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…
Techno-Economic Planning of Spatially-Resolved Battery Storage Systems in Renewable-Dominant Grids Under Weather Variability
Seyed Ehsan Ahmadi, Elnaz Kabir, Mohammad Fattahi +2
The ongoing energy transition is significantly increasing the share of renewable energy sources (RES) in power systems; however, their intermittency and variability pose substantia…
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…
Physics-Augmented Data-EnablEd Predictive Control for Eco-driving of Mixed Traffic Considering Diverse Human Behaviors
Dongjun Li, Kaixiang Zhang, Haoxuan Dong +3
Data-driven cooperative control of connected and automated vehicles (CAVs) has gained extensive research interest as it can utilize collected data to generate control actions witho…
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…