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The high cost and competitive nature of automotive product development necessitates the search for less expensive and faster methods of predicting vehicle performance. Continual improvements in High Performance Computing (HPC) and new computational schemes allow for the digital evaluation of vehicle comfort parameters including wind noise. Recently, the commercially available Computational Fluid Dynamics (CFD) code PowerFlow, was evaluated for its accuracy in predicting wind noise generated by an external automotive tow mirror. This was accomplished by running simulations of several mirror configurations, choosing the quietest mirror based on the predicted performance, prototyping it, and finally, confirming the prediction with noise measurements taken in an aeroacoustic wind tunnel. Two testing methods, beam-forming and direct noise measurements, were employed to correlate the physical data with itself before correlating with simulation.

For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

In the development of an FAW SUV, one of the goals is to achieve a state of the art drag level. In order to achieve such an aggressive target, feedback from aerodynamics has to be included in the early stage of the design decision process. The aerodynamic performance evaluation and improvement is mostly based on CFD simulation in combination with some wind tunnel testing for verification of the simulation results. As a first step in this process, a fully detailed simulation model is built. The styling surface is combined with engine room and underbody detailed geometry from a similar size existing vehicle. From a detailed analysis of the flow field potential areas for improvement are identified and five design parameters for modifying overall shape features of the upper body are derived. In a second step, a response surface method involving design of experiments and adaptive sampling techniques are applied for characterizing the effects of the design changes.

On-highway tractor-trailer vehicles operate in a complex aerodynamic environment that includes influences of surrounding vehicles. Typical aerodynamic analyses and testing of single vehicles on test track, in wind tunnel or in computational fluid dynamics (CFD) do not account for these real world effects. However, it is possible with simulation and on-road testing to evaluate these aerodynamic interactions. CFD and physical testing of multiple vehicle interactions show that traffic interactions can impact the overall drag of leading and trailing vehicles. This paper will discuss results found in evaluating the effects of separation distances on tractor-trailer aerodynamics in on-road and CFD evaluations using a time-accurate Lattice Boltzmann Method based approach and the ramifications for improving real world prediction versus controlled single vehicle testing.

Fuel efficiency for tractor/trailer combinations continues to be a key area of focus for manufacturers and suppliers in the commercial vehicle industry. Improved fuel economy of vehicles in transit can be achieved through reductions in aerodynamic drag, tire rolling resistance, and driveline losses. Fuel economy can also be increased by improving the efficiency of the thermal to mechanical energy conversion of the engine. One specific approach to improving the thermal efficiency of the engine is to implement a waste heat recovery (WHR) system that captures engine exhaust heat and converts this heat into useful mechanical power through use of a power fluid turbine expander. Several heat exchangers are required for this Rankine-based WHR system to collect and reject the waste heat before and after the turbine expander. The WHR condenser, which is the heat rejection component of this system, can be an additional part of the front-end cooling module.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

For the automotive industry, the quality and level of the wind noise contribution has a growing importance and therefore should be addressed as early as possible in the development process. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof broadband noise is generated by the turbulent flow developed over the roof opening. A strong shear layer and vortices impacting on the trailing edge of the sunroof are typical mechanisms related to the noise production. Sunroof designs are tested to meet broadband noise targets. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions and potentially late design changes.

Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.

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.

Modern aerodynamic Class 8 freight tractors can improve vehicle freight efficiency and fuel economy versus older traditional style tractors when pulling Canadian style A- or B-Train double trailer long combination vehicles (LCV's) at highway speeds. This paper compares the aerodynamic performance of a current generation aerodynamic tractor with several freight hauling configurations through computational fluid dynamics evaluations using the Lattice-Boltzmann methodology. The configurations investigated include the tractor hauling a standard 53′ trailer, a platooning configuration with a 30′ separation distance, and an A-Train configuration including two 48′ trailers connected with a dolly converter. The study demonstrates CFD's capability of evaluating extremely long vehicle combinations that might be difficult to accomplish in traditional wind tunnels due to size limitations.

The primary purpose of this paper is to correlate the CFD simulations performed using PowerFLOW, a Lattice Boltzmann based method, and wind tunnel tests performed at a wind tunnel facility on 1/8th scaled tractor-trailer models. The correlations include results using an aerodynamic-type tractor paired with several trailer configurations, including a baseline trailer without any aerodynamic devices as well as combinations of trailer side skirts and a tractor-trailer gap flow management device. CFD simulations were performed in a low blockage open road environment at full scale Reynolds number to understand how the different test environments impact total aerodynamic drag values and performance deltas between trailer aerodynamic devices. There are very limited studies with the Class-8 sleeper tractor and 53ft long trailer comparing wind tunnel test and CFD simulation with and without trailer aerodynamic device. This paper is to fill this gap.

The ultimate goal for vehicle aerodynamicists is to develop vehicles that perform well on the road under real-world conditions. One of the most important metrics to evaluate vehicle performance is the drag coefficient. However, vehicle development today is performed mostly under controlled settings using wind tunnels and computational fluid dynamics (CFD) with artificially uniform upstream conditions, neglecting real-world effects due to road turbulence from wind and other vehicles. Thus, the drag coefficients computed with these methods might not be representative of the real performance of the car on the road. This might ultimately lead engineers to develop design solutions and aerodynamic devices which, while performing well in idealized conditions, do not perform well on the road. For this reason, it is important to assess the vehicle’s drag as seen in real-world environments. An effort in this direction is represented by using the wind-averaged drag.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

As vacuum suction cups are widely used in stamping plants, it becomes urgent and important to understand their performance and failure mode. Vacuum suction cups are employed to lift, move, and place sheet metal instead of human hands. Occasionally the vacuum cups would fail and drop parts, even it would cause expensive delays in the production line. In this research, several types of vacuum cups have been studies and compared experimentally. A new tensile device and test method was developed to measure the pulling force and deformation of vacuum cups. The digital image correlation technique has been adopted to capture and analyze the contour, deformation and strain of the cups under different working conditions. The experimental results revealed that the relevant influential parameters include cup type, pulling force angles, vacuum levels, sheet metal curvatures, etc.

Self-piercing riveting (SPR) has been used in production to join sheet materials since the early 1990s. A large amount of experimental trial work was required in order to determine an appropriate combination of rivet and anvil design to fulfill the required joint parameters. The presented study is describing the methodology of SPR joint design based on numerical simulation and experimental methods of defining required simulation input parameters. The required inputs are the stress-strain curves of sheet materials and rivets for the range of strains taking place in the SPR joining process, parameters required for a fracture model for all involved materials, and friction parameters for all interfaces of SPR process. In the current study, the normalized Cockroft-Latham fracture criterion was used for predicting fracture. Custom hole and tube expansion tests were used for predicting fracture of the riveted materials and the rivet, respectively.

A correlation study was performed between static wind tunnel testing and computational fluid dynamics (CFD) for a small hatchback vehicle, with the intent of evaluating a variety of different wheel and tire designs for aerodynamic forces. This was the first step of a broader study to develop a tool for assessing wheel and tire designs with real world (rolling road) conditions. It was discovered that better correlation could be achieved when actual tire scan data was used versus traditional smooth (CAD) tire geometry. This paper details the process involved in achieving the best correlation of the CFD prediction with experimental results, and describes the steps taken to include the most accurate geometry possible, including photogrammetry scans of an actual tire that was tested, and the level of meshing detail utilized to capture the fluid effects of the tire detail.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

Numerical simulation of aerodynamics for vehicle development is used to meet a wide range of performance targets, including aerodynamic drag for fuel efficiency, cooling flow rates, and aerodynamic lift for vehicle handling. The aerodynamic flow field can also be used to compute the advection of small particles such as water droplets, dust, dirt, sand, etc., released into the flow domain, including the effects of mass, gravity, and the forces acting on the particles by the airflow. Previous efforts in this topic have considered the water sprays ejected by rotating wheels when driving on a wet road. The road spray carries dirt particles and can obscure the side and rear glazing. In this study, road sprays are considered in which the effects of additional water droplets resulting from splashing and dripping of particles from the wheel house and rear under body are added to help understand the patterns of dirt film accumulation on the side glass and rear glass.

A vehicle on the road encounters an unsteady flow due to turbulence in the natural wind, the unsteady wakes from other vehicles and as a result of traversing through the stationary wakes of road side obstacles. There is increasing concern about potential differences in aerodynamic behaviour measured in steady flow wind tunnel conditions and that which occurs for vehicles on the road. It is possible to introduce turbulence into the wind tunnel environment (e.g. by developing active turbulence generators) but on-road turbulence is wide ranging in terms of both its intensity and frequency and it would be beneficial to better understand what aspects of the turbulence are of greatest importance to the aerodynamic performance of vehicles. There has been significant recent work on the characterisation of turbulent airflow relevant to road vehicles. The simulation of this time-varying airflow is now becoming possible in wind tunnels and in CFD.

Long haul tractor design in the future will be challenged by freight efficiency standards and emission legislations. Along with any improvements in aerodynamics, this will also require additional cooling capacity to handle the increased heat rejection from next generation engines, waste heat recovery and exhaust gas recirculation systems. Fan engagement will also have to be minimized under highway conditions to maximize fuel economy. These seemingly contradictory requirements will require design optimization via analysis techniques capable of predicting both the aerodynamic drag and engine cooling airflow accurately. This study builds on previous work [1] using a Lattice Boltzmann based computational method on a Volvo VNL tractor trailer combination. Simulation results are compared to tests conducted at National Research Council (NRC) Canada's wind tunnel.