litlas
Log inCreate account

Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning

Authors: Guijun Ma, Songpei Xu, Benben Jiang, Cheng Cheng, Xin Yang, Yue Shen, Tao Yang, Yunhui Huang, Han Ding, Ye Yuan - Energy & Environmental Science 2022 cited by 247

We have developed a high-performance deep transfer learning framework to predict the health status of lithium-ion batteries for each end-user at any charge–discharge cycle.

Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning | Litlas