Yeardley, A.J., Bugryniec, P.J., Milton, R.A. et al. (1 more author) (2020) A study of the thermal runaway of lithium-ion batteries : a Gaussian process based global sensitivity analysis. Journal of Power Sources, 456. 228001. ISSN 0378-7753
Abstract
A particular safety issue with Lithium-ion (Li-ion) cells is thermal runaway (TR), which is the exothermic decomposition of cell components creating an uncontrollable temperature rise leading to fires and explosions. The modelling of TR is difficult due to the broad range of cell properties and potential conditions. Understanding the effect that thermophysical and heat transfer characteristics have on the TR abuse model output is essential to develop more accurate and robust TR models. This study uses global sensitivity analysis (GSA) to investigate the effect of the cell parameters on the outcome of TR events. Using a Gaussian Process (GP) surrogate model to calculate the Sobol’ indices, it is shown that the emissivity value is the dominant thermo-characteristic throughout the overall abuse scenario. Further analysis, investigating three key TR features shows the conductivity coefficient to be the most important with respect to the maximum temperature reached during TR. Results demonstrate that researchers can confidently estimate some thermo-characteristics but require accurate characterisation of the emissivity and conductivity coefficient to ensure robust predictions. Given the importance of battery technology to aid in global de-carbonisation, these findings are key to increasing their safe design and operation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier. This is an author produced version of a paper subsequently published in Journal of Power Sources. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Gaussian Process; Thermal Runaway; Sobol’ Indices; Global Sensitivity Analysis; Li-ion Cells |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council N/a |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Mar 2020 10:49 |
Last Modified: | 18 Mar 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.jpowsour.2020.228001 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158216 |