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One of the remaining challenges in the simulation of the aerodynamics of ground vehicles is the modeling of the airflows around the spinning tires and wheels of the vehicle. As in most advances in the development of simulation capabilities, it is the lack of appropriately detailed and accurate experimental data with which to correlate that holds back the advance of the technology. The flow around the wheels and tires and their interfaces with the vehicle body and the ground is a critical area for the development of automobiles and trucks, not just for aerodynamic forces and moments, and their result on fuel economy and vehicle handling and performance, but also for the airflows and pressures that affect brake cooling, engine cooling airflows, water spray management etc.

The engineering process in the development of commercial vehicles is facing more and more stringent emission regulations while at the same time the market demands for better performance but with lower fuel consumption. The optimization of aerodynamic performance for reduced drag is a key element for achieving related performance targets. Closely related to aerodynamics are wind noise and cabin soiling and both of them are becoming more and more important as a quality criterion in many markets. This paper describes the aerodynamic and aero-acoustic performance evaluation of a Dongfeng heavy truck using digital simulation based on a LBM approach. It includes a study for improving drag within the design of a facelift of the truck. A soiling analysis is performed for each aerodynamic result by calculating the accumulation of particles emitted form the wheels on the cabin. One of the challenges in the development process of trucks is that different cabin types have to be designed.

Water accumulating on a vehicle's wind screen, driven over the A-pillar by a combination of aerodynamic forces and the action of the windscreen wipers, can be a significant impediment to driver vision. Surface water film, or streams, persisting in key vision areas of the side glass can impair the drivers' ability to see clearly through to the door mirror, and laterally onto junctions. Common countermeasures include: water management channels and hydrophobic glass coatings. Water management channels have both design and wind noise implications. Hydrophobic coatings entail significant cost. In order to manage this design optimisation issue a water film and wiper effect model has been developed in collaboration with Jaguar Land Rover, extending the capabilities of the PowerFLOW CFD software. This is complimented by a wind-tunnel based test method for development and validation. The paper presents the progress made to date.

More stringent heavy vehicle emissions legislation demands considerably higher performance for engine cooling systems. This paper presents a study of cooling airflow for a Freightliner Class 8 truck. The predicted radiator coolant inlet and charge-air-cooler outlet temperatures are in very good agreement with the measured data. The under hood flow behavior is described and potential areas of improvement leading to better cooling airflow performance are highlighted. The airflow simulation approach is based on the Lattice-Boltzmann Method (LBM) and is described in detail. It is shown that the presented simulation approach can provide accurate predictions of cooling airflow and coolant temperature across different fan speeds.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

This paper describes the methodology used to design and perform a CFD analysis of a Chevrolet Impala SS Funny Car body. This body was designed for the purpose of making it available for teams to race it in the National Hot Rod Association (NHRA) drag racing series beginning with the 2007 race season. Several challenges were presented in this project: (1) This was the first time a General Motors drag racing body for use in professional classes (Funny Car or otherwise) was ever designed in CAD. (2) The body was originally designed as a 2007 Chevrolet Monte Carlo. After the tooling was completed, changes in Chevrolet’s product lineup required that the body be changed to a 2007 Impala SS. (3) Budget constraints precluded CFD analysis until after the bodies were already being manufactured. There were several teams that raced the new body during the 2007 race season. One of these teams won the Funny Car Driver’s Championship.

A newly developed simulation methodology for a long term, transient tractor cabin cool-down is presented in this paper. The air flow was simulated using a Lattice-Boltzmann Equation (LBE) based 3-dimensional flow solver. The conduction and radiation effects on the solid parts as well as the average cabin air temperature evolution were solved by the thermal solver, which also includes a human comfort model. The simulation results were compared with the measured experimental test data and good agreement was observed validating the developed simulation approach. The developed methodology can be applied to all other ground vehicles cabin comfort applications.

The engineering process in the development of commercial vehicles is facing more and more stringent emission regulations while at the same time the market demands for better performance but with lower fuel consumption and higher reliability. Respective targets require better utilization of existing or even higher engine cooling capacity and optimization of aerodynamic performance for reduced drag. In order to aid on achieving both goals, special attention should be paid on understanding both external and under hood flow structures. This paper describes an optimization study for reducing aerodynamic drag and increasing engine cooling performance conducted on a Light Truck at Jiangling Motors Corporation (JMC). The approach is using simulation based on a LBM solver coupled with a heat exchanger model. Such methodology was used to predict both aerodynamic and cooling characteristics and help highlighting potential areas for improvement.

The Tesla Motors Model S has been designed from a clean sheet of paper to prove that no compromises to a desirable aesthetic style and world class driving experience are necessary in order to be energy efficient. Aerodynamic optimization is a major contributor to the overall efficiency of an electric vehicle and the close integration of the Design and Engineering groups at Tesla Motors was specifically arranged to process design iterations quickly and enable the fully informed development of the exterior surfaces at a very rapid pace. Clear communication and a working appreciation of each other's priorities were vital to this collaboration and underpinning this was extensive use of the powerful analysis and visualization capabilities of CFD. CFD was used to identify and effectively communicate the nature of beneficial and detrimental design features and to find ways to enhance or ameliorate them accordingly.

Charge air temperature needs to be kept low for optimum engine operation. If charge air temperature is too high, engine performance reduction strategies are invoked to protect engines by limiting torque available to drivers. A 1D-3D coupling simulation methodology is developed to accurately predict internal air temperature after charge air cooler (CAC) during a racing drive cycle. The 3D flow simulation is used to characterize external air flow before CAC in steady-state cases. Then, interpolated 3D simulation results between steady operating points are used as transient external air boundary conditions in front of CAC in a 1D system model. 3D flow simulation is also used to predict internal flow rate ratio between CAC tubes. Finally, an 1D system model is used to predict time-trace of charge air temperature at CAC internal outlet during the racing drive cycle. The simulation results show that prediction errors are within 5 degrees for charge air temperature at internal outlets.

The management of surface water flows driven from the wind screen by the action of wipers and aerodynamic shear is a growing challenge for automotive manufacturers. Pressure to remove traditional vehicle features, such as A-Pillar steps for aesthetic, aeroacoustic and aerodynamic reasons increases the likelihood that surface water may be convected over the A-Pillar and onto the front side glass where it can compromise drivers’ vision. The ability to predict where and under which conditions the A-Pillar will be breached is important for making correct design decisions. The use of numerical simulation in this context is desirable, as experimental testing relies on the use of aerodynamics test properties which will not be fully representative, or late-stage prototypes, making it difficult and costly to correct issues. This paper provides an update on the ability of simulation to predict A-Pillar overflow, comparing physical and numerical results for a test vehicle.

Ground transportation industry contributes to about 14% of the global CO2 emissions. Therefore, any effort in reducing global CO2 needs to include the design of cleaner and more energy efficient vehicles. Their design needs to be optimized for the real-world conditions. Using wind tunnels that can only reproduce idealized conditions quite often does not translate into real-world on-road CO2 reduction and improved energy efficiency. Several recent studies found that very rarely can the real-world environment be represented by turbulence-free conditions simulated in wind tunnels. The real-world conditions consist of both transversal flow velocity component (causing an oncoming yaw flow) as well as large-scale turbulent fluctuations, with length scales of up to many times the size of a vehicle. The study presented in this paper shows how the realistic wind affects the aerodynamics of the vehicle.

Windscreen wipers are an integral component of the windscreen cleaning systems of most vehicles, trains, cars, trucks, boats and some planes. Wipers are used to clear rain, snow, and dirt from the windscreen pushing the water from the wiped surface. Under certain conditions however, water which has been driven to the edge of the windscreen by the wiper can be drawn back into the driver’s field of view by aerodynamic forces introduced by the wiper motion. This is wiper drawback, an undesirable phenomenon as the water which is drawn back on to the windscreen can reduce driver’s vision and makes the wiper less effective. The phenomena of wiper drawback can be tested for in climatic tunnels using sprayer systems to wet the windscreen. However, these tests require a bespoke test property or prototype vehicle, which means that the tests are done fairly late in the development of the vehicle.

Aerodynamic evaluation of vehicles using static yaw angle changes in wind tunnel testing and numerical simulation has been used as standard practice for evaluating vehicle performance under a range of wind conditions. However, this approach does not consider dynamic wind effects coming from changing wind conditions, passing other vehicles and roadside obstacles, and transient non-uniform wind conditions coming from environmental turbulence. In previous work by the authors, computational fluid dynamics (CFD) simulation methodology for considering dynamic wind conditions and on-road turbulence was demonstrated, showing the important effects of the wind conditions on the vehicle aerodynamics. The technique allows the vehicle to be tested under a range of transient gust conditions, also accounting for wind turbulence coming from upstream vehicles and natural environmental wind fluctuations.

Pickup trucks are designed with a taller ride height and a larger tire envelope compared to other vehicle types given the duty cycle and environment they operate in. These differences play an important role in the flow field around spinning wheels and tires and their interactions with the vehicle body. From an aerodynamics perspective, understanding and managing this flow field are critical for drag reduction, wheel design, and brake cooling. Furthermore, the validation of numerical simulation methodology is essential for a systematic approach to aerodynamically efficient wheel design as a standard practice of vehicle design. This paper presents a correlation the near-wheel flow field for both front and rear spinning wheels with two different wheel designs for a Ram Quad Cab pick-up truck with moving ground. Twelve-hole probe experimental data obtained in a wind tunnel with a full width belt system are compared to the predictions of numerical simulations.

Aerodynamic efficiency plays an increasingly important role in the automotive industry, as the push for increased fuel economy becomes a larger factor in the engineering and design process. Longitudinal drag is used as the primary measure of aerodynamic performance, usually cited as the coefficient of drag (CD). This drag is created mostly by the body shape of the vehicle, but the wheel and tire system also contributes a significant portion. In addition to the longitudinal drag created by the body and wheels, rotational drag can add an appreciable amount of aerodynamic resistance to the vehicle as well. Reducing power consumption is an especially vital aspect in electric vehicle (EV) design. As the world's first luxury electric sedan, the Tesla Model S combines a premium driving experience with an electric drivetrain package that allows for unique solutions to many vehicle subsystems.