Model-Free Reconstruction of Capacity Degradation Trajectory of Lithium-Ion Batteries Using Early Cycle Data

no code implementations • 31 Mar 2023 • Seongyoon Kim, Hangsoon Jung, Minho Lee, Yun Young Choi, Jung-Il Choi

The method involves predicting a few knots at specific retention levels using a deep learning-based model and interpolating them to reconstruct the trajectory.

Bayesian Optimization Trajectory Prediction

Impedance-based Capacity Estimation for Lithium-Ion Batteries Using Generative Adversarial Network

no code implementations • 2 Jul 2021 • Seongyoon Kim, Yun Young Choi, Jung-Il Choi

This paper proposes a fully unsupervised methodology for the reliable extraction of latent variables representing the characteristics of lithium-ion batteries (LIBs) from electrochemical impedance spectroscopy (EIS) data using information maximizing generative adversarial networks.

Capacity Estimation Generative Adversarial Network