Genetic Algorithm for UTS Plug-in Hybrid Electric Vehicle Parameter Optimization

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dc.contributor.author Abdul Rahman, Salisa en_US
dc.contributor.author Zhang, Nong en_US
dc.contributor.author Zhu, Jianguo en_US
dc.contributor.editor Conference Technical Committee en_US
dc.date.accessioned 2010-05-28T10:01:13Z
dc.date.available 2010-05-28T10:01:13Z
dc.date.issued 2009 en_US
dc.identifier 2009003174 en_US
dc.identifier.citation Abdul Rahman Salisa, Zhang Nong, and Zhu Jianguo 2009, 'Genetic Algorithm for UTS Plug-in Hybrid Electric Vehicle Parameter Optimization', University of Canterbury, Christchurch, New Zealand, New Zealand, pp. 1-8. en_US
dc.identifier.issn 978-0-473-16050-0 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/11011
dc.description.abstract This paper covers modeling, energy management strategy development, genetic algorithm (GA) optimization and simulation results based on the model of the UTS plug-in hybrid electric vehicle (PHEV). The UTS PHEV configuration consists of energy storage system, electric machine (EM), power control unit and internal combustion engine. The difference between the UTS PHEV and the conventional powertrain configurations is that the existing configurations need two EMs to function as the electric generator and motor, respectively, while the UTS PHEV needs only one EM to function as either a generator or electric motor in different time intervals specified by the energy management strategy and therefore, can save space, weight and cost. Extensive research has been conducted on the modeling and comparison of the new and existing powertrain configurations. The objective of this paper is to minimize the fuel consumption and greenhouse gas emissions by optimizing the powertrain parameters. The powertrain was simulated for a standard U.S environmental protection agency drive cycle, the highway drive cycle, and the optimization was performed by using the GA. en_US
dc.language English en_US
dc.publisher University of Canterbury, Christchurch, New Zealand en_US
dc.relation.isbasedon NA en_US
dc.title Genetic Algorithm for UTS Plug-in Hybrid Electric Vehicle Parameter Optimization en_US
dc.parent Proceedings of the 13th Asia-Pacific Vibration Conference (APVC 09) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation New Zealand en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 8 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 091304 en_US
dc.personcode 10736585 en_US
dc.personcode 950854 en_US
dc.personcode 910870 en_US
dc.percentage 100 en_US
dc.classification.name Dynamics, Vibration and Vibration Control en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom Asia Pacific Vibration Conference en_US
dc.date.activity 20051122 en_US
dc.location.activity Christchurch, New Zealand en_US
dc.description.keywords Plug-in hybrid electric vehicle, hybrid electric vehicle, energy management strategy, genetic algorithm, series-parallel en_US
dc.staffid en_US
dc.staffid 910870 en_US


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