As the regulations on the fuel economy and emissions standards become higher, Hybrid Electric Vehicles (HEV) are gaining more popularity in the market. HEVs improvements in fuel economy and emissions strongly depend on the energy management strategy. An optimization based power flow controller is presented in this thesis to find the appropriate power split between the Internal Combustion Engine (ICE) and the electric motor to reduce the energy consumption and emissions. However, emissions were not taken into consideration in results due to lack of reliable results. A basic power flow controller was built to compare to the optimization based controller. A plant model of each component of the vehicle was built in Simulink to evaluate the performance of each controller. Compared to the basic power flow controller, the real-time energy and emission minimization controller using shift schedule (ReTEEM-SS) reduced the energy consumption by approximately 6.2% in city driving style and 5.4% in highway driving style. The optimization based controller was further modified to replace the shift schedule with a shift logic. The real-time energy and emission minimization controller using shift logic (ReTEEM-SL) reduced the energy consumption by 10.2% in city drive style and 5.3% in highway driver style, when compared to the basic controller.
","abstract_html":"<p>As the regulations on the fuel economy and emissions standards become higher, Hybrid Electric Vehicles (HEV) are gaining more popularity in the market. HEVs improvements in fuel economy and emissions strongly depend on the energy management strategy. An optimization based power flow controller is presented in this thesis to find the appropriate power split between the Internal Combustion Engine (ICE) and the electric motor to reduce the energy consumption and emissions. However, emissions were not taken into consideration in results due to lack of reliable results. A basic power flow controller was built to compare to the optimization based controller. A plant model of each component of the vehicle was built in Simulink to evaluate the performance of each controller. Compared to the basic power flow controller, the real-time energy and emission minimization controller using shift schedule (ReTEEM-SS) reduced the energy consumption by approximately 6.2% in city driving style and 5.4% in highway driving style. The optimization based controller was further modified to replace the shift schedule with a shift logic. The real-time energy and emission minimization controller using shift logic (ReTEEM-SL) reduced the energy consumption by 10.2% in city drive style and 5.3% in highway driver style, when compared to the basic controller.</p>","abstract_has_math":false,"creators":["Karmustaji, Abdulla Abdulaziz"],"institution":null,"degree_name":"Master of Science in Mechanical Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-05-01T07:00:00Z","date_published":"2016-05-01T07:00:00Z","updated_at":"2026-07-27T19:26:02Z","subjects":["optimization","power flow","energy consumption","emissions","HEV","Mechanical Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/271","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Karmustaji, Abdulla Abdulaziz"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Mechanical Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["optimization","power flow","energy consumption","emissions","HEV","Mechanical Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/271"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["As the regulations on the fuel economy and emissions standards become higher, Hybrid Electric Vehicles (HEV) are gaining more popularity in the market. HEVs improvements in fuel economy and emissions strongly depend on the energy management strategy. An optimization based power flow controller is presented in this thesis to find the appropriate power split between the Internal Combustion Engine (ICE) and the electric motor to reduce the energy consumption and emissions. However, emissions were not taken into consideration in results due to lack of reliable results. A basic power flow controller was built to compare to the optimization based controller. A plant model of each component of the vehicle was built in Simulink to evaluate the performance of each controller. Compared to the basic power flow controller, the real-time energy and emission minimization controller using shift schedule (ReTEEM-SS) reduced the energy consumption by approximately 6.2% in city driving style and 5.4% in highway driving style. The optimization based controller was further modified to replace the shift schedule with a shift logic. The real-time energy and emission minimization controller using shift logic (ReTEEM-SL) reduced the energy consumption by 10.2% in city drive style and 5.3% in highway driver style, when compared to the basic controller.
"]},{"key":"dc:title","label":"Title","values":["Real-Time Optimization Based Power Flow Controller for Energy Consumption and Emissions Reduction in a Parallel HEV"]}]}],"canonical_facts":{"dc:creator":["Karmustaji, Abdulla Abdulaziz"],"dc:description.abstract":["As the regulations on the fuel economy and emissions standards become higher, Hybrid Electric Vehicles (HEV) are gaining more popularity in the market. HEVs improvements in fuel economy and emissions strongly depend on the energy management strategy. An optimization based power flow controller is presented in this thesis to find the appropriate power split between the Internal Combustion Engine (ICE) and the electric motor to reduce the energy consumption and emissions. However, emissions were not taken into consideration in results due to lack of reliable results. A basic power flow controller was built to compare to the optimization based controller. A plant model of each component of the vehicle was built in Simulink to evaluate the performance of each controller. Compared to the basic power flow controller, the real-time energy and emission minimization controller using shift schedule (ReTEEM-SS) reduced the energy consumption by approximately 6.2% in city driving style and 5.4% in highway driving style. The optimization based controller was further modified to replace the shift schedule with a shift logic. The real-time energy and emission minimization controller using shift logic (ReTEEM-SL) reduced the energy consumption by 10.2% in city drive style and 5.3% in highway driver style, when compared to the basic controller.
"],"dc:identifier":["https://commons.erau.edu/edt/271"],"dc:subject":["optimization","power flow","energy consumption","emissions","HEV","Mechanical Engineering"],"dc:title":["Real-Time Optimization Based Power Flow Controller for Energy Consumption and Emissions Reduction in a Parallel HEV"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Mechanical Engineering"]},"updated_at":"2026-07-27T19:26:02Z"}