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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.

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.

The reduction of both harmful emissions (CO, HC, NOx, etc.) and gases responsible for greenhouse effects (especially CO2) are mandatory aspects to be considered in the development process of any kind of propulsion concept. Focusing on ICEs, the main development topics are today not only the reduction of harmful emissions, increase of thermodynamic efficiency, etc. but also the decarbonization of fuels which offers the highest potential for the reduction of CO2 emissions. Accordingly, the development of future ICEs will be closely linked to the development of CO2 neutral fuels (e.g. biofuels and e-fuels) as they will be part of a common development process. This implies an increase in development complexity, which needs the support of engine simulations. In this work, the virtual modeling of real fuel behavior is addressed to improve current simulation capabilities in studying how a specific composition can affect the engine performance.

The simulation of transient engine behavior has gained importance mainly due to stringent emission limits, measured under real driving conditions and the concurrently demanded vehicle performance. This is especially true for turbocharged engines, as the coupling of the combustion engine and the turbocharger forms a complex system in which the components influence each other remarkably causing, for example, the well-known turbo lag. Because of this strong interaction, during a transient load case, the components should not be analyzed separately since they mutually determine their boundary conditions. Three-dimensional computational fluid dynamics (3D-CFD) simulations of full engines in stationary operating points have become practicable several years ago and will remain a valuable tool in virtual engine development; however, the next logical step is to extend this approach into the transient domain.

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.

Engine valve flow coefficients are not only used to characterize the performance of valve/port designs, but also for modelling gas exchange in 0D/1D engine simulation. Flow coefficients are usually estimated with small pressure ratios and at ambient air conditions. In contrast, the ranges for pressure ratio, pressure and temperature level during engine operation are much more extensive. In this work the influences of these three parameters on SI engine poppet valve flow coefficients are investigated using 3D CFD and measurements for validation. While former investigations already showed some pressure ratio dependencies by measurement, here the use of 3D CFD allows a more comprehensive analysis and a deeper understanding of the relevant effects. At first, typical ranges for the three mentioned parameters during engine operation are presented.

Engine valve flow coefficients are used to describe the flow throughput performance of engine valve/port designs, and to model gas exchange in 0D/1D engine simulation. Valve flow coefficients are normally determined at a stationary flow test bench, separately for intake and exhaust side, in the absence of the piston. However, engine operation differs from this setup; i. a. the piston might interact with valve flow around scavenging top dead center, and instead of steady boundary conditions, valve flow is nearly always subjected to pressure pulsations, due to pressure wave reflections within the gas exchange ports. In this work the influences of piston position and flow pulsation on valve flow coefficients are investigated for different SI engine geometries by means of 3D CFD and measurements at an enhanced flow test bench.

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.

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.

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.

Two combustion models are presented: A quasi-dimensional approach, based on the injection shape and an empirical model. Both models have computation times of less than one second per cycle. The quasi-dimensional approach for CI combustion discretizes the injection jet in slices. Pilot-injections are modeled as separate zones. The forecast capability and the limitations of the model are discussed on the basis of measurements. Mentioned above the base of the quasi-dimensional model is the injection rate. Often it is difficult to obtain these data. There is therefore another empirical approach for combustion, which does not need the injection rate as input. Both models have to be calibrated. This can be done by an automatic calibration tool on the basis of the advanced Powell method. The differences and advantages compared with other optimization methods are shown. Emission-simulation models are highly important in simulating CI engines.

A new phenomenological CI combustion model was developed. Within this model the given injection rate may contain an arbitrary number of injections during one cycle. Another target was a short computation time of one second per cycle on average. The new approach should also have the ability to simulate a wide engine spectrum from passenger-car engines through to marine engines. The ignition delay is calculated separately for each single injection. In this way the model depicts the influence of pilot injections on the ignition delay of proximate injections. Each pilot injection is modeled as a single air-fuel mixture cloud with air entrainment. The burn rate of the pilot injection is modeled as a function of flame propagation and of the current local excess air ratio. If the local excess air ratio becomes too lean the pilot combustion stops or does not start at all. Main and post-injections are calculated by means of a slice approach.

Longitudinal models are used to evaluate different vehicle-engine concepts with respect to driving behavior and emissions. The engine is generally map-based. An explicit calculation of both fluid dynamics inside the engine air path and cylinder combustion is not considered due to long computing times. Particularly for dynamic certification cycles (WLTC, US06 etc.), dynamic engine effects severely influence the quality of results. Hence, an evaluation of transient engine behavior with map-based engine models is restricted to a certain extent. The coupling of detailed 1D-engine models is an alternative, which rapidly increases the model computation time to approximately 300 times higher than that of real time. In many technical areas, the Fourier transformation (FT) method is applied, which makes it possible to represent superimposed oscillations by their sinusoidal harmonic oscillations of different orders.

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.

The research institute FKFS in cooperation with the IVK Universität Stuttgart has recently presented QuickSim, a 3D-CFD-tool, that works integrated into the commercial 3D-CFD-code Star-CD. QuickSim has been developed to cover a vacancy in the market of simulation programs for engine development. The code introduces a new concept in the 3D-CFD-simulation of internal combustion engines (SI-Manifold-Injection and SI-GDI), that drastically reduces the CPU-time in comparison to a conventional 3D-CFD-simulation. QuickSim, as a 3D-CFD-tool, combines the advantages of local resolution of the fluid-dynamical field of internal combustion engines exactly like that provided by traditional 3D-CFD-simulations and the versatility and clearness of the real working-process analysis (WP) and of the full 1D-flow calculations. The CPU-time always remains in an acceptable range (few hours over a full operating cycle for a single-processor computing simulation).

Due to the EU6 emission standard that will be mandatory starting in September 2014 the particulate emissions of GDI engines come into the focus of development. For this reason, soot and the mechanisms responsible for the soot formation are of particular importance. A very significant source of particulate emissions from engines with gasoline direct injection is the wall film formation. Therefore, the analysis of soot emission sources in the CFD calculation requires a detailed description of the entire underlying model chain, with special emphasis on the spray-wall interaction and the wall film dynamics. The validation of the mentioned spray-wall interaction and wall film models is performed using basic experimental investigations, like the infrared-thermography and fluorescence based measurements conducted at the University of Magdeburg.

High combustion pressure in combination with high pressure gradient, as they e.g. can be evoked by high efficient combustion systems and e.g. by alternative fuels, acts as broadband excitation force which stimulates natural vibrations of piston, connecting rod and crankshaft during engine operation. Starting from the combustion chamber the assembly of piston, connecting rod and crankshaft and the main bearings represent the system of internal vibration transfer. To generate exact input and validation values for simulation models of structural dynamic and elasto-hydrodynamic coupled multi-body systems, experimental investigations are done. These are carried out on a 1.5-l inline four cylinder Euro 6 Diesel engine. The modal behaviour of the system was examined in detail in simulation and test as a basis for the investigations. In an anechoic test bench airborne and structure-borne noises and combustion pressure are measured to identify the engine´s vibrational behaviour.

Improvement of heat-transfer calculation for SI-engines in the three-dimensional simulation has been achieved and widely been tested by using a phenomenological heat-transfer model. The model is based on the local application of an improved Re-Nu-correlation (dimensional analysis) proposed by Bargende [1]. This approach takes advantage of long experience in engine heat transfer modeling in the real working process analysis. The results of numerous simulations of different engine meshes show that the proposed heat-transfer model enables to calculate the overall as well as the local heat transfer in good agreement with both real working process analyses and experimental investigations. The influence of the mesh structure has also been remarkably reduced and compared to the standard wall function approach, no additional CPU-time is required.

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.

Main limiting factor in the application of 3D-CFD simulations within an engine development is the very high time demand, which is predominantly influenced by the number of cells within the computational mesh. Arbitrary cell coarsening, however, results in a distinct distortion of the simulation outcome. It is rather necessary to adapt the calculation models to the new mesh structure in order to ensure reliability and predictability of the 3D-CFD engine simulation. In the last decade, a fast response 3D-CFD tool was developed at FKFS in Stuttgart. It aims for a harmonized interaction between computational mesh, implemented calculation models and defined boundary conditions in order to enable fast running simulations for engine development tasks. Their susceptibility to errors is significantly minimized by various measures, e.g. extension of the simulation domain (full engine) and multi-cycle simulations.