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The introduction of real driving emissions cycles and increasingly restrictive emissions regulations force the automotive industry to develop new and more efficient solutions for emission reductions. In particular, the cold start and catalyst heating conditions are crucial for modern cars because is when most of the emissions are produced. One interesting strategy to reduce the time required for catalyst heating is post-oxidation. It consists in operating the engine with a rich in-cylinder mixture and completing the oxidation of fuel inside the exhaust manifold. The result is an increase in temperature and enthalpy of the gases in the exhaust, therefore heating the three-way-catalyst. The following investigation focuses on the implementation of post-oxidation by means of scavenging in a four-cylinder, turbocharged, direct injection spark ignition engine. The investigation is based on detailed measurements that are carried out at the test-bench.

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.

Ignition delay times are major information needed to allow the simulation of auto-ignition and knocking combustion in internal combustion engines (ICEs). Due to their variance over changing boundary conditions (BC) and limitations of measurement processes, a common way to obtain them is via reaction kinetic simulations. To facilitate and accelerate the simulation process with varying operating conditions and gas composition definitions, an efficient tool that uses Cantera’s Python interface has been created. It allows the end-user to easily calculate the ignition delay data needed for engine simulation without the necessity for in-depth knowledge of the underlying processes. All calculations are based on the creation of a homogeneously mixed gaseous mixture corresponding to engine-based environmental conditions. Depending on the desired fuel, oxidizer, temperature, pressure, water, and exhaust gas recirculation (EGR) rate, the resulting reactant composition is computed.

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.

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.

Intensified emission regulations as well as consumption demands lead to an increasing significance of carbon monoxide (CO) emissions for diesel engines. On the one hand, the quantity of CO raw emissions is important for emission predictions as well as for the exhaust gas after treatment. On the other hand, CO 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 CO molecules. Due to these reasons, a simulation model for predicting CO raw emissions was developed for diesel engines based on a phenomenological two-zone model. The CO model takes three main sources of CO emissions of diesel engines into account: Firstly, it contains a sub model that describes CO from local understoichiometric areas. Secondly, CO emissions from overmixed regions are considered.

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.

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.

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.

Fulfilling exhaust emissions regulations and meet customer performance needs mainly drive the current engine development. Turbocharging system plays a key role for that. Currently turbocharging should provide highest engine power density at high engine speed by also allowing a very responsive performance at low end. This represents a trade-off in turbocharger development. A large scaled turbine allows having moderate exhaust gas back pressure for peak power region, but leading to loss of torque in low engine speed. In the last years of engine development scavenging helped to get away a bit from this trade-off as it increases the turbine mass flow and also reduces cylinder internal residual gas at low engine speed. The mostly in-use lean strategy runs air fuel ratios of closed to stoichiometric mixture in cylinder and global (pre catalyst) of λ = 1.05 to l = 1.3. This will be out of the narrow air fuel ratio band of λ = 1 to ensure NOx conversion in the 3-way-catalyst.

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.

CO2 emission constraints taking effect from 2020 lead to further investigations of technologies to lower knock sensitivity of gasoline engines, main limiting factor to increase engine efficiency and thus reduce fuel consumption. Moreover the RDE cycle demands for higher power operation, where fuel enrichment is needed for component protection. To achieve high efficiency, the engine should be run at stoichiometric conditions in order to have better emission control and reduce fuel consumption. Among others, water injection is a promising technology to improve engine combustion efficiency, by mainly reducing knock sensitivity and to keep high conversion rates of the TWC over the whole engine map. The comprehension of multiple thermodynamic effects of water injection through 3D-CFD simulations and their exploitation to enhance the engine combustion efficiency is the main purpose of the analysis.

The development of future gasoline engines is dominated by the study of new technologies aimed at reducing the engine negative environmental impact and increase its thermal efficiency. One common trend is to develop smaller engines able to operate in stoichiometric conditions across the whole engine map for better efficiency, lower fuel consumption, and optimal conversion rate of the three-way catalyst (TWC). Water injection is one promising technique, as it significantly reduces the engine knock tendency and avoids fuel enrichment for exhaust temperature mitigation at high power operation. With the focus on reducing the carbon footprint of the automotive sector, another vital topic of research is the investigation of new alternative CO2-neutral fuels or so-called eFuels. Several studies have already shown how these new synthetic fuels can be produced by exploiting renewable energy sources and can significantly reduce engine emissions.

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.

In this paper the development approach and the results of numerical and experimental investigations on homogeneous charge compression ignition in a free piston engine are presented. The Free Piston Linear Generator (FPLG) is a new type of internal combustion engine designed for the application in a hybrid electric vehicle. The highly integrated system consists of a two-stroke combustion unit, a linear generator, and a mass-variable gas spring. These three subsystems are arranged longitudinally in a double piston configuration. The system oscillates linearly between the combustion chamber and the gas spring, while electrical energy is extracted by the centrally arranged linear generator. The mass-variable gas spring is used as intermediate energy storage between the downstroke and upstroke. Due to this arrangement piston stroke and compression ratio are no longer determined by a mechanical system.