Electric vehicle powertrain design with battery swapping and vehicle to grid implementation.

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dc.contributor.advisorJouanne, Annette von.
dc.contributor.advisorLee, Kwang Y.
dc.creatorAdegbohun, Feyijimi R., 1995-
dc.date.accessioned2021-07-14T14:05:05Z
dc.date.available2021-07-14T14:05:05Z
dc.date.created2021-05
dc.date.issued2021-03-31
dc.date.submittedMay 2021
dc.date.updated2021-07-14T14:05:06Z
dc.description.abstractDescribed in this work are methodologies for the design and development of electric vehicle (EV) powertrains through modeling, simulation and validation on a real-world systems, with detailed analysis of results. A system for swapping, storing and managing EV batteries, including a Deep Neural Network (DNN) based state of health estimation model is developed and analyzed. The system is designed to enable advanced interface with the electric grid and address challenges in the adoption of EVs which include : Cost, range anxiety, charging time and charging infrastructure, battery state of health, and impacts of vehicle to grid (V2G) operations. The EV battery swapping system (BSS) consists of the EV powertrain equipped with swapping capability, modular swappable battery packs, battery storage apparatus, bidirectional charging system, battery and charge management system, and battery swapping equipment. This system provides a cost-effective way of adopting electrification, reducing strain on the electricity grid during peak periods and extending the life of EV batteries.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2104/11416
dc.language.isoen
dc.rights.accessrightsWorldwide access.
dc.rights.accessrightsAccess changed 9/25/23.
dc.subjectElectric vehicle. Chassis dynamometer. Drive cycle. On-board diagnostics. Battery swapping.
dc.titleElectric vehicle powertrain design with battery swapping and vehicle to grid implementation.
dc.typeThesis
dc.type.materialtext
local.embargo.lift2023-05-01
local.embargo.terms2023-05-01
thesis.degree.departmentBaylor University. Dept. of Electrical & Computer Engineering.
thesis.degree.grantorBaylor University
thesis.degree.levelDoctoral
thesis.degree.namePh.D.

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