Publikation: A-posteriori error analysis for lithium-ion concentrations in batteries utilizing the reduced-basis method
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2016
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Mathematical and Computer Modelling of Dynamical Systems. 2016, 22(4), pp. 362-379. ISSN 1387-3954. eISSN 1744-5051. Available under: doi: 10.1080/13873954.2016.1198387
Zusammenfassung
In this paper, the authors consider a parametrized non-linear parabolic differential equation, which is motivated by lithium-ion battery models. A standard finite volume discretization leads to a high-dimensional discrete non-linear problem so that simulation of the parametrized problem for various different parameters is very costly. Therefore, the reduced-basis method is applied, so that the number of degrees of freedom is reduced significantly and a fast numerical simulation of the model is possible. To control the error, an a-posteriori error estimator is derived. Numerical experiments show the efficiency of the approach.
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510 Mathematik
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IAPICHINO, Laura, Stefan VOLKWEIN, Andrea WESCHE, 2016. A-posteriori error analysis for lithium-ion concentrations in batteries utilizing the reduced-basis method. In: Mathematical and Computer Modelling of Dynamical Systems. 2016, 22(4), pp. 362-379. ISSN 1387-3954. eISSN 1744-5051. Available under: doi: 10.1080/13873954.2016.1198387BibTex
@article{Iapichino2016-07-03Apost-35383,
year={2016},
doi={10.1080/13873954.2016.1198387},
title={A-posteriori error analysis for lithium-ion concentrations in batteries utilizing the reduced-basis method},
number={4},
volume={22},
issn={1387-3954},
journal={Mathematical and Computer Modelling of Dynamical Systems},
pages={362--379},
author={Iapichino, Laura and Volkwein, Stefan and Wesche, Andrea}
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<dcterms:abstract xml:lang="eng">In this paper, the authors consider a parametrized non-linear parabolic differential equation, which is motivated by lithium-ion battery models. A standard finite volume discretization leads to a high-dimensional discrete non-linear problem so that simulation of the parametrized problem for various different parameters is very costly. Therefore, the reduced-basis method is applied, so that the number of degrees of freedom is reduced significantly and a fast numerical simulation of the model is possible. To control the error, an a-posteriori error estimator is derived. Numerical experiments show the efficiency of the approach.</dcterms:abstract>
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