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For metrological traceability of pressure sensors, static calibration procedures are standard. If these sensors are used in dynamic systems, unexpected phenomena or deviations occur in the recorded signal characteristics. By setting up a dynamic pressure calibration facility, it is possible to investigate this dynamic behavior and learn about the interactions between sensor and investigated system. To be able to identify the disturbing influences and interactions occurring during calibration and in subsequent measurement use, it is necessary to increase the existing understanding of the system. In the context of the contribution, the calibration procedure used, its properties such as repeatability, reproducibility as well as the system interaction of the influencing variables are analyzed. Special attention is paid to the effects of varying gas content in the calibration medium, its influence on the system and on the observed phenomena occurring.

In this paper, a serial/parallel hybrid electric vehicle with a 17 kWh battery and 400 V voltage level is simulated. The vehicle is a C-segment vehicle, which has optimized driving resistances. It also has an external recharge possibility, which enables fully electric driving. The vehicle uses an Otto-engine concept as well as two electric motors. One motor is a permanent magnet synchronous motor and can be used as traction motor or generator, the other one is an induction motor used as main traction motor for the vehicle. The vehicle uses a 2-speed gearbox, where the electric motors are mounted in P2-configuration. To reach optimal results for the fuel consumption, an operating strategy based on the Equivalent Consumption Minimization Strategy (ECMS) is introduced and implemented in the vehicle simulation.

Synthetic fuels from renewable energy sources can be a significant contribution on the roadmap to sustainable mobility. Porsche sees electro-mobility as the top priority, but eFuels produced by renewable electricity are an effective addition to support the defossilization of the transportation sector. In addition to the sustainability aspect, the composition and properties of eFuels can be optimized via the synthetic fuel production path. The use of optimized fuel formulations has a direct influence on combustion and emission behavior. The latter is one focus of the development of internal combustion engines in the wake of constantly tightening emissions legislation. The increasing restrictions on vehicles with internal combustion engines require the reduction of emissions. Particulate matter emissions are among others the focus of criticism. The composition and properties of fuels can reduce particulate emissions and the formation of unburned hydrocarbons to a high degree.

Due to its high benefit-cost ratio, decreasing mechanical friction losses in internal combustion engines represents one of the most effective and widely applicable solutions for improved engine efficiency. Especially the piston group - consisting of piston, rings and pin - shows significant potential for friction reduction, which can be evaluated through extensive experimental parameter studies. For each investigated variant, the steady-state friction measurements are fitted to an empirical polynomial model. In order to calculate the associated fuel consumption and CO2 emissions in transient driving cycles, the steady-state friction model is used in a map-based vehicle simulation. If transient engine operation entails friction phenomena that are not included in the steady-state model, the simulation could yield erroneous fuel consumption and CO2 predictions.

A wide variety of applications such as driver assistant and energy management systems are researched and developed in virtual test environments. The safe testing of the applications in early stages is based on parameterizable and reproducible simulations of different driving scenarios. One possibility is modeling the microscopic driving behavior to simulate the longitudinal vehicle dynamics of individual vehicles. The currently used driver models are characterized by a conflict regarding comprehensibility, accuracy and calibration effort. Due to the importance for further analyses this conflict of interests is addressed by the presentation of a new microscopic driver model in this paper. The proposed driver model stores measured driving behaviors with its statistical distributions in maps. Thereby, the driving task is divided into free flow, braking in front of stops and following vehicles ahead. This makes it possible to display the driving behavior in its entirety.

As the importance of sustainability increases and dominates the powertrain development within the automotive sector, this issue has to be addressed in motorsports as well. The development of sustainable high-performance fuels defined for the use in motorsports offers technical and environmental potential with the possibility to increase the sustainability of motorsports at the same or even a better performance level. At the moment race cars are predominantly powered by fossil fuels. However due to the emerging shift regarding the focus of the regulations towards high efficient powertrains during the last years the further development of the used fuels gained in importance. Moreover during the last decades a huge variety of sustainable fuels emerged that offer a range of different characteristics and that are produced based on waste materials or carbon dioxide.

With the increasingly strict emission regulations and economic demands, variable valve trains are gaining in importance in Diesel engines. A valve control strategy has a great impact on the in-cylinder charge motions, turbulence level, thus also on the combustion and emission formation. In order to predict in-cylinder charge motions and turbulence properties for a working process calculation, a zero−/quasi-dimensional flow model is developed for the Diesel engines with a fully variable valve train. For the purpose of better understanding the in-cylinder flow phenomena, detailed 3D CFD simulations of intake and compression strokes are performed at different operating conditions with various piston configurations. In the course of model development, global in-cylinder charge motions are assigned to idealized flow fields. Among them, swirl flow is characterized by an engine swirl number that is determined by both developments of the swirl angular momentum and the moment of inertia.

Minimizing the lap time for a given race track is the main target in racecar development. In order to achieve the highest possible performance of the vehicle configuration the mutual interaction at the level of assemblies and components requires a balance between the advantages and disadvantages for each design decision. Especially the major shift in the focus of racecar powerunit development to high efficiency powertrains is driving a development of lean boosted and rightsized engines. In terms of dynamic engine behavior the time delay from requested to provided torque could influence the lap time performance. Therefore, solely maximizing the full load behavior objective is insufficient to achieve minimal lap time. By means of continuous predictive virtual methods throughout the whole development process, the influence on lap time by dynamic power lags, e.g. caused by the boost system, can be recognized efficiently even in the early concept phase.

Upcoming regulations and new technologies are challenging the internal combustion engine and increasing the pressure on car manufacturers to further reduce powertrain emissions. Indeed, RDE pushes engineering to keep low emissions not only at the bottom left of the engine map, but in the complete range of load and engine speeds. This means for gasoline engines that the strategy used to increase the low end torque and power by moving out of lambda one conditions is no longer sustainable. For instance scavenging, which helps to increase the enthalpy of the turbine at low engine speed cannot be applied and thus leads to a reduction in low-end torque. Similarly, enrichment to keep the exhaust temperature sustainable in the exhaust tract components cannot be applied any more. The proposed study aims to provide a solution to keep the low end torque while maintaining lambda at 1. The tuning of the air intake system helps to improve the volumetric efficiency using resonance charging effects.

In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that employs a Random Forest (RF) based dissimilarity measure in the dimensionality reduction technique t-Distributed Stochastic Neighbor Embedding (t-SNE) to automatically identify and visualize different types of vehicle usage by applying these methods to aggregated logged on-board data, i.e., load spectrum data. This kind of data is calculated and recorded directly on the control units of the vehicles and consists of aggregated numerical data, like the histogram of the velocity signal or the traveled distance of a vehicle.

In this paper a rule-based energy management for parallel hybrid electric vehicles (HEVs) is presented, which is based on the principles describing the optimal control behavior. Therefore we first show the general relations that can be used to describe the optimal limit of electric driving as well as the optimal torque split among the two propulsion systems. Subsequently these relations are employed to derive maps, which represent the optimal behavior depending on several input parameters. These maps are then used as inputs for the rules in the proposed energy management. This not only makes it possible to automatically calibrate the rule-based controller but also gives the optimal control in every driving situation. Given it is not fuel-efficient to turn the internal combustion engine (ICE) on or off for short intervals, it is further shown how this approach allows to adjust the established limit for electric driving by additional rules.

In the last years motorsport is facing a technical revolution concerning the engine technology in every category, from touring car championships up to the F1. The strategy of the car manufacturers to bring motorsport engine technology closer to mass production one (e.g. turbo-charging, downsizing and direct injection) allows both to reduce development costs and to create a better image and technology transfer by linking motorsport activities to the daily business. Under these requirements the so-called Global Race Engine (GRE) concept has been introduced, giving the possibility to use one unique engine platform concept as basis for different engine specifications and racing categories. In order to optimize the performance of this kind of engines, especially due to the highly complex mixture formation mechanisms related to the direct injection, it is nowadays mandatory to resort to reliable 3D-CFD simulations.

In this paper the development approach and the results of numerical and experimental investigations on homogeneous charge compression ignition in a free piston engine are presented. The Free Piston Linear Generator (FPLG) is a new type of internal combustion engine designed for the application in a hybrid electric vehicle. The highly integrated system consists of a two-stroke combustion unit, a linear generator, and a mass-variable gas spring. These three subsystems are arranged longitudinally in a double piston configuration. The system oscillates linearly between the combustion chamber and the gas spring, while electrical energy is extracted by the centrally arranged linear generator. The mass-variable gas spring is used as intermediate energy storage between the downstroke and upstroke. Due to this arrangement piston stroke and compression ratio are no longer determined by a mechanical system.

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Until a few years ago the discussion of reduction of CO₂ emissions was completely out of place in motorsports. Nowadays, also in this field, car manufacturers want to investigate different approaches towards a more responsible and sustainable concept. For this target an interesting and feasible solution is the use of methane as an alternative fuel. At the 2009 edition of the 24-hour endurance race of the Nürburgring the Volkswagen Motorsport GmbH, in addition to vehicles powered by gasoline engines, introduced two vehicles powered by turbocharged CNG engines. The aim was to prove that also an "environment-friendly" concept is able to provide the required efficiency, dynamic and reliability for a successful participation in motorsports. After the success in the 2009 edition the engagement has been continued in 2010; this time exclusively with CNG vehicles.

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.

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).

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.

Today, mechanical systems such as the piston groups of internal combustion engines are simulated using Multiple Body-System (MBS) - approaches. However, the use of these models is restricted to a few problems as their adaptability is limited. The simulation of mechanical systems only by means of finite elements shows great promise for the future. In order to consider lubrication effects between two touching bodies of a mechanical system, a hydrodynamic contact algorithm (HCA) for finite element (FE) applications was developed. This paper discusses the technical background and first results for the simulation of a piston group using this new approach.