Life Prediction of Lithium Battery for New Energy Vehicles - A Long and Short-Term Memory Network Based on Adaptive Moment Estimation and Bayesian Optimization

This paper analyzes historical charge/discharge cycle data to predict the remaining service life of lithium-ion batteries using a long short-term memory network model, which is crucial for the emerging new energy vehicle industry. The study refines predictions with adaptive moment estimation and Bayesian optimization, establishes a capacity threshold to determine battery life expectancy, and proposes recommendations to address challenges related to battery life prediction.