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Turbulence is known to influence the aerodynamic and aeroacoustic performance of ground vehicles. What is not thoroughly understood are the characteristics of turbulence that influence this performance and how they can be applied in a consistent manner for aerodynamic design and evaluation purposes. Through collaboration between Transport Canada and the National Research Council Canada (NRC), a project was undertaken to develop a system for generating road-representative turbulence in the NRC 9 m Wind Tunnel, named the Road Turbulence System (RTS). This endeavour was undertaken in support of a larger project to evaluate new and emerging drag reduction technologies for heavy-duty vehicles. A multi-stage design process was used to develop the RTS for use with a 30% scale model of a heavy-duty vehicle in the NRC 9m Wind Tunnel.

The 9-meter wind tunnel of the National Research Council (NRC) of Canada is commonly employed in testing of class 8 tractors at full- and model-scales. In support of this work a series of tests of an identical model at full- and half-scale were performed to investigate some of the effects resulting from simulation compromises. Minimum Reynolds Number considerations drive the crucial decisions of what scale and speed to employ for testing. The full- and half-scale campaigns included Reynolds Number sweeps allowing conclusions to be reached on the minimum Reynolds number required for testing of fully-detailed commercial truck models. Furthermore the Reynolds sweeps were repeated at a variety of yaw angles to examine whether the minimum Reynolds Number was a function of yaw angle and the resulting flow regime changes. The test section of the NRC 9-meter wind tunnel is not sufficiently long to accommodate a full-scale tractor and a typical trailer length of 48′ or more.

This article presents an autonomous steering control scheme for articulated heavy vehicles (AHVs). Despite economic and environmental benefits in freight transportation, lateral stability is always a concern for AHVs in high-speed highway operations due to their multi-unit vehicle structures, and high centers of gravity (CGs). In addition, North American harsh winter weather makes the lateral stability even more challenging. AHVs often experience amplified lateral motions of trailing vehicle units in high-speed evasive maneuvers. AHVs represent a 7.5 times higher risk than passenger cars in highway operation. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous steering control of AHVs.

Recent research to investigate the aerodynamic-drag reduction associated with truck platooning systems has begun to reveal that surrounding traffic has a measurable impact on the aerodynamic performance of heavy trucks. A 1/15-scale wind-tunnel study was undertaken to measure changes to the aerodynamic drag experienced by heavy trucks in the presence of upstream traffic. The results, which are based on traffic conditions with up to 5 surrounding vehicles in a 2-lane configuration and consisting of 3 vehicle shapes (compact sedans, SUVs, and a medium-duty truck), show drag reductions of 1% to 16% for the heavy truck model, with the largest reductions of the same order as those experienced in a truck-platooning scenario. The data also reveal that the performance of drag-reduction technologies applied to the heavy-truck model (trailer side-skirts and a boat-tail) demonstrate different performance when applied to an isolated vehicle than to conditions with surrounding traffic.

Road vehicles have been shown to experience measurable changes in aerodynamic performance when travelling in everyday safe-distance driving conditions, with a major contributor being the lower effective wind speed associated with the wakes from forward vehicles. Using a novel traffic-wake-generator system, a comprehensive test program was undertaken to examine the influence of traffic wakes on the aerodynamic performance of heavy-duty vehicles (HDVs). The experiments were conducted in a large wind tunnel with four primary variants of a high-fidelity 30%-scale tractor-trailer model. Three high-roof-tractor models (conventional North-American sleeper-cab and day-cab, and a zero-emissions-cab style) paired with a standard dry-van trailer were tested, along with a low-roof day-cab tractor paired with a flat-bed trailer.

A novel method was developed to predict the free-stream velocity experienced by a traveling vehicle based on track-side anemometric measurements. The end objective of this research was to enhance the reliability of the prediction of free-stream conditions in order to improve the accuracy of aerodynamic drag coefficient (CD) assessments from track tests of surface vehicles. Although the technique was applied to heavy-duty vehicles in the present work, it is equally applicable to any vehicle type. The proposed method is based on Taylor’s hypothesis, a principle applied in fluid mechanics to convert temporal signals into the spatial domain. It considers that the turbulent wind velocity fluctuations measured at one point are due to the "passage of an unchanging pattern of turbulent motion over the point". The method is applied to predict the wind velocity that the vehicle will experience as it encounters a wind pattern detected earlier by an anemometer located upwind.