2 citations · 2 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Transformer-based Capacity Prediction for Lithium-ion Batteries with Data Augmentation
Gift Modekwe, Saif Al-Wahaibi, Qiugang Lu
Lithium-ion batteries are pivotal to technological advancements in transportation, electronics, and clean energy storage. The optimal operation and safety of these batteries requir…