Journal article
Asymptotic reduction and homogenization of a thermo-electrochemical model for a lithium-ion battery
- Abstract:
- In this study, matched asymptotic expansions are used to systematically reduce a thermo-electrochemical model of a lithium-ion battery based on volume averaging the electrode microstructure. In the cases with a constant or oscillating applied current, explicit asymptotic solutions of the full model can be obtained. In the case with a constant cell potential, the reduced model comprises a low-order differential-algebraic system. The asymptotic and numerical solutions of the volume-averaged model are compared with the numerical solutions of a thermal pseudo-two-dimensional (P2D) model, which treats the electrode as a collection of spherical particles. Excellent agreement is found between the models at (dis)charge rates up to 2C, and reasonable agreement is found at 4C. Homogenization is then used to derive a thermal model of a battery comprising several connected lithium-ion cells. We derive a closed-form solution to the homogenized model when the effective Biot number is small, which corresponds to a spatially uniform battery temperature. By comparing simulation times, we show that the asymptotically reduced and homogenized models provide substantial computational savings compared with the full numerical simulations, thereby making them ideal for use in onboard thermal management systems. We also show that thermal runaway does not occur in the model, despite accounting for the Arrhenius dependence of the reaction coefficients.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 3.1MB, Terms of use)
-
- Publisher copy:
- 10.1016/j.apm.2019.11.018
Authors
- Publisher:
- Elsevier
- Journal:
- Applied Mathematical Modelling More from this journal
- Volume:
- 80
- Pages:
- 724-754
- Publication date:
- 2019-11-17
- Acceptance date:
- 2019-11-13
- DOI:
- ISSN:
-
0307-904X
- Language:
-
English
- Keywords:
- Pubs id:
-
pubs:1071552
- UUID:
-
uuid:b7ed3427-9607-497e-bb1f-cb7b7edd4530
- Local pid:
-
pubs:1071552
- Source identifiers:
-
1071552
- Deposit date:
-
2019-11-13
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Inc
- Copyright date:
- 2019
- Rights statement:
- Copyright © 2019 Elsevier Inc.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Elsevier at https://doi.org/10.1016/j.apm.2019.11.018
If you are the owner of this record, you can report an update to it here: Report update to this record