As the year comes to an end, it is a good time to pause and reflect on the Ionworks journey so far. It has been a very special year for us: we incorporated in February and this first year has been full of learning, collaboration and growth.

One of the main challenges in physics-based modelling of batteries, as discussed in our previous blog post, is parameterisation. Parameterisation requires a broad range of experiments to be run and the resulting data to be carefully analysed, which makes it an extremely time and resource intensive process. But why is that?

In the past few blogposts we have seen what physics-based models for batteries are about. However, not everything is done and dusted in this area. The aim of this post is to discuss the current main challenges (or what we believe are the main challenges) for physics-based models.

We learned in our previous blog post that physics-based battery models typically impose conservation of lithium and charge in both the electrode and the electrolyte, but we did not discuss specific models. The focus of this post is on two of the most popular models: the Doyle-Fuller-Newman (DFN) and the Single Particle Model (SPM).

In our last blog post, we introduced what physics-based models and discussed their strengths in a general context. Now, let's narrow our focus and explore how these models specifically apply to lithium-ion batteries.

Physics-based models for lithium-ion batteries are quite popular these days, and they have literally seen an exponential growth in the past decades. According to Google Scholar results, the number of articles published each year (since 2000) matching the search «"physics-based" model "lithium" battery» have been doubling every 3.3 years. But what are physics-based models?