This paper examines the problem of estimating the parameters of a Lithium-Sulfur (LiS) battery from experimental cycling data. LiS batteries are attractive compared to traditional Lithium-Ion batteries, thanks largely to their potential to provide higher energy densities. The literature presents a number of different LiS battery models, with different fidelities and complexities. This includes both higher-fidelity diffusion-reaction models as well as "zero-dimensional" models that neglect diffusion dynamics while capturing the physics of the underlying reduction-oxidation reactions. The paper focuses on zero-dimensional LiS battery models, and develops four such models from the literature, reflecting different choices of which redox reactions to model. There is a growing need for using experimental cycling datasets to both parameterize these models and compare their fidelities. To address this need, we fabricated LiS coin cells and performed charge/discharge cycling tests on these cells. In parallel, we analyzed the sensitivity of simulated LiS battery charge/discharge characteristics to underlying model parameters. Using this sensitivity analysis, we selected a subset of model parameters for identification, and estimated these parameters for all four LiS battery models from cycling data, thereby arriving at a consistent experimental comparison and assessment of these models' respective fidelities.


Parameter Identification and Sensitivity Analysis for Zero-Dimensional Multi-Physics Lithium-Sulfur Battery Models

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

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