Search Results

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.

To demonstrate the potential of a CO2-minimized propulsion concept a study of a natural-gas, micro-hybrid powertrain was carried out. The basis was built by experimental investigations of a turbocharged 1.0-l, 3-cylinder engine operated at stoichiometric and lean air/fuel ratio with EGR and an optimized combustion strategy. With the results of this study a still existing model for micro-hybrid vehicles was filled and the CO2 emissions for several concepts were calculated. It could be shown that CO2 improvements of 30 to 40% for the IC engine and up to 50% for the complete micro-hybrid propulsion system accompanied with better driveability are possible.

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).

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 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.

Predictive physical modeling is an established method used in the development process for automotive components and systems. While accurate predictions can be issued after tuning model parameters, long computation times are expected depending on the complexity of the model. As requirements for components and systems continuously increase, new optimization approaches are constantly being applied to solve multidimensional objectives and resulting conflicts optimally. Some of those approaches are deemed not feasible, as the computational times for required single predictions using conventional simulation models are too high. To address this issue it is proposed to use data-driven model such as neural networks. Previous efforts have failed due to sparse data sets and resulting poor predictive ability. This paper introduces an AI Toolchain used for data-driven modeling of combustion engine components. Two methods for generating scalable and fully variable datasets will be shown.

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.

Variation of the geometric compression ratio in gasoline combustion engines during engine operation enables potential for decreasing fuel consumption as well as emissions. One way to achieve a variable geometric compression ratio (VCR) is the application of a connecting rod with a variable effective length between its large end and its small end. Such a system consists of a connecting rod body with an eccentrically supported piston pin and a linkage which is supported hydraulically. Therefore, the connecting rod evolves from a solid part to a complex assembly of mechanical and hydraulic parts. In order to deploy this system in the most efficient way, an understanding of the physics and the dynamic behavior of the VCR connecting rod is necessary. This includes the mechanical subsystem as well as the hydraulic subsystem. This paper describes the experimental examination of a two stage variable connecting rod.

Comparative analyses of a high-performance 4-cylinder DISI-engine and its equivalent single-cylinder research engine were performed by means of fast response 3D-CFD simulations. Both engines have identical geometries of intake and exhaust channels, cylinder head and piston. The used 3D-CFD tool QuickSim was developed at the Forschungsinstitut für Kraftfahrwesen und Fahrzeugmotoren Stuttgart (FKFS), particularly for the numerical simulation of internal combustion engines (ICE). A calibration of the air consumption enabled a comparison of in-cylinder processes, including charge motion, mixture formation and combustion. All calculated operating points showed a similar trend. Deviations during the gas exchange phase led to a higher turbulence level and hence combustion velocity for the single-cylinder research engine. This resulted in a slightly higher maximum cylinder pressure and indicated mean effective pressure.

This study presents a comparison of different approaches for the simulation of HEV fuel consumption. For this purpose a detailed 1D-CFD model within an HEV drivetrain is compared to a ‘traditional’ map-based combustion engine model as well as different types of simplified engine models which are able to reduce computing time significantly while keeping the model accuracy at a high level. First, a simplified air path model (fast running model) is coupled with a quasi dimensional, predictive combustion model. In a further step of reducing the computation time, an alternative way of modeling the in cylinder processes was evaluated, by replacing the combustion model with a mean value model. For this approach, the most important influencing factors of the 1D-CFD air path model (temperature, pressure, A/F-ratio) are used as input values into neural nets, while the corresponding outputs are in turn used as feedback for the air path model.

The emission of particulate matter from future GDI engines has to be optimized, to comply with more stringent emission standards such as EU6. Therefore, the mechanisms responsible for the formation of particles have to be analyzed in detail. The understanding of the in-cylinder processes, necessary for this purpose, can only be achieved by a complementary use of optically accessible single-cylinder engines as well as the numerical simulation. This however leads to great demands on the 3D flow simulation. In this paper the complete CFD approach, incorporating a detailed description of the entire underlying model chain is shown. Particularly the wall surface temperature and the temperature drop due to the interaction with liquid fuel spray were identified as important parameters influencing the spray-wall interaction and thus also the particulate emissions. Nevertheless, in conventional CFD models, the spray cooling cannot be captured because of an assumed constant wall temperature.

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.

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.

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.

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.

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.

Future combustion engine applications require highest possible energy conversion efficiencies to reduce their environmental impact and be economically competitive. So far, spark-ignition (SI) engine combustion development mostly consisted of optimizing the hemispherical flame propagation combustion method. Thereby, a significant efficiency increase is only achievable in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Simultaneously, researchers have been investigating homogeneous charge compression ignition (HCCI) that achieves higher efficiencies due to its rapid volume reaction combustion and also enables high excess air dilution. However, the combustion is complex to control as it is initiated by auto-ignition (AI) processes. In-cylinder conditions reliably need to be reproduced to prevent damaging pre-ignitions.

Prospective combustion engine applications require the highest possible energy conversion efficiencies for environmental and economic sustainability. For conventional Spark-Ignition (SI) engines, the quasi-hemispherical flame propagation combustion method can only be significantly optimized in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Pre-Chamber (PC) initiated jet ignition combustion systems significantly shift the flammability and flame stability limits towards higher dilution areas due to high levels of introduced turbulence and a significantly increased flame area in early combustion stages, leading to considerably increased combustion speeds and high efficiencies. By now, vehicle implementations of PC-initiated combustion systems remain niche applications, especially in combination with lean mixtures.