The use of high-capacity, thick electrodes for energy-dense lithium ion cells is limited by poor material utilization, especially in high-rate scenarios. This is primarily due to high resistances to Li-ion transport arising from the length scales and tortuosity in thick porous electrodes.^1,2 Novel electrode architectures can be engineered to reduce overall transport limitations by creating additional pathways for lithium ion diffusion and migration (Fig.1). These architectures consist of the active material distributed in such a way as to enable higher overall ion fluxes and intercalation rates, ensuring higher active material utilization than would be possible with the same amount of active material in a conventional homogeneous distribution.^1,2

Since the design of these architectures is essentially a problem of improving ion transport, the macro-homogeneous electrochemical models of Newman and coworkers (pseudo-3D models) are widely used to study the relationship between electrode architectures and electrochemical performance .⁴ Studies have mainly focused on two-dimensional (2D) simulations of the effect of specific geometric parameters such as pillar widths, heights, and aspect ratios.^1,3,5,6 While these studies provide useful insights, they are limited to a given set of battery chemistry parameters. Any change in electrode chemistry or material properties will entail repeating the entire analysis, often using detailed finite-element simulations, which can be extremely computationally expensive. ³

The purpose of this work is therefore to develop a 2D Li-ion cell model capable of simulating novel electrode architectures in a computationally efficient manner. We use the governing equations of the pseudo-3D model. Orthogonal collocation techniques used in past work will be adapted to enable fast solution of the model equations.⁷ Comparisons with finite-element simulations will be presented to demonstrate the accuracy and computational performance of the new 2D cell model. The fast simulation is then used to evaluate certain representative architectures by iterating through a parameter space that includes electrode and electrolyte properties in addition to geometric parameters. The performance of these architectures will be reported in terms of metrics relating to discharge performance, ion concentration profiles, and material utilization trends. The computationally fast simulation can potentially provide greater flexibility by enabling access to a larger parameter space, and by permitting the evaluation of a larger number of designs than would be possible by conventional simulations of parametric variations. The fast simulation is also envisaged to be integrated into optimization algorithms in future work.

Acknowledgements

The authors are thankful for financial support by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U.S. Department of Energy through the Advanced Battery Materials Research (BMR) Program (Battery500 Consortium).

References

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