Couto, L.D., Drummond, R. orcid.org/0000-0002-2586-1718, Zhang, D. et al. (2 more authors) (2022) Identifiability of lithium-ion battery electrolyte dynamics. In: 2022 American Control Conference (ACC) Proceedings. 2022 American Control Conference (ACC), 08-10 Jun 2022, Atlanta, GA, USA. Institute of Electrical and Electronics Engineers (IEEE) , pp. 1087-1093. ISBN 9781665494809
Abstract
The growing need for improved battery fast charging algorithms and management systems is pushing forward the development of high-fidelity electrochemical models of cells. Critical to the accuracy of these models is their parameterisation, however this challenge remains unresolved, both in terms of theoretical analysis and practical implementation. This paper develops a framework to analyse from impedance measurements the identifiability of electrolyte dynamics—a subcomponent of a general Li-ion model that is key to enabling accurate fast charging simulations. By assuming that the electrolyte volume fractions in the electrode and separator regions are equal, an analytic expression for the impedance function of the electrolyte dynamics is obtained, and this can be tested for structural identifiability. It is shown that the only parameters of the electrolyte model that may be identified are the diffusion time scale and a geometric coupling parameter. Simulations highlight the identifiability issues of electrolyte dynamics (relating to symmetric cells) and explain how the electrolyte parameters might be identified.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 AACC. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Lithium-ion batteries; Electrodes; Analytical models; Impedance measurement; Parameter estimation; Particle separators; Electrolytes |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering |
Funding Information: | Funder Grant number ROYAL ACADEMY OF ENGINEERING (THE) ICRF\113 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jan 2025 14:38 |
Last Modified: | 17 Jan 2025 14:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.23919/acc53348.2022.9867154 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:221808 |