Artificial intelligence could have given clues on the best method for fast-charging electric vehicles thanks to a study at the US’ Stanford University.
Instead of charging at the highest current at the beginning of the charge, the computer’s algorithm suggested using the highest current in the middle of the charge.
The finding by a team led by Stanford professors Stefano Ermon and William Chueh were published in the journal Nature and was part of a larger collaboration among scientists from Stanford, MIT and the Toyota Research Institute.
The researcher’s goal was to find the best method for charging an EV battery in 10 minutes that also maximises the battery’s overall lifetime.
Based on 100 charging cycles, the software reduced the length and number of trials needed, cutting the researchers process from almost two years to 16 days.
The machine learning system was “trained” on a few batteries cycled to failure, which enabled it to find patterns in the early data that presaged how long later batteries would last.
“In battery testing, you have to try a massive number of things, because the performance you get will vary drastically,” said Ermon, an assistant professor of computer science.
“With AI, we’re able to quickly identify the most promising approaches and cut out a lot of unnecessary experiments.”
The researchers said their approach could accelerate nearly every piece of the battery development pipeline: from designing the chemistry of a battery to determining its size and shape, to finding better systems for manufacturing and storage.
This would have broad implications not only for electric vehicles but for other types of energy storage.
“This is a new way of doing battery development,” said Patrick Herring, co-author of the study and a scientist at the Toyota Research Institute. “Having data that you can share among a large number of people in academia and industry, and that is automatically analysed, enables much faster innovation.”
The study’s machine learning and data collection system will be made available for future battery scientists to freely use,
Using artificial intelligence, a Stanford-led research team has slashed battery testing times – a key barrier to longer-lasting, faster-charging batteries for electric vehicles. (Image credit: Cube3D)
Mark Golden, Stanford Precourt Institute for Energy: (650) 724-1629, mark.golden@stanford.edu
Stephen Hughes, Toyota Research Institute: (650) 422-8947, stephen.hughes@tri.global