Toyota, MIT and Stanford Use AI to Predict Battery Life
Scientists at the Toyota Research Institute, Massachusetts Institute of Technology, and Stanford University have discovered they can combine comprehensive experimental data with artificial intelligence to accurately predict the useful life of lithium-ion batteries before they begin to lose capacity.
Researchers were able to give an algorithm “a few hundred million data points,” after which it was able to determine how long batteries would last based on voltage declines and other factors. According to Toyota, the predictions were within just nine percent of the actual life cycle.
Better yet, a separate test had the algorithm classify batteries as having either short or long life expectancy based on only their first five charge and discharge cycles. It was accurate 95 percent of the time.
According to Toyota, this new method could help accelerate battery design development and help manufacturers determine which of their batteries will last long enough to be suitable for cell phones, and which will last long enough to be suitable for electric vehicles.
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“The standard way to test new battery designs is to charge and discharge the cells until they die. Since batteries have a long lifetime, this process can take many months and even years,” said Peter Attia, Stanford doctoral candidate in Materials Science and Engineering. “It’s an expensive bottleneck in battery research.”
In addition to shortening the time for validating batteries with new chemistries, the technology can also help scientists discover better ways to charge batteries quickly as well as optimize battery manufacturing processes.
The research is part of Toyota’s efforts to push electric vehicle technology into the mainstream. The automaker has invested $35 million in TRI’s Accelerated Materials Design and Discovery program, which collaborates with universities and companies to “use artificial intelligence to accelerate the design and discovery of advanced materials.”
And all of the data they found about AI’s ability to predict battery life has been made public.
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