Compared to combustion engine cars, electric cars often present drivers with unfamiliar challenges. Many people are still unfamiliar with managing them, making it especially challenging to gauge how far the current charge level will take them. This uncertainty significantly contributes to what’s known as “range anxiety”.
Electric Car: New Technology Against Range Anxiety
While typical battery management systems in electric cars display a state of charge in percent, many drivers don’t know how much range is remaining behind hidden that value. That’s why researchers at the University of California have now developed a model called State of Mission (SOM) that is designed to calculate this precisely.
The model is based on artificial intelligence (AI) and was presented by the team a few days ago in the journal iScience. The special feature of the system is that it doesn’t just provide simple battery status data or generalized range estimates. Instead, SOM integrates a deep understanding of both the physical state of the battery and the complexity of the operating environment, as Bioengineer.org reports.
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“A Forward-Looking Tool”
This means the system can calculate, for example, whether the electric car can handle a 100-mile drive through hilly terrain on its current battery level, even with energy-intensive systems like the heating running. The algorithm also incorporates factors such as traffic dynamics, elevation profiles, and ambient temperature fluctuations.
This is a groundbreaking difference from previous charge level indicators. The researchers hope that their new electric car technology can also gain a foothold in other areas. In the study, they write that their development offers “a forward-looking tool for next-generation battery management systems in electric vehicles, aerial systems, and grid storage”.
Sources: Bioengineer.org, “State of mission: Battery management with neural networks and electrochemical AI” (iScience 2025)
This article was translated with the help of AI and carefully reviewed by our editorial team.