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Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling

Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling

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LASS, Oliver, Stefan VOLKWEIN, 2015. Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling. In: Computational Optimization and Applications. 62(1), pp. 217-239. ISSN 0926-6003. eISSN 1573-2894

@article{Lass2015-09Param-32549, title={Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling}, year={2015}, doi={10.1007/s10589-015-9734-8}, number={1}, volume={62}, issn={0926-6003}, journal={Computational Optimization and Applications}, pages={217--239}, author={Lass, Oliver and Volkwein, Stefan} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/32549"> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-01-13T13:21:56Z</dc:date> <dcterms:issued>2015-09</dcterms:issued> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/32549"/> <dc:contributor>Volkwein, Stefan</dc:contributor> <dc:creator>Volkwein, Stefan</dc:creator> <dcterms:title>Parameter identification for nonlinear elliptic-parabolic systems with application in lithium-ion battery modeling</dcterms:title> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-01-13T13:21:56Z</dcterms:available> <dc:contributor>Lass, Oliver</dc:contributor> <dcterms:abstract xml:lang="eng">In this paper the authors consider a parameter estimation problem for a nonlinear systems, which consists of one parabolic equation for the concentration and two elliptic equations for the potentials. The measurements are given as boundary values for one of the potentials. For its numerical solution the Gauss Newton method is applied. To speed up the solution process, a reduced-order approach based on proper orthogonal decomposition is utilized, where the accuracy is controlled by error estimators. Parameters, which can not be identified from the measurements, are identified by the subset selection method with QR pivoting. Numerical examples show the efficiency of the proposed approach.</dcterms:abstract> <dc:creator>Lass, Oliver</dc:creator> <dc:language>eng</dc:language> </rdf:Description> </rdf:RDF>

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