Physical Modelling of the Slow Voltage Relaxation Phenomenon in Lithium-Ion Batteries

Kirk, Toby; Please, Colin P.; Chapman, S. Jonathan

doi:10.1149/1945-7111/ac0bf7

Cited by 19 publications

(8 citation statements)

References 35 publications

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“…12,17 Continuum-scale simulations of physicochemical processes in porous media both obviate the need for this elusive information and significantly accelerate the computation by averaging out the porescale variability and replacing various phases of an electrolyte-filled porous material with a single continuum characterized by aggregate properties such as porosity and tortuosity. 18,19 The pseudo-twodimensional (P2D) models 20,21 occupy the middle ground between these pore-and continuum-scale simulation frameworks in that they retain a micro-scale description of transport in the active solid-phase but represent the latter as an effective/equivalent sphere or a collection of spheres. Like all effective/continuum-scale models, the P2D models and their various simplifications 22 trade the highfidelity of pore-scale simulations for computational efficiency.…”

mentioning

confidence: 99%

Impact of Carbon Binder Domain on the Performance of Lithium-metal Batteries

Boso¹,

Li²,

Um³

et al. 2022

J. Electrochem. Soc.

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Pseudo-2-dimensional models are routinely used to predict the lithiation curves for energy storage devices, including lithium-metal batteries. The performance of such models is as good as their parameterization, which remains a challenge especially in the presence of carbon binder domain (CBD). We propose two alternative parameterization strategies, which explicitly account for the CBD volume fraction and physical properties. The first aggregates CBD with the electrolyte-filled pore space and expresses the Bruggeman exponent in terms of a solution of microstructure-specific closure problem. The second treats CBD and active particles as a composite solid phase, whose effective properties are computed (semi-)analytically via homogenization. We show that the latter strategy used to parameterize the Doyle-Fuller-Newman model provides an attractive middle ground between the model complexity and the prediction accuracy. Our modeling results suggest that the battery discharge time decreases as either the CBD volume fraction increases or the CBD ionic diffusivity decreases, and is insensitive to the CBD ionic conductivity. The quantitative nature of these observations can be used in the optimal design of porous cathodes.

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mentioning

confidence: 99%

Impact of Carbon Binder Domain on the Performance of Lithium-metal Batteries

Boso¹,

Li²,

Um³

et al. 2022

J. Electrochem. Soc.

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“…The spatial heterogeneities of a battery cell significantly impact its performance and are best captured by microstructure-resolved modelling. [12,88] The link between exponential relaxation times at rest and heterogeneity has been discussed by Kirk et al [89] They propose at least a multiparticle 1D + 1D model, the MP-DFN, that incorporates the different length scales of the electrode particles.…”

Section: Discussionmentioning

confidence: 99%

Bayesian Parameterization of Continuum Battery Models from Featurized Electrochemical Measurements Considering Noise**

Yannick

Wolf

Latz

et al. 2022

Batteries & Supercaps

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Physico-chemical continuum battery models are typically parameterized by manual fits, relying on the individual expertise of researchers. In this article, we introduce a computer algorithm that directly utilizes the experience of battery researchers to extract information from experimental data reproducibly. We extend Bayesian Optimization (BOLFI) with Expectation Propagation (EP) to create a black-box optimizer suited for modular continuum battery models. Standard approaches compare the experimental data in its raw entirety to the model simulations.By dividing the data into physics-based features, our datadriven approach uses orders of magnitude less simulations. For validation, we process full-cell GITT measurements to characterize the diffusivities of both electrodes non-destructively. Our algorithm enables experimentators and theoreticians to investigate, verify, and record their insights. We intend this algorithm to be a tool for the accessible evaluation of experimental databases.

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“…The spatial heterogeneities of a ba ery cell significantly impact its performance and are best captured by microstructure-resolved modelling [12,86]. The link between exponential relaxation times at rest and heterogeneity has been discussed by Kirk et al [87]. They propose at least a multi-particle 1D+1D model, the MP-DFN, that incorporates the di erent length scales of the electrode particles.…”

Section: Discussionmentioning

confidence: 99%

Bayesian Parameterization of Continuum Battery Models from Featurized Electrochemical Measurements Considering Noise

Yannick¹,

Wolf²,

Latz³

et al. 2022

Preprint

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Physico-chemical continuum ba ery models can predict the performance of new materials and cell geometries. The physical model parameters are typically determined by manually fi ing to experimental data. However, this process relies on the individual expertise of researchers. In this article, we introduce a computer algorithm that directly utilizes the experience of ba ery researchers to extract information from experimental data reproducibly. We extend Bayesian Optimization (BOLFI) with Expectation Propagation (EP) to create a black-box optimizer suited for modular continuum ba ery models. Standard approaches compare the experimental data in its raw entirety to the model simulations. By dividing the data into physics-based features, our data-driven approach uses one to two orders of magnitude less evaluations of the simulations. This enables the fi ing of complex models that take up to a few minutes to simulate. For validation, we process full-cell GITT measurements to characterize the di usivities of both electrodes non-destructively. Our algorithm enables experimentators and theoreticians to investigate, verify, and record their insights. We intend this algorithm to be a tool for the accessible evaluation of experimental databases.

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Physical Modelling of the Slow Voltage Relaxation Phenomenon in Lithium-Ion Batteries

Cited by 19 publications

References 35 publications

Impact of Carbon Binder Domain on the Performance of Lithium-metal Batteries

Impact of Carbon Binder Domain on the Performance of Lithium-metal Batteries

Bayesian Parameterization of Continuum Battery Models from Featurized Electrochemical Measurements Considering Noise**

Bayesian Parameterization of Continuum Battery Models from Featurized Electrochemical Measurements Considering Noise

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