33 citations · 41 across the 4 of their papers we have counts for
Showing eess.SYShow all
3 papers · 1 filter
eess.SY2025★ 8 cited
Real-Time Physics-Aware Battery Health Monitoring from Partial Charging Profiles via Physics-Informed Neural Networks
Xubo Gu, Xun Huan, Yao Ren +3
Monitoring battery health is essential for ensuring safe and efficient operation. However, there is an inherent trade-off between assessment speed and diagnostic depth-specifically…
eess.SY2025
Enhanced Battery Capacity Estimation in Data-Limited Scenarios through Swarm Learning
Jiawei Zhang, Yu Zhang, Wei Xu +5
Data-driven methods have shown potential in electric-vehicle battery management tasks such as capacity estimation, but their deployment is bottlenecked by poor performance in data-…
eess.SY2023★ 33 cited
Driving behavior-guided battery health monitoring for electric vehicles using machine learning
Nanhua Jiang, Jiawei Zhang, Weiran Jiang +4
An accurate estimation of the state of health (SOH) of batteries is critical to ensuring the safe and reliable operation of electric vehicles (EVs). Feature-based machine learning…