3 papers
cs.LG2026
Physics-Informed Neural Network with Transfer Learning for State Estimation in Lithium-Ion Batteries using the Single Particle Model with Electrolyte
Gift Modekwe, Qiugang Lu
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving nonlinear partial differential equations (PDEs), including battery electrochemical models. They…
cs.LG2026
Multi-Level Temporal Graph Networks with Local-Global Fusion for Industrial Fault Diagnosis
Bibek Aryal, Gift Modekwe, Qiugang Lu
Fault detection and diagnosis are critical for the optimal and safe operation of industrial processes. The correlations among sensors often display non-Euclidean structures where g…
eess.SY2025
Lithium-ion Battery Capacity Prediction via Conditional Recurrent Generative Adversarial Network-based Time-Series Regeneration
Myisha A. Chowdhury, Gift Modekwe, Qiugang Lu
Accurate capacity prediction is essential for the safe and reliable operation of batteries by anticipating potential failures beforehand. The performance of state-of-the-art capaci…