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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.

A finite element model of the Transport Research Laboratory (TRL) honeycomb barrier, which is being proposed for use in vehicle compatibility studies, has been developed for use in LSDYNA. The model employs penalty parameters to enforce continuity between adjacent finite elements of the honeycomb barrier. Results of impact tests with indentors of various shapes and sizes were used to verify the performance of the computational model. Numerical simulations show reasonably good agreement with the test results.

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.

Proper electric and thermal management of an HEV battery pack, consisting of many modules of cells, is imperative. During operation, voltage and temperature differences in the modules/cells can lead to electrical imbalances from module to module and decrease pack performance by as much as 25%. An active battery management system (BMS) is a must to monitor, control, and balance the pack. The University of Toledo, with funding from the U.S. Department of Energy and in collaboration with DaimlerChrysler and the National Renewable Energy Laboratory has developed a modular battery management system for HEVs. This modular unit is a 2nd generation system, as compared to a previous 1st generation centralized system. This 2nd generation prototype can balance a battery pack based on cell-to-cell measurements and active equalization. The system was designed to work with several battery types, including lithium ion, NiMH, or lead acid.

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.

Once a vehicle powertrain is designed and the first prototype is built, extensive on-board instrumentation and testing needs to be carried out at the proving grounds (PG) to generate load histograms for various components. The load histograms can then be used to carry out durability tests in the laboratory. When a component in the vehicle powertrain is changed, the load histograms need to be generated again at the proving grounds. This adds much time and money to the vehicle's development. The objective is to develop a virtual powertrain model that can be simulated through a powertrain endurance driving cycle in order to predict torque histograms and total damage. The predictions are then correlated against measured data acquired on a test vehicle that was driven through the same driving cycle at the proving grounds.

Stochastic simulation is used to account for the uncertainties inherent to the system and enables the study of crash phenomenon. For analytical purposes, random variables such as material crash properties, angle of impact, human response and the like can be characterized using statistical models. The methodology outlined in this approach is based on using the information about the probability of random variables along with structural behavior in order to quantify the scatter in the structural response. Thus the analysis gives a more complete picture of the actual simulation. Practical examples for the use of this technique are demonstrated and an overview of this approach is presented.

Virtual testing has grown to be an efficient tool in vehicle passive safety design. Most simulations currently are deterministic. Since the responses observed in real-life and standardized tests are greatly affected by scatter, a stochastic approach should be adopted in order to improve the predictability of the numerical responses with respect to the experimental data. In addition, an objective judgement of the performance of numerical models with respect to experimental data is necessary in order to improve the reliability of virtual testing. In the European VITES & ADVANCE project the software tool Adviser was developed in order to fulfil these two requirements. With Adviser, stochastic simulations can be performed and the quality of the numerical responses with respect to the experimental can be objectively rated using pre-defined and user-defined objective correlation criteria. The software Adviser was used to develop a stochastic HybridIII 50th% Madymo numerical model.

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.

Today the worldwide convergence towards stricter fuel consumption and emission regulations is pushing carmakers and suppliers into new fields of innovation. Valeo Engine Cooling, VEC, is contributing towards these goals by applying its thermal management system expertise in order to reduce fuel consumption and emissions by using an advanced engine cooling system that incorporated variable speed PWM fans, an electric water pump and an electric water control valve. The paper discusses the benefits in terms of engine cooling, fuel economy and emissions over the FTP drive cycle. The paper gives some examples of advanced engine cooling strategies based on a virtual, predictive metal temperature sensor that is used to actuate the electrical water pump at the desired flow rate. The electrical balance between the 42V pump and fans has also been optimized to reduce the vehicle electrical power consumption and to keep the coolant temperature close to 110°C.

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.

Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

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.

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 order to meet the severe emission restrictions imposed by SULEV and EURO V standards the catalytic converter must reach light-off temperature during the first 20 seconds after engine cold start. Thermal losses in the exhaust manifold are driven by the heat transfer of the pulsating and turbulent exhaust flow and affect significantly the warm-up time of the catalyst. In the present paper an investigation concerning the gas-side heat transfer in the exhaust system of a spark ignited (SI) combustion engine with retarded ignition timing and secondary air injection into the exhaust port is reported. Based on this analysis, the warm-up simulation of a one-dimensional flow simulation tool is improved for an evaluation of different exhaust system configurations.

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.

BMW can look back on 20 years of research activities on hydrogen propulsion systems. Hydrogen fuel is the only means of offering pure driving pleasure on the basis of a sustainable energy loop. As the hydrogen era is still quite a while away the BMW Energy Strategy „Via Natural Gas to Hydrogen” has been developed. The first step was to build series-production compressed natural gas (CNG) cars back in 1995. By switching to liquefied natural gas (LNG) not only is the cruising range tripled but technologically the final stepping-stone is reached in preparing the way for liquefied hydrogen. BMW's automotive and drive technology for hydrogen is now available and ready to move out of the laboratory on to the road. At Munich Airport a BMW „Clean Energy” car is already providing shuttle services. Its fuel is supplied by the world's first public filling station for liquefied hydrogen.