Whats happened? Engineers at the University of California, Riverside (UCR) have developed a new, smarter method to estimate the expected performance of a lithium-ion battery for a specific task under dynamic, real-world conditions a breakthrough that could significantly alleviate EV battery anxiety.

They call it State of Mission (SOM). While traditional battery indicators display the amount of charge left in the battery as a percentage, SOM is different (via the iScience journal). The metric predicts whether a battery can reliably and safely complete a specific real-world task. It combines physics-based electrochemical and thermodynamic principles with machine learning to factor in driving variables such as elevation, environmental temperature, traffic, and driving style.

Why is this important? The researchers have tested SOM with NASA and Oxford datasets, and it has proven proficient at reducing prediction errors related to battery voltage, temperature, and the current state of charge.

By factoring in all the variables that affect a battery and its operation in real-time, SOM has the potential to outperform conventional battery management systems. Recommended Videos Why should I care? The technology will eliminate the guesswork associated with operating battery-driven systems, such as driving electric vehicles, flying battery-operated drones, or home-inverter setups for solar panels.

For instance, SOM can help you determine whether your electric vehicle can drive 50 miles uphill with its current state of charge, whereas the traditional system provides a percentage-based range. If youre an EV owner, SOM can practically revolutionize your travel planning with realistic and trip-specific range predictions. OK, whats next? Given that SOM uses a hybrid model that combines traditional calculation with environmental conditions and machine learning, it requires much more processing power than what lightweight battery management systems currently offer.

The team at UCR is working to optimize the SOM performance so that it can work with electric vehicles, drones, and other grid applications, but real-world deployment remains distant. Scientists also plan to make the system compatible with energy storage technologies, such as sodium-ion or solid-state batteries. I believe that the system, if it can access a companion devices processing power (such as a smartphone capable of running AI models), can benefit both EV makers and owners.