Hierarchical Control Strategies for Connected Heavy-Duty Modular Fuel Cell Vehicles via Decentralized Convex Optimization
Long Hao, Arash Khalatbarisoltani, Yalian Yang, Xiaosong Hu
Abstract
Fuel cell vehicles (FCVs) are gaining popularity in heavy-duty transportation applications because of their high efficiency, lack of local emissions, and short refueling time. Moreover, cooperative adaptive cruise control (CACC), which plans the longitudinal movements of heavy-duty vehicles, is also a potential solution to increase fuel efficiency, safety, and road capacity. In order to integrate the aforementioned two technologies, in this research, a homogeneous heavy-duty modular fuel cell vehicle (MFCV) platoon is hierarchically created using a decentralized optimization technique called the consensus alternating direction method of multipliers (C-ADMM). The higher-level controllers coordinate platoon members’ movements by accounting for aerodynamic effects, balancing string stability, and ensuring comfortable driving. Furthermore, power allocation is accomplished by lower-level controllers, minimizing total costs, which include hydrogen and degradation expenses. According to the simulation's findings, integrating the suggested power allocation approach with the proposed CACC method can reduce the overall cost by up to 7.5%. The calculation time of the presented technique can be reduced by an average of 60.17% and 68.27% compared to centralized and distributed methods, respectively. In addition, both the cybersecurity and delay analyses of the recommended decentralized architecture are also examined. The results indicate that the modularity of the proposed strategy leads to highly favorable consequences.