Search Results

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.

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.

For a reliable and accurate simulation of SI engines reproduction of their operation limits (misfiring and knock limit) and in this context the knowledge of cyclic combustion variations and their influence on knock simulation are mandatory. For this purpose in this paper a real working-process simulation approach for the ability to predict cycle-to-cycle variations (ccv) of gasoline engines is proposed. An extensive measurement data base of four different test engines applying various operation strategies was provided in order to gain a better understanding of the physical background of the cyclic variations. So the ccv initiated by dilution strategies (internal EGR, lean operation), the ccv at full load and at the knock limit could be investigated in detail. Finally, the model was validated on the basis of three further engines which were not part of the actual development process.

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.

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.

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.

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.

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.

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.

The setting of boundary conditions on the boundaries of a 3D-CFD grid under certain conditions is a source of significant errors. The latter might occur by numerical reflection of pressure waves on the boundary or by incorrect setting of the chemical composition of the gas mixture in recirculation zones (e.g. in the intake manifold of internal combustion engines when the burnt gas from the cylinder enters the intake manifold and passes the boundary of the CDF-grid. When the flow direction is changed the setting of pure new charge on the boundary leads to errors). This type of problems should receive attention in operation points with low engine speed and load. The direct coupling of a 3D-CFD program (Star-CD) with a 1D-CFD program (GT-Power) is done by integration of the 3D-grid of the engine component as a „CFD-component” of the 1D computational model of a complete engine.

The industry is working intensively on the precision of thermal management. By using complex thermal management strategies, it is possible to make engine heat distribution more accurate and dynamic, thereby increasing efficiency. Significant efforts are made to improve the cooling efficiency of the engine water jacket by using 3D CFD. As well, 1D simulation plays a significant role in the design and analysis of the cooling system, especially for considering transient behaviour of the engine. In this work, a practice-oriented universal method for creating a 1D water jacket model is presented. The focus is on the discretization strategy of 3D geometry and the calculation of heat transfer using Nusselt correlations. The basis and reference are 3D CFD simulations of the water jacket. Guidelines for the water jacket discretization are proposed. The heat transfer calculation in the 1D-templates is based on Nusselt-correlations (Nu = Nu(Re, Pr)), which are derived from 3D CFD simulations.

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.

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.

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.

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.

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.

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.

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.

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.