Battery electric vehicles (BEVs) are among the most promising solutions to transportation decarbonization, yet some vehicle-days' energy requirements cannot be satisfied by an existing, affordable BEV. These days account for a significant percentage of total personal vehicle energy consumption in the United States (US). Identifying activity patterns on these high-energy days is important for estimating the potential for mass adoption of BEVs. However, the current literature has yet to understand the characteristics of such days at the national level, and the implications for the electrification potential of personal vehicles. This thesis aims to understand what kinds of vehicle activity patterns constitute highenergy vehicle-days and to evaluate potential solutions for vehicle electrification, namely improving BEV charging infrastructure and car-sharing. We have developed a set of methods to extract representative high-energy vehicle-day activity profiles. Targeting such days, the thesis evaluates the increase in BEV adoption potential through expanded charging infrastructure, providing commercial car-sharing, and allowing intra-household vehicle-sharing. This research finds that high-energy days across the US have relatively regular vehicleday activity patterns. Car-sharing and expanded charging infrastructure an help enable BEV adoption potential. On a typical day, providing commercial car-sharing services for the longest home-based tour to 9% of vehicle-days is equivalent to increasing everyones' battery capacity level by 17%, in terms of BEV adoption potential. Furthermore, intrahousehold vehicle-sharing shows promise for increasing BEV adoption potential. Methods and insights from this research can help decision-makers identify efficient policy options for accelerating BEV adoption.


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    Title :

    Vehicle activity patterns and electrification potential



    Publication date :

    2017


    Size :

    73 pages


    Remarks:

    Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2017.
    Cataloged from PDF version of thesis.
    Includes bibliographical references (pages 69-73).


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English





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