Adaptive Energy Management Strategy for a Hybrid Vehicle Using Energetic Macroscopic Representation

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dc.contributor.author Mansour, C.
dc.contributor.author Salloum, N.
dc.contributor.author Francis, S.
dc.contributor.author Baroud, W.
dc.date.accessioned 2020-09-29T07:45:29Z
dc.date.available 2020-09-29T07:45:29Z
dc.date.copyright 2016 en_US
dc.date.issued 2020-09-29
dc.identifier.isbn 9781509035281 en_US
dc.identifier.uri http://hdl.handle.net/10725/12177
dc.description.abstract The Energetic Macroscopic Representation is used in this paper to model a pre-transmission parallel hybrid electric vehicle and its control and energy management system. Since optimizing energy management onboard is among the key factors in reducing consumption of hybrid vehicles, several strategies are developed in the literature such as instantaneous-optimization rule-based strategies and global-optimization strategies; however, being implemented separately and for different purposes. For instance, rule-based strategies serve for real-time operation, where the global-optimization strategies for benchmarking, as it lacks the ability to be used in real-time control. Hence, the combination of both strategies would result in close-to-optimal energy consumption through a real-time control system. Therefore, a simple adaptive rule-based strategy is presented in this study, based on short-term driving pattern recognition and the global optimization routine of dynamic programming. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Motor vehicles--Fuel systems--Congresses en_US
dc.subject Propulsion systems--Congresses en_US
dc.subject Fuel cells--Congresses en_US
dc.subject Hybrid electric vehicles--Congresses en_US
dc.subject Alternative fuel vehicles--Congresses en_US
dc.subject Power transmission--Congresses en_US
dc.title Adaptive Energy Management Strategy for a Hybrid Vehicle Using Energetic Macroscopic Representation en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SOE en_US
dc.author.idnumber 201001655 en_US
dc.author.department Industrial And Mechanical Engineering en_US
dc.description.embargo N/A en_US
dc.description.physdesc 1 online resource (various pagings) : illustrations en_US
dc.publication.place Piscataway, N.J. en_US
dc.keywords Energy management en_US
dc.keywords Energy management en_US
dc.keywords Mechanical power transmission en_US
dc.keywords Vehicles en_US
dc.keywords Optimization en_US
dc.keywords Torque en_US
dc.keywords Engines en_US
dc.keywords Energy consumption en_US
dc.description.bibliographiccitations Includes bibliographical references en_US
dc.identifier.doi https://doi.org/10.1109/VPPC.2016.7791606 en_US
dc.identifier.ctation Mansour, C., Salloum, N., Francis, S., & Baroud, W. (2016, October). Adaptive energy management strategy for a hybrid vehicle using energetic macroscopic representation. In 2016 IEEE Vehicle Power and Propulsion Conference (VPPC) (pp. 1-7). IEEE. en_US
dc.author.email charbel.mansour@lau.edu.lb en_US
dc.conference.date 17-20 October 2016 en_US
dc.conference.place Hangzhou, China en_US
dc.conference.subtitle proceedings en_US
dc.conference.title 2016 IEEE Vehicle Power and Propulsion Conference (VPPC) en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/7791606 en_US
dc.publication.date 2016 en_US
dc.author.affiliation Lebanese American University en_US

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