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More and more high-level algorithms are emerging to improve the existing systems in a car. Often these algorithms only need a platform with a bus connection and some resources such as CPU time and memory space. These functions can easily be integrated into existing systems that have free resources. This paper describes some encapsulation techniques and mechanisms that can be used in the automotive domain. The discussion also takes into account the additional resources consumed on the microcontroller to meet these requirements and by the software to implement the encapsulation mechanisms. Overviews of some general concepts of software-architectures that provide encapsulation are also shown.

With the ever increasing amount of available software processing resources in a vehicle, more and more high-level algorithms are emerging to improve the existing systems in a car. Often these algorithms only need a platform with a bus connection and some resources such as processing power and memory space. These functions are predestined to be integrated into existing systems that have free resources. This paper will examine the role of time protection in these multi-algorithm systems and describe what timing protection means and why it is required. The processing time will be partitioned to the different processing levels like interrupts, services and tasks. The problems of timing protection will be illustrated as well as its limitations. The conflict between real-time requirements and timing protection will be shown. Finally Autosar will be examined with focus on timing protection and applicability in actual development projects.

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 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.

The anti-lock braking system (ABS) is a widespread driver assistance system which allows a short braking distance while simultaneously maintaining the stability and steerability of the car. Vehicles with electric single-wheel drive offer many possibilities of improving the energy efficiency and the braking performance during ABS braking. In this paper, two different ways of including the electric machines in the ABS are analyzed in detail: the damping of torsional drive train vibrations in combination with recuperation and the dynamic split of the braking torque, where the hydraulic braking torque is kept constant and the dynamic modulation of the braking torque is performed by the electric machines. The damping algorithm is developed on the basis of a linearized model of the drive train and the tire-road contact by using state feedback and pole placement methods. Simulation results with a detailed multi-body system show the effectiveness of the control algorithms.

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.

Increasing demand for utilities like navigation systems or user-defined electronic phonebooks on one hand and sophisticated engine and gear controls on the other hand leads to growing bus load between distributed local control units. This paper shows the benefits and the characteristics of various state of the art data-compression algorithms and their impact on typical automotive multiplex dataclasses. The evaluation and optimization of promising algorithms can be done via a proposed “communications prototyping”-approach. The hardware/software components of such a rapid prototyping package are outlined. Finally, first performance results of suitable data-compression measures are presented.

The improvement of low-speed MUX-systems in car-body areas gets important in a scenario where on one hand, the possible number of integrated local control units (LCU's) gets larger and on the other hand, the possible versions of a car range from basic to top-of-the-line. Cost and developement time can be reduced if the same MUX-System is used throughout this whole range. A possibility to realize this is the use of data-compression (DC) for data-transmission. Basic configurations integrating only a small number of LCU's of a car-MUX can communicate without using data-compression, whereas for the top-of-the-line versions, the performance can be enhanced using DC only for communication processes between additional control units causing critical peak load situations. Specifically, the use of adaptive algorithms in automotive multiplex systems is a promising way to improve the MUX's capacity performance by minimizing redundant symbols/information in peak-load situations.

Multicore-based ECUs are increasingly used in embedded automotive software systems to allow more demanding automotive applications at moderate cost and energy consumption. Using a high number of parallel processors together with a high number of executed software components results in a practically unmanageable number of deployment alternatives to choose from. However correct deployment is one important step for reaching timing goals and acceptable latency, both also a must to reach safety goals of safety-relevant automotive applications. In this paper we focus at reducing the complexity of deployment decisions during the phases of allocation and scheduling. We tackle this complexity of deployment decisions by a mixed constructive and analytic approach.

Fast and exact measurement of engine oil consumption is a very difficult task. Our aim is to achieve this measurement at a common test bed without engine modifications. We resolved this problem with a new technique using Laser Mass Spectrometry to detect appropriate tracers in the raw engine exhaust. The tracers are added to the engine oil. to the engine oil. For detection of these tracers we use a Laser Mass Spectrometer (LAMS). This is a combination of resonant laser ionization (with an all-solid-state laser) and Time-of-Flight Mass Spectrometry. Currently this is the only way to detect oil originated molecules (like our tracers) in the raw exhaust very fast (50 Hz) and sensitive (ppb-region). Thus, engine mapping of oil consumption over load and speed can be performed in 1-2 days with about 90 measurements. Even measurement during dynamic engine operation is possible, but not quantitative (due to the lack of information about dynamic exhaust gas mass flow).

The continuous encouragement of lightweight design in modern vehicles demands a reliable and efficient method to predict and ameliorate the interior acoustic comfort for passengers. Due to considerable psychological effects on stress and concentration, the low frequency contribution plays a vital rule regarding interior noise perception. Apart other contributors, low frequency noise can be induced by transient aerodynamic excitation and the related structural vibrations. Assessing this disturbance requires the reliable simulation of the complex multi-physical mechanisms involved, such as transient aerodynamics, structural dynamics and acoustics. The domain of structural dynamics is particularly sensitive regarding the modelling of attachments restraining the vibrational behaviour of incorporated membrane-like structures. In a later development stage, when prototypes are available, it is therefore desirable to replace or update purely numerical models with experimental data.