Ecological Electric Vehicle Platooning: An Adaptive Tube-Based Distributed Model Predictive Control Approach
Hao Sun, Bingbing Li, Hao Zhang, Li Dai, Giuseppe Fedele, Weichao Zhuang, Boli Chen
Abstract
The advent connected and autonomous vehicle technologies have greatly improved traffic in terms of energy efficiency and road safety. This paper addresses an ecological control problem of electric vehicle platoons subject to various system uncertainties, including but not limited to modeling uncertainties and measurement noise from different sources. Based on a spatial domain modeling approach with appropriate coordination change and nonconvex constraints relaxation, the traditional nonlinear optimal control problem is convexified. Reformulation in spatial domain can incorporate accurate road information, and convexification substantially improves computational efficiency. Then, aforementioned models are employed within an adaptive tube-based distributed model predictive control (AT-DMPC) framework, taking into account platoon formation consensus, road safety, energy consumption and driver comfort under the predecessor-following communication topology. Finally, numerical simulations and hardware-in-the-loop experiments are conducted to assess the performance of the proposed method relative to several state-of-the-art algorithms.