AI open data predicts usable life of batteries : Page 2 of 2

April 01, 2019 //By Nick Flaherty
Younghee Lee/CUBE3D
Toyota has teamed up with MIT and Stanford University to predict the usable life of battery cells using early cell cycle data and machine learning. The resulting data has been made publicly available. 
useful life, which they defined as capacity loss of 20 percent. En route to optimizing fast charging, the researchers wanted to find out whether if it was necessary to run their batteries into the ground.

The new method has many potential applications says Attia. For example, it can shorten the time for validating batteries with new chemistries, which is especially important given rapid advances in materials. Also, manufacturers can use the sorting technique to grade batteries with longer lifetimes to be sold at higher prices for more demanding uses, like electric vehicles. Recyclers can use the method to find cells in used EV battery packs that have enough life in them for secondary uses.

Yet another use is optimizing battery manufacturing. “The last step in manufacturing batteries is called ‘formation’ which can take days to weeks,” he said. “Using our approach could shorten that significantly and lower the production cost.”

The researchers are using this early prediction model to optimize charging procedures that could enable batteries to be charged in ten minutes. By using this model, the optimization time can be cut by more than a factor of ten, significantly accelerating research and development.

tri.global

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