Lithium-ion battery degradation: how to model it
Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between mor...
| Asıl Yazarlar: | , , , , , , , , , |
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| Materyal Türü: | Journal article |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
Royal Society of Chemistry
2022
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| _version_ | 1826307822783037440 |
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| author | O'Kane, S Ai, W Madabattula, G Alonso-Albarez, D Timms, R Sulzer, V Edge, JS Wu, B Offer, GJ Marinescu, M |
| author_facet | O'Kane, S Ai, W Madabattula, G Alonso-Albarez, D Timms, R Sulzer, V Edge, JS Wu, B Offer, GJ Marinescu, M |
| author_sort | O'Kane, S |
| collection | OXFORD |
| description | Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between more than two degradation mechanisms, and none do so within a single electrode. In this paper, the first published attempt to directly couple more than two degradation mechanisms in the negative electrode is reported. The results are used to map different pathways through the complicated path dependent and non-linear degradation space. Four degradation mechanisms are coupled in PyBaMM, an open source modelling environment uniquely developed to allow new physics to be implemented and explored quickly and easily. Crucially it is possible to see ‘inside the model and observe the consequences of the different patterns of degradation, such as loss of lithium inventory and loss of active material. For the same cell, five different pathways that can result in end-of-life have already been found, depending on how the cell is used. Such information would enable a product designer to either extend life or predict life based upon the usage pattern. However, parameterization of the degradation models remains as a major challenge, and requires the attention of the international battery community. |
| first_indexed | 2024-03-07T07:10:23Z |
| format | Journal article |
| id | oxford-uuid:29c5e513-5553-47b9-97e5-61c321a31365 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:10:23Z |
| publishDate | 2022 |
| publisher | Royal Society of Chemistry |
| record_format | dspace |
| spelling | oxford-uuid:29c5e513-5553-47b9-97e5-61c321a313652022-06-17T15:53:00ZLithium-ion battery degradation: how to model itJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:29c5e513-5553-47b9-97e5-61c321a31365EnglishSymplectic ElementsRoyal Society of Chemistry2022O'Kane, SAi, WMadabattula, GAlonso-Albarez, DTimms, RSulzer, VEdge, JSWu, BOffer, GJMarinescu, MPredicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between more than two degradation mechanisms, and none do so within a single electrode. In this paper, the first published attempt to directly couple more than two degradation mechanisms in the negative electrode is reported. The results are used to map different pathways through the complicated path dependent and non-linear degradation space. Four degradation mechanisms are coupled in PyBaMM, an open source modelling environment uniquely developed to allow new physics to be implemented and explored quickly and easily. Crucially it is possible to see ‘inside the model and observe the consequences of the different patterns of degradation, such as loss of lithium inventory and loss of active material. For the same cell, five different pathways that can result in end-of-life have already been found, depending on how the cell is used. Such information would enable a product designer to either extend life or predict life based upon the usage pattern. However, parameterization of the degradation models remains as a major challenge, and requires the attention of the international battery community. |
| spellingShingle | O'Kane, S Ai, W Madabattula, G Alonso-Albarez, D Timms, R Sulzer, V Edge, JS Wu, B Offer, GJ Marinescu, M Lithium-ion battery degradation: how to model it |
| title | Lithium-ion battery degradation: how to model it |
| title_full | Lithium-ion battery degradation: how to model it |
| title_fullStr | Lithium-ion battery degradation: how to model it |
| title_full_unstemmed | Lithium-ion battery degradation: how to model it |
| title_short | Lithium-ion battery degradation: how to model it |
| title_sort | lithium ion battery degradation how to model it |
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