DandeLiion v1: An extremely fast solver for the Newman model of lithium-ion battery (dis)charge
DandeLiion v1: An extremely fast solver for the Newman model of lithium-ion battery (dis)charge
DandeLiion (available at dandeliion.com) is a robust and extremely fast solver for the Doyle Fuller Newman (DFN) model, the standard electrochemical model for (dis)charge of a planar lithium-ion cell. DandeLiion conserves lithium, uses a second order spatial discretisation method (enabling accurate computations using relatively coarse discretisations) and is many times faster than its competitors. The code can be used "in the cloud"and does not require installation before use. The difference in compute time between DandeLiion and its commercial counterparts is roughly a factor of 100 for the moderately-sized test case of the discharge of a single cell. Its linear scaling property means that the disparity in performance is even more pronounced for bigger systems, making it particularly suitable for applications involving multiple coupled cells. The model is characterised by a number of phenomenological parameters and functions, which may either be provided by the user or chosen from DandeLiion's library. This library contains data for the most commonly used electrolyte (LiPF6) and a number of common active material chemistries including graphite, lithium iron phosphate (LFP), nickel cobalt aluminum (NCA), and a variant of nickel cobalt manganese (NMC).
Lithium-ion battery, Newman model, P2D model, Porous Electrode Theory, Stiff systems, Solver, Simulation engine, Finite Elements
Korotkin, Ivan
1ca96363-075e-41d9-a0c1-153c8c0cc31a
Sahu, Smita
42f2e875-624b-4c88-b960-9da5070ca63b
O'Kane, Simon
32fb9f47-9021-449f-aad8-702fb00744f0
Richardson, Giles
3fd8e08f-e615-42bb-a1ff-3346c5847b91
Foster, Jamie M
0786436b-150f-4b67-bd8c-126dbfce76bb
24 June 2021
Korotkin, Ivan
1ca96363-075e-41d9-a0c1-153c8c0cc31a
Sahu, Smita
42f2e875-624b-4c88-b960-9da5070ca63b
O'Kane, Simon
32fb9f47-9021-449f-aad8-702fb00744f0
Richardson, Giles
3fd8e08f-e615-42bb-a1ff-3346c5847b91
Foster, Jamie M
0786436b-150f-4b67-bd8c-126dbfce76bb
Korotkin, Ivan, Sahu, Smita, O'Kane, Simon, Richardson, Giles and Foster, Jamie M
(2021)
DandeLiion v1: An extremely fast solver for the Newman model of lithium-ion battery (dis)charge.
Journal of the Electrochemical Society, 168 (6), [060544].
(doi:10.1149/1945-7111/ac085f).
Abstract
DandeLiion (available at dandeliion.com) is a robust and extremely fast solver for the Doyle Fuller Newman (DFN) model, the standard electrochemical model for (dis)charge of a planar lithium-ion cell. DandeLiion conserves lithium, uses a second order spatial discretisation method (enabling accurate computations using relatively coarse discretisations) and is many times faster than its competitors. The code can be used "in the cloud"and does not require installation before use. The difference in compute time between DandeLiion and its commercial counterparts is roughly a factor of 100 for the moderately-sized test case of the discharge of a single cell. Its linear scaling property means that the disparity in performance is even more pronounced for bigger systems, making it particularly suitable for applications involving multiple coupled cells. The model is characterised by a number of phenomenological parameters and functions, which may either be provided by the user or chosen from DandeLiion's library. This library contains data for the most commonly used electrolyte (LiPF6) and a number of common active material chemistries including graphite, lithium iron phosphate (LFP), nickel cobalt aluminum (NCA), and a variant of nickel cobalt manganese (NMC).
Text
DandeLiion_v1.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 28 May 2021
Published date: 24 June 2021
Additional Information:
Publisher Copyright:
© 2021 The Electrochemical Society.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Keywords:
Lithium-ion battery, Newman model, P2D model, Porous Electrode Theory, Stiff systems, Solver, Simulation engine, Finite Elements
Identifiers
Local EPrints ID: 450063
URI: http://eprints.soton.ac.uk/id/eprint/450063
ISSN: 0013-4651
PURE UUID: 1389d3b8-7323-4d65-8ce8-b3d53c18bd90
Catalogue record
Date deposited: 07 Jul 2021 16:31
Last modified: 17 Mar 2024 03:54
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Contributors
Author:
Smita Sahu
Author:
Simon O'Kane
Author:
Jamie M Foster
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