Título Numerical Analysis of Degradation and Capacity Loss in Graphite Active Particles of Li-Ion Battery Anodes
Publicación externa No
Medio Materials
Alcance Article
Naturaleza Científica
Cuartil JCR 2
Cuartil SJR 2
Impacto JCR 3.40000
Impacto SJR 0.56300
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131740016&doi=10.3390%2fma15113979&partnerID=40&md5=bd8705c44f7d420659410b35582c852d
Fecha de publicacion 01/06/2022
ISI 808748800001
Scopus Id 2-s2.0-85131740016
DOI 10.3390/ma15113979
Abstract It is well known that the performance and durability of lithium-ion batteries (LIBs) can be severely impaired by fracture events that originate in stresses due to Li ion diffusion in fast charge-discharge cycles. Existing models of battery damage overlook either the role of particle shape in stress concentration, the effect of material disorder and preexisting defects in crack initiation and propagation, or both. In this work we present a novel, three-dimensional, and coupled diffusive-mechanical numerical model that simultaneously accounts for all these phenomena by means of (i) a random particle generator and (ii) a stochastic description of material properties implemented within the lattice method framework. Our model displays the same complex fracture patterns that are found experimentally, including crack nucleation, growth, and branching. Interestingly, we show that irregularly shaped active particles can suffer mechanical damage up to 60% higher than that of otherwise equivalent spherical particles, while material defects can lead to damage increments of up to 110%. An evaluation of fracture effects in local Li-ion diffusivity shows that effective diffusion can be reduced up to 25% at the particle core due to lithiation, while it remains at ca. 5% below the undamaged value at the particle surface during delithiation. Using a simple estimate of capacity loss, we also show that the C-rate has a nonlinear effect on battery degradation, and the estimated capacity loss can surpass 10% at a 2C charging rate.
Palabras clave Li-ion battery; active particles; graphite; capacity loss; modeling
Miembros de la Universidad Loyola

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