Fuzzy Logic Controller for Parallel Plug-in Hybrid Vehicle

dc.contributor.advisorAnoop K. Dhingra
dc.contributor.advisorRonald A. Perez
dc.contributor.committeememberAnoop K. Dhingra
dc.contributor.committeememberRonald A. Perez
dc.contributor.committeememberBenjamin C. Church
dc.creatorHasan, Sk. Khairul
dc.date.accessioned2025-01-16T19:32:56Z
dc.date.available2025-01-16T19:32:56Z
dc.date.issued2012-12-01
dc.description.abstractHybrid electric vehicles combine two methods for propelling a vehicle. In a parallel hybrid vehicle, the two propulsion methods work in parallel to meet the total power demand. Among different combination of power sources, internal combustion engine and electric motor drive system are the most popular because of their availability and controllability. Plug-in hybrid vehicle is the latest version in hybrid vehicle family. In plug-in hybrid vehicle, battery is directly recharged from the electrical power grid and it can be used for a long distance with higher efficiency. Most of the hybrid vehicles on the road are parallel in nature and battery is recharged directly by the engine. If it is possible to convert existing hybrid vehicle into plug-in hybrid vehicle, it will lead to significant improvements in fuel economy and emissions.In this thesis, two fuzzy logic controllers have been developed for the energy management system of the hybrid vehicle. For the first controller, it is assumed that the vehicle will work like a plug-in hybrid vehicle. For the second controller it is assumed that the battery will always recharged by the engine. It is found that with the help of developed fuzzy logic controller, the plug-in hybrid vehicle can run up to 200 miles with high efficiency. Both controllers are developed and their performance is tested on the highly reliable vehicle modeling and simulation software AUTONOMIE. The main objective of developing the controllers is increasing the fuel economy of the vehicle. The results from the both developed controllers are compared with the default controller in AUTONOMIE in order to show performance improvements.
dc.identifier.urihttp://digital.library.wisc.edu/1793/88285
dc.relation.replaceshttps://dc.uwm.edu/etd/436
dc.subjectArgone National Lab
dc.subjectAutonomie
dc.subjectFuzzy Logic
dc.subjectParallel Hybrid
dc.subjectPlug-in Hybrid
dc.titleFuzzy Logic Controller for Parallel Plug-in Hybrid Vehicle
dc.typethesis
thesis.degree.disciplineEngineering
thesis.degree.grantorUniversity of Wisconsin-Milwaukee
thesis.degree.nameMaster of Science

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