A team at Uppsala University has developed a new AI model that significantly improves predictions of battery ageing, offering a potential breakthrough in electric vehicle (EV) performance and safety.
The model, which increases the robustness of battery health forecasts by up to 70%, could help extend battery life and reduce safety risks – key barriers to wider EV adoption.
“Being able to learn more about the life and ageing of batteries will benefit future control systems in electric vehicles,” said Professor Daniel Brandell, who led the study at the Ångström Advanced Battery Centre. “It also shows how important it is to understand what happens inside the batteries. If we stop looking at them as black boxes that are simply expected to provide power, and instead acquire a detailed picture of the processes, we can manage them so that they stay in good condition longer,”
The research, conducted in collaboration with Aalborg University, involved several years of battery testing and the creation of a database using short charging segments. These were combined with a detailed model of internal chemical reactions to map battery degradation.
“Altogether, this gives us a very precise picture of the various chemical reactions that result in the battery generating power, but also of how it ages during use,” said researcher Wendi Guo.
By relying on short charging data, the model reduces the need for sensitive vehicle datasets, offering a privacy-conscious approach to battery diagnostics. “This research shows how far you can get without needing complete datasets,” added Brandell.
Image: Wendi Guo and Daniel Brandell have developed the model that makes it possible to better understand what happens inside batteries. Credit: Mikkel Lønsman Hukiær/Tobias Sterner, Bildbyrån
