Lithium-ion battery degradation: how to model it
File(s)
Accepted version
Supporting information
Author(s)
Type
Working Paper
Abstract
Predicting lithium-ion battery degradation is worth billions to the global
automotive, aviation and energy storage industries, to improve performance and
safety and reduce warranty liabilities. However, very few published models of
battery degradation explicitly consider the interactions between more than two
degradation mechanisms, and none do so within a single electrode. In this
paper, the first published attempt to directly couple more than two degradation
mechanisms in the negative electrode is reported. The results are used to map
different pathways through the complicated path dependent and non-linear
degradation space. Four degradation mechanisms are coupled in PyBaMM, an open
source modelling environment uniquely developed to allow new physics to be
implemented and explored quickly and easily. Crucially it is possible to see
'inside' the model and observe the consequences of the different patterns of
degradation, such as loss of lithium inventory and loss of active material. For
the same cell, five different pathways that can result in end-of-life have
already been found, depending on how the cell is used. Such information would
enable a product designer to either extend life or predict life based upon the
usage pattern. However, parameterization of the degradation models remains as a
major challenge, and requires the attention of the international battery
community.
automotive, aviation and energy storage industries, to improve performance and
safety and reduce warranty liabilities. However, very few published models of
battery degradation explicitly consider the interactions between more than two
degradation mechanisms, and none do so within a single electrode. In this
paper, the first published attempt to directly couple more than two degradation
mechanisms in the negative electrode is reported. The results are used to map
different pathways through the complicated path dependent and non-linear
degradation space. Four degradation mechanisms are coupled in PyBaMM, an open
source modelling environment uniquely developed to allow new physics to be
implemented and explored quickly and easily. Crucially it is possible to see
'inside' the model and observe the consequences of the different patterns of
degradation, such as loss of lithium inventory and loss of active material. For
the same cell, five different pathways that can result in end-of-life have
already been found, depending on how the cell is used. Such information would
enable a product designer to either extend life or predict life based upon the
usage pattern. However, parameterization of the degradation models remains as a
major challenge, and requires the attention of the international battery
community.
Date Issued
2022-03-08
Citation
2022
ISSN
1463-9076
Publisher
Royal Society of Chemistry
Copyright Statement
©2022 The Author(s)
Sponsor
The Faraday Institution
Identifier
http://arxiv.org/abs/2112.02037v2
Grant Number
FIRG025
Subjects
physics.chem-ph
physics.chem-ph
physics.app-ph
Notes
First version submitted to Energy and Environmental Science on 15th November 2021. Second version submitted to Physical Chemistry: Chemical Physics on 25th January 2022
Publication Status
Published