Energy-Efficient Adaptive Cruise Control for Electric Connected and Autonomous Vehicles

dc.contributor.author Lu, Chaoru
dc.contributor.author Dong, Jing
dc.contributor.author Dong, Jing
dc.contributor.author Hu, Liang
dc.contributor.department Civil, Construction and Environmental Engineering
dc.date 2021-05-13T04:15:56.000
dc.date.accessioned 2021-08-14T02:55:05Z
dc.date.available 2021-08-14T02:55:05Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2019
dc.date.issued 2019-10-01
dc.description.abstract <p>This paper presented an energy-efficient adaptive cruise control, called Energy-Efficient Electric Driving Model (E3DM), for electric, connected, and autonomous vehicles (e-CAVs) in a mixed traffic stream. E3DM is able to maintain high energy efficiency of regenerative braking by adjusting the spacing between the leading and the following vehicles. Moreover, a power-based energy consumption model is proposed to estimate the on-road energy consumption for battery electric vehicles, considering the impact of ambient temperature on auxiliary load. Using the proposed energy consumption model, the impact of E3DM on vehicle energy consumption is investigated. In particular, single-lane vehicle dynamics in a traffic stream with a mixed of e-CAVs and human-driven vehicles are simulated. The result shows that E3DM outperforms existing adaptive cruise control (i.e. Nissan-ACC) and cooperative adaptive cruise control (i.e. Enhanced-IDM and Van Arem Model) strategies in terms of energy consumption. Moreover, higher market penetration of e-CAVs may not result in better energy efficiency of the entire fleet. The reason is that more e-CAVs in the traffic stream results in faster string stabilization which decreases the regenerative energy. Considering mix traffic streams with battery electric (BEVs) and internal-combustion engine (ICEVs) vehicles, the energy consumption of entire fleet reduces when the market penetration of BEV (contains both e-CAV and human-driven BEV) increases. A higher ratio of e-CAV to human-driven BEV results in higher energy efficiency.</p>
dc.description.comments <p>This is a manuscript of an article published as Lu, Chaoru, Jing Dong, and Liang Hu. "Energy-efficient adaptive cruise control for electric connected and autonomous vehicles." <em>IEEE Intelligent Transportation Systems Magazine</em> 11, no. 3 (2019): 42-55. DOI: <a href="https://doi.org/10.1109/MITS.2019.2919556" target="_blank">10.1109/MITS.2019.2919556</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ccee_pubs/296/
dc.identifier.articleid 1296
dc.identifier.contextkey 22904618
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ccee_pubs/296
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/aw4N4D5r
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ccee_pubs/296/2019_DongJing_EnergyEfficient.pdf|||Fri Jan 14 23:15:26 UTC 2022
dc.source.uri 10.1109/MITS.2019.2919556
dc.subject.disciplines Transportation Engineering
dc.subject.keywords Electric connected and autonomous vehicle (e-CAV)
dc.subject.keywords Energy-efficient adaptive cruise control
dc.subject.keywords Energy consumption model
dc.title Energy-Efficient Adaptive Cruise Control for Electric Connected and Autonomous Vehicles
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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