The Whole-Day Driving Prediction (WDDP) concept is a unique plug-in hybrid electric vehicle (PHEV) control strategy that uses the day's planned travels to determine if a small range-extending engine should be turned on at the start of each day. This control strategy allows for the use of a very small engine, in contrast to commercially available PHEVs, which generally have engines large enough to propel the vehicle. This paper presents modeling and simulation results for WDDP vehicles on the real-world logged driving cycles of 100 drivers who were each logged for between 2 and 6 weeks. The simulation results show that with an engine size between 5 and 7 kW, the WDDP vehicle with a 35-kWh battery has similar range capabilities to a pure EV with a 60-kWh battery. The consequence is that purchase price can be decreased while keeping similar range performance, encouraging a higher market penetration of plug-in vehicles. The results of this paper show that the WDDP concept is viable for real-world use, and has the potential to reduce plug-in vehicle costs while achieving driving ranges similar to the new long-range EVs recently introduced to the market.


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    Titel :

    Whole-Day Driving Prediction Control Strategy: Analysis on Real-World Drive Cycles


    Beteiligte:
    Palcu, Petru (Autor:in) / Bauman, Jennifer (Autor:in)


    Erscheinungsdatum :

    01.03.2018


    Format / Umfang :

    2441459 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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