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The main objective of the FVV-project “Cylinder Module” was the development of a profoundly modular designed concept for object-oriented modeling of in-cylinder processes of internal combustion engines. It was designed in such a way, that it can either be used as a stand-alone real working-process calculation tool or in tools for whole vehicle simulations. It is possible to run the “Cylinder Module”-code inside the FVV-“GPA”-software for transient vehicle and driving cycle simulations and it is possible to use the graphical user interface “ATMOS” of the “GPA”-project. The code can also be used as a user-subroutine in 1-D-flow simulation codes. Much effort was spent on the requirements of flexibility and expandability in order to be well prepared to cope with the diversity of both today's and future tasks. The code is freely available for members of the German Research Association for Combustion Engines (FVV).

This paper presents an integrated numerical and experimental approach to take best possible advantage of the common development tools at hand (1D, CFD and wind tunnel) to determine the cooling air mass flow at the different vehicle development stages. 1D tools can be used early in development when neither 3D data nor wind tunnel models with detailed underhood flow are available. A problem that has to be resolved is the dependency on input data. In particular, the pressure coefficients on the outer surface (i.e. at the air inlet and outlet region) and the pressure loss data of single components are of great importance since the amount of cooling air flow is directly linked to these variables. The pressure coefficients at the air inlet and outlet are not only a function of vehicle configuration but also of driving velocity and fan operation. Both, static and total pressure coefficient, yield different advantages and disadvantages and can therefore both be used as boundary conditions.

The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

Cooling air flow is an important factor when it comes to vehicle performance and operating safety. In addition, it is closely linked to vehicle aerodynamics. In recent years more and more effort is being spent to optimize the losses generated by the flow through the vehicle. Grille shutters, better sealing and ducting are only some examples for innovations in this field of work, resulting in a lower contribution of the cooling air flow to overall drag. When investigating those effects, both experiments and numerical simulations are commonly used in the automotive environment. Still, when comparing the results from both methods, differences in the effect of cooling air flow can often be observed. To better understand the effects of cooling air flow, the ECARA Subgroup CFD decided to establish a common design for a generic open source vehicle model with a detailed underhood compartment to lay the foundation for a common investigation model.

In this article the unsteady aerodynamic properties of a 25% scale DrivAer notchback model as well as the influence of the wind tunnel environment on the resulting unsteady aerodynamic forces and moments under crosswind excitation are investigated using experimental and corresponding numerical methods. Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) swing® (side wind generator) is used to reproduce the essential properties of natural stochastic crosswind in the open jet test section of the Institute for Internal Combustion Engines and Automotive Engineering (IVK) model scale wind tunnel (MWK). The results show that the test environment of an open jet wind tunnel alters the amplitudes of side force and yaw moment under crosswind excitation when compared to an ideal environment neglecting wind tunnel interference effects.

Cooling air flow is an important factor when it comes to vehicle performance and operating safety. In addition, it is closely linked to vehicle aerodynamics. In recent years more and more effort is being spent to optimize the losses generated by the flow through the vehicle. Grille shutters, better sealing and ducting are only some examples for innovations in this field of work, resulting in a lower contribution of the cooling air flow to overall drag. But cooling air not only affects the internal flow of the vehicle but also changes the flow around it. This paper will show changes in the flow field around the generic DrivAer model resulting from cooling air flow, especially in the wake behind the car and in the region around the front wheels. The results were gathered using PIV measurements, multi-hole-probe measurements and pitot tube measurements in the 1:4 model scale wind tunnel of IVK University of Stuttgart.

In this paper the influence of different turbulent flow conditions on the aerodynamic drag of a quarter scale model with notchback and estate back rear ends is investigated. FKFS swing® (Side Wind Generator) is used to generate a turbulent flow field in the test section of the IVK model scale wind tunnel. In order to investigate the increase in drag with increasing yaw, a steady state yaw sweep is performed for both vehicle models. The shape of the drag curves vary for each vehicle model. The notchback model shows a more pronounced drag minimum at 0° yaw angle and experiences a more severe increase in drag at increasing yaw when compared to the estate back model. Unsteady time averaged aerodynamic drag values are obtained at two flow situations with different turbulent length scales, turbulence intensities, and yaw angle amplitudes. While the first one is representing light wind, the second one is recreating the presence of strong gusty wind.

In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.

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.

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.

This paper presents an autonomous cruise control for battery electric vehicles. The presented approach is based on the usage of predictive route data which is extracted out of a digital map and a wide range radar system in order to capture vehicles in front. By using the predictive route data and the information of the radar system, the autonomous cruise control can control the vehicle's speed over a wide range of driving situations without any driver interaction. The main aim of the presented autonomous cruise control is to optimize the battery electric vehicle's energy consumption. The main idea is to use predictive route data in order to calculate a consumption optimal vehicle speed trajectory by means of online optimization. The benefits of the autonomous cruise control are shown by means of real test drives and measured data evaluation.

For many years FKFS has operated the full-scale aeroacoustic wind tunnel of University of Stuttgart. To keep this wind tunnel as one of the most modern ones of its kind, it has again been upgraded significantly. The upgrade improved the aerodynamic as well as the aeroacoustic performance and accelerated the operational processes. Additionally, new innovative features have significantly enlarged the test capabilities. A new patented, modular belt system (FKFS first®) allows high performance measurements for race cars in a 3-belt mode as well as efficient measurements for production vehicle development in a 5-belt mode. The belt system is accompanied by a new, larger turntable and a new under-floor balance which enables high-accuracy measurements of forces and moments also for a high resolution in time. For the elimination of parasitic forces generated at the wheel drive units, a specific correction procedure has been implemented, which is patented, too (FKFS pace®).

In this paper the effect of aerodynamic modifications that influence the unsteady aerodynamic properties of a vehicle on the response of the closed loop system driver-vehicle under side wind conditions is investigated. In today's aerodynamic optimization the side wind sensitivity of a vehicle is determined from steady state values measured in the wind tunnel. There, the vehicle is rotated with respect to the wind tunnel flow to create an angle of attack. In this approach however, the gustiness that is inherent in natural wind is not reproduced. Further, unsteady forces and moments acting on the vehicle are not measured due to the limited dynamic response of the commonly used wind tunnel balances. Therefore, a new method is introduced, overcoming the shortcomings of the current steady state approach. The method consists of the reproduction of the properties of natural stochastic crosswind that are essential for the determination of the side wind sensitivity of a vehicle.

The hybrid power train technology offers various prospects to optimize the engine efficiency in order to minimize the CO₂ emissions of an internal-combustion-engine-powered vehicle. Today different types of hybrid architectures like parallel, serial, power split or through-the-road concepts are commonly known. To achieve lowest fuel consumption the following hybrid electric vehicle drive modes can be used: Start/Stop, pure electric/thermal driving, recuperation of brake energy and the hybrid mode. The high complexity of the interaction between those power sources requires an extensive investigation to determine the optimal configuration of a natural-gas-powered SI engine within a parallel hybrid power train. Therefore, a turbocharged 1.0-liter 3-cylinder CNG engine was analyzed on the test bench. Using an optimized combustion strategy, the engine was operated at stoichiometric and lean air/fuel ratio applying both high- and low-pressure EGR.

Brake system development and testing is spread over vehicle manufacturers, system and component suppliers. Test equipment from different sources, even resulting from different technology generations, different data analysis and report tools - comprising different and sometimes undocumented algorithms - lead to a difficult exchange and analysis of test results and, at the same time, contributes to unwanted test variability. Other studies regarding the test variability brought up that only a unified and unambiguous data format will allow a meaningful and comparative evaluation of these data and only standardization will reveal the actual reasons of test variability. The text at hand illustrates that a substantial part of test variability is caused by a misinterpretation of data and/or by the application of different algorithms.

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 design of the PORSCHE wind tunnels - two facilities, one in full- and the other in quarter-scale - was determined by the demand for simulating both passenger car models and racing vehicles. One peculiarity, the very low ride height of the latter requires a reduction of the oncoming boundary layer that develops along the test- section floor. The number of difficult practical engineering problems in using and operating full-scale moving belts (*Bearman et al. [14]), led to the development of two suction systems using porous plates in the test section floor. These have been installed in the full-scale and in the 1:4 - scale windtunnels. For verification or optimization of the originally estimated suction rates required to meet realistic road conditions, a number of experiments on the road and in a moving-belt facility were conducted and the results compared to values from the suction facilities.

Turbocharged SI-DI-engines in combination with a reduction of engine displacement (“Downsizing”) offer the possibility to remarkably reduce the overall fuel consumption. In charged mode it is possible to scavenge fresh unburnt air into the exhaust system if a positive slope during the overlap phase of the gas exchange occurs. The matching of the turbo system in SI-engines always causes a trade-off between low-end torque and high power output. The higher mass flow at low engine speeds of an engine using scavenging allows a partial solution of this trade-off. Thus, higher downsizing grades and fuel consumption reduction potential can be obtained. Through scavenging the global fuel to air ratio deviates from the local in-cylinder fuel to air ratio. It is possible to use a rich in-cylinder fuel to air ratio, whereas the global fuel to air ratio remains stochiometrical. This could be very beneficial to reduce the effect of catalytic aging on the one hand and engine knock on the other hand.

Enhanced technological capabilities render the application of various, increasingly complex, functional concepts for automated driving possible. In the process, the significance of automotive software for a satisfactory driving experience is growing. To benefit from these new opportunities, thorough assessment in early development stages is highly important. It enables manufacturers to focus resources on the most promising concepts. For early assessment, a common approach is to set up vehicles with additional prototyping hardware and perform real world testing. While this approach is essential to assess the look-and-feel of newly developed concepts, its drawbacks are reduced reproducibility and high expenses to achieve a sufficient and balanced sample. To overcome these drawbacks, new flexible, realistic and preferably automated virtual test methods to complement real world verification and validation are especially required during early development phases.

Optimization-based strategy planning for predictive optimal cruise control has the potential for significant improvements in passenger comfort and fuel efficiency. It is, however, associated with a high computational complexity that complicates its implementation in an electronic control unit. When implementing predictive cruise control, real-time capability must be ensured while maintaining optimal control performance in the presence of disturbance and model uncertainty. Real-time capability can be achieved either by a significant simplification of the optimization problem or by a layered control approach, combining the strategy planner with a low-level controller. Both approaches, however, are prone to deteriorate optimal control performance, particularly in the presence of disturbance. We present a model-predictive controller structure that extends the layered control approach by using the same optimization algorithm on two layers.