Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation
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 basi...
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2018
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| Online Access: | http://hdl.handle.net/10725/12256 https://doi.org/10.4172/2167-7670.1000188 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php 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 |
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| _version_ | 1864513489734729728 |
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| author | Basma, Hussein M. |
| author2 | Mansour, Charbel J. Halaby, Houssam Radwan, Anis Baz |
| author2_role | author author author |
| author_facet | Basma, Hussein M. Mansour, Charbel J. Halaby, Houssam Radwan, Anis Baz |
| author_role | author |
| dc.creator.none.fl_str_mv | Basma, Hussein M. Mansour, Charbel J. Halaby, Houssam Radwan, Anis Baz |
| dc.date.none.fl_str_mv | 2018 2020-10-13T12:00:20Z 2020-10-13T12:00:20Z 2020-10-13 |
| dc.identifier.none.fl_str_mv | 2167-7670 http://hdl.handle.net/10725/12256 https://doi.org/10.4172/2167-7670.1000188 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). http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php 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 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Advances in Automobile Engineering |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation Case of Plug-In Series Hybrid Electric Vehicle |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | 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). |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_f3afdc71bce8cc128dfcd3638bec7fd4 |
| identifier_str_mv | 2167-7670 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). |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/12256 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic RepresentationCase of Plug-In Series Hybrid Electric VehicleBasma, Hussein M.Mansour, Charbel J.Halaby, HoussamRadwan, Anis BazThe 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).PublishedN/A2020-10-13T12:00:20Z2020-10-13T12:00:20Z20182020-10-13Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article2167-7670http://hdl.handle.net/10725/12256https://doi.org/10.4172/2167-7670.1000188Basma, 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).http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://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_VehicleenAdvances in Automobile Engineeringinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/122562021-03-19T10:47:41Z |
| spellingShingle | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation Basma, Hussein M. |
| status_str | publishedVersion |
| title | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| title_full | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| title_fullStr | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| title_full_unstemmed | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| title_short | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| title_sort | Methodology to Design an Optimal Rule Based Energy Management Strategy Using Energetic Macroscopic Representation |
| url | http://hdl.handle.net/10725/12256 https://doi.org/10.4172/2167-7670.1000188 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php 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 |