<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=235002737667895&amp;ev=PageView&amp;noscript=1">

New Method Could Supercharge Battery Development For Electric Vehicles

machine-learning-batteries-1For decades, advances in electric vehicle batteries have been limited by a major bottleneck: evaluation times. At every stage of the battery development process, new technologies must be tested for months or even years to determine how long they will last. But now, a team led by Stanford professors Stefano Ermon and William Chueh has developed a machine learning-based method that slashes these testing times by 98 percent. Although the group tested their method on battery charge speed, they said it can be applied to numerous other parts of the battery development pipeline and even to non-energy technologies.

Battery testing is also made efficient by Associated Environmental Systems patent-pending easy to set up and modify drastically reduces the time required to set up test environments.

Share:   Associated Environmental Systems on LinkedIn   Associated Environmental Systems on Twitter   Associated Environmental Systems on Facebook   

IMAGE CREDIT: CUBE3D

Read the source article at EurekAlert! Science News