Researchers from Uppsala University have developed an AI model that shows an accurate picture of how electric vehicle batteries age and degrade over time.
This comes as the electrification of the transport sector is slowing down due to the fast wearing of electric vehicle batteries.
The new model could lead to longer life and enhanced safety for these batteries and enable a quicker electric transition.
Professor Daniel Brandell, who led the study and oversees the Ångström Advanced Battery Centre at Uppsala University, explained: “Being able to learn more about the life and ageing of batteries will benefit future control systems in electric vehicles. 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.”
EV batteries are the first components to age
It’s not uncommon for batteries in electric cars to be the first component of the vehicle to age. This is a major waste of resources today and is holding back the transformation of the transport sector.
Over time, lithium-ion batteries, the most common type used in EVs, gradually lose their ability to hold a full charge. Several factors, including charge/discharge cycles, high temperatures, fast charging, and the depth of discharge influence this degradation.
Typically, an EV battery may lose around 2–3% of its capacity per year, although rates can vary. After 8–10 years of regular use, an EV battery might retain 70–80% of its original capacity. While this often still allows the vehicle to function, it may reduce driving range.
To address this issue, the automotive industry is developing software, often based on AI, to optimise battery management and control.
The model created by Uppsala University can increase the robustness of battery health predictions by up to 70%.
Mapping the battery cycle life
Several years of battery testing are behind the study, carried out in collaboration with Aalborg University in Denmark.
A database was built up by collecting data from numerous very short charging segments. This was then combined with a detailed model of all the different chemical processes taking place inside electric vehicle batteries.
“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,” commented Wendi Guo, who conducted the study.
Reducing the need for sensitive vehicle data
The discovery could also address the safety of electric vehicle batteries. The safety problems that can occur in the battery are often due to design flaws and side reactions, which can also be predicted by studying data from the battery’s charging and discharging.
Brandell concluded: “The fact that we only use short charging segments is probably an added advantage. Battery data from electric vehicles is sensitive, both for the industry and from an anonymisation point of view for users.
“This research shows how far you can get without needing complete datasets.”