autor:in) / Eo, Jeongsoo (Autor:in) / Kim, Kwang-Ki K. (Autor:in)


    Erscheinungsdatum :

    20.09.2020


    Format / Umfang :

    819444 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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