Battery modelling – Why ‘physics-based’ is not always best

Abstract

Models are essential for engineering efficient systems both quickly and cost-effectively. They focus the mind on what’s important and inform where our precious testing resources should be allocated. Batteries are complex, with behaviours covering a wide range of length-scales and timescales; yet a strong understanding of them pays dividends at all stages of the value chain, from materials R&D, to manufacturing, optimal control, reuse, and recycling. But what does understanding truly mean when it comes to battery modelling to address real-world problems? The academic ‘Physics-based’ battery modelling landscape is highly derivative in nature. As industry looks to apply this research, it can be tempting to be led down a rabbit hole of ever-increasing depth while progressively losing touch with reality; overwhelmed by an information overload, one can lose track of what’s important, and forget the caveats and assumptions made along the way. In the words of Douglas Adams, “the most misleading assumptions are the ones you don’t even know that you are making”; these cautionary words of warning are especially pertinent to battery modellers. It’s time to take a step back, and ask ourselves What questions are we trying to answer?, and How should we best equip ourselves to answer them’?. To coin a phrase ‘all models are wrong, but some are useful’, the goal of battery models is to empower battery developers & and operators to make more grounded decisions in managing...