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A continuum of physics-based lithium-ion battery models reviewed

A continuum of physics-based lithium-ion battery models reviewed
A continuum of physics-based lithium-ion battery models reviewed
Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complexity, is needed for different applications. For example, in battery design we can afford longer computational times and the use of powerful computers, while for real-time battery control (e.g. in electric vehicles) we need to perform very fast calculations using simple devices. For this reason, simplified models that retain most of the features at a lower computational cost are widely used. Even though in the literature we often find these simplified models posed independently, leading to inconsistencies between models, they can actually be derived from more complicated models using a unified and systematic framework. In this review, we showcase this reductive framework, starting from a high-fidelity microscale model and reducing it all the way down to the single particle model, deriving in the process other common models, such as the Doyle–Fuller–Newman model. We also provide a critical discussion on the advantages and shortcomings of each of the models, which can aid model selection for a particular application. Finally, we provide an overview of possible extensions to the models, with a special focus on thermal models. Any of these extensions could be incorporated into the microscale model and the reductive framework re-applied to lead to a new generation of simplified, multi-physics models.
Doyle–Fuller–Newman (DFN), degradation models, lithium-ion batteries, mathematical modelling, physics-based models, single particle model (SPM), thermal models
2516-1083
Brosa Planella, Ferran
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Ai, Weilong
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Ghosh, Abir
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Boyce, Adam
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Korotkin, Ivan
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Sahu, Smita
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Sulzer, Valentin
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Timms, Robert
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Tranter, Tom
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Zyskin, Maxim
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Cooper, Sam
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Edge, Jacqueline
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Foster, Jamie
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Marinescu, Monica
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Wu, Billy
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Richardson, Giles
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Brosa Planella, Ferran
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Ai, Weilong
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Ghosh, Abir
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Boyce, Adam
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Korotkin, Ivan
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Sahu, Smita
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Sulzer, Valentin
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Timms, Robert
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Tranter, Tom
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Zyskin, Maxim
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Cooper, Sam
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Edge, Jacqueline
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Foster, Jamie
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Marinescu, Monica
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Wu, Billy
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Richardson, Giles
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Brosa Planella, Ferran, Ai, Weilong, Ghosh, Abir, Boyce, Adam, Korotkin, Ivan, Sahu, Smita, Sulzer, Valentin, Timms, Robert, Tranter, Tom, Zyskin, Maxim, Cooper, Sam, Edge, Jacqueline, Foster, Jamie, Marinescu, Monica, Wu, Billy and Richardson, Giles (2022) A continuum of physics-based lithium-ion battery models reviewed. Progress in Energy, 4 (4), [042003]. (doi:10.1088/2516-1083/ac7d31).

Record type: Article

Abstract

Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complexity, is needed for different applications. For example, in battery design we can afford longer computational times and the use of powerful computers, while for real-time battery control (e.g. in electric vehicles) we need to perform very fast calculations using simple devices. For this reason, simplified models that retain most of the features at a lower computational cost are widely used. Even though in the literature we often find these simplified models posed independently, leading to inconsistencies between models, they can actually be derived from more complicated models using a unified and systematic framework. In this review, we showcase this reductive framework, starting from a high-fidelity microscale model and reducing it all the way down to the single particle model, deriving in the process other common models, such as the Doyle–Fuller–Newman model. We also provide a critical discussion on the advantages and shortcomings of each of the models, which can aid model selection for a particular application. Finally, we provide an overview of possible extensions to the models, with a special focus on thermal models. Any of these extensions could be incorporated into the microscale model and the reductive framework re-applied to lead to a new generation of simplified, multi-physics models.

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Accepted/In Press date: 29 June 2022
Published date: 19 July 2022
Keywords: Doyle–Fuller–Newman (DFN), degradation models, lithium-ion batteries, mathematical modelling, physics-based models, single particle model (SPM), thermal models

Identifiers

Local EPrints ID: 469097
URI: http://eprints.soton.ac.uk/id/eprint/469097
ISSN: 2516-1083
PURE UUID: 9c92921d-2400-43fc-8336-118bf9e7b31f
ORCID for Ivan Korotkin: ORCID iD orcid.org/0000-0002-5023-3684
ORCID for Giles Richardson: ORCID iD orcid.org/0000-0001-6225-8590

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Date deposited: 06 Sep 2022 18:47
Last modified: 31 Jan 2023 02:59

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Contributors

Author: Ferran Brosa Planella
Author: Weilong Ai
Author: Abir Ghosh
Author: Adam Boyce
Author: Ivan Korotkin ORCID iD
Author: Smita Sahu
Author: Valentin Sulzer
Author: Robert Timms
Author: Tom Tranter
Author: Maxim Zyskin
Author: Sam Cooper
Author: Jacqueline Edge
Author: Jamie Foster
Author: Monica Marinescu
Author: Billy Wu

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