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Electrochimica Acta
Article . 2021 . Peer-reviewed
License: CC BY
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Electrochimica Acta
Article
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https://dx.doi.org/10.48550/ar...
Article . 2020
License: arXiv Non-Exclusive Distribution
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Systematic derivation and validation of a reduced thermal-electrochemical model for lithium-ion batteries using asymptotic methods

Authors: Ferran Brosa Planella; Muhammad Sheikh; W. Dhammika Widanage;

Systematic derivation and validation of a reduced thermal-electrochemical model for lithium-ion batteries using asymptotic methods

Abstract

The widely used Doyler-Fuller-Newman (DFN) model for lithium-ion batteries is too computationally expensive for certain applications, which has motivated the appearance of a plethora of simpler models. These models are usually posed in an ad hoc manner, leading to inconsistencies with the DFN model and to multiple formulations of the same model, with the Single Particle Model (SPM) being a very good example of the latter. In this work, we discuss the concept of SPM-type models showing that, despite the multiple formulations found in the literature, these models always follow the same structure, and we extend this discussion to models accounting for thermal effects. Then, we present a Thermal Single Particle Model with electrolyte (TSPMe) derived in a systematic manner using asymptotic techniques. The validation of the TSPMe against a thermal DFN model shows very high accuracy with a computational cost over forty times smaller. The comparison against experimental data shows that the model does a reasonable job predicting the behaviour of a real battery, but a very good parameter set is required to obtain accurate predictions.

Accepted version to Electrochimca Acta, 27 pages, 13 pages of appendix, 12 figures

Keywords

Chemical Physics (physics.chem-ph), TK, Physics - Chemical Physics, FOS: Physical sciences, Computational Physics (physics.comp-ph), Physics - Computational Physics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Top 1%
Green
hybrid