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Due to increasingly strict emission regulations, lean combustion concept has become an essential direction of internal combustion engine development to reduce engine emissions. However, lean combustion will lead high combustion instability and unpredictive engine emissions. The combustion instability is represented as the high cycle-to-cycle variation. Therefore, understanding the mechanism of cycle-to-cycle variation is crucial for the internal combustion engine design. This paper investigates the cause-and-effect chain of cycle-to-cycle variation of spark ignition engines using 3D CFD simulations with CONVERGE v3.0. The cyclic variations were simulated through Large Eddy Simulations, and the simulations based on Reynolds-averaged Navier–Stokes were used as supplements. The analysis focuses on two key factors that determine the combustion process: the turbulent intensity and the homogeneity of the air/fuel mixture.

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.

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.

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.

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.

For the gasoline engine, the isochoric process is the ideal limit of the ideal processes. During the project, a combustion engine with real isochoric boundary conditions is built. A “resting time” of the piston for several degrees crank angle in the top dead center (TDC) can be realized with a special crank drive. This crank drive consists of two crankshafts with different strokes, which are combined. The two crankshafts rotate with a ratio of two to one in opposite directions. The total stroke corresponds to the amount of the first crankshaft, so it is possible to investigate different strokes of the second crankshaft in the same crankcase. Different “resting times” can be achieved by different strokes of the second crankshaft. A specific combination of both crankshafts make a stroke possible which corresponds to that of a conventional combustion engine.

In order to meet increasingly stringent exhaust emission regulations, new engine concepts need to be developed. Lean combustion systems for stationary running large gas engines can reduce raw NOx-emissions to a very low level and enable the compliance with the exhaust emission standards without using a cost-intensive SCR-aftertreatment system. Experimental investigations in the past have already confirmed that a strong reduction of the charge air temperature even below ambient conditions by using an absorption chiller can significantly reduce NOx emissions. However, test bench operation of large gas engines is costly and time-consuming. To increase the efficiency of the engine development process, the possibility to use 0D/1D engine simulation prior to test bench studies of new concepts is investigated using the example of low temperature charge air cooling. In this context, a reliable prediction of engine efficiency and NOx-emissions is important.

The reduction of engine-out emissions and increase of the total efficiency is a fundamental approach to reduce the fuel consumption and thus emissions of vehicles driven by combustion engines. Conventional passenger cars are operated mainly in lower part loads for most of their lifetime. Under these conditions, oil temperatures are far below the maximum temperature allowed and dominate inside the journal bearings. Therefore, the objective of this research was to investigate possible potentials of friction reduction by optimizing the combustion engine’s thermal management of the oil circuit. Within the engine investigations, it was shown that especially the friction of the main and connecting rod bearings could be reduced with an increase of the oil supply temperature. Furthermore, on a journal bearing test rig, it was shown that no excessive wear of the bearings is to be expected in case of load increase and simultaneous supply of cooler oil.

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.

The real cycle simulation is an important tool to predict the engine efficiency. To evaluate Extended Expansion SI-engines with a multi-link cranktrain, the challenge is to consider all concept specific effects as best as possible by using appropriate submodels. Due to the multi-link cranktrain, the choice of a suitable heat transfer model is of great importance since the cranktrain kinematics is changed. Therefore, the usage of the mean piston speed to calculate a heat-transfer-related velocity for heat transfer equations is not sufficient. The heat transfer equation according to Bargende combines for its calculation the actual piston speed with a simplified k-ε model. In this paper it is assessed, whether the Bargende model is valid for Extended Expansion engines. Therefore a single-cylinder engine is equipped with fast-response surface-thermocouples in the cylinder head. The surface heat flux is calculated by solving the unsteady heat conduction equation.

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.

More than 20 years after the first presentation of the heat transfer equation according to Bargende [1,2], it is time to introduce some useful additions and enhancements, with respect to new and advanced combustion principles like diesel- and gasoline- homogeneous charge compression ignition (HCCI). In the existing heat transfer equation according to Bargende the calculation of the actual combustion chamber surface area is formulated in accordance with the work of Hohenberg. Hohenberg found experimentally that in the piston top land only about 20-30% of the wall heat flux values from the combustion chamber are transferred to the liner and piston wall. Hohenberg explained this phenomenon that is caused by lower gas temperature and convection level in charge within the piston top land volume. The formulation just adds the existing piston top land surface area multiplied by a specified factor to the surface of the combustion chamber.

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 basic research on the piston group a new simulation technique is developed using the contact algorithm of a commercial FE-code (MARC). Several improvements were made in order to adapt the MARC solver to the problem of sliding and dynamic contact. The first computations, a real transient analysis simulating the piston group, of both a two-stroke engine and a modern direct injected four-stroke Diesel engine for passenger cars, show that the new method is able to calculate the movements, velocities and accelerations of the piston. The quality of the results is mainly influenced by the hydrodynamic effects.