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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.

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.

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.

Innovative electric systems demand a new approach for the distribution of electric energy in passenger cars. This paper describes a very promising solution-the dual voltage power network with an upper voltage level of 42V, and the considerations which led to the selection of this voltage level. Owing to the significant impact on the industry, a common standard is required. Depending on their profile, OEMs will select their own strategies for implementation, either as a base for innovation or to enhance overall system efficiency. This will lead to different approaches and timeframes.

a practice-oriented approach for an accelerated product development and product design process for mechatronic systems is presented. The handling of complex and versatile product data to perform this process is shown in the area of electrical drives and actuators in cars. It is discussed, how the coordination of all the necessary disciplines as development, design, testing field, specification and release management should be software supported and PDM integrated. The advantages and benefits of the presented methods are shown on particular examples. The necessary software modules are introduced, showing that the realized solution gives both opportunities - the integration into a PDM backbone and at the same time an independent communication within department and/or company. The practical way, to realize the expert-specific needs of the development department, which is not possible with a general PDM system is pointed out.

A stationary model of a car air conditioning system was developed to evaluate refrigerant, mechanical power and all the fluid properties along the circuit. The model requires only the characteristics of the constituents, which are normally available from suppliers. This approach enables estimation of system performance with satisfactory accuracy, already during the design approach, and allows to determine the most appropriate components in order to meet target requirements with a satisfactory balance of the refrigerant circuit.

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.

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.

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.

In the early stages of conceptual design the available geometric data are very coarse and the lifespan of a design idea is very short. The structural evaluation and improvement of a design has to take both facts into account. Its focus is on the total vehicle and its performance. This can be estimated by a modeling technique, which is adequate for the lack of geometric details. Static and dynamic global stiffness as well as some aspects of crash and NVH have to be considered. Optimization will lead to the proper sizing and some indication of the potential of the structure. In order to maintain high quality standards this approach has to be supported by specialized CAE tools and extensive rules on modeling techniques and analysis procedures.

A new simulation tool was established and approved by TRW as part of the continuous improvement of the development process. This tool allows the OEM and the system supplier to keep high quality even with further reduced development times. The introduction of the tool in a side air-bag development program makes it possible to ensure high development confidence with a reduced number of vehicle crash tests and late availability of interior component parts.

Centro Ricerche Fiat in collaboration with Fiat Auto vehicle test department has developed a numerical-experimental procedure in order to support on-road development and fine tuning of a new car with electric power steering. The integration of an electric power steering model, given by the supplier, in a full vehicle model, in order to evaluate steering feel objective quality indices, has allowed to improve vehicle performance in term of steering feel and reduce on-road development time.

The attention to the perceived quality, e.g. the quality as it is evaluated by the final customer, is becoming more and more important for the car makers. The paper will describe how such aspects of handling and steering system feel may become manageable by an engineering process, through some fundamental steps: definition of measurable performance for the subjective aspects; identification of the target values for such aspects coherent with product positioning; deployment of such overall values generally fixed at vehicle level into functional requirements for the different subsystems and design specifications (sub targets level quantities). This new approach at car advanced design represents an evolution of the traditional one based on some general criteria and experienced designers; it has the aims of reducing time to market and guaranteeing a “customer oriented handwriting” in handling behaviour and steering feel.

The cabin comfort is one of the most competitive issues in the automotive area of business. The thermal comfort and the environmental well-being are fundamental performances that contribute to generate the more general idea of perceived quality. The CRF developed in the past the concept so-called “healthy bubble” that was implemented in the Lancia Dialogos concept car. The passengers are surrounded by an air bubble, created by generating low velocity air flows, that are diffused through the interior panels and components (e.g. dashboard, roof, back of the seats, etc.), and by surfaces temperature control (e.g. carpet, seats, etc.). At present the original idea has generally been accepted, and different solutions to diffuse air and to control surface temperature of vehicle interiors have been proposed by some automotive supplier.

One of the objectives of the Atena project was the definition of methods for the predictive evaluation of the environmental impact of different types of vehicles used in an urban scenario. The target is to obtain a methodology that allows the decision maker to verify in simulation the effects of possible measures like the law enforcement to the access restrictions or vehicle fleet composition. The main obstacle is the realization and managing of real driving cycles in order to overtake the limits derived from the utilization of typical cycles (i.e., ECE + EUDC) or the simple consideration of average speed. The starting point is a digital representation of the urban network where all the roads are represented with one or more arcs and for all these arcs are available an estimation of the traffic variables like the vehicle flow (vehicles per hour) or the average speed (kph). Every arc is described in terms of traffic parameters like the type of road (i.e., highway, district road).

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

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.