Physics-Informed Optimal Experiment Design of Calendar Aging Tests and Sensitivity Analysis for SEI Parameters Estimation in Lithium-ion Batteries

Abstract

This paper focuses on sensitivity analysis and optimal experiment design for calendar aging tests to find SEI (solid-electrolyte interface) degradation parameters. This parameterization facilitates predicting the Li-ion battery end-of-life. To this end, a physics-based model of SEI layer is used to develop a closed form solution for loss of Lithium inventory during calendar aging. This model is shown to match experimental data. Further, the developed model is used to find the sensitivity of LLI (loss of Lithium inventory) to SEI parameters in diffusion-limited and kinetically limited SEI patterns.Through this sensitivity analysis, we show that in the kinetically limited case, performing calendar aging tests at high SOCs gives the most accurate results. For the diffusion limited case, we use optimal experiment design techniques to find the optimal calendar aging SOCs. It is also shown that, these optimal SOC values result in higher accuracy estimations compared to sub-optimal SOCs.