Predictive Energy-Saving Optimization Based on Nonlinear Model Predictive Control for Cooperative Connected Vehicles Platoon with V2V Communication

Abstract The rise of the intelligent transportation system (ITS) brings golden opportunity to accelerate the development of environment-friendly smart mobility eco-system. The intelligent control of connected autonomous vehicles (CAV) platoon with V2V communication as the core technology exhibits superior energy-saving potential. However, there still exist plentiful technologies of the emerging vehicle platoon need to be improved. Hence, this paper describes a predictive optimization strategy as ecological cooperative adaptive cruise control (eCACC) based on nonlinear model predictive control (NMPC) to minimize the energy consumption of an electrified CAV platoon considering V2V topological communication structure of leader predecessor follower. The cost function for NMPC includes the following velocity, range deviation and energy consumption. Through the simulation analysis under various drive cycles, the advantage of the proposed scheme emerges that the platoon consisted of three vehicles possesses the nice string stability, excellent following performance and significant energy-saving potential at same time. Moreover, the acceleration of the following vehicles is in a small range, improving the drive comfort. By the comparison with the existed Eco ACC controller, the simulation results demonstrate the proposed controller owns better following performance and energy-saving behavior of 16.1%, 6.2% and 11.7% under full UDDS, HWFET and NEDC drive cycle, respectively.