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Lithium-ion battery electrodes exhibit complex interplay among multiple electrochemically coupled transport processes, which rely on the underlying functionality and relative arrangement of different constituent phases. The electrochemically inactive solid phases (e.g., conductive additive and binder, referred to as the secondary phase), while beneficial for improved electronic conductivity and mechanical integrity, may partially block the electrochemically active sites and introduce additional transport resistances in the pore (electrolyte) phase. In this work, the role of mesoscale interactions and inherent stochasticity in porous electrodes is elucidated in the context of short-range (interface) and long-range (transport) characteristics. The electrode microstructure significantly affects kinetically and transport-limiting scenarios and thereby the cell performance. The secondary-phase morphology is also found to strongly influence the microstructure-transport-kinetics interactions. Apropos, strategies have been proposed for performance improvement via electrode microstructural modifications.

Battery performance is strongly correlated with electrode microstructural properties. Of the relevant properties, the tortuosity factor of the electrolyte transport paths through microstructure pores is important as it limits battery maximum charge/discharge rate, particularly for energy-dense thick electrodes. Tortuosity factor however, is difficult to precisely measure, and thus its estimation has been debated frequently in the literature. Herein, three independent approaches have been applied to quantify the tortuosity factor of lithium-ion battery electrodes. The first approach is a microstructure model based on three-dimensional geometries from X-ray computed tomography (CT) and stochastic reconstructions enhanced with computationally generated carbon/binder domain (CBD), as CT is often unable to resolve the CBD. The second approach uses a macro-homogeneous model to fit electrochemical data at several rates, providing a separate estimation of the tortuosity factor. The third approach experimentally measures tortuosity factor via symmetric cells employing a blocking electrolyte. Comparisons have been made across the three approaches for 14 graphite and nickel-manganese-cobalt oxide electrodes. Analysis suggests that if the tortuosity factor were characterized based on the active material skeleton only, the actual tortuosities would be 1.35-1.81 times higher for calendered electrodes. Correlations are provided for varying porosity, CBD phase interfacial arrangement and solid particle morphology.

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To improve electric vehicle market acceptance, the charge time of their batteries should be reduced to 10-15 minutes. However, achieving 4C to 6C charge rates with today's batteries is only possible for cells with thin electrodes coming at the expense of low energy density and high battery manufacturing cost. An electrochemical model is validated versus high rate charge data for cells with several loadings. The model elucidates that the main limitations for high energy density cells are poor electrolyte transport resulting in salt depletion within the anode and Li plating at the graphite/separator interface. Next, the model is used to understand what future electrode and electrolyte properties can help enable 4C and 6C charging. Ideally, future electrolytes would be identified with 2X conductivity, 3-4X diffusivity, and transference number of 0.5-0.6. Alternatively charging at elevated temperatures enhances electrolyte transport by 1.5X conductivity and 2-3X diffusivity with a negligible effect on transference number. Another effective strategy to enable 4C and 6C charging is reducing electrode tortuosity. Conversely, increasing electrode porosity and negative/positive ratio are ineffective strategies to improve fast charge capability.

This paper presents a general multi-scale multi-physics lithium-ion battery model framework, the Multi-Scale Multi-Dimensional model. The model introduces multiple coupled computational domains to resolve the interplay of lithium-ion battery physics in varied length scales. Model geometry decoupling and domain separation for the physicochemical process interplay are valid where the characteristic time or length scale is segregated. Assuming statistical homogeneity for repeated architectures typical of lithium-ion battery devices is often adequate and effective for modeling submodel geometries and physics in each domain. The modularized hierarchical architecture of the model provides a flexible and expandable framework facilitating modeling of the multiphysics behavior of lithium-ion battery systems. In this paper, the Multi-Scale Multi-Dimensional model is introduced and applied to a model analysis that resolves electrochemical-, electrical-, and thermal-coupled physics in large-format stacked prismatic cell designs.

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