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It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

Today's automotive software integration is a static process. Hardware and software form a fixed package and thus hinder the integration of new electric and electronic features once the specification has been completed. Usually software components assigned to an ECU cannot be easily transferred to other devices after they have been deployed. The main reasons are high system configuration and integration complexity, although shifting functions from one to another ECU is a feature which is generally supported by AUTOSAR. The concept of a Virtual Functional Bus allows a strict separation between applications and infrastructure and avoids source code modifications. But still further tooling is needed to reconfigure the AUTOSAR Basic Software (BSW). Other challenges for AUTOSAR are mixed integrity, versioning and multi-core support. The upcoming BMW E/E-domain oriented architecture will require all these features to be scalable across all vehicle model ranges.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

Wheel slip control system have found a remarkable penetration in all car segments. The information on the wheel behavior has lead to further developments which control the brake performance as well as the driving of the car in general. Latest systems introduced especially on luxury cars use wheel individual brake intervention to ensure vehicle stability under various driving maneuvers within the physical limits. Such systems use vehicle dynamic sensors and special hydraulics which serve as energy source for the automatic brake application. The technical effort of such systems like the Dynamic Stability Control DSC has limited the installation to upper class cars so far. New approaches are required to allow for a more wide spread penetration. Optimized hydraulics together with a rational design of the electronics seems to offer a basis for a more cost effective design.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

Simple component models are advantageous when simulating vehicle AC systems so that overall model complexity and computation time can be minimized. These models must be robust enough to avoid instability in the iteration method used for determining the AC system operating or “balance” point. Simplicity and stability are especially important when the AC system model is coupled with a vehicle interior model for studies of transient performance because these are more computationally intensive. This paper presents a semi-empirical modeling method for compressors based on dimensionless parameters. Application to some sample compressor data is illustrated. The model equations are simple to employ and will not introduce significant stability problems when used as part of a system simulation.

This paper presents the results of CFD study on sunroof buffeting suppression using a dividing bar. The role of a dividing bar in side window buffeting case was illustrated in a previous study [8]. For the baseline model of the selected vehicle in this study, a very high level of sunroof buffeting, 133dB, has been found. The CFD simulation shows that the buffeting noise can be significantly reduced if a dividing bar is installed at the sunroof. A further optimization study on the dividing bar demonstrates that the peak buffeting level can be reduced to 123dB for the selected vehicle if the dividing bar is installed at its optimal location, 65% of the total length from the front edge of the sunroof. The peak buffeting level can be further reduced to 100dB if the dividing bar takes its optimal width 80mm, 15% of the total length of the sunroof for this vehicle, while staying at its optimal location.

This paper describes a practical approach to extract the global static stiffness of a body in white (BIW) from dynamic measurements in free-free conditions. Based on a limited set of measured frequency response functions (FRF), the torsional and bending stiffness values are calculated using an FRF based substructuring approach in combination with inverse force identification. A second approach consists of a modal approach whereby the static car body stiffness is deduced from a full free-free modal identification including residual stiffness estimation at the clamping and load positions. As an extra important result this approach allows for evaluating the modal contribution of the flexible car body modes to the global static stiffness values. The methods have been extensively investigated using finite element modeling data and verified on a series of body in white measurements.

Electronic Control Units (ECUs) are typically programmed using external programming devices - frequently called Diagnostic Testers. We propose a system and software architecture that requires no Diagnostic Tester for ECU (re)programming. ECU (re)programming is instead managed by an on-board software component, the Flashware-Reprogramming-Controller. It can reside in any ECU that has sufficient memory and processing power as well as good connectivity to internal networks and external sources from which to receive the software to be installed. Appropriate choices could be modern telematic devices. A second co-located on-board software component - the Installation-Configuration-Controller - is used to supervise the installation of new software releases and to validate their integrity after installation. The proposed architecture can be used for software download into ECUs in development, end-of-line production and after sales.

The cambore distortion is one of major concerns of an engine performance. A good design does not ensure a quality product. To meet product performance requirements, engineering community turns efforts to both design and manufacturing at an early stage of product development. This paper will discuss this process by providing an example of design and manufacturing of an overhead cambore. In this study a methodology to evaluate bore distortions is introduced. FEA cambore distortion analysis will use it to provide necessary data so that the product team can make a sound decision.

Vehicle exhaust flow is difficult to measure accurately and with high precision due to the highly transient nature of the cyclic events which are dependent on engine combustion parameters, varying exhaust gas compositions, pulsation effects, temperature and pressure. Bag mini-diluter (BMD) is becoming one of the few technologies chosen for SULEV and PZEV exhaust emission measurement and certification. A central part of the BMD system is an accurate and reliable exhaust flow measurement which is essential for proportional bag fill. A new device has been developed to accurately and reliably calibrate exhaust flow measurement equipments such as the E-Flow. The calibration device uses two different size laminar flow elements (LFE), a 40 CFM (1.13 m3/min) LFE for low end calibration and a 400 CFM (11.32 m3/min) LFE for higher flows. A blower is used to push flow through a main flow path, which then divides into two flow pathways, one for each of the two LFE's.

This paper show how the automotive product development process is presented in four distinct stages. The specific type of task, to be presented at each stage, is discussed. Specific CAE (Computer-Aided-Engineering) tasks, such as FEA (Finite Element Analysis), to be used at each stage are discussed. Detailed steps to follow are presented, as well as a check list of tasks are included. The changes and increased effectiveness (developed over 15 years of utilization) are discussed.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.

The automakers that comprise MOST® describe the reasons for this decision. First, they present the automobile industry's needs relative to multimedia networks in vehicles. Then, they present the different aspects of the MOST® technology. Multimedia networks are used in the electronics market, but they do not meet the technical and industrial constraints of the automobile electronics, which is why six automakers are working on most technology under the aegis of ""Most Cooperation.'' The transmission rate is a decisive aspect in the selection of a multimedia network. The rate of sound and video applications require fiber optics. The multimedia network rate must be adequate for a vehicle equipped with the maximum number of options, but the maximum rate is limited by the number of passengers.

The future of diesel-engine-powered passenger cars and light-duty vehicles in the United States depends on their ability to meet Federal Tier 2 and California LEV2 tailpipe emission standards. The experimental purpose of this work was to examine the potential role of fuels; specifically, to determine the sensitivity of engine-out NOx and particulate matter (PM) to gross changes in fuel formulation. The fuels studied were a market-average California baseline fuel and three advanced low sulfur fuels (<2 ppm). The advanced fuels were a low-sulfur-highly-hydrocracked diesel (LSHC), a neat (100%) Fischer-Tropsch (FT100) and 15% DMM (dimethoxy methane) blended into LSHC (DMM15). The fuels were tested on modern, turbocharged, common-rail, direct-injection diesel engines at DaimlerChrysler, Ford and General Motors. The engines were tested at five speed/load conditions with injection timing set to minimize fuel consumption.

A joint study was conducted between BMW and Goodyear with the objective of analysing the cause and identifying methods to reduce the structure-borne interior noise in a vehicle driving on rough road surfaces. A vibro-acoustic characterization of the car was performed by measuring the car vibro-acoustic transfer functions and by using a transfer path analysis technique to identify the main suspension parts affecting the interior noise at target frequencies. The vibration transmissibility characteristics of the tire were measured and also simulated by Finite Element in [1-200Hz] frequency range. The vibro-acoustic interaction between the tire and car sub-systems was examined. A Finite Element sensitivity analysis was used to define and build new prototype tires. A 3dB(A) interior noise improvement was obtained with these new tires at target frequencies.

The vibration-generating mechanisms inside an engine are highly non-linear (combustion, valve operation, hydraulic bearing behavior, etc.). However, the engine structure, under the influence of these vibration-generating mechanisms, responds in a highly linear way. For the development and optimization of the engine structure for noise and vibration it is beneficial to use fast and ‘simple’ linear models, like linear FE-models, measured modal models or measured FRF-models. All these models allow a qualitative assessment of variants without excitation information. But, for true optimization, internal excitation spectra are needed in order to avoid that effort is spent to optimize non-critical system properties. Unfortunately, these internal excitation spectra are difficult to measure. Direct measurement of combustion pressure is still feasible, but crank-bearing forces, piston guidance forces etc. can only be identified indirectly.