8 citations · 10 across the 7 of their papers we have counts for
5 papers · 1 filter
Direct Data-driven Predictive Control: A Computationally Efficient Alternative to DeePC for Eco-driving in Mixed Traffic Flows
Dongjun Li, Haoxuan Dong, Liangcai Xu +1
Improving energy efficiency in the transportation sector is critical for achieving sustainable mobility, with eco-driving emerging as a key strategy. However, implementing effectiv…
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…
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-…
Integrated Power and Thermal Management for Enhancing Energy Efficiency and Battery Life in Connected and Automated Electric Vehicles
Dongjun Li, Qiuhao Hu, Weiran Jiang +2
Effective power and thermal management are essential for ensuring battery efficiency, safety, and longevity in Connected and Automated Electric Vehicles (CAEVs). However, real-time…
Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances
Ke Lu, Dongjun Li, Qun Wang +3
This paper presents a safe learning-based eco-driving framework tailored for mixed traffic flows, which aims to optimize energy efficiency while guaranteeing safety during real-sys…