The rise of autonomous technologies may reflect on new vehicle traffic characteristics, likely reducing vehicle-to-vehicle proximity and emerging platooning formations. Energy consumption, stability, and surface contamination are relevant factors that are sensitive to aerodynamic interference while platooning. From the experimental perspective, most wind tunnels were originally designed to host isolated models, and these constraints often limit the investigation of multiple full-body vehicle formations (e.g. test section length, moving ground dimensions, standard testing points).
This paper introduces the ‘MultiWake’ model - a parametric bluff-body device based on a morphing concept, which can emulate the aerodynamic wake characteristics of different vehicle classes. The goal is the enhancement of experimental facilities to investigate vehicle-to-vehicle interference by (i) expanding the effective test section length, and (ii) improving time efficiency since the model morphology can be automated; therefore, allowing a given vehicle model to be exposed to multiple wakes during the same wind tunnel run. The design development pursued, with a focus on parametric simplicity and efficiency, the emulation of three wake types based on the experimental dataset of four full-body DrivAer models: Fastback, Notchback, Estateback, and high-performance Fastback.
An experimental campaign was conducted to characterise the recommended MultiWake configurations, where each wake is characterised on multiple downstream planes as a function of total pressure. The ‘Fastback’ and ‘Notchback’ modes are classified as Wake Type 1: a small wake with minor downwash; with attenuated downwash and increasing total pressure loss on the ‘Notchback’ mode. Wake Type 2 achieved in ‘Estateback’ mode provides a full detached flow and wake size proportional to the rear base, with lateral inwash. Wake Type 3 resembles motorsport applications, where the wake features a strong upwash linked with a coherent counter-rotating vortex pair. A Reynolds number dependency study and confidence interval mappings of the measurement approach complement the experimental validation.
