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Efforts in aerodynamic optimization of road vehicles have been steadily increasing in recent years, mainly focusing on the reduction of aerodynamic drag. Of a car's total drag, wheels and wheel houses account for approx. 25 percent. Consequently, the flow around automotive wheels has lately been investigated intensively. Previously, the authors studied a treaded, deformable, isolated full-scale tire rotating in contact with the ground in the wind tunnel and using the Lattice-Boltzmann solver Exa PowerFLOW. It was shown that applying a common numerical setup, with velocity boundary condition prescribed on the tread, significant errors were introduced in the simulation. The contact patch separation was exaggerated and the flow field from wind tunnel measurements could not be reproduced. This investigation carries on the work by examining sensitivities and new approaches in the setup.

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.

For car manufacturers, seating comfort is becoming more and more important in distinguishing themselves from their competitors. There is a simultaneous demand for shorter development times and more comfortable seats. Comfort in automobile seats is a multi-dimensional and complex problem. Many current sophisticated measuring tools were consulted, but it is unclear on which factors one should concentrate attention when measuring comfort. The goal of this paper is to find a model in order to predict the overall seating discomfort based on body area ratings. Besides micro climate, the pressure distribution appears to be the most objective measure comprising with the clearest association with the subjective ratings. Therefore an analysis with three different test series was designed, allowing the variation of pressure on the seat surface. In parallel the subjects were asked to judge the local and the overall sensation.

Being able to integrate consumer electronics (CE) devices into the automobile is an increasingly important goal. In this paper, we focus on the HMI (human machine interaction) aspects of consumer electronics in the car. We describe the requirements concerning HMI integration of consumer electronics and offer several possible solutions. One of the requirements is minimal driver distraction. A desired property in this context concerns the mental model that the user builds of the service that is to be operated: ideally, this model (i.e., appearance and interaction logic) need not change when integrating the service into the automobile, even though the operating elements differ considerably (e.g., touch screen vs. iDrive commander). A further requirement is posed by the dynamic nature of CE services: often, they are not known at design/deploy time of the HMI software of the automobile.

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.

Efficiency and dynamic behavior of a vehicle are strongly affected by its weight. Taking into consideration comfort, safety and emissions in modern automobiles, lightweight design is more of a challenge than ever in automotive engineering. Materials development plays an important role against this background, since significant weight decrease is made possible through the substitution of high density materials and more precise adjustment of material parameters to the functional requirements of components. Reinforced light metals, therefore, offer a promising approach due to their high strength to weight ratio. The paper gives an overview on matrix and reinforcement structures suited for the high volume output of the automotive industry. Further analytical and numerical approaches to describe the strengthening effects and the good mechanical characteristics of these composite materials are presented.

Currently, the aerodynamic development of a car concentrates on steady state aerodynamic forces. Development is mainly performed in wind tunnels with very low turbulence. On the road we find other boundary conditions. Natural wind, other cars and trucks influence the yawing moment and the side force. During acceleration and deceleration the vehicle speed is not constant, the effect of unsteady aerodynamic forces is especially important and can not be neglected. The approach to measure unsteady effects is to use a wind tunnel that has the capability to produce unsteady flow and in addition to instrument a car to drive under natural windy conditions. The wind tunnel, with its reproducible conditions, allows measurements to be made with well defined frequencies of the approaching flow. This is important since the aerodynamic forces are not sensitive to all frequencies in the same way. One way to increase driving comfort is to reduce these forces at specific frequencies.

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.

As the popularity of vehicle navigation systems rises, incorporating Real Time Traffic Information (RTTI) has been shown to enhance the systems' value by helping drivers avoid traffic delays. As an innovative premium automaker, BMW has developed a testing process to acquire and analyze RTTI data in order to ensure delivery of a high quality service and to enhance the customer experience compared to audible broadcast services. With a methodology to obtain valid and repeatable RTTI data quality measurements, BMW and its service partner, Clear Channel's Total Traffic Network (TTN), can improve its offered service over time, implement corrective measures when appropriate, and confidently ensure the service meets its premium objectives. BMW has partnered with TTN and SoftSolutions GmbH to implement a traffic data quality process and software tools.

Underbody aerodynamics has become increasingly important over the last three decades because of its vital contribution to improving a vehicle's overall performance. This was the motivation for the research conducted by BMW Aerodynamics, concerning the determination of the overall pressure distribution on the underbody of a series-production vehicle. Static pressure measurements have been taken under various test conditions. Real on-road tests were carried out as well as wind tunnel experiments under application of different road simulation techniques. The analyzed vehicle configurations include wheel rim-tire and body modifications. The results presented include surface pressure data, drag and lift coefficients, ride heights, pitch and roll angles. The acquired data is used to examine the underbody flow topology and determine how the diverse attempts to represent the real on-road conditions affect its pressure distribution.

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.

In the environmentally conscious world we live in, auto manufacturers are under extreme pressure to reduce tailpipe emissions from cars and trucks. The manufacturers have responded by creating clean-burning engines and exhaust treatments that mainly produce CO2 and water vapor along with trace emissions of pollutants such as CO, THC, NOx, and CH4. The trace emissions are regulated by law, and testing must be performed to show that they are below a certain level for the vehicle to be classified as road legal. Modern engine and pollution control technology has moved so quickly toward zero pollutant emissions that the testing technology is no longer able to accurately measure the trace levels of pollutants. Negative emission values are often measured for some pollutants, as shown by results from eight laboratories independently testing the same SULEV automobile.

Cutting development times in car manufacturing means bringing forward the knowledge processes. Simulations based directly on CAD data reduce or replace time-consuming hardware loops significantly and therefore make a significant contribution to this. Ergonomic product design is an area that is challenged as far as the further development of virtual methods is concerned. Simulation of the static and quasi-static positions of passengers inside the car is the current state of the art in ergonomic product design. For this reason, interest is strongly focused on the simulation of complex movement processes within the context of enhancing simulation tools. For the car manufacturer, the manner in which people enter and leave the car is of particular interest. Getting into the car is the customers' first actual contact with it. It may also develop into a serious problem for car drivers, as they get older.

A new generation of BMW child seat and occupant detection system SBE2 for a smart airbag system is described. The SBE2 system consists of two subsystems: OC (occupant classification) and FDS (field detection system). The OC system is a force-sensitive sensor array that measures a pressure profile. The FDS system detects child seat and occupant according to the change of electrical field generated by four capacitive plates. Combining the signals from both subsystems, the BMW SBE2 system can distinguish fully automatically between a child seat and a person.

Engine management systems in modern motor vehicles are becoming increasingly extensive and complex. The functionality of the control units which are the central components of such systems is determined by the hardware and software. They are the result of a lengthy development and production process. Road testing of control units, together with testing them on the engine test bench, is very time consuming and costly. An alternative is to test control units away from their actual environment, in a virtual context. This involves operating the control unit on a Hardware-in-the-Loop test bench. The control unit's large number of individual and interlinked functions necessitates a structured, reproducible test procedure. These tests can, however, only be conducted once an engine prototype has been completed, as the parameters for the existing conventional models are determined from the data measured on the test bench.

Unsteady aerodynamic flow phenomena are investigated in the wind tunnel by oscillating a realistic 50% scale model around its vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi-steady loads. In particular, the unsteady yaw moment exceeds the quasi-steady approximation by 80%. On the other hand, side force and roll moment are over predicted by quasi-steady approximation but exhibit a significant time delay. Using hotwire anemometry, a delayed reaction of the wake flow of Δt/T = 0.15 is observed, which is thought to be the principal cause for the differences between unsteady and quasi-steady aerodynamic loads. A schematic mechanism explaining these differences due to the delayed reaction of the wake flow is proposed.

Unsteady aerodynamic flow phenomena are investigated in a wind tunnel by oscillating a realistic 50% scale model around the vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi steady loads. In particular, the unsteady yaw moment exceeds the quasi steady approximation significantly. On the other hand, side force and roll moment are over predicted by quasi steady approximation but exhibit a significant time delay. Part 2 of this study proves that a delayed and enhanced response of the surface pressures at the rear side of the vehicle is responsible for the differences between unsteady and quasi steady loads. The pressure changes at the vehicle front, however, are shown to have similar amplitudes and almost no phase shift compared to quasi steady flow conditions.

Highly Automated Driving (HAD) opens up new middle-term perspectives in mobility and is currently one of the main goals in the development of future vehicles. The focus is the implementation of automated driving functions for structured environments, such as on the motorway. To achieve this goal, vehicles are equipped with additional technology. This technology should not only be used for a limited number of use cases. It should also be used to improve Active Safety Systems during normal non-automated driving. In the first approach we investigate the usage of machine learning for an autonomous emergency braking system (AEB) for the active pedestrian protection safety. The idea is to use knowledge of accidents directly for the function design. Future vehicles could be able to record detailed information about an accident. If enough data from critical situations recorded by vehicles is available, it is conceivable to use it to learn the function design.

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.

A test center for aging analysis and characterization of Lithium-Ion batteries for automotive applications is optimized by means of a dedicated cell tester. The new power tester offers high current magnitude with fast rise time in order to generate arbitrary charge and discharge waveforms, which are identical to real power net signals in vehicles. Upcoming hybrid and electrical cars show fast current transients due to the implemented power electronics like inverter or DC/DC converter. The various test procedures consider single and coupled effects from current profile, state of charge and temperature. They are simultaneously applied on several cells in order to derive statistical significance. Comprehensive safely functions on both the hardware and the software level ensure proper operation of the complex system.