Battery capacity design for electric vehicles considering the diversity of daily vehicles miles traveled

dc.contributor.author Li, Zhiheng
dc.contributor.author Jiang, Shan
dc.contributor.author Dong-O'Brien, Jing
dc.contributor.author Dong, Jing
dc.contributor.author Wang, Shoufeng
dc.contributor.author Ming, Zhennan
dc.contributor.author Li, Li
dc.contributor.department Department of Civil, Construction and Environmental Engineering
dc.date 2018-12-22T00:37:07.000
dc.date.accessioned 2020-06-30T01:12:46Z
dc.date.available 2020-06-30T01:12:46Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2016
dc.date.issued 2016-11-01
dc.description.abstract <p>In this paper, we study battery capacity design for battery electric vehicles (BEVs). The core of such design problems is to find a good tradeoff between minimizing the capacity to reduce financial costs of drivers and increasing the capacity to satisfy daily travel demands. The major difficulty of such design problems lies in modeling the diversity of daily travel demands. Based on massive trip records of taxi drivers in Beijing, we find that the daily vehicle miles traveled (DVMT) of a driver (e.g., a taxi driver) may change significantly in different days. This investigation triggers us to propose a mixture distribution model to describe the diversity in DVMT for various driver in different days, rather than the widely employed single distribution model. To demonstrate the merit of this new model, we consider value-at-risk and mean-variance battery capacity design problems for BEV, with respect to conventional single and new mixture distribution models of DVMT. Testing results indicate that the mixture distribution model better leads to better solutions to satisfy various drivers.</p>
dc.description.comments <p>This is a manuscript of an article published as Li, Zhiheng, Shan Jiang, Jing Dong, Shoufeng Wang, Zhennan Ming, and Li Li. "Battery capacity design for electric vehicles considering the diversity of daily vehicles miles traveled." <em>Transportation Research Part C: Emerging Technologies</em> 72 (2016): 272-282. DOI: <a href="https://dx.doi.org/10.1016/j.trc.2016.10.001" target="_blank">10.1016/j.trc.2016.10.001</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ccee_pubs/201/
dc.identifier.articleid 1204
dc.identifier.contextkey 13475421
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ccee_pubs/201
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/13850
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ccee_pubs/201/2016_DongJing_BatteryCapacity.pdf|||Fri Jan 14 22:19:51 UTC 2022
dc.source.uri 10.1016/j.trc.2016.10.001
dc.subject.disciplines Civil Engineering
dc.subject.disciplines Transportation Engineering
dc.subject.keywords Battery electric vehicle (BEV)
dc.subject.keywords Daily vehicle miles traveled (DVMT)
dc.subject.keywords Battery capacity design
dc.title Battery capacity design for electric vehicles considering the diversity of daily vehicles miles traveled
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 02eacfea-376d-45b0-a048-1b6d00cfbf26
relation.isOrgUnitOfPublication 933e9c94-323c-4da9-9e8e-861692825f91
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