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INL team designs tailored superfast charging methods

Researchers at Idaho National Laboratory have used machine learning techniques that incorporate charging data to create unique charging protocols for superfast charging methods tailored to different types of electric vehicle batteries.

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

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 optimize 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. Currently, we’re seeing batteries charge to over 90% in 10 minutes without lithium plating or cathode cracking.

—Eric Dufek, Ph.D.

Charging EV Li-ion batteries is a balancing act. Ideally, drivers want to power up as quickly as possible to get back on the highway, but with current technology, speeding up the process can damage the battery. When a lithium-ion battery is being charged, lithium ions migrate from one side of the device, the cathode, to the other, the anode. By making the lithium ions migrate faster, the battery is charged more quickly, but sometimes the lithium ions don’t fully move into the anode. In this situation, lithium metal can build up, and this can trigger early battery failure. It can also cause the cathode to wear and crack.

All of these issues will reduce the lifetime of the battery and the effective range of the vehicle.

Developing optimal fast charging protocols requires a huge amount of data on how various methods affect these devices’ lifetimes, efficiencies and safety. The design and condition of batteries, as well as the feasibility of applying a given charging protocol with the current electric grid infrastructure, are also key variables.

The researchers plan to use their model to develop even better methods and to help design new lithium-ion batteries that are optimized to undergo fast charging. Dufek says 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 US Department of Energy’s Vehicle Technologies Office.


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