Quantifying Electrolyte Variation through Coupled Molecular Dynamics and Porous Electrode Modeling of Lithium-Ion Battery Cells

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Lithium-ion battery cell modeling using physics-based approaches such as porous electrode theory is a powerful tool for battery design and performance analysis both at the beginning and end of life[1]. Cell metrics such as resistance and thermal performance[2-6] can be quickly calculated in a pseudo-two-dimensional (P2D) framework. For engineering of electric vehicle batteries, speed and fidelity of electrochemical models is paramount in a competitive landscape. Physics-based models[7, 8] allow for high fidelity but require detailed knowledge of the cell component material properties. Acquiring these material characteristics typically requires time-consuming and expensive experiments limiting the ability to quickly screen through cell designs. One approach to circumvent costly experiments is to use molecular dynamics[9, 10] to calculate electrolyte transport properties. We demonstrate how cell modeling using simulated transport properties enables predictions of cell level metrics, allowing for experiment-free component screening. We also show how the variation in transport property predictions from molecular dynamics affects the final cell level performance predictions.