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Battery Identification Methods Based On Equivalent Circuit Model

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Battery Identification Methods Based On Equivalent Circuit Model

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dc.contributor.author Ragsdale, Matthew Cole en_US
dc.date.accessioned 2010-03-03T23:30:26Z
dc.date.available 2010-03-03T23:30:26Z
dc.date.issued 2010-03-03T23:30:26Z
dc.date.submitted January 2009 en_US
dc.identifier.other DISS-10396 en_US
dc.identifier.uri http://hdl.handle.net/10106/1994
dc.description.abstract Development of an intelligent battery diagnostic system is a necessity for future transportation industry. These technologies will have the potential to create profound impact in other industries such as portable electronics. This thesis reports on battery identification methods that are primarily engineered to detect the chemistry, number of cells, and state of charge in an unknown package of batteries. The proposed methods have the potential to be used for condition monitoring in a known set of batteries thereby, creating a health monitoring apparatus that can be an integral part of a battery management system using any of the prominent lead acid, lithium-ion, and Nickel Metal Hydride batteries. The proposed methods are based on distinct signatures that one can identify in a relatively straightforward equivalent circuit of a battery. These signatures are extracted using time domain diagnostics and are used in combination with nonlinear mappings such as exponential regression and artificial neural networks for pattern recognition purposesThis thesis presents the design and development of three battery identification methods based on a single RC equivalent circuit model. The first method compares measured circuit parameters with lookup tables using MSE analysis to identify chemistry, cell count, and SOC of the battery. The second method uses an artificial neural network to identify battery chemistry based on measured circuit parameters. The final method uses an artificial neural network to identify battery chemistry and SOC based on raw voltage waveforms, bypassing the need to calculate equivalent circuit parameters. en_US
dc.description.sponsorship Fahimi, Babak en_US
dc.language.iso EN en_US
dc.publisher Electrical Engineering en_US
dc.title Battery Identification Methods Based On Equivalent Circuit Model en_US
dc.type M.S. en_US
dc.contributor.committeeChair Fahimi, Babak en_US
dc.degree.department Electrical Engineering en_US
dc.degree.discipline Electrical Engineering en_US
dc.degree.grantor University of Texas at Arlington en_US
dc.degree.level masters en_US
dc.degree.name M.S. en_US
dc.identifier.externalLink https://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=237
dc.identifier.externalLinkDescription Link to Research Profiles

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