Lithium-Sulfur batteries are part of the next generation of beyond Li-ion technologies currently under development. These batteries have nearly 10 times higher theoretical specific energy density than Li-ion and are composed of materials which are less environmentally harmful. However, a complete understanding of Li-S batteries has not been achieved.
Physics-based cell-level models of Li-S batteries precisely codify our leading hypotheses for the underlying mechanisms of these highly complex batteries. The simulation of such models allows for quantitative tests of these hypotheses and therefore can be directly incorporated into the development cycle of Li-S technology. Moreover, quantitatively accurate models can be used to help optimize design parameters as well as to be incorporated into battery management systems. However, the Li-S modelling community is still attempting to create models which both quantitatively capture experimental data to which the model is fit as well as to obtain quantitative predictions for out-of-sample data.
In this talk, a physics-based cell-level one-dimensional model for Lithium-Sulfur batteries is proposed. This model advances our previous minimal zero-dimensional model which yielded accurate quantitative predictions of experimental voltage and resistance data. A comparison is made between the zero- and one-dimensional models to illustrate the effects of spatial variations within the cell. Compared to alternative models in the literature, this novel one-dimensional model has been formulated to reduce over-fitting of experimental data through minimizing the complexity by including only the necessary features.
The models discussed have been developed using PyBaMM and will be made open access shortly.