Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation

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dc.contributor.author Basma, Hussein M.
dc.contributor.author Mansour, Charbel J.
dc.contributor.author Halaby, Houssam
dc.contributor.author Radwan, Anis Baz
dc.date.accessioned 2020-10-13T12:00:20Z
dc.date.available 2020-10-13T12:00:20Z
dc.date.copyright 2018 en_US
dc.date.issued 2020-10-13
dc.identifier.issn 2167-7670 en_US
dc.identifier.uri http://hdl.handle.net/10725/12256
dc.description.abstract The energy management strategy implemented in plug-in hybrid electric vehicles largely affects their energy consumption and emissions. Rule-Based (RB) controllers are commonly used for their simplicity and suitability in real-time applications. However, these controllers are most often based on basic engineering intuition such as the charge depleting-charge sustaining strategy, and lack to provide optimal energy savings compared to global optimization strategies. This paper presents to powertrain modeling practitioners a comprehensive methodology to design an optimal rule-based controller for series plug-in hybrid electric vehicles, derived from global optimization control routine. Dynamic programming control is used first and based on the resulting powertrain components behavior; power management rules are then derived. The resulting optimal rule-based controller is further adapted to capture the variation in trip distance lengths and to accommodate for different traffic intensities. The Energetic Macroscopic Representation is used to model the vehicle, where the proposed optimal rule-based controller is implemented. The performance of the investigated rule-based and dynamic programming control strategies is then compared and analyzed on the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). en_US
dc.language.iso en en_US
dc.title Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation en_US
dc.type Article en_US
dc.description.version Published en_US
dc.title.subtitle Case of Plug-In Series Hybrid Electric Vehicle 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.relation.journal Advances in Automobile Engineering en_US
dc.journal.volume 7 en_US
dc.journal.issue 3 en_US
dc.identifier.doi https://doi.org/10.4172/2167-7670.1000188 en_US
dc.identifier.ctation Basma, H. M., Mansour, C. J., Halaby, H., & Radwan, A. B. (2018). Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation: Case of Plug-In Series Hybrid Electric Vehicle. Advances in Automobile Engineering, 7(3). en_US
dc.author.email charbel.mansour@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://www.researchgate.net/publication/334170663_Methodology_to_Design_an_Optimal_Rule-Based_Energy_Management_Strategy_Using_Energetic_Macroscopic_Representation_Case_of_Plug-In_Series_Hybrid_Electric_Vehicle en_US
dc.author.affiliation Lebanese American University en_US

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