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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

Multicore processor are well established in classical and tablet personal computers for some year. Such processors use more then one central core for computation and allow to integrate more computational power with smaller costs. However more than 90% of all processors worldwide are not placed in classical IT but are empedded in bigger systems like in modern vehicles or airplanes. Such systems face a very high demand in terms of safety, security an reliability which hinders the use of multicores in such systems. The funded project ARAMiS faces these demands and has the goal to enable the usability of multicore systems in the domains automotive and avionics, as well as later also railway. ARAMiS is the basis for higher traffic safety, traffic efficiency and comfort.

Several space agencies have announced plans to return humans to the Moon in the near future. The objectives of these missions include using the Moon as a stepping-stone towards crewed missions to Mars, to test advanced technology, and to further exploration of the Moon for scientific research and in-situ resource utilization. To meet these objectives, it will be necessary to establish and operate a lunar base. As a result, a wide variety of tasks that may pose a number of crew health and safety risks will need to be performed on the surface of the Moon. Therefore, to ensure sustainable human presence on the Moon and beyond, it is essential to anticipate potential risks, assess the impact of each risk, and devise mitigation strategies. To address this, a nine-week intensive investigation was performed by an international, interdisciplinary and intercultural team on how to maximize crew safety on the lunar surface through a symbiotic relationship between astronauts and robots.

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.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

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.

Hybrid electric vehicle (HEV) powertrains are characterized by a complex design environment as a result of both the large number of possible layouts and the need for dedicated energy management strategies. When selecting the most suitable hybrid powertrain architecture at an early design stage of HEVs, engineers usually focus solely on fuel economy (directly linked to tailpipe emissions) and vehicle drivability performance. However, high voltage batteries are a crucial component of HEVs as well in terms of performance and cost. This paper introduces a multitarget assessment framework for HEV powertrain architectures which considers both fuel economy and battery lifetime. A multi-objective formulation of dynamic programming is initially presented as an off-line optimal HEV energy management strategy capable of predicting both fuel economy performance and battery lifetime of HEV powertrain layout options.

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 Model-Based Development (MBD) paradigm is widely used for embedded controls development, with the MathWorks Simulink modelling environment being extensively used in the automotive industry. As production-scale Simulink models are typically large and complex, there exists a need to decompose them properly in order to facilitate their maintainability, understandability, and evolution. MathWorks recommends the use of three constructs for model “componentization” or decomposition: the Subsystem, Library, and Model Reference. However, a recently added construct introduced in Simulink R2014b, the Simulink Function, can also be used for this purpose, while also supporting information hiding due to the construct’s ability to be scoped and encapsulate data.

Today, body vibration energy of passenger cars gets dissipated by linear working shock absorbers. A new approach substitutes the damper of a passenger car by a cardanic gimbaled flywheel mass. The constructive design leads to a rotary damper in which the vertical movement of the wheel carrier leads to revolution of the rotational axis of the flywheel. In this arrangement, the occurring precession moments are used to control damping moments and to store vibrational energy. Different damper characteristics are achieved by different induced precession. From almost zero torque output to high torque output, this damper has a huge spread. Next to the basic principal, in this paper an integration in the chassis, including a constructive proposal is shown. A conflict with high torque and high angular velocity leads to a special design. Moreover concepts to deal with all vehicle situations like yawing, rolling and pitching are shown.

Starting from the USA and followed by the European Union, legal requirements concerning “Tire Pressure Monitoring Systems” (TPMS) for passenger cars and light trucks will be introduced in China as well and therefore in the third of the three largest automobile markets worldwide. Changes of pressure dependent physical tire properties such as dynamic roll radius and a certain tire eigenfrequency, which are included in the ESC-wheel speed signals, indicates pressure loss in an indirect manner. Systems with corresponding working principles are called “indirect Tire Pressure Monitoring System” (iTPMS). Since the tire is a structural element with varying characteristics according to the design parameters, the roll radius and frequency behavior due to pressure loss is variable as well. As a consequence, tires have to be evaluated regarding there compatibility to iTPMS during the vehicle development process.

In ride comfort as well as driving dynamics, the behavior of the vehicle is affected by several subsystems and their properties. When analyzing the suspension, especially the characteristics of the main spring and damper but also rubber bushings are of main importance. Still, the properties of the different components are dependent on the present operating conditions. Concerning rubber bushings, several effects have already been investigated, e.g. dependencies of the transfer function of frequency, amplitude or load history. In this context influences of changes in temperature are often neglected. However, in the following research, the focus specifically lies on determination and analysis of the temperature dependency of rubber bushings. For this purpose, initially the relationship between properties of pure rubber and rubber bushings is described, which serves as a basis for correlating respective temperature dependencies.

A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered.

The open jet wind tunnel is a widespread test section configuration for developing full scale passenger cars in the automotive industry. However, using a realizable nozzle cross section for cost effective aerodynamic development is always connected to the presence of wind tunnel effects. Wind tunnel wall interferences which are not present under open road conditions, can affect the measurement of aerodynamic forces. Thus, wind tunnel corrections may be required. This work contains the results of a CFD (Computational Fluid Dynamics) approach using unsteady Delayed Detached Eddy Simulations (DDES) to evaluate wind tunnel interferences for open jet test sections. The Full Scale DrivAer reference geometry of the Technical University of Munich (TUM) using different rear end shapes has been selected for these investigations.

Recent attempts to find energy-efficient thermal management systems for electric and plug-in hybrid electric vehicles have led to secondary loop systems as an alternative approach to meet dynamic heating and cooling demands and to reduce refrigerant charge. The choice of refrigerant for the primary refrigeration cycle is an important issue regarding the overall system performance. In this work, an HFC refrigerant (R-134a) and a natural refrigerant (R-744) are evaluated regarding a potential use in secondary loop systems. To meet the demands of R-744 cycles such as higher system pressure, most components have to be redeveloped. Nonetheless the use of the environmentally friendly refrigerant has advantages such as better applicability and performance in heat pump systems under cold ambient conditions.

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.

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

In this paper, a comparison between different six-phase machine topologies is conducted considering their technical performance for automotive applications. Asymmetrical and symmetrical configurations, as well as neutral point connection, are considered as candidate topologies and modelled using vector space decomposition (VSD) and double stator or double dq transformations. In both cases, a generalized model to include an arbitrary phase shift between the windings is presented as well as the effect of the neutral connection on the inverter model. For the selection, the steady-state and post-fault performance are considered in terms of control flexibility, fault-tolerant capability, and dc-link voltage utilization. For the latest, the different topologies are evaluated operating in both linear and overmodulation regions based on space vector modulation (SVM).