Vehicle activity patterns and electrification potential

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Wei, Wei (Scientist in system design and management) Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Advisor dc:contributor.advisor

• Jessika E. Trancik.

• Civil and Environmental Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/111418

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/111418