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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.

A physically based model to predict the amount of snow which is entering the air intake of an automobile is extremely important for the automotive industry. It allows to improve the air intake system in the development state so that new vehicles can be developed in a shorter time. Using an Eulerian/Lagrangian approach within a commercial CFD-software we set up a model and calculated the snow ingress into an air intake of an automobile. In our numerical investigations we considered different particle shapes when calculating the drag coefficient, different coefficients of restitution and different particle sizes. Furthermore two-way coupling was considered. To obtain key parameters for the simulation, we measured the size of snow particles in the Daimler climatic wind tunnel in Sindelfingen by using a microscope and a measuring device from Malvern. Besides we used mechanical snow traps to determine the snow mass flux in the climatic wind tunnel and on a test area in Sweden.

A simulation approach to predict the amount of snow which is penetrating into the air filter of the vehicle’s engine is important for the automotive industry. The objective of our work was to predict the snow ingress based on an Eulerian/Lagrangian approach within a commercial CFD-software and to compare the simulation results to measurements in order to confirm our simulation approach. An additional objective was to use the simulation approach to improve the air intake system of an automobile. The measurements were performed on two test sites. On the one hand we made measurements on a natural test area in Sweden to reproduce real driving scenarios and thereby confirm our simulation approach. On the other hand the simulation results of the improved air intake system were compared to measurements, which were carried out in a climatic wind tunnel in Stuttgart.

As a consequence of reduced fuel consumption, direct injection gasoline engines have already prevailed against port fuel injection. However, in-cylinder fuel homogenization strongly depends on charge motion and injection strategies and can be challenging due to the reduced available time for mixture formation. An insufficient homogenization has generally a negative impact on the combustion and therefore also on efficiency and emissions. In order to reach the targets of the intensified CO2 emission reduction, further increase in efficiency of SI engines is essential. In this connection, 0D/1D simulation is a fundamental tool due to its application area in an early stage of development and its relatively low computational costs. Certainly, inhomogeneities are still not considered in quasi dimensional combustion models because the prediction of mixture formation is not included in the state of the art 0D/1D simulation.

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.

The Institute for Polymer Testing and Polymer Science of the University of Stuttgart has been investigating automotive parts, structures and cars during their life cycle in plenty cooperation with the European automobile producers and their suppliers for the last 9 years. Therefore a holistic approach has been developed to combine tasks from technique, economic and environment in a methodology called Life Cycle Engineering (LCE). The goal is to find a way to support designer and engineers as well as police makers and public with this three-dimensional interrelated information to have the possibility to manufacture future products in a more sustainable way without loosing contact two the traditional parameters technique and costs.

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.

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.

Automotive electric and electronic devices are commonly tested with standard pulses at the battery lines according to ISO 7637-Part 1 and 2. As these pulses do not cover all disturbances that occur in modern passenger cars, each OEM defines its own additional test-pulses which makes it difficult for component suppliers to satisfy all existing requirements. The paper shows a comparison between measurement and simulation such as slow “ignition on” pulses of a modern passenger car. Additionally, the ability of the computing model to calculate the propagation of fast transients and characteristic pulses of currently used electric and electronic devices is demonstrated. This data can be used for the definition of new test-pulses.

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.

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.

The aim of this article is to show a method, how the buyer's and supplier's cost management programs can be linked via Target Costing to find ways to reduce product cost and development time through intense interaction within the whole supply chain.

In automotive open-jet wind tunnels reference velocity is usually measured in terms of a static pressure difference between two different cross-sectional areas of the tunnel. Most commonly used are two sections within the nozzle (Method 1: ΔP-Nozzle). Sometimes, the reference velocity is deduced from the static pressure difference between settling chamber and plenum (Method 2: ΔP-Plenum). Investigations in three full-scale open-jet automotive wind tunnels have clearly shown that determination of reference dynamic pressure according to ΔP-Plenum is physically incorrect. Basically, all aerodynamic coefficients, including drag coefficient, obtained by this method are too low. For test objects like cars and vans it was found that the error ΔcD depends on the test object's drag blockage in an open-jet wind tunnel.

The Energy and Environment Test Centre (EVZ) is a complex comprising three large climatic wind tunnels, two smaller test chambers, nine soak rooms and support infrastructure. The capabilities of the wind tunnels and chambers are varied, and as a whole give BMW the ability to test at practically all conditions experienced by their vehicles, worldwide. The three wind tunnels have been designed for differing test capabilities, but share the same air circuit design, which has been optimized for energy consumption yet is compact for its large, 8.4 m₂, nozzle cross-section. The wind tunnel test section was designed to meet demanding aerodynamic specifications, including a limit on the axial static pressure gradient and low frequency static pressure fluctuations - design parameters previously reserved for larger aerodynamic or aero-acoustic wind tunnels. The aerodynamic design was achieved, in-part, by use of computational fluid dynamics and a purpose-built model wind tunnel.

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.