The importance of reducing CO \(_2\) , NO \(_x\) and particulate emissions in mitigating climate change and improving human health is well-known and often stated. Widespread phasing out of vehicles with traditional combustion engines, and replacement with electric vehicles (EVs) is a key step towards achieving a low-carbon economy. Lithium-ion batteries are presently the key technology powering EVs, however, improved performance is highly desirable and would lead to an increase in the rate of EV adoption. Battery development costs can be significantly reduced by robust predictive models, allowing new device designs to be tested in-silico without costly and time-consuming physical prototyping. Here, we describe how physics-based battery models have been used to help the industrial sector develop high-performance batteries.