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Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets

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dc.contributor.authorTrinko, David A., author
dc.contributor.authorBradley, Thomas H., advisor
dc.contributor.authorQuinn, Jason C., committee member
dc.contributor.authorSimske, Steven, committee member
dc.contributor.authorHurrell, James, committee member
dc.date.accessioned2023-06-01T23:55:50Z
dc.date.available2024-05-26T23:55:50Z
dc.date.issued2023
dc.description.abstractThis project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierTrinko_colostate_0053A_17631.pdf
dc.identifier.urihttps://hdl.handle.net/10217/236655
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.rights.accessEmbargo Expires: 05/26/2024
dc.titleModeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets
dc.typeText
dcterms.embargo.expires2024-05-26
dcterms.embargo.terms2024-05-26
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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