Eco-driving policy for connected and automated fuel cell hybrid vehicles platoon in dynamic traffic scenarios

Abstract

Cooperation of platooning vehicles enabled by eco-driving and connected and automated technology has shown considerable potential in energy saving and traffic efficiency improvement. However, affected by the impacts of the randomly changed states of traffic vehicles and the uncertainty of future road conditions, the adoption of eco-driving for the connected and automated fuel cell vehicle (CAFCHV) platoon in a dynamic traffic environment will encounter significant challenges. Additionally, improper inter-vehicle spacing can significantly affect operating safety and energy efficiency. To address this problem, a centralized variable spacing control strategy that adaptively adjusts with velocity and slope for the CAFCHV platoon is designed to calculate the optimal speed and promote energy allocation efficiency. In the upper control layer, gradient-based model prediction control (GRAMPC) is leveraged to calculate the optimal speed of the platoon, where the velocity of each vehicle can be regulated via its own and the surrounding vehicle's state and relative position. In the bottom layer, each vehicle in the platoon solves an MPC-based energy management strategy (EMS) to achieve power allocation in various power sources. Compared with the adaptive cruise control (ACC) driving manner, the simulation results regulated by the Planning manner display a considerable improvement in terms of the global cost, hydrogen consumption, battery degradation, and SOC by 1.36%, 1.48%, 2.47%, and 1.56%, respectively.