234 citations · 286 across the 7 of their papers we have counts for
5 papers · 1 filter
Plug-in Hybrid Electric Vehicle Energy Management with Clutch Engagement Control via Continuous-Discrete Reinforcement Learning
Changfu Gong, Jinming Xu, Yuan Lin
Energy management strategy (EMS) is a key technology for plug-in hybrid electric vehicles (PHEVs). The energy management of certain series-parallel PHEVs involves the control of co…
Co-Optimization of Adaptive Cruise Control and Hybrid Electric Vehicle Energy Management via Model Predictive Mixed Integer Control
Qitao Li, Changfu Gong, Yuan Lin
In this paper, a model predictive mixed integer control method for BYD Qin Plus DM-i (Dual Model intelligent) plug-in hybrid electric vehicle (PHEV) is proposed for co-optimization…
Co-Optimization of On-Ramp Merging and Plug-In Hybrid Electric Vehicle Power Split Using Deep Reinforcement Learning
Yuan Lin, John McPhee, Nasser L. Azad
Current research on Deep Reinforcement Learning (DRL) for automated on-ramp merging neglects vehicle powertrain and dynamics. This work considers automated on-ramp merging for a po…
Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control
Yuan Lin, John McPhee, Nasser L. Azad
This study compares Deep Reinforcement Learning (DRL) and Model Predictive Control (MPC) for Adaptive Cruise Control (ACC) design in car-following scenarios. A first-order system i…
Anti-Jerk On-Ramp Merging Using Deep Reinforcement Learning
Yuan Lin, John McPhee, Nasser L. Azad
Deep Reinforcement Learning (DRL) is used here for decentralized decision-making and longitudinal control for high-speed on-ramp merging. The DRL environment state includes the sta…