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GTL (Gas-To-Liquid) fuel is well known to improve tailpipe emissions when fuelling a conventional diesel vehicle, that is, one optimized to conventional fuel. This investigation assesses the additional potential for GTL fuel in a GTL-dedicated vehicle. This potential for GTL fuel was quantified in an EU 4 6-cylinder serial production engine. In the first stage, a comparison of engine performance was made of GTL fuel against conventional diesel, using identical engine calibrations. Next, adaptations enabled the full potential of GTL fuel within a dedicated calibration to be assessed. For this stage, two optimization goals were investigated: - Minimization of NOx emissions and - Minimization of fuel consumption. For each optimization the boundary condition was that emissions should be within the EU5 level. An additional constraint on the latter strategy required noise levels to remain within the baseline reference.

Fully variable valve trains provide comprehensive means of adjustment in terms of variable valve timing and valve lift. The efficiency of the engine is improved in the operating range and in return, an increasing complexness of the mechanical design and control engineering must be handled. For optimization and design of these kinds of complex systems, detailed simulation models covering different physical domains, i.e. mechanics, hydraulics, electrodynamics and control are needed. Topic of this work is the variable valve train named Audi valvelift system (AVS) e.g. used in the Audi 2.8l V6 FSI engine. The idea of AVS is to use different cam lobes at different operating points. Each intake valve can be actuated by a large and a small cam. For full load, the two inlet valves are opened by the large cam profile - ideal for high charge volumes and flow speeds in the combustion chamber. Under partial load, the small cam profiles are used.

The development of hydrogen-fueled vehicles has created the need for established fuel consumption testing methods. Until now the EPA has only accepted three methods of hydrogen fuel consumption testing, gravimetric, PVT (stabilized pressure, volume and temperature), and Coriolis mass flow; all of which necessitate physical measurements of the fuel supply [1]. BMW has developed an equation and subsequent testing methods to accurately and effectively determine hydrogen fuel consumption in light-duty vehicles using only exhaust emissions. Known as “Hydrogen-Balance”, the new equation requires no changes to EPA procedures and only slight modifications to most existing chassis dynamometers and CVS (Constant Volume Sampling) systems. The SAE 2008-01-1036, also written by BMW, explains the background as well as required equipment and changes to the CVS testing system. This paper takes hydrogen balance further by testing it against the three EPA established forms of fuel consumption.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

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.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

The results of previous Life Cycle Assessments indicate the ecological dominance of the vehicle's use phase compared to its production and recycling phase. Particularly the so-called weight-induced fuel saving coefficients point out the great spectrum (0.15 to 1.0 l/(100 kg · 100 km)) that affects the total result of the LCA significantly. The objective of this article, therefore, is to derive a physical based, i.e. scientific chargeable and practical approved, concept to determine the significant parameters of a vehicle's use phase for the Life Cycle Inventory. It turns out that - besides the aerodynamic and rolling resistance parameters and the efficiencies of the power train - the vehicle's weight, the rear axle's transmission ratio and the driven velocity profile have an important influence on a vehicle's fuel consumption.

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.

Audi's successful 3.6 L V8 twin turbo Le Mans engine of 2000 has been developed to fuel direct injection (FSI®). Most of the modifications have been done in the area of the cylinderhead. Simulation and flow test bench work helped to define the basic parameters. The FSI® engine has a reduction in fuel consumption of 8 - 10 %, up to 9 % more torque throughout the entire speed range and much better driveability.

Flame Ionization Detectors (FID) can be used to detect organic hydrocarbons that occur in plastics, lacquers, adhesives, solvents and gasoline. These substances are ionized in the hydrogen flame of the FID. The ionization current that is produced depends on the amount of hydrocarbon in the sample. With the lowering of emissions limits, measuring instruments, including the FID, have to be able to detect very low values. For SULEV (Super-Ultra Low Emissions Vehicle) measurements the accuracy and also the general applicability of the CVS (Constant Volume Sampling) measuring technique are now questioned. Basic understanding is necessary to ask the right questions. One important issue is the science behind the measurement principle of the FID. And in this case especially the influence of contamination of the operating gases, cross sensitivity and data processing on the Limit of Detection (LOD).

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.

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.

ISO 26262 is the actual standard for Functional Safety of automotive E/E (Electric/Electronic) systems. One of the challenges in the application of the standard is the distribution of safety related activities among the participants in the supply chain. In this paper, the concept of a Safety Element out of Context (SEooC) development will be analyzed showing its current problematic aspects and difficulties in implementing such an approach in a concrete typical automotive development flow with different participants (e.g. from OEM, tier 1 to semiconductor supplier) in the supply chain. The discussed aspects focus on the functional safety requirements of generic hardware and software development across the supply chain where the final integration of the developed element is not known at design time and therefore an assumption based mechanism shall be used.

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.

There is a common understanding that hydrogen has a great potential to be the fuel of the future. In addition to the challenge of developing appropriate hydrogen propulsion systems the development of hydrogen storage systems is the second big issue. Due to its high potential in cost and weight and specific storage capacity, the BMW Group is focusing on the development of liquid hydrogen storage systems. In the next hydrogen 7-Series the BMW Group is about to make for the first time the step from demonstration fleets to cars used by external users with a liquid hydrogen storage system. To realize this significant goal, special focus has to be put on high safety standards so that hydrogen can be considered as safe as common types of fuel, and on the every day reliability of the storage system. Moreover, the development of strong partnerships with suppliers is a key factor to realize the design and identify appropriate manufacturing processes.

The reduction of fuel consumption in vehicles remains an important target in vehicle development to meet the carbon dioxide emission reduction target. One of the significant consumers of energy in a vehicle is the hydraulic power-assisted steering system (HPS) powered by the engine belt drive. To reduce the energy consumption an electric motor can be used to drive the pump (electro-hydraulic power steering or EHPS). In this work a simulation model was developed and validated to model the energy consumption of the whole steering system. This includes an advanced friction model for the steering rack, a physically modeled steering valve, the hydraulic pump and the electric motor with the control unit. The model is used to investigate the influence of various parameters on the energy consumption for different road situations. The results identified the important parameters influencing the power consumption and showed the potential to reduce the power consumption of the system.