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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.

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.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (≻ 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying 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 development of a reliable numerical prediction capability. This paper presents a computational approach that can be used to predict the vehicle interior noise from the greenhouse wind noise sources, during the early stages of the vehicle developmental process so that design changes can be made to improve the wind noise performance of the vehicle.

Trucks can carry heavy load and when applying the brakes during for example a mountain downhill or for an abrupt stop, the brake temperatures can rise significantly. Elevated temperatures in the drum brake region can reduce the braking efficiency or can even cause the brake system to fail, catch fire or even break. It therefore needs to be designed such to be able to transfer the heat out of its system by convection, conduction and/or radiation. All three heat transfer modes play an important role since the drum brakes of trucks are not much exposed to external airflow, a significant difference from disk brakes of passenger cars analyzed in previous studies. This makes it a complex heat transfer problem which is not easy to understand. Numerical methods provide insight by visualization of the different heat transfer modes. Presented is a numerical method that simulates the transient heat transfer of a truck drum brake system cooldown at constant driving speed.

Once the design of a door sheetmetal and accessories is confirmed, the acoustics of the door system depends on the sound package assembly. This essentially consists of a watershield which acts as a barrier and a porous material which acts as an absorber. The acoustical performance of the watershield and the reverberant sound build-up in the door cavity control the performance. This paper discusses the findings of a design study that was developed based on design of experiments (DOE) concepts to determine which parameters of the door sound package assembly are important to the door acoustics. The study was based on conducting a minimum number of tests on a five factor - two level design that covered over 16 different design configurations. In addition, other measurements were made that aided in developing a SEA model which is also compared with the findings of the results of the design study.

Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.

Load data representing severe customer usage is required during the chassis development process. One area of current research is the use of road profiles for predicting chassis loads. The most direct method of predicting these loads is to run dynamic simulations of the vehicle using numerous road profiles as the excitation. This onerous task may be avoided, and a greatly reduced number of simulations would be required, if roads having similar characteristics can be grouped. Currently, road profiles are characterized by their spectral content. It has been noted by several researches, however, that road profiles are generally nonstationary signals that contain significant transient events and are not well described in the spectral domain. The objective of this work, then, is to develop a method by which the characteristics of the road can be captured by describing these constitutive transient events.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

A simple strategy for building lightweight automobile body-in-whites (BIWs) is developed and discussed herein. Because cost is a critical factor, expensive advanced materials, such as carbon fiber composites and magnesium, must only be used where they will be most effective. Constitutive laws for mass savings under various loading conditions indicate that these materials afford greater opportunity for mass saving when used in bending, buckling or torsion than in tensile, shear or compression. Consequently, it is recommended that these advanced materials be used in BIW components subject to bending and torsion such as rails, sills, “A-B-C” pillars, etc. Furthermore, BIW components primarily subject to tension, compression, or shear, such as floor pans, roofs, shock towers, etc., should be made from lower cost steel. Recommendations for future research that are consistent with this strategy are included.

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.

As the hybrid automotive market becomes quickly saturated with highly competitive products and vehicles, auto manufacturers struggle with business models and the combination of current manufacturing with next generation development. The hybrid development cooperation amongst General Motors, DaimlerChrysler, and BMW offers a new business model that promotes the advancement of the state of strong hybrid technology while maintaining the strong global leadership and competition.

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.

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.

As part of the United States Department of Energy's SuperTruck program, Volvo Trucks and its partners were tasked with demonstrating 50% improvement in overall freight efficiency for a tractor-trailer, relative to a best in class 2009 model year truck. This necessitated that significant gains be made in reducing aerodynamic drag of the tractor-trailer system, so trailer side-skirts and a trailer boat-tail were employed. A Lattice-Boltzmann based simulation method was used in conjunction with a Kriging Response Surface optimization process in order to efficiently describe a design space of seven independent parameters relating to boat-tail and side-skirt dimensions, and to find an optimal configuration. Part 1 concerns a fully-skirted tractor-trailer system, and consists of an initial phase of optimization, followed by a mid-project re-evaluation of constraints, and an additional period of optimization.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.

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.

The aerodynamics of a rotating tire can contribute up to a third of the overall aerodynamic force on the vehicle. The flow around a rotating tire is very complex and is often affected by smallest tire features. Accurate prediction of vehicle aerodynamics therefore requires modeling of tire rotation including all geometry details. Increased simulation accuracy is motivated by the needs emanating from stricter new regulations. For example, the upcoming Worldwide harmonized Light vehicles Test Procedures (WLTP) will place more emphasis on vehicle performance at higher speeds. The reason for this is to bring the certified vehicle characteristics closer to the real-world performance. In addition, WLTP will require reporting of CO2 emissions for all vehicle derivatives, including all possible wheel and tire variants. Since the number of possible derivatives can run into the hundreds for most models, their evaluation in wind tunnels might not be practically possible.

The accuracy of the Lattice-Boltzmann based simulation method for prediction of aerodynamic drag on a heavy truck was evaluated by comparing results to twenty percent scale model wind tunnel measurements from the University of Washington Aeronautical Laboratory (UWAL). A detailed preproduction Kenworth T2000 tractor trailer was used as the scale model. The results include a comparison of normalized drag between simulation and wind tunnel as well as percentage drag change with the addition of a radius to the rear edge of the trailer. Significant effort was involved to model all of the wind tunnel details affecting the tractor-trailer drag. These are discussed along with the results of additional simulations which were performed to study the impact of the UWAL tunnel geometry relative to a tunnel with the same blockage and constant cross-sectional area, and a case with negligible blockage.

Aerodynamic simulations of a 1:8-scale simplified tractor-trailer, designated as the Generic Conventional Model (GCM), were conducted using a Lattice-Boltzmann based solver. Comparisons were made to experimental measurements from the NASA Ames 12-Foot Pressure Wind Tunnel, including drag coefficients as a function of yaw, static and transient surface pressures, and three-component particle image velocimetry. The baseline model configuration was tested at yaw angles from 0 to 12 degrees, allowing the calculation of the wind-averaged drag coefficient. Results demonstrated that the simulation predicted body-axis drag within experimental uncertainty and also resolved the correct pressure distribution and flow structure in the separated flow regions including the tractor-trailer gap and trailer wake regions. The comparison of the experimental transient pressure spectra showed good agreement with the simulation results, both in magnitude and identification of dominant spectral peaks.

The importance of fuel economy and emission standards has increased rapidly with high fuel costs and new environmental regulations. This requires analysis techniques capable of designing the next generation long-haul truck to improve both fuel efficiency and cooling. In particular, it is important to have a predictive design tool to assess how exterior design changes impact aerodynamic performance. This study evaluates the use of a Lattice Boltzmann based numerical simulation and the National Research Council (NRC) Canada's wind tunnel to assess aerodynamic drag on a production Volvo VNL tractor-trailer combination. Comparisons are made between the wind tunnel and simulation to understand the influence of wind tunnel conditions on truck aerodynamic performance. The production VNL testing includes a full range of yaw angles to demonstrate the influence of cross wind on aerodynamic drag.