EV batteries could offer longer lifespan, higher safety with new tech

Researchers at Uppsala University have developed an AI-driven model that significantly enhances the accuracy and robustness of electric vehicle (EV) battery health and lifetime predictions, improving these metrics by up to 65% and 69%, respectively. The model leverages a machine learning framework built on a digital twin approach, which integrates key design parameters with real-world battery behaviors under various fast charging and discharge conditions typical of Nordic climates. This framework enables rapid health assessments within seconds by inferring six critical design parameters from short charging segments, offering a detailed understanding of the chemical processes inside lithium-ion batteries (LiBs) and their aging mechanisms. The study, conducted in collaboration with Aalborg University and published in the journal Energy and Environmental Science, addresses the persistent challenge of EV battery degradation that limits battery lifespan and slows the electrification of transport. By moving beyond treating batteries as “black boxes” and instead modeling their internal chemical reactions, the new approach allows for better battery management and control systems that can extend battery life and improve