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 exa...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
IOP Publishing
2022
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| _version_ | 1826308561989271552 |
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| author | Brosa Planella, F Ai, W Boyce, AM Ghosh, A Korotkin, I Sahu, S Sulzer, V Timms, R Tranter, TG Zyskin, M Cooper, SJ Edge, JS Foster, JM Marinescu, M Wu, B Richardson, G |
| author_facet | Brosa Planella, F Ai, W Boyce, AM Ghosh, A Korotkin, I Sahu, S Sulzer, V Timms, R Tranter, TG Zyskin, M Cooper, SJ Edge, JS Foster, JM Marinescu, M Wu, B Richardson, G |
| author_sort | Brosa Planella, F |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T07:21:19Z |
| format | Journal article |
| id | oxford-uuid:6d58cb9d-7f7e-4519-9873-350ec3be1b6f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:21:19Z |
| publishDate | 2022 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | oxford-uuid:6d58cb9d-7f7e-4519-9873-350ec3be1b6f2022-10-14T12:35:25ZA continuum of physics-based lithium-ion battery models reviewedJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:6d58cb9d-7f7e-4519-9873-350ec3be1b6fEnglishSymplectic ElementsIOP Publishing2022Brosa Planella, FAi, WBoyce, AMGhosh, AKorotkin, ISahu, SSulzer, VTimms, RTranter, TGZyskin, MCooper, SJEdge, JSFoster, JMMarinescu, MWu, BRichardson, GPhysics-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. |
| spellingShingle | Brosa Planella, F Ai, W Boyce, AM Ghosh, A Korotkin, I Sahu, S Sulzer, V Timms, R Tranter, TG Zyskin, M Cooper, SJ Edge, JS Foster, JM Marinescu, M Wu, B Richardson, G A continuum of physics-based lithium-ion battery models reviewed |
| title | A continuum of physics-based lithium-ion battery models reviewed |
| title_full | A continuum of physics-based lithium-ion battery models reviewed |
| title_fullStr | A continuum of physics-based lithium-ion battery models reviewed |
| title_full_unstemmed | A continuum of physics-based lithium-ion battery models reviewed |
| title_short | A continuum of physics-based lithium-ion battery models reviewed |
| title_sort | continuum of physics based lithium ion battery models reviewed |
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