Cooperative Ecological Adaptive Cruise Control for Plug-in Hybrid Electric Vehicle Based on Approximate Dynamic Programming

Eco-driving control generates significant energy-saving potential in car-following scenarios. However, the influence of preceding vehicle may impose unnecessary velocity waves and deteriorate fuel economy. In this research, a learning-based method is exploited to achieve satisfied economy for connected plug-in hybrid electric vehicles (PHEVs) with advantage vehicle-to-vehicle communication system. A data-driven energy consumption model leveraged generate reinforcement signals approximate dynamic programming (ADP) consideration nonlinear efficiency characteristics powertrain An advanced ADP scheme designed PHEVs driving Additionally, cooperative information incorporated further improve under premise safety. The proposed mode-free showcases acceptable computational as well adaptability. simulation results demonstrate that during processes remarkably improved through information, thereby partially paving theoretical basis transportation.