The Operation Dependence of C − N Fatigue for Lithium-Ion Batteries

Chen, C; Zou, Q; Wen, J; Liu, J; Notten, PHL; Wei, Y

The Operation Dependence of C − N Fatigue for Lithium-Ion Batteries

Chen, C Zou, Q Wen, J Liu, J Notten, PHL Wei, Y

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Publisher:: Wiley
Publication Type:: Journal Article
Citation:: Advanced Energy Materials, 2023, 13, (27)
Issue Date:: 2023-07-21

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Field	Value	Language
dc.contributor.author	Chen, C
dc.contributor.author	Zou, Q
dc.contributor.author	Wen, J
dc.contributor.author	Liu, J
dc.contributor.author	Notten, PHL
dc.contributor.author	Wei, Y
dc.date.accessioned	2024-02-29T00:34:00Z
dc.date.available	2024-02-29T00:34:00Z
dc.date.issued	2023-07-21
dc.identifier.citation	Advanced Energy Materials, 2023, 13, (27)
dc.identifier.issn	1614-6832
dc.identifier.issn	1614-6840
dc.identifier.uri	http://hdl.handle.net/10453/175952
dc.description.abstract	Lithium-ion batteries (LIBs) fatigue in repeated service, and their cycle-life, in resemblance to most materials subject to cyclic loading, scatters over a broad range. The dependence of critical fatigue parameters on ambient temperature and charging or discharging rate, along with the scattering nature of cycle-life is of practical significance. Through large-scale experimental investigations, it is shown how both temperatures and charging-discharging rates may influence critical parameters in the C − N fatigue dependence for LIBs. The cycle-life N of a battery subject to an average charging rate C follows C = c0 (T)Nb(D), where c0 varies with temperature T and b is a function of the discharging rate D. It is further shown that the cycle-life of LIBs follows a lognormal distribution. The revealed cycle-life distribution of LIBs and their fatigue law enable the construction of a probabilistic C − N model, which can be used to quantify the fatigue failure probability in LIBs. Results reported here are of compelling importance for the life-span evaluation and safety design of large-scale battery packing in electric vehicles and energy storage where tens of hundreds of batteries working in concert is desired.
dc.language	en
dc.publisher	Wiley
dc.relation.ispartof	Advanced Energy Materials
dc.relation.isbasedon	10.1002/aenm.202300942
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0303 Macromolecular and Materials Chemistry, 0912 Materials Engineering, 0915 Interdisciplinary Engineering
dc.subject.classification	3403 Macromolecular and materials chemistry
dc.subject.classification	4016 Materials engineering
dc.title	The Operation Dependence of C − N Fatigue for Lithium-Ion Batteries
dc.type	Journal Article
utslib.citation.volume	13
utslib.for	0303 Macromolecular and Materials Chemistry
utslib.for	0912 Materials Engineering
utslib.for	0915 Interdisciplinary Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2024-02-29T00:33:55Z
pubs.issue	27
pubs.publication-status	Published
pubs.volume	13
utslib.citation.issue	27

Abstract:

Lithium-ion batteries (LIBs) fatigue in repeated service, and their cycle-life, in resemblance to most materials subject to cyclic loading, scatters over a broad range. The dependence of critical fatigue parameters on ambient temperature and charging or discharging rate, along with the scattering nature of cycle-life is of practical significance. Through large-scale experimental investigations, it is shown how both temperatures and charging-discharging rates may influence critical parameters in the C − N fatigue dependence for LIBs. The cycle-life N of a battery subject to an average charging rate C follows C = c0 (T)Nb(D), where c0 varies with temperature T and b is a function of the discharging rate D. It is further shown that the cycle-life of LIBs follows a lognormal distribution. The revealed cycle-life distribution of LIBs and their fatigue law enable the construction of a probabilistic C − N model, which can be used to quantify the fatigue failure probability in LIBs. Results reported here are of compelling importance for the life-span evaluation and safety design of large-scale battery packing in electric vehicles and energy storage where tens of hundreds of batteries working in concert is desired.

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http://hdl.handle.net/10453/175952