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Systems and operational modeling and simulation to address research gaps in transportation electrification

dc.contributor.authorRabinowitz, Aaron I., author
dc.contributor.authorBradley, Thomas, advisor
dc.contributor.authorDaily, Jeremy, committee member
dc.contributor.authorPasricha, Sudeep, committee member
dc.contributor.authorWeinberger, Chris, committee member
dc.date.accessioned2023-08-28T10:29:00Z
dc.date.available2023-08-28T10:29:00Z
dc.date.issued2023
dc.description.abstractTransportation electrification is increasingly thought of as a necessity in order to mitigate the negative effects of climate change and this has recently resulted in large investments, within the US and globally, into green transportation technology. In order to ensure that the electrification transition of the transportation sector is carried out in an efficient and effective manner, it is important to address key research gaps. The proposed research involves addressing 4 important research gaps related to electrification in the transportation sector. The four research gaps addressed are quantifying the energetic benefits which may be achieved via the use of Connected Autonomous Vehicle (CAV) technology to enable optimal operational and dynamic control in Electric Vehicles (EVs), the quantification of the operational inconvenience experienced by Battery Electric Vehicle (BEV) users compared to Internal Combustion Vehicle (ICV) users for given infrastructural parameters, and quantification of the potential economic competitiveness of BEVs for Heavy Duty (HD) Less Than Truckload (LTL) fleets. The identified research gaps are addressed via quantitative, data-based, and transparent modeling and simulation. In the first two cases, comprehensive simulation experiments are conducted which show both the potential energetic improvements available as well as the best methods to achieve these improvements. In the second case, a novel method is developed for the quantification of operational inconvenience due to energizing a vehicle and an empirical equation is derived for estimating said inconvenience based on vehicular and infrastructural parameters. The empirical equation can be deployed on a geo- spatial basis in order to provide quantitative measures of BEV inequity of experience. In the last case a novel, data-driven simulation based Total Cost of Ownership (TCO) model for class 8 BEV tractors is developed and used to project economic competitiveness in the near and medium term future. Findings from the proposed research will provide critical information for industry and policy-makers in their mission to enable an efficient and equitable transportation future.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierRabinowitz_colostate_0053A_17875.pdf
dc.identifier.urihttps://hdl.handle.net/10217/236926
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.titleSystems and operational modeling and simulation to address research gaps in transportation electrification
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineSystems Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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