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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. The goal of this paper is to present a computational approach developed to predict the greenhouse windnoise contribution to the interior noise heard by the vehicle passengers. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the windnoise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior.

Over the past 30 years, the computer-aided engineering (CAE) tools have been applied extensively in the automotive industry. In order to accelerate time-to-market while coping with legal limits that have become increasingly restrictive over the last decades, CAE has become an indispensable tool covering all major fields in a modern automotive product design process. However, when tackling complex real-life engineering problems, the computational models might become rather involved and thus less efficient. Therefore, the overall trend in the automotive industry is currently heading towards combined approaches, which allow the best of the both worlds, namely the experimental measurement and numerical simulation, to be merged into one integrated scheme. In this paper, the so-called patch transfer function (PTF) approach is adopted to solve coupled vibro-acoustic problems. In the PTF scheme, the interfaces between fluid and structure are discretised in terms of patches.

In order to correctly predict the impact of tire dimensions and properties on ride comfort in the early phases of the vehicle development process, it is necessary to fully understand their influence on the dynamic tire behavior. The currently existing models for reproducing tire forces often need many measurements for parametrization, simplify physical properties by empiric functions, or have an insufficient simulation speed to analyze many variants in the short periods of early process phases. In the following analysis, a tire concept model is presented, which utilizes relations between the static and dynamic behavior of tires in order to efficiently predict the dynamic forces in the vertical and longitudinal direction during obstacle crossing. The model allows for efficient parametrization by minimizing the number of parameters as well as measurements and ensures a high simulation speed. To realize this, initially, a selection of tires is measured on a tire test rig.

The analysis of the acoustic behavior of flow fields has gained importance in recent years, especially in the automotive industry. The comfort of the driver is heavily influenced by the noise levels and characteristics, especially during long distance drives. Simulation tools can help to analyze the acoustic properties of a car at an early stage of the development process. This work focuses on the low-frequency sound effects, which can be a significant noise component under certain operating conditions. As a first step in the fluid-structure interaction workflow, the flow around a series-production vehicle is simulated, including passenger cabin and underhood flow. The complexity of this model poses extensive demands on the simulation software, concerning meshing, turbulence modeling and level of parallelism. We conducted a transient simulation of the compressible fluid flow, using a hybrid RANS/LES approach.

Comfort and well-being have always been connected with a flawless interior acoustic, free of any background noise or BSR, (buzz, squeak and rattle). BSR noises dominate the interior acoustic and represent one of the main sources for discomfort often causing considerable warranty costs. Traditionally BSR issues have been identified and rectified through extensive hardware testing, which by its nature intensifies toward the end of the car development process. In the following paper the integration of a virtual BSR validation technique in a modern development process by the use of appropriate CAE methods is presented. The goal is to shift, in compliance with the front loading concept, the development activities into the early phase. The approach is illustrated through the example of an instrument panel, from the early concept draft for single components to an assessment of the complete assembly.

As computational methodologies become more integrated into industrial vehicle pre-development processes the potential for high transient vehicle thermal simulations is evident. This can also been seen in conjunction with the strong rise in computing power, which ultimately has supported many automotive manufactures in attempting non-steady simulation conditions. The following investigation aims at exploring an efficient means of utilizing the new rise in computing resources by resolving high time-dependent boundary conditions through a series of averaging methodologies. Through understanding the sensitivities associated with dynamic component temperature changes, optimised boundary conditions can be implemented to dampen irrelevant input frequencies whilst maintaining thermally critical velocity gradients.

Open jet wind tunnels are normally tuned to measure “correct” results without any modifications to the raw data. This is an important difference to closed wall wind tunnels, which usually require wind tunnel corrections. The tuning of open jet facilities is typically done experimentally using pilot tunnels and adding final adjustments in the commissioning phase of the full scale tunnel. This approach lacked theoretical background in the past. There is still a common belief outside the small group of people designing and using open jet wind tunnels, that - similar to closed wind tunnels, which generally measure too high aerodynamic forces and moments without correction - open jet wind tunnels measure coefficient too low compared to the real world. The paper will try to show that there is a solid physical foundation underlying the experimental approach and that the expectation to receive self-correcting behavior can be supported by theoretical models.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

Future automotive systems will be connected with other vehicles and information systems for improved road safety, mobility and comfort. This new connectivity establishes data and command channels between the internal automotive system and arbitrary external entities. One significant issue of this paradigm shift is that formerly closed automotive systems now become open systems that can be maliciously influenced through their communication interfaces. This introduces a new class of security challenges for automotive design. It also indirectly impacts the safety mechanisms that rely on a closed-world assumption for the vehicle. We present a new security analysis approach that helps to identify and prioritize security issues in automotive architectures. The methodology incorporates a new threat classification for data flows in connected vehicle systems.

Advanced Driver Assistance systems support the driver in his driving tasks. They can be designed to enhance the driver's performance and/or to take over unpleasant tasks from the driver. An important optimization goal is to maintain the driver's activation at a moderate level, avoiding both stress and boredom. Functions requiring a situational interpretation based on the vehicle environment are associated with lower performance reliability than typical stability control systems. Thus, driver assistance systems are designed assuming that drivers will monitor the assistance function while maintaining full control over the vehicle, including the opportunity to override as required. Advanced driver assistance systems have a substantial potential to increase active safety performance of the vehicle, i.e., to mitigate or avoid traffic accidents.

Advanced material technologies play a key role in automotive engineering. The main objective of the development of advanced material technologies for automotive applications is to promote the desired properties of a vehicle. It is characteristic of most materials in modern cars that they have been developed especially for automotive requirements. Requirements are not only set by the customer who expects the maximum in performance, comfort, reliability, and safety from a modern car. Existing legal regulations also have to be met, e.g., in the areas of environmental compatibility, resource preservation, and minimization of emissions. To achieve goals like weight reduction or increased engine performance permanent material developments are essential. In this paper, numerous examples chosen from body, suspension, and powertrain components show clearly how low weight technologies, better comfort, and high level of recyclability can be achieved by advanced material solutions.

The aim of this report is to present the results obtained from the wind tunnel tests performed in the BMW wind tunnel regarding the pressure distribution on a rotating wheel. The acquired data is used to examine its flow topology for the “open” and “enclosed” cases and determine the wheel drag, lift and side forces by integrating the pressure distribution on its surface. The investigation concerned such measurements on a half scale model wheel. Its pressure distribution was identified with and without the presence of a racecar body. The wheel was also mounted on a half scale passenger car body and pressure measurements were taken with and without a wheel spoiler. After the pressure distributions were known for all configurations, the aerodynamic forces generated were determined. The influence of boundary layer thickness on them was also investigated. A better understanding of the forces the model wheel is subjected to is gained.

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.

The detailed presentation of fundamental aerodynamics principles that influence and improve vehicle design have made Aerodynamics of Road Vehicles the engineer’s “source” for information. This fifth edition features updated and expanded information beyond that which was presented in previous releases. Completely new content covers lateral stability, safety and comfort, wind noise, high performance vehicles, helmets, engine cooling, and computational fluid dynamics.

The importance of the automotive interior as a characteristic feature in the competition for the goodwill of the customer has increased significantly in recent years. Whilst there are established, more or less efficient CAE processes for the solution of problems in the areas of occupant safety and service strength, until now the implementation of CAE in themes such as dimensional stability, warpage and corrugation1 of plastic parts has been little investigated. The developmental support in this field is predominantly carried out by means of hardware tests. Real plastic components alter their form as a result of internal forces often during the first weeks following production. The process, known as “creep”, can continue over an extended period of time and is exacerbated by high ambient temperatures and additional external loads stemming from installation and post assembly position.

Within the pre-development phase of a vehicle validation process, the role of computational simulation is becoming increasingly prominent in efforts to ensure thermal safety. This gain in popularity has resulted from the cost and time advantages that simulation has compared to experimental testing. Additionally many of these early concepts cannot be validated through experimental means due to the lack of hardware, and must be evaluated via numerical methods. The Race Track Simulation (RTS) can be considered as the final frontier for vehicle thermal management techniques, and to date no coherent method has been published which provides an efficient means of numerically modeling the temperature behavior of components without the dependency on statistical experimental data.

In this paper, the human intra- and interpersonal adjustment accuracy (or aiming) of headlamp cutoff lines with different methods are examined. Intrapersonal aiming accuracy is the repeatability of a single person, while interpersonal aiming accuracy describes the differences between different people. For this purpose, a study is developed, implemented and evaluated. In one experiment, the subjects set up three different headlamps using three different methods according to the ECE regulation. In addition, the three adjustment methods used are compared with each other and evaluated in terms of the variation resulting aim. The most common aiming method, the visual adjustment of the cutoff line, such as the 10-meter wall method or analog headlamp aiming devices shows the highest variations. It is shown that digital headlamp aiming devices generally also have a lower dispersion variance, while still being better than all other adjustment methods.

A computational analysis of underbody windnoise sources on a production automobile at 180 km/h free stream air speed and 0° yaw is presented. Two different underbody geometry configurations were considered for this study. The numerical results have been obtained using the commercial software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice-Boltzmann Method (LBM), combined with a two-equation RNG turbulence model. This scheme accurately captures time-dependent aerodynamic behavior of turbulent flows over complex detailed geometries, including the pressure fluctuations causing wind noise. Comparison of pressure fluctuations levels mapped on a fluid plane below the underbody shows very good correlation between experiment and simulation. Detailed flow analysis was done for both configurations to obtain insight into the transient nature of the flow field in the underbody region.

The aerodynamic optimization of an AUDI Q5 vehicle is presented using the continuous adjoint approach within the OpenFOAM framework. All calculations are performed on an unstructured automatically generated mesh. The primal flow, which serves as input for the adjoint method, is calculated using the standard CFD process at AUDI. It is based on DES calculations using a Spalart-Allmaras turbulence model. The transient results of the primal solution are time averaged and fed to a stationary adjoint solver using a frozen turbulence assumption. From the adjoint model, drag sensitivity maps are computed and measures for drag reduction are derived. The predicted measures are compared to CFD simulations and to wind tunnel experiments at 1:4 model scale. In this context, general challenges, such as convergence and accuracy of the adjoint method are discussed and best practice guidelines are demonstrated.

A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity.