DEGWO-LSTM: A Hybrid Model for Accurate State of Health Estimation in Lithium-Ion Batteries
Aditya Bintang Aprilio- Djati Handoko- Dian Premana- I Bagus Ngurah Alit Putra Wiryawan- Muhammad Azimuthal Hikam- Awaludin Ahmad Hafiz

Department of Physics, Faculty of Mathematics and Natural Sciences, University of Indonesia, UI Depok Campus, Depok, 16424 Indonesia

Abstract

Abstract is submitted as file

Keywords: Lithium-Ion Battery, State of Health (SOH), Long Short-Term Memory (LSTM), Differential Evolution - Grey Wolf Optimizer (DEGWO)

Topic: AI, IoT, Sensor and Instrumentation for Energy