Optimization of aerodynamic characteristics of longitudinal sedan platoon with non-uniform spacing based on response surface method

Abstract

Reducing energy consumption and improving driving stability are the core challenges for the development of intelligent connected transportation. The coordinated driving of sedan platoons can effectively reduce energy consumption, but optimizing their aerodynamic stability under crosswind conditions is still a challenge. This study is the first to apply the response surface methodology to the aerodynamic layout collaborative optimization of non-uniform sedan platoons, in order to solve the complex flow interference problem in multi sedan systems. The study first compared the aerodynamic coefficients of the Ahmed model with wind tunnel experimental results to verify the reliability of the Realizable k − ε turbulence model. A global response model for the aerodynamic performance of a convoy under crosswind conditions was constructed with the front to rear distance (x₁/L) and the middle to rear distance (x₂/L) in the platoon as design variables, and the average drag, lift, and lateral force coefficients of the convoy as multiple objectives. The optimization results show that this method can intelligently provide the optimal safety distance strategy under different crosswind threat levels. Using uniform platoon driving (x₁/L = x₂/L = 0.25) in the absence of crosswind to maximize energy-saving benefits. As the crosswind angle increases to 30°, the system recommends using non-uniform platoon driving (x₁/L = 1.009, x₂/L = 0.251) to prioritize stability. This study proposes a non-uniform platoon driving strategy based on previous uniform platoon driving, and investigates the aerodynamic characteristics of platoon driving in crosswind environments. Finally, the response variable optimization method is proposed to find the optimal spacing arrangement between sedans. A data-driven collaborative design method has been provided for the aerodynamic layout of intelligent connected sedan fleets, achieving a scenario adaptive balance between energy conservation and stability.