[B3-P202] Poster 202

[B3-P202-12] A Universal Data-Driven Model for Battery Degradation Prediction: Achieving High Accuracy through End-to-End Learning

*Kim Inseop^1,2, Lee Junhyeong^1,3, Han SungWon², Lee ChanWoo^1,4 (1. Korea Institute of Energy Res. (Korea), 2. Korea Univ. (Korea), 3. Hanyang Univ. (Korea), 4. University of Science and Tech. (Korea))

Keywords:

Lithium-ion Battery,State-of-health Estimation,Deep Learning,Battery Life Forecasting