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.

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.

Further advancing key technologies requires the optimization of increasingly complex systems with strongly interacting parameters—like efficiency optimization in engine development for optimizing the use of energy. Systematic optimization approaches based on metamodels, so-called Metamodel-Based Design Optimization (MBDO), present one key solution to these demanding problems. Recent advanced methods either focus on Single-Objective Optimization (SoO) on local metamodels with online adaptivity or Multiobjective Optimization (MoO) on global metamodels with only limited adaptivity. In the scope of this work, a fully online adaptive (“in the loop”) optimization approach, capable of both SoO and MoO, is developed which automatically approximates the global system response and determines the (Pareto) optimum.

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.

Laser induced fluorescence (LIF) is used to investigate oil transport mechanisms under real engine conditions. The engine oil is mixed with a dye that can be induced by a laser. The emitted light intensity from the dye correlates with the residual oil at the sensor position and the resulting oil film thicknesses can be precisely determined for each crank angle. However, the general expectation is not always achieved, e.g. an exact representation of piston ring barrel shapes. In order to investigate the responsible lubrication effects of this behavior, a new cavitation algorithm for the Reynolds equation has been developed. The solution retains the mass conservation and does not use any switch function in its mathematical approach. In contrast to common approaches, no vapor-liquid ratio is used, but one or several bigger bubbles are approximated, as have been observed in other experiments already.

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.

Improving fuel efficiency while meeting relevant emission limits set by emissions legislation is among the main objectives of engine development. Simultaneously the development costs and development time have to be steadily reduced. For these reasons, the high demands in terms of quality and validity of measurements at the engine test bench are continuously rising. This paper will present a new methodology for efficient testing of an industrial combustion engine in order to improve the process of decision making for combustion-relevant component setups. The methodology includes various modules for increasing measurement quality and validity. Modules like stationary point detection to determine steady state engine behavior, signal quality checks to monitor the signal quality of chosen measurement signals and plausibility checks to evaluate physical relations between several measurement signals ensure a high measurement quality over all measurements.

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.

This SAE Technical Paper contains detailed data which are relevant for the calculation of the friction forces of the piston assembly in internal combustion engines. Useful ways of employing calculations besides measurements are exactly classified for the optimization of the piston assembly system in order to reduce friction losses. In the first step the theoretical basics for the calculation of the tribological system are introduced. Referring to the theory, the paper goes into detail about the basic set-up and the modeling degree of the calculation program. Furthermore, measured and calculated curves of friction forces are compared for different operating points. In addition, analysis of the crank-angle resolved friction force are presented with varying engine speeds, oil temperatures and loads and a detailed interpretation of the results is given.

A new constant volume combustion chamber (CVCC) apparatus is presented that calculates the cetane number (CN) of fuels from their ignition delay by means of a primary reference fuel calibration. It offers the benefits of low fuel consumption, suitability for non-lubricating substances, accurate and fast measurements and a calibration by primary reference fuels (PRF). The injection system is derived from a modern common-rail passenger car engine. The apparatus is capable of fuel injection pressures up to 1200 bar and requires only 40 ml of the test fuel. The constant volume combustion chamber can be heated up to 1000 K and pressurized up to 50 bar. Sample selection is fully automated for independent operation and low levels of operator involvement. Capillary tubes employed in the sampling system can be heated to allow the measurement of highly viscous fuels.

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.

Modern methods of engine development use complex mathematical models. Adding advanced components such as variable valve trains or direct injection systems to the model increases the degrees of freedom resulting in a high number of measurements for validation. Steadily rising costs for development, time and staff make it crucial for industry to improve the quality of measurements with advanced analysis techniques. Often, such models consider the simulated system as stationary, implying that system variables no longer change with time. This paper presents an internal combustion engine measurement system utilizing algorithms for the real-time evaluation of the state of the engine or its components. Several approaches have been reviewed and tested regarding their applicability. The most straightforward algorithms compare the gradient of a sensor signal to a pre-defined threshold.

For the next stage of Homogeneous Charge Compression Ignition (HCCI) engine researches, the development of an engine controller, taking account of dynamics is required. The objective of this paper is to develop dynamic multi input and multi output HCCI engine models and a controller to deal with variable valve lift, variable valve phase, and fuel injection. First, a physical continuous model has been developed. This model mainly consists of air flow models, an ignition model, and a combustion and mechanical model of the engine. The flow models use a receiver model on volumetric elements such as an intake manifold and a valve flow model on throttling elements such as intake valves. Livengood-wu integration of Arrhenius function is used to predict ignition timing. The combustion duration is expressed as a function of ignition timings.

In the present work the benefit of a 50 MPa gasoline direct injection system (GDI) in terms of particle number (PN) emissions as well as fuel consumption is shown on a 0.5 l single cylinder research engine in different engine operating conditions. The investigations show a strong effect of injection timing on combustion duration. As fast combustion can be helpful to reduce fuel consumption, this effect should be investigated more in detail. Subsequent analysis with the method of particle image velocimetry (PIV) at the optical configuration of this engine and three dimensional (3D) computational fluid dynamics (CFD) calculations reveal the influence of injection timing on large scale charge motion (tumble) and the level of turbulent kinetic energy. Especially with delayed injection timing, high combustion velocities can be achieved. At current series injection pressures, the particle number emissions increase at late injection timing.

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.