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The European Union has defined legally binding CO2-fleet targets for new cars until 2030. Therefore, improvement of fuel economy and carbon dioxide emission reduction is becoming one of the most important issues for the car manufacturers. Today’s conventional car powertrain systems are reaching their technical limits and will not be able to meet future CO2 targets without further improvement in combustion efficiency, using low carbon fuels (LCF), and at least mild electrification. This paper demonstrates a highly efficient and performant combustion engine concept with a passive pre-chamber spark plug, operating at stoichiometric conditions and powered with liquefied petroleum gas (LPG). Even from fossil origin, LPG features many advantages such as low carbon/hydrogen ratio, low price and broad availability. In future, it can be produced from renewables and it is in liquid state under relatively low pressures, allowing the use of conventional injection and fuel supply components.

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.

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.

The adequate dimensioning of drive train components such as gearbox, clutch and driveshaft presents a major technical task. The one of manual transmissions represents a special significance due to the customer’s ability of inducing high force, torque and thermic energy into the powertrain through direct mechanical interconnection of gearstick, clutch pedal and gearbox. Out of this, the question about how to capture behavior and strain of the components during real operation, as well as their objective evaluation evolves. Furthermore, the gained insights must be considered for designing and development. As a basis for the examination, measuring data from imposing driving tests are adduced. Therefore, a trial study has been conducted, using a representative circular course in the metropolitan area of Stuttgart, showing the average German car traffic. The more than 40 chosen drivers constitute the average driver in Germany with respect to age, gender and annual mileage.

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.

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.

The most significant operation limit prohibiting the further reduction of the CO2 emissions of gasoline engines is the occurrence of knock. Thus, being able to predict the incidence of this phenomenon is of vital importance for the engine process simulation - a tool widely used in the engine development. Common knock models in the 0D/1D simulation are based on the calculation of a pre-reaction state of the unburnt mixture (also called knock integral), which is a simplified approach for modeling the progress of the chemical reactions in the end gas where knock occurs. Simulations of thousands of knocking single working cycles with a model representing the Entrainment model’s unburnt zone were performed using a detailed chemical reaction mechanism. The investigations showed that, at specific boundary conditions, the auto-ignition of the unburnt mixture resulting in knock happens in two stages.

As a result of the R&D focus being shifted from internal combustion engines to electrified powertrains, resources for the development of internal combustion engines are restricted more and more. With that, the importance of highly efficient engine development tools is increased. In this context, 0D/1D engine simulation offers the advantage of low computational effort and fast engine model set-up. To ensure a high predictive ability of the engine simulation, a reliable burn rate model is needed. Considering the increasing interest in alternative fuels, the aspect of predicting the fuel influence on combustion is of special importance. To reach these targets, the change of engine combustion characteristics with changing fuels and changing air-fuel-ratios were investigated systematically in a first step. For this purpose, engine test bed data were compared with expected fuel-dependent flame wrinkling trends based on Markstein/Lewis number theory.

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.

Since 0D/1D-simulations of natural gas spark ignition engines use model theories similar to gasoline engines, the impact of changing fuel characteristics needs to be taken into consideration in order to obtain results of higher quality. For this goal, this paper proposes some approaches that consider the influence of binary fuel mixtures such as methane with up to 40 mol-% of ethane, propane, n-butane or hydrogen on laminar flame speed and knock behavior. To quantify these influences, reaction kinetics calculations are carried out in a wide range of the engine operation conditions. Obtained results are used to update and extend existing sub-models. The model quality is validated by comparing measured burn rates with simulation results. The benefit of the new sub-models are utilized by predicting the influence the fuel takes on engine operating limits in terms of knocking and lean misfire limits, the latter being determined by using a cycle-to-cycle variation model.

The development process of electronic control units (ECU) is increasingly supported by different tools. The target-specific code-generation for single micro-controllers becomes a standard technology. Thus a continuous tool support during the whole development cycle is possible. This extends from the specification of the functionality to the implementation of the software on the controller. The next generation of tool support is not only focused on single micro-controllers it also supports the design of systems consisting of different controllers connected via various communication entities. Thus the goal of the tool support is the automatic code-generation for such distributed embedded real-time systems including support of different communication buses (e.g., Controller Area Network CAN, Time Triggered Protocol TTP) and different processor targets.

Engine Knock is a stochastic phenomenon that occurs during the regular combustion of spark ignition (SI) engines and limits its efficiency. Knock is triggered by an autoignition of local “hot spots” in the unburned zone, ahead of the flame front. Regarding chemical kinetics, the temperature and pressure history as well as the knock resistance of the fuel are the main driver for the autoignition process. In this paper, a new knock modeling approach for natural gas blends is presented. It is based on a kinetic fit for the ignition delay times that has been derived from chemical kinetics simulations. The knock model is coupled with an enhanced burn rate model that was modified for Methane-based fuels. The two newly developed models are incorporated in a predictive 0D/1D simulation tool that provides a cost-effective method for the development of natural gas powered SI engines.

CNG direct injection is a promising technology to promote the acceptance of natural gas engines. Among the beneficial properties of CNG, like reduced pollutants and CO2 emissions, the direct injection contributes to a higher volumetric efficiency and thus to a better driveability, one of the most limiting drawbacks of today’s CNG vehicles. But such a combustion concept increases the demands on the injection system and mixture formation. Among other things it requires a much higher flow rate at low injection pressure. This can be only provided by an outward-opening nozzle due to its large cross-section. Nevertheless its hollow cone jet with a specific propagation behavior leads to an adverse fuel-air distribution especially at higher loads under scavenging conditions. This paper covers numerical and experimental analysis of CNG direct injection to understand its mixture formation.

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.

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.

Methane as an alternative fuel in motorsports? Actually this solution is well known for the reduction of CO₂ emissions but apparently it does not really awake race feelings. At the 2009 edition of the 24-hour endurance race on the Nürburgring the Volkswagen Motorsport GmbH, in addition to vehicles powered by gasoline engines, introduced two vehicles powered by innovative turbo-charged CNG engines for the first time. 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 also in 2010, this time exclusively with CNG vehicles. Focusing on the CO₂ emission, reclusively the higher hydrogen content of methane which represents the main component of NG leads to a CO₂ reduction during the combustion of about 20% compared to gasoline.

Knocking is one of today’s main limitations in the ongoing efforts to increase efficiency and reduce emissions of spark-ignition engines. Especially for synthetic fuels or any alternative fuel type in general with a much steeper increase of the knock frequency at the KLSA, such as hydrogen, precise knock prediction is crucial to exploit their full potential. This paper therefore proposes a post-processing tool enabling further investigations to continuously gain better understanding of the knocking phenomenon. In this context, evaluation of local auto-ignitions preceding knock is crucial to improve knowledge about the stochastic occurrence of knock but also identify critical engine design to further optimize the geometry. In contrast to 0D simulations, 3D CFD simulations provide the possibility to investigate local parameters in the cylinder during the combustion.

In order to decarbonize and lower the overall emissions of the transport sector, immediate and cost-effective powertrain solutions are needed. Natural gas offers the advantage of a direct reduction of carbon dioxide (CO2) emissions due to its better Carbon to Hydrogen ratio (C/H) compared to common fossil fuels, e.g. gasoline or diesel. Moreover, an optimized engine design suiting the advantages of natural gas in knock resistance and lean mixtures keeping in mind the challenges of power density, efficiency and cold start manoeuvres. In the public funded project MethMag (Methane lean combustion engine) a gasoline fired three-cylinder-engine is redesigned based on this change of requirements and benchmarked against the previous gasoline engine.

The new CO2 and emissions limits imposed to European manufacturers require the adoption of different innovative solutions, such as the use of potentially CO2-neutral synthetic fuels alongside a tailored development of the internal combustion engine, as an excellent solution to accompany the hybridization of vehicles. Dr.Ing. h.c. F. Porsche AG and FKFS, already partners for the development of engines with eFuels, propose a new study carried out on a research engine, investigating the combination of Porsche synthetic gasoline (POSYN) with an engine with millerization and passive pre-chamber. The use of CO2-neutral fuels allow for an immediate reduction in CO2 emissions from all cars already on the market, particularly since Porsche is one of the manufacturers whose cars remain in use for the longest time. The data collected on a single-cylinder engine test bench, for different fuels, with conventional spark plug are used as input for the calibration of 3D-CFD simulations.