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The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG

Active safety systems will have a great impact in the next generation of vehicles. This is partly originated by the increasing consumer's interest for safety and partly by new traffic safety laws. Control actions in the vehicle are based on an extensive environment model which contains information about relevant objects in vehicle surroundings. Sensor data fusion integrates measurements from different surround sensors into this environment model. In order to avoid system malfunctions, high reliability in the interpretation of the situation, and therefore in the environment model, is essential. Hence, the main idea of data fusion is to make use of the advantages of using multiple sensors and different technologies in order to fulfill these requirements, which are especially high due to autonomous interventions in vehicle dynamics (e. g. automatic emergency braking).

Regarding the strongly growing two-wheeler market fuel economy, price and emission legislations are in focus of current development work. Fuel economy as well as emissions can be improved by introduction of engine management systems (EMS). In order to provide the benefits of an EMS for low cost motorcycles, efforts are being made at BOSCH to reduce the costs of a port fuel injection (PFI) system. The present paper describes a method of how to reduce the number of sensors of a PFI system by the use of sophisticated software functions based on high-resolution engine speed evaluation. In order to improve the performance of a system working without a MAP-sensor (manifold air pressure sensor) an air charge feature (ACFn) based on engine speed is introduced. It is shown by an experiment that ACFn allows to detect and adapt changes in manifold air pressure. Cross-influences on ACFn are analyzed by simulations and engine test bench measurements.

In order to comply with more and more stringent emission standards, like EU6 which will be mandatory starting in September 2014, GDI engines have to be further optimized particularly in regard of PN emissions. It is generally accepted that the deposition of liquid fuel wall films in the combustion chamber is a significant source of particulate formation in GDI engines. Particularly the wall surface temperature and the temperature drop due to the interaction with liquid fuel spray were identified as important parameters influencing the spray-wall interaction [1]. In order to quantify this temperature drop at combustion chamber surfaces, surface temperature measurements on the piston of a single-cylinder engine were conducted. Therefore, eight fast-response thermocouples were embedded 0.3 μm beneath the piston surface and the signals were transmitted from the moving piston to the data acquisition system via telemetry.

Due to the principle of direct injection, which is applied in modern homogeneously operated gasoline engines, there are various operation points with significant particulate emissions. The spray droplets contact the piston surface during the warm-up and early injections, in particular. The fuel wall films and the resulting delayed evaporation of the liquid fuel is one of the main sources of soot particles. It is therefore necessary to carry out investigations into the formation of wall film. The influence of the spray impact angle is of special interest, as this is a major difference between engines with side-mounted injectors and centrally positioned injectors. This paper describes an infrared thermography-based method, which we used to carry out a systematic study of fuel deposits on the walls of the combustion chamber. The boundary conditions of the test section were close to those of real GDI engines operated with homogeneous charge.

Equipping low cost two-wheelers with engine management systems (EMS) enables not only a reduction of emissions but also an improvement in fuel consumption and system robustness. These benefits are accompanied by initially higher system costs compared to carburetor systems. Therefore, intelligent software solutions are developed by Bosch, which enable a reduction of the necessary sensors for a port fuel injection system (PFI) and furthermore provide new possibilities for combustion control. One example for these intelligent software solutions is a model based evaluation of the engine speed. By use of the information contained in the engine speed signal, characteristic features like air charge, indicated mean effective pressure (imep) and combustion phasing are derivable. The present paper illustrates how these features could be used to reduce the system costs and to improve fuel consumption and system robustness.

Cost reduction of engine management systems (EMS) for two-wheeler applications is the key to utilize their potentials compared to carburetor bikes regarding emissions, fuel economy and system robustness. In order to reduce the costs of a system with port fuel injection (PFI) Bosch is developing an EMS without a manifold air pressure (MAP) sensor. The pressure sensor is usually used to compensate for different influences on the air mass, which cannot be detected via the throttle position sensor (TPS) and mean engine speed. Such influences are different leakage rates of the throttle body and changing ambient conditions like air pressure. Bosch has shown in the past that a virtual sensor relying on model based evaluation of engine speed can be used for a detection of leakage air mass in idling to improve the pre-control of the air-fuel ratio. This provides a functionality which so far was only possible with an intake pressure sensor.

The introduction of real driving emissions cycles and increasingly restrictive emissions regulations force the automotive industry to develop new and more efficient solutions for emission reductions. In particular, the cold start and catalyst heating conditions are crucial for modern cars because is when most of the emissions are produced. One interesting strategy to reduce the time required for catalyst heating is post-oxidation. It consists in operating the engine with a rich in-cylinder mixture and completing the oxidation of fuel inside the exhaust manifold. The result is an increase in temperature and enthalpy of the gases in the exhaust, therefore heating the three-way-catalyst. The following investigation focuses on the implementation of post-oxidation by means of scavenging in a four-cylinder, turbocharged, direct injection spark ignition engine. The investigation is based on detailed measurements that are carried out at the test-bench.

Vibration testing is often carried out for automotive components to meet guidelines based on their operational environments. This is an iterative process wherein design changes may need to be made depending on an intermediate model’s dynamic behavior. Predicting the behavior based on modifications in boundary conditions of a well-defined numerical model imparts practical insights to the component’s responses. To this end, application of a general method using experimental free-free condition frequency response functions of a structure is discussed in the presented work. The procedure is shown to be useful for prediction of responses when kinematic boundary conditions are applied, without the need for an actual measurement. This approach is outlined in the paper and is applied to datasets where dynamic modifications are made at multiple boundary nodes.

Further improvements of internal combustion engines to reduce fuel consumption and to face future legislation constraints are strictly related to the study of mixture formation. The reason for that is the desire to supply the engine with homogeneous charge, towards the direction of a global stoichiometric blend in the combustion chamber. Fuel evaporation and thus mixture quality mostly depend on injector atomization features and charge motion within the cylinder. 3D-CFD simulations offer great potential to study not only injector atomization quality but also the evaporation behavior. Nevertheless coupling optical measurements and simulations for injector analysis is an open discussion because of the large number of influencing parameters and interactions affecting the fuel injection’s reproducibility. For this purpose, detailed numerical investigations are used to describe the injection phenomena.

Intensified emission regulations as well as consumption demands lead to an increasing significance of unburned hydrocarbon (UHC) emissions for diesel engines. On the one hand, the quantity of hydrocarbon (HC) raw emissions is important for emission predictions as well as for the exhaust after treatment. On the other hand, HC emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the HC molecules. Due to these reasons, a simulation model for predicting HC raw emissions was developed for diesel engines based on a phenomenological two-zone model. The HC model takes three main sources of HC emissions of diesel engines into account: Firstly, it contains a sub-model that describes the fuel dribble out of the injector after the end of injection. Secondly, HC emissions from cold peripheral zones near cylinder walls are determined in another sub-model.

In order to optimize spray layouts of commonly used high-pressure injectors for gasoline direct injection (GDI) engines featuring multi-hole valve seats, a detailed understanding of the cause-effect relation between inner spray hole geometries and inner flow conditions, initializing the process of internal mixture formation, is needed. Therefore, a novel measurement setup, capable of determining spray hole individual mass flow rates, is introduced and discussed. To prove its feasibility, a 2-hole configuration is chosen. The injected fuel quantities are separated mechanically and guided to separate pressure tight measurement chambers. Each measurement chamber allows for time resolved mass flow rate measurements based on the HDA measurement principle (German: “Hydraulisches Druck-Anstiegsverfahren”).

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 industry is working intensively on the precision of thermal management. By using complex thermal management strategies, it is possible to make engine heat distribution more accurate and dynamic, thereby increasing efficiency. Significant efforts are made to improve the cooling efficiency of the engine water jacket by using 3D CFD. As well, 1D simulation plays a significant role in the design and analysis of the cooling system, especially for considering transient behaviour of the engine. In this work, a practice-oriented universal method for creating a 1D water jacket model is presented. The focus is on the discretization strategy of 3D geometry and the calculation of heat transfer using Nusselt correlations. The basis and reference are 3D CFD simulations of the water jacket. Guidelines for the water jacket discretization are proposed. The heat transfer calculation in the 1D-templates is based on Nusselt-correlations (Nu = Nu(Re, Pr)), which are derived from 3D CFD simulations.

Aircraft cabin systems, especially cabin management systems (CMS) have to cope with frequent cabin changes during their lifecycle. This includes not only layout rearrangements and technological upgrades during the service, but also extensive CMS customizations and product variations before aircraft delivery. Therefore it is inevitable for the CMS to be highly changeable and offer an easy and agile change process. Today's CMS solutions face this challenge with configurable system architectures. Although such architectures offer a vast change domain, they usually come with time consuming and error prone change processes. This paper introduces an adaptive avionics software architecture that enables the CMS to cope with cabin changes highly automatically and with minimal human interactions. The adaptation is performed during an on ground organization phase, in which system changes are detected and evaluated by the CMS itself.

Due to the new CO2 targets for vehicles, electrification of powertrains and operation strategies for electrified powertrains have drawn more attention. This article presents a predictive multi-objective operation strategy for hybrid electric vehicles (HEVs), which simultaneously minimizes the fuel consumption and the cycle aging of traction batteries. This proposed strategy shows better performance by using predictive information and high robustness to inaccuracy of predictive information. In this work, the benefits of the developed operation strategies are demonstrated in a strong hybrid electric vehicle (sHEV) with P2-configuration. For the cycle aging of a lithium-ion battery, an empirical model is built up with Gaussian processes based on experimental data.

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.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

For the gasoline engine, the isochoric process is the ideal limit of the ideal processes. During the project, a combustion engine with real isochoric boundary conditions is built. A “resting time” of the piston for several degrees crank angle in the top dead center (TDC) can be realized with a special crank drive. This crank drive consists of two crankshafts with different strokes, which are combined. The two crankshafts rotate with a ratio of two to one in opposite directions. The total stroke corresponds to the amount of the first crankshaft, so it is possible to investigate different strokes of the second crankshaft in the same crankcase. Different “resting times” can be achieved by different strokes of the second crankshaft. A specific combination of both crankshafts make a stroke possible which corresponds to that of a conventional combustion engine.

In order to meet increasingly stringent exhaust emission regulations, new engine concepts need to be developed. Lean combustion systems for stationary running large gas engines can reduce raw NOx-emissions to a very low level and enable the compliance with the exhaust emission standards without using a cost-intensive SCR-aftertreatment system. Experimental investigations in the past have already confirmed that a strong reduction of the charge air temperature even below ambient conditions by using an absorption chiller can significantly reduce NOx emissions. However, test bench operation of large gas engines is costly and time-consuming. To increase the efficiency of the engine development process, the possibility to use 0D/1D engine simulation prior to test bench studies of new concepts is investigated using the example of low temperature charge air cooling. In this context, a reliable prediction of engine efficiency and NOx-emissions is important.