Intelligent energy management agent for a parallel hybrid vehicle

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dc.contributorLangari, Reza
dc.creatorWon, Jong-Seob
dc.date.accessioned2004-09-30T01:49:13Z
dc.date.accessioned2017-04-07T19:48:16Z
dc.date.available2004-09-30T01:49:13Z
dc.date.available2017-04-07T19:48:16Z
dc.date.created2005-05
dc.date.issued2004-09-30
dc.description.abstractThis dissertation proposes an Intelligent Energy Management Agent (IEMA) for parallel hybrid vehicles. A key concept adopted in the development of an IEMA is based on the premise that driving environment would affect fuel consumption and pollutant emissions, as well as the operating modes of the vehicle and the driver behavior do. IEMA incorporates a driving situation identification component whose role is to assess the driving environment, the driving style of the driver, and the operating mode (and trend) of the vehicle using long and short term statistical features of the drive cycle. This information is subsequently used by the torque distribution and charge sustenance components of IEMA to determine the power split strategy, which is shown to lead to improved fuel economy and reduced emissions.
dc.identifier.urihttp://hdl.handle.net/1969.1/271
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjecthybrid vehicle
dc.subjectenergy management
dc.subjectdriving cycle
dc.subjectintelligent energy management agent
dc.subjecttorque distribution
dc.subjectcharge sustenance
dc.titleIntelligent energy management agent for a parallel hybrid vehicle
dc.typeBook
dc.typeThesis

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Texas A&M University at College Station