Ecological Cooperative Adaptive Cruise Control for Heterogenous Vehicle Platoons Subject to Time Delays and Input Saturations

• Published in: IEEE transactions on intelligent transportation systems Vol. 24; no. 3; pp. 1 - 12
• Main Authors: Zhai, Chunjie, Chen, Chuqiao, Zheng, Xinlei, Han, Zhimin, Gao, Yuhan, Yan, Chenggang, Luo, Fei, Xu, Jianmin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Algorithms; Cooperative control; Cruise control; Delay effects; Delays; ecological cooperative adaptive cruise control; Ecological effects; Emissions; Energy consumption; Energy efficiency; Feedback control; Fuel consumption; Fuel economy; Fuel economy standards; Greenhouse gases; Heterogenous vehicle platoon; input saturations; Particle swarm optimization; Passenger comfort; Platooning; Predictive control; Protocols; Roads; Stability criteria; time delays; Vehicle dynamics; Vehicles
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2022.3222324

Public concerns about energy crisis and environmental issues lead to higher fuel economy standards and more stringent limitations on greenhouse gas emissions for ground vehicles, and ecological cooperative adaptive cruise control (eco-CACC) is considered to be effective in reducing fuel consumption and greenhouse gas emissions of vehicle platoons. In this paper, an eco-CACC strategy is presented for heterogeneous platoons with time delays and input saturations to achieve platoon stability, fuel economy, riding comfort and driving efficiency. The proposed eco-CACC strategy includes distributed linear feedback control (DLFC) for following vehicles and model predictive control (MPC) for the leading one. To obtain platoon stability, the DLFC protocol is designed using state errors between an ego vehicle and its preceding one, and the frequency domain method is employed to derive the sufficient conditions of platoon stability for the DLFC protocol. Then, to achieve fuel economy, passenger comfort and driving efficiency without violating the different input saturations of vehicles, the constrained fuel consumption optimization problem of the leading vehicle (CFCO-LV) is formulated based on delay MPC, where the weighted sum of the overall fuel consumption and velocity band-stop functions of vehicle platoon is minimized. To quickly obtain the MPC controller, an improved particle swarm optimization (PSO) algorithm is used to solve the CFCO-LV problem. Simulations are implemented to validate the effectiveness of the proposed eco-CACC strategy, and the simulation results demonstrate that, compared with benchmark, the proposed strategy can save 2.19%<inline-formula> <tex-math notation="LaTeX">\sim</tex-math> </inline-formula>8.24% of fuel for the heterogeneous platoon under different velocity ranges.