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Physical validation of predictive acceleration control on a parallel hybrid electric vehicle

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dc.contributor.authorWhite, Samantha M., author
dc.contributor.authorBradley, Thomas, advisor
dc.contributor.authorQuinn, Jason, committee member
dc.contributor.authorDaily, Jeremy, committee member
dc.contributor.authorWindom, Bret, committee member
dc.date.accessioned2022-08-29T10:15:56Z
dc.date.available2022-08-29T10:15:56Z
dc.date.issued2022
dc.description.abstractPrevious research has been conducted towards the development of predictive control strategies for Hybrid Electric Vehicles (HEVs). These methods have been shown to be effective in reducing fuel consumption in simulation, but no physical validation has been conducted. This is likely due to the fundamental "curses" of dynamic programming mostly the "curse of dimensionality" wherein the run-time needed to generate the optimal solution renders the method unfit as a real-time control. Predictive Acceleration Event (PAE) control combats the run-time issues associated with dynamic programming based control methods by pre-computing the optimal solutions for common Acceleration Events (AEs). This method was physically implemented on a 2019 Toyota Tacoma that was converted into a Parallel-3 (P3) HEV with limited information on the vehicle, including a reduced access to the vehicle's Controller Area Network (CAN) bus. Results from on-track testing indicate a Fuel Economy (FE) improvement in the range of 7% is possible to achieve using PAE control in the real world. To the author's knowledge this is the first time that this type of testing has ever been implemented on a vehicle in the real world.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierWhite_colostate_0053N_17277.pdf
dc.identifier.urihttps://hdl.handle.net/10217/235586
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.subjectcontrols
dc.subjectfuel economy
dc.subjectpredictive acceleration control
dc.subjectelectric vehicle
dc.subjectautomotive
dc.subjecthybrid
dc.titlePhysical validation of predictive acceleration control on a parallel hybrid electric vehicle
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.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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