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dc.contributor.authorDoshi-Velez, Finale P.
dc.contributor.authorRoy, Nicholas
dc.contributor.authorJoseph, Joshua Mason
dc.date.accessioned2013-10-03T13:02:14Z
dc.date.available2013-10-03T13:02:14Z
dc.date.issued2012-05
dc.identifier.isbn978-1-4673-1405-3
dc.identifier.isbn978-1-4673-1403-9
dc.identifier.isbn978-1-4673-1578-4
dc.identifier.isbn978-1-4673-1404-6
dc.identifier.urihttp://hdl.handle.net/1721.1/81281
dc.description.abstractThe batteries of many consumer products are both a substantial portion of the product's cost and commonly a first point of failure. Accurately predicting remaining battery life can lower costs by reducing unnecessary battery replacements. Unfortunately, battery dynamics are extremely complex, and we often lack the domain knowledge required to construct a model by hand. In this work, we take a data-driven approach and aim to learn a model of battery time-to-death from training data. Using a Dirichlet process prior over mixture weights, we learn an infinite mixture model for battery health. The Bayesian aspect of our model helps to avoid over-fitting while the nonparametric nature of the model allows the data to control the size of the model, preventing under-fitting. We demonstrate our model's effectiveness by making time-to-death predictions using real data from nickel-metal hydride battery packs.en_US
dc.description.sponsorshipUnited States. Army Research Office (Nostra Project STTR W911NF-08-C-0066)en_US
dc.description.sponsorshipiRoboten_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICRA.2012.6225178en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleA Bayesian nonparametric approach to modeling battery healthen_US
dc.typeArticleen_US
dc.identifier.citationJoseph, Joshua, Finale Doshi-Velez, and Nicholas Roy. “A Bayesian nonparametric approach to modeling battery health.” In 2012 IEEE International Conference on Robotics and Automation, 1876-1882. Institute of Electrical and Electronics Engineers, 2012.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.mitauthorJoseph, Joshua Masonen_US
dc.contributor.mitauthorDoshi-Velez, Finale P.en_US
dc.contributor.mitauthorRoy, Nicholasen_US
dc.relation.journalProceedings of the 2012 IEEE International Conference on Robotics and Automationen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsJoseph, Joshua; Doshi-Velez, Finale; Roy, Nicholasen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8293-0492
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US


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