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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.

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 article describes the methods, which are employed in order to ensure high performance, safety and quality of ABS and ASR. System behaviour is evaluated and optimized by computer simulation. Moreover, a real-time simulator has been developed by which the consequences of hardware defects can be investigated systematically, Despite the increasing use of simulation the testing of vehicles remains the most important tool for system evaluation. For that purpose, a digital data acquisition system has been developed and objective evaluation criteria have been established. In order to achieve high product quality the Failure Mode and Effect Analysis (FMEA) is carried out at an early phase of development. Another prerequisite for high product quality is thorough durability and endurance testing before release of production.

The usage of Electronic Diesel Control is increasing with todays stringent emissions regulations. This requirement also necessitates that such systems be versatile to meet the needs of the engine/vehicle manufacturer. EGR, start of injection, and fuel delivery can be electronically controlled. Depending on the design goals of the manufacturer any one or two of these can be controlled for partial and all of them for full Electronic Diesel Control. The development and application process has several critical areas. These include, development of the sensors, application of the different subsystems, failure warning and failure mode operation. All of these must be combined if design goals are to be met. As the capabilities of electronics increase it follows that electronic vehicle systems will also improve. Today impressive results have been achieved with systems that are in full or pilot production.

The increasing number of local control units in automotive systems led to growing emphasis on developing and using multiplex systems. For reasons of price and robustness the use of asynchronous and slow multiplex systems is preferred. Since the communication volume now reaches critical dimensions in peak load situations during the use of those systems, new concepts on different communication levels have to be developed. Due to the use of many different message types (wide range of message length) and the statistical dependence of the communication behaviour of control units (e.g. question-answer-combinations), the application of standard methodologies is only partly suitable for a performance analysis of automotive multiplex systems.

Methodologies of a vehicle assessment through computer simulation comes to enable every day to preview difficulties in developing models, which also contributes to reducing the time to develop a new model. For initial assessment of the vibroacoustic behavior of a vehicle, in the early months of development, the frequency response functions, known as inertance (a/F), are analyzed, at the points of attachment of the engine and suspension to the body still in the Body-in-White configuration. Usually the finite element simulations are performed up to the limit of 300Hz. In the aim at increasing the range of inertance analysis, enabling a more comprehensive analysis in NVH, the results by elements finites simulation were compared, in this work, with the results obtained in experimental measurements focused on the validation of this simulation methodology until the limit of 800Hz.

Acoustics and vibrations are amongst the foremost indicators in perceiving the quality of drive units. Analyzing these factors is vital for improve the performances of electro-mechanical systems. This paper deals with the study of vibro-acoustic behavior concerning the drivetrain components using system modeling and Finite Element calculations. A generic simulation methodology within system modeling is proposed enabling the vibro-acoustic simulation of electro-mechanical drivetrains. Excitations for these systems mostly arise from the electric motor and mechanical gears. The paper initially depicts the system model for gear whining considering the associated nonlinearities of the mesh. The results obtained from the gear mesh submodel, together with the excitations resulting from the motor, aid in the comprehension of the forces at the bearings and of the vibrations at the housings.

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.

The behavior of an automotive dashboard has been evaluated using mathematical FEM models in combination with explicit structural codes in accordance with EEC homologation test 78/632. The test simulates the impact of the human head against the dashboard which can occur during a front crash. The simulation of the impact phenomenon in the basic dashboard configuration was examined as related to a series of design variants elaborated to eliminate critical areas. Variations in the stresses were determined in the component in reference to the basic model. An indispensable premise to achieving these results was the execution of FEM process simulations aimed at obtaining the actual distribution of the mechanical strength properties, which were weighted according to the localized influence of different temperatures and flow stresses during injection.

The German funded project ARAMiS included work on several demonstrators one of which was a multicore approach on large scale software integration (LSSI) for the automotive domain. Here BMW and Audi intentionally implemented two different integration platforms to gain both experience and real life data on a Hypervisor based concept on one side as well as using only native AUTOSAR-based methods on the other side for later comparison. The idea was to obtain figures on the added overhead both for multicore as well as safety, based on practical work and close-to-production implementations. During implementation and evaluation on one hand there were a lot of valuable lessons learned about multicore in conjunction with safety. On the other hand valuable information was gathered to make it finally possible to set up a cost model for estimation of potential overhead generated by different integration approaches for safety related software functions.

In this contribution functional safety is discussed from a car manufacturer's point of view. Typical elements of a safety standard concerning safety activities during the product development process are described as well as management and other supporting processes. Emphasis is laid on the aspect of risk assessment and the determination of safety classes. Experiences with methods for safety analysis like FTA or FMEA are discussed and pros and cons of quantitative safety assessment are argued.

The prime factor which influences noise and vibrations of electro-mechanical drives is wear at the components. This paper discusses the numerical methods developed for abrasion, vibration calculations and the coupling between wear and Noise Vibration and Harshness (NVH) models of the drive unit. The vibration domain model, initially, focuses on the calculations of mechanical excitations at the gear shafts which are generated via a nonlinear dynamic model. Furthermore, the bearings are studied for the influences on their stiffness and eventually their impact on the harmonics of the drivetrain. Later, free and forced vibrations of the complete drivetrain are simulated via a steady-state dynamic model. Consequently, the paper concentrates on the abrasion calculations at the gears. Wear is a complex process and understanding it is essential for determining the vibro-acoustics characteristics.

The increasing complexity of communication protocols for asynchronous multiplex systems requires the use of simulation during the optimisation of these protocols or the integration of other control units. Consideration of realistic communication behaviour of the connected control units is essential for performance analysis of multiplex systems. For a first pass, the use of simple statistical distributions (e.g. Poisson distribution) is suitable to get some simulation results. A better way to get realistic results is the approximation of empirical communication data through the use of more complex statistical distribution (e.g. mixed Erlang distributions). In this paper several approaches for the approximation of empirical data are presented. Beside simple statistical distributions (with one parameter), the use of more complex statistical distributions is discussed and methods for the identification of their parameters are presented.

In vehicle NVH development, vibroacoustic simulations with Finite Element (FE) models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time, the need for multiple evaluations of the same model with different input parameters, e.g., for uncertainty quantification, optimization, or robustness investigations, is also increasing. Therefore, it is crucial to reduce the computational costs in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach.

The AICC is an assisting system for controlling relative speed and distance between two vehicles in the same lane. The AICC system may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting it also to that of a slower one ahead. The main objective of this paper is to illustrate the design of the intelligent cruise control system involving the automatic control of throttle position and braking systems. There is much evidence nowadays that fuzzy approaches to real problems, where the linear control theory fails or can't provide an available and robust design solution, are often the best alternative to more familiar schemes.

Two models for the forecast of road traffic emissions, independently developed in parallel, are comparatively presented and assessed: EPROG developed by BMW and enlarged by VDA for a national application (Germany) and FOREMOVE, developed for application on European Community scale. The analysis of the methodological character of the two algorithms proves that the models are fundamentally similar with regard to the basic calculation schemes used for the emissions. The same holds true as far as the significant dependencies of the emission factors, and the recognition and incorporation of the fundamental framework referring to traffic important parameters (speeds, mileage and mileage distribution etc) are concerned.

The complexity of environmental problem is characterised by the typical difficulty to find an unique quantitative measure for “being green”. Environmental damage cannot easily be compared with parameters such as cost or time that are “hard” metrics. However, techniques like Life Cycle Assessment should make it possible comparing products based on the basis of their environmental profile. In this study a modelled approach that allows to integrate Life Cycle Assessment considerations within multi-criteria analysis methodology is described: this integration is clearly exemplified by a simple software tool called ECOCOST. ECOCOST represents an effort to join different field of evaluation, other than environmental, to the Life Cycle Assessment: then environmental results emerged from LCA can be matched with other kind of evaluation, economical and technical in particular.

The fuel spray behavior in the near nozzle region of a gasoline injector is challenging to predict due to existing pressure gradients and turbulences of the internal flow and in-nozzle cavitation. Therefore, statistical parameters for spray characterization through experiments must be considered. The characterization of spray velocity fields in the near-nozzle region is of particular importance as the velocity information is crucial in understanding the hydrodynamic processes which take place further downstream during fuel atomization and mixture formation. This knowledge is needed in order to optimize injector nozzles for future requirements. In this study, the results of three experimental approaches for determination of spray velocity in the near-nozzle region are presented. Two different injector nozzle types were measured through high-speed shadowgraph imaging, Laser Doppler Anemometry (LDA) and X-ray imaging.

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 article gives an overview of the CARTRONIC® based safety analysis (CSA) including an approach for the automatic determination of failure dependencies in automotive systems. CSA is a safety analysis in an early stage of product development. The goals are to identify safety critical components as soon as practicable in the product development process and to automate the analysis as far as possible. This implies that the system view is abstract, i.e. independent of a certain realization just regarding system functionality. In the CSA so called global failure effects will be systematically identified and assessed regarding severity of potential injuries. Global failure effects are especially important because they reveal failures within the system to the outside world (see also definition 3.1). Additionally the CSA keeps track of failure dependencies and supports the integration of safety measures in the system structure.