Accuracy Assessment of Li-ion Batteries Internal Resistance Model Through CFD Simulations, Experimental Measurements And Uncertainties
SOLAI, Elie
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
BEAUGENDRE, Héloïse
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
BIEDER, Ulrich
Service de Thermo-hydraulique et de Mécanique des Fluides [STMF]
CEA- Saclay [CEA]
Université Paris-Saclay
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Service de Thermo-hydraulique et de Mécanique des Fluides [STMF]
CEA- Saclay [CEA]
Université Paris-Saclay
SOLAI, Elie
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
BEAUGENDRE, Héloïse
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Université de Bordeaux [UB]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
BIEDER, Ulrich
Service de Thermo-hydraulique et de Mécanique des Fluides [STMF]
CEA- Saclay [CEA]
Université Paris-Saclay
Service de Thermo-hydraulique et de Mécanique des Fluides [STMF]
CEA- Saclay [CEA]
Université Paris-Saclay
CONGEDO, Pietro
Centre de Mathématiques Appliquées de l'Ecole polytechnique [CMAP]
Centre National de la Recherche Scientifique [CNRS]
Institut Polytechnique de Paris [IP Paris]
Uncertainty Quantification in Scientific Computing and Engineering [PLATON]
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Centre de Mathématiques Appliquées de l'Ecole polytechnique [CMAP]
Centre National de la Recherche Scientifique [CNRS]
Institut Polytechnique de Paris [IP Paris]
Uncertainty Quantification in Scientific Computing and Engineering [PLATON]
Language
en
Communication dans un congrès
This item was published in
HEFAT 2021 - 15th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, 2021-07-25, Virtual conference.
English Abstract
Internal resistance is a critical parameter of the thermal behavior of Li-ion battery cells. This paper proposes an innovative way to deal with the uncertainties related to this physical parameter using experimental data ...Read more >
Internal resistance is a critical parameter of the thermal behavior of Li-ion battery cells. This paper proposes an innovative way to deal with the uncertainties related to this physical parameter using experimental data and numerical simulation. First, a CFD model is validated against an experimental configuration representing the behavior of heated Li-ion battery cells under constant discharging current conditions. Secondly, an Uncertainty Quantification based methodology is proposed to represent the internal resistance and its inherent uncertainties. Thanks to an accurate and fast to compute surrogate model, the impact of those uncertainties on the temperature evolution of Li-ion cells is quantified. Finally, a Bayesian inference of the internal resistance model parameters using experimental measurements is performed, permitting to reduce the prediction uncertainty by almost 95% for some temperatures of interest.Read less <
Origin
Hal imported