Aerodynamic Drag Analysis of Autonomous Electric Vehicle Platoons

Abstract

Vehicle platooning has been proposed as one of the potential technologies for intelligent transport systems to improve transportation and energy efficiency in urban cities. Despite extensive studies conducted on the platooning of heavy-duty trucks, literature on the analysis of urban vehicle platoons has been limited. To analyse the impact of platooning in urban environments, this paper studies the influence of intervehicle distance, platoon size and vehicle speed on the drag coefficient of the vehicles in a platoon using computational fluid dynamics (CFD). Two vehicle models—a minibus and a passenger car—are analysed to characterise the drag coefficients of the respective platoons. An analysis of energy consumption is conducted to evaluate the energy savings with platooning using a longitudinal dynamics simulation. The results showed a reduction in the average drag coefficient of the platoon of up to 24% at an intervehicle distance of 1 m depending on the number of vehicles in the platoon. With a larger intervehicle distance of 4 m, the reduction in the drag coefficient decreased to 4% of the drag coefficient of the isolated vehicle. Subsequently, energy savings with platooning were calculated to be up to 10% depending on the driving cycle, intervehicle distance and platoon size.

The Effect of Afterbody Geometry on Passenger Vehicles in Platoon

“…These observations contradict the slip-streaming effect as it is commonly understood, however, it agrees with remarks made by other researchers on platoons of vehicles in pairs [5,7,8,13,16,23,31]. This suggests that the slip-streaming effect is not universal and is highly dependent on the chosen geometry and distance between these geometries, which may help explain the misconceptions associated with this term.…”

From PLATO to Platoons

“…Fuel saving results from the reduction of air drag resistance. The problem has been studied through experiments in wind tunnels [7], [8], simulations [9], [10], and field experiments [11]. From these studies, the overall platoon reduction of fuel consumption can be estimated in 4 to 12% depending on inter-vehicle distance, while the fuel saving for single vehicles depends on their position within the platoon [8], [11].…”

Development of a Numerical Investigation Framework for Ground Vehicle Platooning

“…Reynolds Averaged Navier-Stokes equation are achieved by first decomposing the time-dependent velocity field u i into mean (U i ) and fluctuating (u i ) components using the Reynolds decomposition, mathematically expressed as u i = U i + u i , and then ensembleaveraging the original N-S equations. The RANS equations in the conservative form are expressed in Equations ( 5) and (6). Note that, we described here the turbulent flow statistically in terms of the mean velocity field U i (x, t) and mean rate of strain S ij (x, t) instead of the instantaneous velocity field u i (x, t) and instantaneously rate of strain field s ij (x, t), respectively, and these equations are commonly referred to as the Unsteady Reynolds Averaged Navier-Stokes (URANS) equations.…”

“…While this practice is less seen in consumer vehicles, among heavy transport vehicles, such as freight liners, the practice is quite popular and can produce great returns in fuel savings [2][3][4], to cite a few. With the rapid advances in self-driving technology it is believed by many that soon even consumer vehicles will begin platooning in a connected transportation system due to the decreasing follow distances that self-driving cars can achieve with their low reaction times and vehicle to vehicle communication [5,6].…”