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The optimization of the vaporization and mixture formation process is of great importance for the development of modern gasoline direct injection (GDI) engines, because it influences the subsequent processes of the ignition, combustion and pollutant formation significantly. In consequence, the subject of this work was the development of a measurement technique based on the laser induced exciplex fluorescence (LIF), which allows the two dimensional visualization and quantification of the in-cylinder air/fuel ratio. A tracer concept consisting of benzene and triethylamine dissolved in a non-fluorescent base fuel has been used. The calibration of the equivalence ratio proportional LIF-signal was performed directly inside the engine, at a well known mixture composition, immediately before the direct injection measurements were started.

A study was conducted using Ford's nine standard CFD calibration models as described in SAE paper 940323. The models are identical from the B-pillar forward but have different back end configurations. These models were created for the purpose of evaluating the effect of back end geometry variations on aerodynamic lift and drag. Detailed experimental data is available for each model in the form of surface pressure data, surface flow visualization, and wake flow field measurements in addition to aerodynamic lift and drag values. This data is extremely useful in analyzing the accuracy of the numerical simulations. The objective of this study was to determine the capability of a digital physics based commercial CFD code, PowerFLOW ® to accurately simulate the physics of the flow field around the car-like benchmark shapes.

This paper presents an approach to numerically simulate greenhouse windnoise. The term “greenhouse windnoise” here describes the sound transferred to the interior through the glass panels of a series vehicle. Different panels, e.g. the windshield or sideglass, are contributing to the overall noise level. Attached parts as mirrors or wipers are affecting the flow around the vehicle and thus the pressure fluctuations which are acting as loads onto the panels. Especially the wiper influence and the effect of different wiper positions onto the windshield contribution is examined and set in context with the overall noise levels and other contributors. In addition, the effect of different flow yaw angles on the windnoise level in general and the wiper contributions in particular are demonstrated. As computational aeroacoustics requires accurate, highly resolved simulation of transient and compressible flow, a Lattice-Boltzmann approach is used.

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.

A computational process for early stage vehicle shape assessment for automotive front window buffeting and greenhouse wind noise is presented. It is a challenging problem in an experimental process as the vehicle geometry is not always finalized. For example, the buffeting behavior typically worsens during the vehicle development process as the vehicle gets tighter, leading to expensive late counter measures. We present a solution using previously validated CFD/CAA software based on the Lattice Boltzmann Method (LBM). A CAD model with realistic automotive geometry was chosen to simultaneously study the potential of different side mirror geometries to influence the front window buffeting and greenhouse wind noise phenomena. A glass mounted mirror and a door mounted mirror were used for this comparative study. Interior noise is investigated for the two phenomena studied. The unsteady flow is visualized and changes in the buffeting and wind noise behavior are explored.

Vehicle thermal management (VTM) simulations are becoming increasingly important in the development phase of a vehicle. These simulations help in predicting the thermal profiles of critical components over a drive cycle. They are usually done using two methodologies: (1) Solving every aspect of the heat transfer, i.e., convection, radiation, and conduction, in a single solver (Conjugate Heat Transfer) or (2) Simulating convection using a fluid solver and computing the other two mechanisms using a separate thermal solver (Co-simulation). The first method is usually computationally intensive, while the second one isn’t. This is because Co-simulation reduces the load of simulating all heat transfer mechanisms in a single code. This is one of the reasons why the Co-simulation method is widely used in the automotive industry. Traditionally, the methods developed for Co-simulation processes are load case specific.

Vehicle thermal management (VTM) simulations constitute an important step in the early development phase of a vehicle. They help in predicting the temperature profiles of critical components over a drive cycle and identify components which are exceeding temperature design limits. Parts with the highest temperatures in a vehicle with an internal combustion engine are concentrated in the engine bay area. As packaging constraints grow tighter, the components in the engine bay are packed closer together. This makes the thermal protection in the engine bay even more crucial. The fan influences the airflow into the engine bay and plays an important role in deciding flow distribution in this region. This makes modelling of the fan an important aspect of VTM simulations. The challenge associated with modelling the fan is the accurate simulation of the rotation imparted by the fan to the incoming flow. Currently, two modelling approaches are prevalent in the industry.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

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.

Increasing demand for dynamically controlled safety features, passenger comfort, and operational convenience in upper class automobiles requires an intensive use of electronic control units including software portions. Modeling, simulation, rapid prototyping, and verification of the software need new technologies to guarantee passenger security and to accelerate the time-to-market of new products. This paper presents the state-of-the-art of the design methods for the development of electronic control unit software at BMW. These design methods cover both discrete and continuous system parts, smoothly integrating the respective methods not merely on the code level, but on the documentation, simulation, and design level. In addition, we demonstrate two modeling and prototyping tools for discrete and continuous systems, namely Statemate and MatrixX, and discuss their advantages and drawbacks with respect to necessary prototyping demands.

The Advanced Lighting Simulation (ALS) is a development tool for systematically investigating and optimizing the Adaptive Light Control (ALC) system to provide the driver with improved headlamps and light distributions. ALS is based on advanced CA-techniques and modern validation facilities. To improve night time traffic safety the BMW lighting system ALC has been developed and optimized with the help of ALS. ALC improves the headlamp illumination by means of continuous adaptation of the headlamps according to the current driving situation and current environment. BMW has already implemented ALC prototypes in real vehicles to demonstrate the advantages on the real road.

Driving when it is raining can be a stressful experience. Having a clear unobstructed view of the vehicles and road around you under these conditions is especially important. Heavy rain conditions can however overwhelm water management devices resulting in water rivulets flowing over the vehicle's side glass. These rivulets can significantly impair the driver's ability to see the door mirror, and laterally onto junctions. Designing water management features for vehicles is a challenging venture as testing is not normally possible until late in the design phase. Additionally traditional water management features such as grooves and channels have both undesirable design and wind noise implications. Having the ability to detect water management issues such as A-pillar overflow earlier in the design cycle is desirable to minimize the negative impact of water management features. Numerical simulation of windscreen water management is desirable for this reason.

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.

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.

Brake disc materials are being utilised that have low noise/dust properties, but are sensitive to contamination by surface water. This drives large dust shields, making brake cooling increasingly difficult. However, brake cooling must be delivered without compromising aerodynamic drag and hence CO2 emissions targets. Given that front brake discs sit in a region of geometric, packaging and flow complexity optimization of their performance requires the analysis of thermal, aerodynamic and multi-phase flows. Some of the difficulties inherent in this task would be alleviated if the complete analysis could be performed in the same CAE environment: utilizing common models and the same solver technology. Hence the project described in this paper has sought to develop a CFD method that predicts the amount of contamination (water) that reaches the front brake discs, using a standard commercial code already exploited for both brake disc thermal and aerodynamics analysis.

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.