Machine learning helps EV batteries to charge in 10 minutes

The researchers presented their results this week at the autumn meeting of the American Chemical Society (ACS).

“Fast charging is the key to increasing consumer confidence and overall adoption of electric vehicles,” said Eric Dufek, Ph.D. “It would allow vehicle charging to be very similar to filling up at a gas station.”

When a lithium-ion battery is being charged, lithium ions migrate from the cathode to the anode. By making the lithium ions migrate faster, the battery is charged more quickly, but the lithium ions do not always fully move into the anode. In this situation, lithium metal can build up, triggering early battery failure. It can also cause the cathode to wear and crack. Added together, these issues reduce the lifetime of the battery and the effective range of the vehicle.

One solution is to tailor the charging protocol in a way that optimises speed while avoiding damage for different types of battery designs, but this requires a significant amount of data on how various methods affect these devices’ lifetimes, efficiencies and safety. The design and condition of batteries, plus the feasibility of applying a given charging protocol with the current electric grid infrastructure, are also key variables.

To address these challenges, Dufek and his research team at Idaho National Laboratory now report the use of machine learning techniques that incorporate charging data to create unique charging protocols. By inputting information about the condition of many lithium-ion batteries during their charging and discharging cycles, the scientists trained the machine learning analysis to predict lifetimes and the ways that different designs would eventually fail. The team then fed that data back into the analysis to identify and optimise new protocols that they then tested on real batteries.

“We’ve significantly increased the amount of energy that can go into a battery cell in a short amount of time,” Dufek said in a statement. “Currently, we’re seeing batteries charge to over 90 per cent in 10 minutes without lithium plating or cathode cracking.”

Dufek said that one advantage of their machine learning model is that it ties the protocols to the physics of what is happening in a battery.  

The researchers plan to use their model to develop better methods and to help design new lithium-ion batteries that are optimised to undergo fast charging. Dufek said that the ultimate goal is for electric vehicles to be able to ‘tell’ charging stations how to power up their specific batteries quickly and safely.

The researchers acknowledge support and funding from the U.S. Department of Energy’s Vehicle Technologies Office.