Numerical simulations are an important corner stone for the development of lithium-ion batteries as they can save expenses in time and cost for a large number of series of experiments. Empirical models have the advantage of a fast development and a low computational effort, but their predictions are only valid within the range of experimental data used for fitting. In contrast, physically-based models allow a deeper understanding and increase the applicability to different scenarios and the credibility of the model predictions.

We present a multi-scale modelling approach coupling a 1D thermal cell-level (macro-scale) model, a 1D electrode-pair level (micro-scale) model, and a 1D particle-level (nano-scale) model (Figure 1) ¹. A particular feature of the model is detailed electrochemistry, capturing multi-step main and side reactions occurring during ageing or thermal runaway. The model is parametrized to commercial lithium iron phosphate cells. We assume solid electrolyte interphase (SEI) formation at the anode as dominant aging mechanism, which is known to be the main contributor to calendaric aging ². By capturing the nonlinear feedback between electrochemistry and transport, the model is able to simulate cell behavior not only within recommended operating conditions, but also during cell abuse, for example, due to external short circuit, and during long-time operation.

Simulations of short time (external short circuit) and long time (lifetime estimation) scenarios are presented (Figure 2,3). These different events are compared and interpreted, for example in terms of reaction limitation or transport limitation. The sensitivity and reassessment of the model parameter is discussed, and the model as a comprehensive copy of the real battery is verified. Thereby insights into the battery which are experimentally hard to obtain, like concentration and temperature gradients or the distribution of lithium in the active material (Figure 4), are more justified than before.

References

1. C. Kupper and W. G. Bessler, J. Electrochem. Soc., 164(2), A304-A320 (2017).

2. H. Zheng, L. Tan, L. Zhang, Q. Qu, Z. Wan, Y. Wang, M. Shen and H. Zheng, Electrochim. Acta, 173, 323–330 (2015).