Electrochemical Science and Engineering
The Electrochemical Science & Engineering group at °®ÎÛ´«Ã½ works at the interface between the science and engineering of electrochemical devices, mostly focused on automotive & stationary power applications.
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Deep learning diagnostic framework for rapid degradation quantification. An example of a convolutional neural network for degradation mode (component) quantification for lithium-ion batteries. This framework features rapid nature (<0.012s) and generalization (Almost all aging paths involved)
Highly instrumented lithium ion batteries with integrated thermal management ready for testing
