@misc{92dc5d84dd6642409f904a0d3fb58e1b,
title = "Image-Based Failure Assessment of Li-Ion Batteries",
abstract = "In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.",
keywords = "image-based modeling, Li-ion batteries, meshfree methods, multiphysics modeling, reproducing kernel particle method",
author = "Kristen Susuki and Chen, {J. S.} and Jeff Allen",
year = "2024",
language = "American English",
series = "Presented at the American Society for Composites 39th Annual Technical Conference, 21-24 October 2024, San Diego, California",
type = "Other",
}