3 citations · 3 across the 6 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.LG2025
Fast and Generalizable parameter-embedded Neural Operators for Lithium-Ion Battery Simulation
Amir Ali Panahi, Daniel Luder, Billy Wu +3
Reliable digital twins of lithium-ion batteries must achieve high physical fidelity with sub-millisecond speed. In this work, we benchmark three operator-learning surrogates for th…
eess.SY2025
Fast data augmentation for battery degradation prediction
Weihan Li, Harshvardhan Samsukha, Bruis van Vlijmen +4
Degradation prediction for lithium-ion batteries using data-driven methods requires high-quality aging data. However, generating such data, whether in the laboratory or the field,…