Communications of the ACM
AI Techniques Used to Improve Battery Health, Safety
Researchers at two U.K. universities have developed a way to predict battery health with 10 times greater accuracy than the current industry standard.
Credit: University of Cambridge
A machine learning method developed by researchers at the University of Cambridge and Newcastle University in the U.K. can predict battery health with 10 times greater accuracy than the current industry standard.
The new method could help develop safer, more reliable batteries for electric vehicles and consumer electronics.
n add-on compatible with any existing battery system, the method monitors batteries by sending electrical pulses into them, measuring the results, and processing those measurements with a machine learning algorithm to predict the battery's health and useful lifespan.
The researchers trained the model by performing more than 20,000 experimental measurements.
Said Cambridge's Alpha Lee, "By improving the software that monitors charging and discharging, and using data-driven software to control the charging process, I believe we can power a big improvement in battery performance."
From University of Cambridge (UK)
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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