Lithium-ion battery degradation: using degradation mode analysis to validate lifetime prediction modelling
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866917572515987456 |
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| author | Li, Ruihe Kirkaldy, Niall D. Oehler, Fabian Marinescu, Monica Offer, Gregory J. O'Kane, Simon E. J. |
| author_facet | Li, Ruihe Kirkaldy, Niall D. Oehler, Fabian Marinescu, Monica Offer, Gregory J. O'Kane, Simon E. J. |
| contents | Predicting lithium-ion battery lifetime is one of the greatest unsolved problems in battery research right now. Recent years have witnessed a surge in lifetime prediction papers using physics-based, empirical, or data-driven models, most of which have been validated against the remaining capacity (capacity fade) and sometimes resistance (power fade). However, there are many different combinations of degradation mechanisms in lithium-ion batteries that can result in the same patterns of capacity and power fade, making it impossible to find a unique validated solution. Experimentally, degradation mode analysis involving measuring the loss of lithium inventory, loss of active material at both electrodes, and electrode drift/slippage has emerged as a state-of-the-art requirement for cell degradation studies. In this paper we coupled five degradation mechanisms together for the first time. We also showed how three models with different levels of complexity can all fit the remaining capacity and resistance well, but only the model with five coupled degradation mechanisms could also fit the degradation modes at all temperatures. This work proves that validating only against capacity and power fade is no longer sufficient, and state-of-the-art experimental and modelling degradation studies should include degradation mode analysis for validation in the future. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_05482 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Lithium-ion battery degradation: using degradation mode analysis to validate lifetime prediction modelling Li, Ruihe Kirkaldy, Niall D. Oehler, Fabian Marinescu, Monica Offer, Gregory J. O'Kane, Simon E. J. Chemical Physics Predicting lithium-ion battery lifetime is one of the greatest unsolved problems in battery research right now. Recent years have witnessed a surge in lifetime prediction papers using physics-based, empirical, or data-driven models, most of which have been validated against the remaining capacity (capacity fade) and sometimes resistance (power fade). However, there are many different combinations of degradation mechanisms in lithium-ion batteries that can result in the same patterns of capacity and power fade, making it impossible to find a unique validated solution. Experimentally, degradation mode analysis involving measuring the loss of lithium inventory, loss of active material at both electrodes, and electrode drift/slippage has emerged as a state-of-the-art requirement for cell degradation studies. In this paper we coupled five degradation mechanisms together for the first time. We also showed how three models with different levels of complexity can all fit the remaining capacity and resistance well, but only the model with five coupled degradation mechanisms could also fit the degradation modes at all temperatures. This work proves that validating only against capacity and power fade is no longer sufficient, and state-of-the-art experimental and modelling degradation studies should include degradation mode analysis for validation in the future. |
| title | Lithium-ion battery degradation: using degradation mode analysis to validate lifetime prediction modelling |
| topic | Chemical Physics |
| url | https://arxiv.org/abs/2311.05482 |