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Two chemo-mechanical coupled models for electrode particles of lithium-ion batteries are compared. On the one hand a CahnHilliard-type phase-field approach models lithium intercalation, phase separation and large deformations in phase transforming cathode materials like lithium iron phosphate. On the other hand a chemo-mechanical particle model for lithium intercalation and large deformations for an anode material such as silicon is studied. The comparison of two different ways to define the deformation gradient for the large deformation approach and the two different material properties lead to differences in the resulting quantities and equations for the coupling of the chemo-mechanical model. The usage of an adaptive solution algorithm as well as the parallelization of the finite element solver via the message passing interface concept results in a more reasonable computation time to perform two-dimensional simulations. Both materials are numerically investigated and the results are compared from a physical point of view. When fast charging a battery, higher stress values are reached, which can cause a shorter cycle life. A strong scalability analysis shows good performance for the assembling, however a saturation occurs in the performance of the solver used. | Two chemo-mechanical coupled models for electrode particles of lithium-ion batteries are compared. On the one hand a CahnHilliard-type phase-field approach models lithium intercalation, phase separation and large deformations in phase transforming cathode materials like lithium iron phosphate. On the other hand a chemo-mechanical particle model for lithium intercalation and large deformations for an anode material such as silicon is studied. The comparison of two different ways to define the deformation gradient for the large deformation approach and the two different material properties lead to differences in the resulting quantities and equations for the coupling of the chemo-mechanical model. The usage of an adaptive solution algorithm as well as the parallelization of the finite element solver via the message passing interface concept results in a more reasonable computation time to perform two-dimensional simulations. Both materials are numerically investigated and the results are compared from a physical point of view. When fast charging a battery, higher stress values are reached, which can cause a shorter cycle life. A strong scalability analysis shows good performance for the assembling, however a saturation occurs in the performance of the solver used. | ||
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| + | == Abstract == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_4969409431672_abstract.pdf</pdf> | ||
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| + | == Full Paper == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_4969409431672_paper.pdf</pdf> | ||
Latest revision as of 16:06, 25 November 2022
Summary
Two chemo-mechanical coupled models for electrode particles of lithium-ion batteries are compared. On the one hand a CahnHilliard-type phase-field approach models lithium intercalation, phase separation and large deformations in phase transforming cathode materials like lithium iron phosphate. On the other hand a chemo-mechanical particle model for lithium intercalation and large deformations for an anode material such as silicon is studied. The comparison of two different ways to define the deformation gradient for the large deformation approach and the two different material properties lead to differences in the resulting quantities and equations for the coupling of the chemo-mechanical model. The usage of an adaptive solution algorithm as well as the parallelization of the finite element solver via the message passing interface concept results in a more reasonable computation time to perform two-dimensional simulations. Both materials are numerically investigated and the results are compared from a physical point of view. When fast charging a battery, higher stress values are reached, which can cause a shorter cycle life. A strong scalability analysis shows good performance for the assembling, however a saturation occurs in the performance of the solver used.
Abstract
Full Paper
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Published on 24/11/22
Accepted on 24/11/22
Submitted on 24/11/22
Volume Computational Solid Mechanics, 2022
DOI: 10.23967/eccomas.2022.106
Licence: CC BY-NC-SA license
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