Data-driven Energy-efficiency Control towards Air Drag Reduction for Homogeneous Vehicle Platoons

For vehicle nodes which are joining a vehicle platoon, the reduction of wind resistance is the key consideration factor. Due to the complex flow structure and unpredictable external flow field of vehicles, it is hard to determine the optimal following order and distance for wind resistance reduction. This paper proposes a universal hierarchical energy-efficiency control strategy towards wind resistance reduction for homogeneous vehicle platoons. The upper layer is responsible for air drag optimization based on data-driven idea, which learns the wind resistance mapping in the accompanying body coordinates, and utilizes the particle swarm optimization (PSO) algorithm to optimize and determine the platooning configuration. The middle layer is the wind resistance sensing layer. Extended state observer (ESO) is introduced to realize the real-time observation of the total disturbance and the separation of wind resistance. The bottom layer executes vehicle following control, where the active disturbance rejection control (ADRC) strategy is introduced to improve the stability of platoon proceeding. Co-simulation results of CarSim/Simulink verify the effectiveness of the proposed strategy.