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With the huge improvements made during the last years in the area of integrated safety systems, they are one of the main contributors to the massively rising complexity within automotive systems. However, this enormous complexity stimulates the demand for methodologies supporting the efficient development of such systems, both in terms of cost and development time. Within this work, we propose a co-simulation-based approach for the validation of integrated safety systems. Based on data measurements gained from a test bed, models for the sensors and the distributed safety system are established. They are integrated into a co-simulation environment containing models of the ambience, driving dynamics, and the crash-behavior of the vehicle. Hence, the complete heterogeneous system including all relevant effects and dependencies is modeled within the co-simulation.

Driving cycles are valuable tools for emissions calibration at engine and powertrain test beds. While generic velocity profiles were sufficient in the past, legislative changes and increasing complexity of powertrain and exhaust aftertreatment systems require a new approach: Realistically transient cycles - which include critical driving maneuvers and can be tailored to a specific powertrain configuration - are needed to optimize the emission behavior of the said powertrain. For the generation of realistic velocity profiles, the Markov chain approach has been widely used and described in literature. However, this approach, so far, has only been used to generate cycles that are statistically representative of a large database of real driving trips, which is typically not available during the early stages of development of a new powertrain.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

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.

This paper presents a new approach to analyzing and developing low-drag cooling systems. A relation is derived which describes cooling drag by a number of contributions. Interference drag clearly can be identified as one of them. Cooling system parameters can be assigned to different terms of the relation, so that differences due to parameter variations of the individual drag contributions can be estimated. In order to predict the interference-drag dependency on the outlet location and the local outlet mass flow, an extensive study on a standard BMW sedan has been carried out, both experimentally and by CFD. The results show the importance of providing consistent outflow conditions which take into account the outlet location and flow direction, in order to minimize cooling drag.

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.

In addition to the creep properties, the fatigue properties are essential for the design of a power-train component in Mg which is operated at elevated temperatures. In case of the new BMW I6 composite Mg/Al crankcase using the AJ alloy system, material testing focused on both subjects. The basic mechanical properties were determined from separately die cast samples and also from samples machined out from high-pressure die cast components. Tensile, high cycle fatigue properties, low cycle fatigue and crack propagation properties were established and analyzed within the technical context for power-train applications reflected in the temperature and load levels. The aspects of mean stress influence, notch sensitivity and crack propagation are evaluated to estimate the performances of the AJ62A alloy system.

AJ alloy is used with a new Aluminum-Magnesium Composite Design, which is an innovative approach to lightweight crankcase technology. The component is manufactured using high pressure die cast process. A wide range of chemical compositions was used to develop a good understanding of the behavior of this alloy system (castability, thermophysical, mechanical, microstructure). The basic mechanical properties were determined from separately die cast samples and also from samples machined out from high pressure die cast components. Tensile, creep, bolt load retention/relaxation and high cycle fatigue properties were established and analyzed using multivariate analysis and statistical approach. This methodology was used to select the optimal chemical composition to match the requirements. The sensitivity of the alloy to heat exposure was investigated for both mechanical properties and microstructure.

The AUTomotive Open System ARchitecture (AUTOSAR) Development Partnership has published early 2008 the specifications Release 3.0 [1], with a prime focus on the overall architecture, basic software, run time environment, communication stacks and methodology. Heavy developments have taken place in the OEM and supplier community to deliver AUTOSAR loaded cars on the streets starting 2008 [2]. The 2008 achievements have been: Improving the specifications in order to secure the exploitation for body, chassis and powertrain applications Adding major features: safety related functionalities, OBD II and Telematics application interfaces.

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.

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.

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.

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 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.

In large-scale industrial simulations the numerical prediction of fracture in sheet metal forming operations as well as in crash events is still a challenging task of high social and economic relevance. Among several approaches presented in literature, the authors and their colleagues developed a model which accounts each for three different mechanisms leading finally to fracture in thin sheet metals: the local instability (necking), ductile normal fracture and ductile shear fracture. The focus of this paper is to develop and validate a new approach to improve the predictive capabilities for fracture triggered by localized necking for a wide variety of steel grades. It is well known that after the onset of a local instability additional strain is still necessary to induce fracture. In a numerical simulation using shell elements this post instability strain becomes of increasing importance when the ratio of the characteristic shell element edge length to its thickness decreases.

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.

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.

This article focuses on model based development of electronic control units (ECUs) in the automotive domain. The use of model-based approaches solves requirements for the fast-growing integration of formerly isolated logical functions in complex distributed networks of heavily interacting ECUs. One fundamental property of such an approach is the existence of an adequate modeling notation tailored to the specific needs of the application domain together with a precise definition of its syntax and its semantics. However, although these constituents are necessary, they are not sufficient for guaranteeing an efficient development process of ECU networks. In addition, methodical support which guides the application of the modeling notation must be an integral part of a model-based approach.

What are the requirements of customers in an urban environment? What will sustainable mobility look like in the future? This presentation gives an overview of the integrated approach used by BMW to develop the BMW i3 - a purpose-built battery electric vehicle. Very low driving resistances for such a vehicle concept enable the delivery of both impressive range and driving excitement. A small optional auxiliary power unit offers range security for unexpected situations and opens up BEVs to customers who are willing to buy a BEV but are still hesitant due to range anxiety. Additional electric vehicles sold to the formerly range anxious will create additional electric miles. Presenter Franz Storkenmaier, BMW Group

The dramatic increase in data and information exchange has lead to increased communication network complexity within the subsystems of the powertrain itself as well as in all other subsystems of the vehicle. It is essential to manage this complexity during the development process. Applying new processes and methods such as vehicle functions and systems orientation in a top-down structural approach creates a powerful support in development of innovative powertrains. Several technical integration examples of powertrain functions are illustrated for the purpose of demonstrating customer-related advantages. Vehicle functions and systems orientation also has significant impact on organisational structures and cooperation methods to achieve maximum synergies as well as efficient vehicle communication architectures.