Microstructure‐ and Theory‐Based Modeling and Simulation of Batteries and Fuel Cells

Latz, Arnulf; Danner, Timo; Horstmann, Birger; Jahnke, Thomas

doi:10.1002/cite.201800186

Cited by 5 publications

(3 citation statements)

References 51 publications

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“…Phase changes in particles are typically studied using phase-field approaches, such as Bai et al 51 who simulated phase separation in LFP particles. On a higher level, the microstructure of porous electrodes can be simulated using non-equilibrium thermodynamics, for instance Latz et al 52 used the software BEST for virtual electrode design.…”

Section: Methodsmentioning

confidence: 99%

Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries

Reniers

Mulder

Howey

2019

J. Electrochem. Soc.

290

156

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The maximum energy that lithium-ion batteries can store decreases as they are used because of various irreversible degradation mechanisms. Many models of degradation have been proposed in the literature, sometimes with a small experimental data set for validation. However, a thorough comparison between different model predictions is lacking, making it difficult to select modelling approaches which can explain the degradation trends actually observed from data. Here various degradation models from literature are implemented within a single particle model framework and their behaviour compared. It is shown that many different models can be fitted to a small experimental data set. The interactions between different models are simulated, showing how some of the models accelerate degradation in other models, altering the overall degradation trend. The effects of operating conditions on the various degradation models is simulated. This identifies which models are enhanced by which operating conditions and might therefore explain specific degradation trends observed in data. Finally, it is shown how a combination of different models is needed to capture different degradation trends observed in a large experimental data set. Vice versa, only a large data set enables to properly select the models which best explain the observed degradation.

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Section: Methodsmentioning

confidence: 99%

Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries

Reniers

Mulder

Howey

2019

J. Electrochem. Soc.

290

156

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“…55,56 However, the diffusion values for SiOy and graphite have had values reported much higher than observed here, between 10 -11 cm 2 s -1 to 10 -8 cm 2 s -1 and 10 -10 cm 2 s -1 to 10 -8 cm 2 s -1 for the materials respectively. 51,57,58 Diffusion coefficients are often reported over several orders of magnitude due to differences in experimental set-ups and analysis. The solid-phase diffusivity often has to be tuned to a higher value for to provide reasonable simulation values as if the low diffusivity values are included in the fits, the simulations either do not converge or provide unrealistic results.…”

Section: Diffusionmentioning

confidence: 99%

Thermal-electrochemical parameters of a high energy lithium-ion cylindrical battery

O’Regan

Planella

Widanage

et al. 2022

Preprint

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To accurately predict the lifetime of commercial cells, multi-physics models can be used, however the accuracy of the model is heavily reliant upon the quality of the input thermodynamics and kinetic parameters. The thermal properties and the variability of the transport and thermodynamic properties with temperature and state-of-charge (SoC) in a high energy 21700 cylindrical cell were measured. The parameters are used in a DFN and 0D thermal model, and the model was tested against experimental data from the commercial cell. The results demonstrate an improved model fit by 27% when including the parameter dependency upon SoC and temperature, compared to without. The maximum power is limited by the negative electrode, which has lower diffusion coefficients and current exchange density over the full SOC window compared to the positive electrode, particularly at 50% and 80% SoC (x=0.45 and 0.85), reflected in high activation energies of up to 60 kJ K-1 and low diffusion coefficients of 5 x 10-13 cm-2 s-1 at 25 °C. At 45 °C, the reaction rate increases to greater than that of the positive, diffusion also increases, 2 x10-12 cm-2 s-1, but is still limiting. This work provides for the first time an electrochemical and thermal experimental dataset for a high energy cell, and provides insights into the rate limitations and prediction errors.

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“…This was recently successfully demonstrated for the prediction of the performance of thick cathodes for high energy LIBs. Starting with the validation of the model and prediction of limiting factors [17], the microstructures resulting from specific processing routes were investigated [18]. This knowledge was used to model, predict, and validate the influence of binder and carbon distribution and of the salt concentration on the battery performance of high-energy NMC-based LIBs [19,20].…”

Section: Introductionmentioning

confidence: 99%

Absolute Local Quantification of Li as Function of State-of-Charge in All-Solid-State Li Batteries via 2D MeV Ion-Beam Analysis

et al. 2021

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Direct observation of the lithiation and de-lithiation in lithium batteries on the component and microstructural scale is still difficult. This work presents recent advances in MeV ion-beam analysis, enabling quantitative contact-free analysis of the spatially-resolved lithium content and state-of-charge (SoC) in all-solid-state lithium batteries via 3 MeV proton-based characteristic x-ray and gamma-ray emission analysis. The analysis is demonstrated on cross-sections of ceramic and polymer all-solid-state cells with LLZO and MEEP/LIBOB solid electrolytes. Different SoC are measured ex-situ and one polymer-based operando cell is charged at 333 K during analysis. The data unambiguously show the migration of lithium upon charging. Quantitative lithium concentrations are obtained by taking the physical and material aspects of the mixed cathodes into account. This quantitative lithium determination as a function of SoC gives insight into irreversible degradation phenomena of all-solid-state batteries during the first cycles and locations of immobile lithium. The determined SoC matches the electrochemical characterization within uncertainties. The presented analysis method thus opens up a completely new access to the state-of-charge of battery cells not depending on electrochemical measurements. Automated beam scanning and data-analysis algorithms enable a 2D quantitative Li and SoC mapping on the µm-scale, not accessible with other methods.

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Microstructure‐ and Theory‐Based Modeling and Simulation of Batteries and Fuel Cells

Cited by 5 publications

References 51 publications

Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries

Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries

Thermal-electrochemical parameters of a high energy lithium-ion cylindrical battery

Absolute Local Quantification of Li as Function of State-of-Charge in All-Solid-State Li Batteries via 2D MeV Ion-Beam Analysis

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