Existing battery modeling works have limitations in addressing the dependence of transport properties on local field variations and characterizing the response of anisotropic media. These limitations are tackled by means of a nested finite element (FE²) multiscale framework in which microscale simulations are employed to comprehensively characterize an anisotropic medium (macroscale). The approach is applied to the numerical simulation of transport processes in lithium ion battery separators. From the microscale solution, homogenized fluxes and their dependence on the downscaled macroscale variables are upscaled, thereby replacing otherwise assumed macroscale constitutive laws. The tensorial nature of macroscale effective transport properties stems from the numerical treatment. The proposed approach is verified against full-scale simulations. Several numerical examples are used to demonstrate the perils associated with accepted procedures, leading in some cases to severe discrepancies in the prediction of field quantities (from differences in the potential drop across the separator of about 27% for a fixed microstructure to more than 100% in the case of an evolving microstructure). Despite the use of simplified assumptions (e.g., synthetic microstructures), the numerical results demonstrate the importance of a tensorial description of transport properties in the modeling of battery processes.

This study presents a three-dimensional computational model to evaluate effective conductivity and capacity of fiber-based battery electrodes. We employ electrodes composed of conductive and active material nanofibers dispersed in an electrolyte matrix. The effective conductivity is calculated by means of an equivalent resistor network model, while capacity evaluation is based on the identification of active material fibers that are accessible to electrons (i.e., those connected with the electronically conductive network). When a constraint is applied to the total fiber content, an optimal active-conductive material ratio is determined that maximizes the active material utilization and the electrode capacity. We also study fiber orientation effects on the electrode electrochemical properties. It is found that fiber orientation has a strong impact on the percolation threshold, and this impact also reflects on the active material utilization: the more the fiber orientation deviates from the ideal isotropic distribution, the lower the utilization of active material fibers. This is of special interest for practical applications where geometrical constraints on fiber orientation arise, as in the case of electrospun fibers deposited on a substrate. The results of this study are therefore meant to give an insight into how a fibrous electrode architecture performs and suggest effective design solutions.

A fully coupled model for mass and heat transport, mechanics, and chemical reactions with trapping is proposed. It is rooted in non-equilibrium rational thermodynamics and assumes that displacements and strains are small. Balance laws for mass, linear and angular momentum, energy, and entropy are stated. Thermodynamic restrictions are identified, based on an additive strain decomposition and on the definition of the Helmholtz free energy. Constitutive theory and chemical kinetics are studied in order to finally write the governing equations for the multi-physics problem. The field equations are solved numerically with the finite element method, stemming from a three-fields variational formulation. Three case-studies on vacancies redistribution in metals, hydrogen embrittlement, and the charge–discharge of active particles in Li-ion batteries demonstrate the features and the potential of the proposed model.

This review focuses on energy storage materials modeling, with particular emphasis on Li-ion batteries. Theoretical and computational analyses not only provide a better understanding of the intimate behavior of actual batteries under operational and extreme conditions, but they may tailor new materials and shape new architectures in a complementary way to experimental approaches. Modeling can therefore play a very valuable role in the design and lifetime prediction of energy storage materials and devices. Batteries are inherently multi-scale, in space and time. The macro-structural characteristic lengths (the thickness of a single cell, for instance) are order of magnitudes larger than the particles that form the microstructure of the porous electrodes, which in turn are scale-separated from interface layers at which atomistic intercalations occur. Multi-physics modeling concepts, methodologies, and simulations at different scales, as well as scale transition strategies proposed in the recent literature are here revised. Finally, computational challenges toward the next generation of Li-ion batteries are discussed.