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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.

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.

Intensified emission regulations as well as consumption demands lead to an increasing significance of unburned hydrocarbon (UHC) emissions for diesel engines. On the one hand, the quantity of hydrocarbon (HC) raw emissions is important for emission predictions as well as for the exhaust after treatment. On the other hand, HC emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the HC molecules. Due to these reasons, a simulation model for predicting HC raw emissions was developed for diesel engines based on a phenomenological two-zone model. The HC model takes three main sources of HC emissions of diesel engines into account: Firstly, it contains a sub-model that describes the fuel dribble out of the injector after the end of injection. Secondly, HC emissions from cold peripheral zones near cylinder walls are determined in another sub-model.

As a result of the R&D focus being shifted from internal combustion engines to electrified powertrains, resources for the development of internal combustion engines are restricted more and more. With that, the importance of highly efficient engine development tools is increased. In this context, 0D/1D engine simulation offers the advantage of low computational effort and fast engine model set-up. To ensure a high predictive ability of the engine simulation, a reliable burn rate model is needed. Considering the increasing interest in alternative fuels, the aspect of predicting the fuel influence on combustion is of special importance. To reach these targets, the change of engine combustion characteristics with changing fuels and changing air-fuel-ratios were investigated systematically in a first step. For this purpose, engine test bed data were compared with expected fuel-dependent flame wrinkling trends based on Markstein/Lewis number theory.

As a promising solution to improve fuel efficiency of a long-haul heavy duty truck with diesel engine, organic Rankine cycle (ORC) based waste heat recovery system (WHR) by utilizing the exhaust gas from internal combustion engine has continuously drawn attention from automobile industry in recent years. The most attractive concept of ORC-based WHR system is the conversion of the thermal energy of exhaust gas recirculation (EGR) and exhaust gas from Tailpipe (EGT) to kinetic energy which is provided to the engine crankshaft. Due to a shift of the operating point of the engine by applying WHR system, the efficiency of the overall system increases and the fuel consumption reduces respectively. However, the integration of WHR system in truck is challenging by using engine cooling system as heat sink for Rankine cycle. The coolant mass flow rate influences strongly on the exhaust gas bypass which ensures a defined subcooling after condenser to avoid cavitation of pump.

At specific operating conditions, the auto-ignition in the unburnt mixture that precedes the occurrence of knock in conventional SI engines happens in two stages. In a previous publication, the authors demonstrated that the low-temperature heat release significantly influences the auto-ignition behavior of the mixture, thus severely impairing the prediction capabilities of the Livengood-Wu integral that the majority of the commonly used 0D/1D knock models are based on. Consequently, a new two-stage auto-ignition prediction approach for modeling the progress of the chemical reactions was introduced. It was demonstrated that the proposed auto-ignition model predicts the occurrence of two-stage ignition and accurately considers the significant influence of low-temperature heat release on the mixture’s auto-ignition behavior at various operating conditions.

High-efficient simulations are mandatory to manage the ever-increasing complexity of automotive powertrain system and reduce development time and costs. Integrating AI methods into the development process provides an ideal solution thanks to massive increase in computational power. Based on an 1D physical engine model of a turbo-charged direct injection gasoline engine with variable valve timing (VVT), a high-performance hybrid simulation model has been developed for increasing computing performance. The newly developed model is made of a physics-based low-pressure part including intake and exhaust peripheries and a neural-network-based high-pressure part for combustion chamber calculations. For the training and validation of the combustion chamber neural networks, a data set with 10.5 million operating points was generated in a short time thanks to the parallelizable combustion chamber simulations in stand-alone mode.

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.

As a promising concept to improve fuel efficiency of a long-haul heavy duty truck with diesel engine, organic Rankine cycle (ORC) based waste heat recovery system (WHR) by utilizing the exhaust gas from internal combustion engine has continuously drawn attention from industry in recent years. The greatest achievable global efficiency may be, however, restricted by the engine. On one hand, engine operating conditions have direct impact on the temperature and the mass flow of exhaust gas, which is the waste heat source, on the other hand, the engine cooling system limits the heat rejection from the condenser of the WHR system. This paper aims to evaluate the impacts of the varied engine applications considering the effects of the WHR system on the global efficiency and engine emissions.

Since 0D/1D-simulations of natural gas spark ignition engines use model theories similar to gasoline engines, the impact of changing fuel characteristics needs to be taken into consideration in order to obtain results of higher quality. For this goal, this paper proposes some approaches that consider the influence of binary fuel mixtures such as methane with up to 40 mol-% of ethane, propane, n-butane or hydrogen on laminar flame speed and knock behavior. To quantify these influences, reaction kinetics calculations are carried out in a wide range of the engine operation conditions. Obtained results are used to update and extend existing sub-models. The model quality is validated by comparing measured burn rates with simulation results. The benefit of the new sub-models are utilized by predicting the influence the fuel takes on engine operating limits in terms of knocking and lean misfire limits, the latter being determined by using a cycle-to-cycle variation model.

The engine development process has been enhanced significantly by virtual engineering methods during the last decades. In terms of in-cylinder flow field, charge flow and combustion modelling, 3D-CFD (three dimensional) simulations enable detailed analysis and extended investigations in order to gain additional knowledge about design parameters. However, the computational time of the 3D-CFD is an obvious drawback that prevents a reasonable application for extensive analysis with varying speed, load and transient conditions. State-of-the-art 0D (zero dimensional) approaches close the gap between the demand of high computational efficiency and a satisfying accordance with experimental data. Recent improvements of phenomenological combustion approaches for gasoline spark ignition engines deal with the consideration of detailed flow parameters, the accuracy of the laminar flame speed calculation and the prediction of the knock limit.

Knocking is still one of today’s major limitations regarding efficiency-increasing measures for SI combustion engines. Due to the complex stochastic nature of the phenomenon, not only prediction and consideration within the engine development is of relevance. A further challenge is control of the phenomenon during engine operation, with the aim of maximizing the efficiency while preventing engine damage and maintaining the driver comfort. Conventional knock control is characterized by detecting knock events and subsequently adjusting the spark timing depending on whether knock was detected. This paper proposes a new knock control concept based on the prediction and direct control of the knock frequency, compared to the conventional reactive and indirect control of the knock frequency. For the prediction of the knock frequency, a calculation approach based on three different parameters is utilized.

Engine knock is limiting the efficiency of spark ignition engines and consequently further reduction of CO2 emissions. Thus, an combustion process simulation needs a well working knock model to take this phenomenon into account. As knocking events result from auto-ignitions, the basis of a knock model is the accurate modeling of the latter. For this, the introduced 0D/1D knock model calculates the Livengood-Wu integral to estimate the state of the pre-reactions of the unburnt mixture and considers the two-stage auto-ignition of gasoline fuels, which occurs at specific boundary conditions. The model presented in this publication is validated against measurement data of a single cylinder engine. For this purpose, more than 12 000 knocking working cycles are investigated, covering extensively varied operating conditions for a wide-ranging validation.

As engine knock limits the efficiency of spark ignition engines and consequently further reduction of CO2 emissions, SI engines are typically designed to operate at the knock boundary. Therefore, a precise knock model is necessary to consider this phenomenon in an engine process simulation. The basis of the introduced 0D/1D knock model is to predict when the unburnt mixture auto-ignites, since auto-ignitions precede knocking events. The knock model further needs to evaluate the auto-ignition, because not every auto-ignition results in engine knock. As the introduced model’s prediction of the auto-ignition onset is already validated at extensive variations of operating conditions, this publication focusses on its evaluation. For this, two new, independent criteria are developed that take the pre-reactions of the unburnt mixture before the start of combustion into account to calculate a respective threshold for the auto-ignition onset at the knock boundary.

On the way to emission-free mobility, future fuels must be CO2 neutral. To achieve this, synthetic fuels are being developed. In order to better assess the effects of the new fuels on the engine process, simulation models are being developed that reproduce the chemical and physical properties of these fuels. In this paper, the fuel DMC+ is examined. DMC+ (a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo) mainly, characterized by the lack of C-C Bonds and high oxygen content) offers advantages with regard to evaporation heat, demand of oxygen and knock resistance. Furthermore, its combustion is almost particle free. With the aid of modern 0D/1D simulation methods, an assessment of the potential of DMC+ can be made. It is shown that the simulative conversion of a state-of-the-art gasoline engine to DMC+ fuel offers advantages in terms of efficiency in many operating points even if the engine design is not altered.

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.

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.

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.

For long haul transport, diesel engine due to its low fuel consumption and low operating costs will remain dominant over a long term. In order to achieve CO2 neutrality, the use of electricity-based, synthetic fuels (e-fuels) provides a solution. Especially the group of oxymethylene ethers (OME) is given much attention because of its soot-free combustion. However, the new fuel properties and the changed combustion characteristics place new demands on engine design. Meanwhile, the use of new fuels also creates new degrees of freedom to operate diesel engines. In this work, the application of dimethoxymethane (OME1) is investigated by means of 1D simulation at three operating points in a truck diesel engine. The subsystems of fuel injection, air path and exhaust gas are sequentially adjusted for the purpose of low emissions, especially for low nitrogen oxides (NOx).

This paper presents a quasi-dimensional emission model for calculating the transient nitric oxide emissions of a diesel engine. Using conventional and high-speed measurement technology, steady-state and transient emissions of a V6 diesel engine were examined. Based on measured load steps and steady-state measurements a direct influence of the combustion chamber wall temperature on the nitric oxide emissions was found. Load steps to and from, as well as steady-state measurements down to almost stoichiometric global combustion air ratios were used to examine the behavior of nitric oxide formation under these operating conditions. An existing emission model was expanded in order to represent the direct influence of the combustion chamber wall temperature on the nitric oxide emissions as well as enabling the forecasting of nitric oxide emissions at low global combustion air ratios: Both particularly important aspects for the simulation of transient emissions.