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Beside the main trend technologies such as downsizing, down speeding, external exhaust gas recirculation, and turbocharging in combination with Miller cycles, the optimization of the mechanical efficiency of gasoline engines is an important task in meeting future CO2 emission targets. Friction in the piston assembly is responsible for up to 45% of the total mechanical loss in a gasoline engine. Therefore, optimizing piston assembly friction is a valuable approach in improving the total efficiency of an internal combustion engine. The form honing process enables new specific shapes of the cylinder liner surface. These shapes, such as a conus or bottle neck, help enlarge the operating clearance between the piston assembly and the cylinder liner, which is one of the main factors influencing piston assembly friction.

Development processes for modern combustion engines already make substantial use of more or less sophisticated simulation approaches. The enhancement of computational resources additionally allows the increasing use of simulation tools in terms of time-consuming three-dimensional CFD approaches. In particular, the preliminary estimation of feasible operating ranges and strategies requires a vast multitude of single simulations. Here, multi-zone simulation approaches incorporate the advantages of comparably short simulation durations. Nevertheless, the combination with more detailed sub-models allows these rather simple modeling approaches to offer considerable insight into relevant engine operation phenomena. In the context of combustion process development, this paper describes a phenomenological model approach for the prediction of operating point characteristics of a dual-fuel pilot injection combustion process.

To meet LEV and EU Stage III emission requirements, it is necessary for new catalytic converters to be designed which exceed light-off temperature as quickly as possible. The technical solutions are secondary air injection, active heating systems such as the electrically heated catalytic converter, and the close coupled catalytic converter. Engine control functions are extensively used to heat the converter and will to play a significant role in the future. The concept of relocating the converter to a position close to the engine in an existing vehicle involves new conflicts. Examples include the space requirements, the thermal resistance of the catalytic coating and high temperature loads in the engine compartment.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

The study of oil emission is of essential interest for the engine development of modern cars, as well as for the understanding of hydrocarbon emissions especially during cold start conditions. A laser mass spectrometer has been used to measure single aromatic hydrocarbons in unconditioned exhaust gas of a H2-fueled engine at stationary and transient motor operation. These compounds represent unburned oil constituents. The measurements were accompanied by FID and GC-FID measurements of hydrocarbons which represent the burned oil constituents. The total oil consumption has been determined by measuring the oil sampled by freezing and weighing. It has been concluded that only 10 % of the oil consumption via exhaust gas has burned in the cylinders. A correlation of the emission of single oil-based components at ppb level detected with the laser mass spectrometer to the total motor oil emission has been found.

The optimization of the vaporization and mixture formation process is of great importance for the development of modern gasoline direct injection (GDI) engines, because it influences the subsequent processes of the ignition, combustion and pollutant formation significantly. In consequence, the subject of this work was the development of a measurement technique based on the laser induced exciplex fluorescence (LIF), which allows the two dimensional visualization and quantification of the in-cylinder air/fuel ratio. A tracer concept consisting of benzene and triethylamine dissolved in a non-fluorescent base fuel has been used. The calibration of the equivalence ratio proportional LIF-signal was performed directly inside the engine, at a well known mixture composition, immediately before the direct injection measurements were started.

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.

This study discusses model-based injection rate estimation in common rail diesel injectors exhibiting aging phenomena. Since they result in unexpected injection behavior, aging effects like coking or cavitation may impair combustion performance, which justifies the need for new modeling and estimation approaches. To predict injection characteristics, a simulation model for the bottom section of the injector is introduced, with a main focus on modeling the hydraulic components. Using rail pressure and control piston lift as inputs, a reduced model is then derived in state-space representation, which may be used for the application of an observer in hardware-in-the-loop (HIL) environments. Both models are compared and validated with experimental data, with which they show good agreement. Aging effects and nozzle wear, which result in model uncertainties, are considered using a fault model in combination with an extended Kalman filter (EKF) observer scheme.

Due to its molecular structure, methane provides several advantages as fuel for internal combustion engines. To cope with nitrogen oxide emissions high levels of excess air are beneficial, which on the other hand deteriorates the flammability and combustion duration of the mixture. One approach to meet these challenges and ensure a stable combustion process are fuelled prechambers. The flow and combustion processes within these prechambers are highly influenced by the position, orientation, number and overall cross-sectional area of the orifices connecting the prechamber and the main combustion chamber. In the present study, a water-cooled single cylinder test engine with a displacement volume of 0.5 l is equipped with a methane-fuelled prechamber. To evaluate influences of the aforementioned orifices several prechambers with variations of the orientation and number of nozzles are used under different operating conditions of engine speed and load.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Natural gas and especially biogas combustion can be seen as one of the key technologies towards climate-neutral energy supply. With its extensive availability, biogas is amongst the most important renewable energy sources in the present energy mix. Today, the use of gaseous fuels is widely established, for example in cogeneration units for combined heat and power generation. In contrast to conventional spark plug ignition, the combustion can also be initialized by a pilot injection. In order to further increase engine efficiency, this article describes the process for a targeted optimization of the pilot fuel injection. One of the crucial points for a more efficient dual fuel combustion process, is to optimize the amount of pilot injection in order to increase overall engine efficiency, and therefore decrease fuel consumption. In this connection, the injection system plays a key role.

Existing electronic combustion engine control systems only guarantee a desired air-to-fuel-ratio λ in stationary operation. In order to achieve the desired λ also in in-stationary use of the engine, it is necessary to use new-technology-based control systems. Artificial Intelligence provides methods to cope with difficulties like wide operation range, unknown nonlinearities and time delay. We will propose a strategy for control of a Spark Ignition Engine to determine the mass of air inside the combustion chambers with the highest accuracy. Since Neural Networks are universal approximators for multidimensional nonlinear static functions they can be used effectively for identification and compensation purposes of unknown nonlinearities in closed control loops.

In order to reduce emissions of spare ignition engines using a three way catalyst, a stoichiometric air-fuel ratio must be guaranteed in stationary and transient operation of the engine. This aim can be reached by using a specific feed-forward structure for the control of the paths of air and fuel based on identification abilities of Artificial Intelligence. As approximators for multidimensional nonlinear static functions we will use specific Neural Networks (NN) together with sophisticated stability-proven learning structures. The acquired knowledge within the NN determines our control action mainly through using feed-forward structures. Our investigations are based on the so-called mean-value-modelling approach of SI engines; it is our aim to present this strategy.

In the near future, pollutant and GHG emission regulations in the transport sector will become increasingly stringent. For this reason, there are many studies in the field of internal combustion research that investigate alternative fuels, one example being oxygenated fuels. Additionally, the design of engine components needs to be optimized to improve the thresholds of clean combustion and thus reduce particulates. Simulations based on PRiME 3D® for dynamic behaviors inside the piston ring group provide a guideline for experimental investigation. Gas flows into the combustion chamber are controlled by adjusting the piston ring design. A direct comparison of regular and synthetic fuels enables to separate the emissions caused by oil and fuel. This study employed a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo).

Future emission regulations require further development for internal combustion engines operating on gasoline. To comply with such regulations and simultaneously improve fuel efficiency, major development trends are found in reduced displacements, increased compression ratios and turbocharging. To counteract such engines’ increased tendencies to knocking combustion, direct fuel injection systems are necessarily applied. Compared to standard port fuel injection, direct injection systems cause increased particle emissions. State-of-the-art magnet-driven gasoline direct injectors are capable of realizing various injection events of small injected mass per event and short dwell time between one another. Thereby, they facilitate multiple injection strategies, able to overcome the drawbacks of direct injection systems in relation to exhaust emissions. However, the full potential of multiple injection strategies is not yet taken advantage of.

In this study a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo) was used as a synthetic gasoline replacement. These synthetic fuels offer CO2-neutral mobility if the fuels are produced in a closed CO2-cycle and they reduce harmful emissions like particulates and NOX. For base potential investigations, a single-cylinder research engine (SCE) was used. An in-depth analysis of real driving cycles in a series 4-cylinder engine (4CE) confirmed the high potential for emission reduction as well as efficiency benefits. Beside the benefit of lower exhaust emissions, especially NOX and particle number (PN) emissions, some additional potential was observed in the SCE. During a start of injection (SOI) variation it could be detected that a late SOI of DMC/MeFo has less influence on combustion stability and ignitability. With this widened range for the SOI the engine application can be improved for example by catalyst heating or stratified mode.

In this study, a fully optically accessible single-cylinder research engine is the basis for the visualization and generation of extensive knowledge about the in-cylinder processes of mixture formation, ignition and combustion of oxygenated synthetic fuels. Previous measurements in an all-metal engine showed promising results by using a mixture of dimethyl carbonate and methyl formate as a fuel substitute in a DISI-engine. Lower THC and NOx emissions were observed along with a low PN-value, implying low-soot combustion. The flame luminosity transmitted via an optical piston was split in the optical path to simultaneously record the natural flame luminosity with an RGB high-speed camera. The second channel consisted of OH*-chemiluminescence recording, isolated by a bandpass filter via an intensified monochrome high-speed camera.

The European Commission has released strict emission regulations for passenger cars in the past decade in order to improve air quality in cities and limit harmful emission exposure to humans. In the near future, even stricter regulations containing more realistic/demanding driving scenarios and covering more exhaust gas components are expected to be released. Passenger cars fueled with gasoline are one contributor to unhealthy air conditions, due to the fact that gasoline engines emit harmful air pollutants. One option to minimize harmful emissions would be to utilize specifically tailored, low emission synthetic fuels or fuel blends in internal combustion engines. Methyl formate and dimethyl carbonate are two promising candidates to replace or substitute gasoline, which in previous studies have proven to significantly decrease harmful pollutants.

Aging effects such as coking or cavitation in the nozzle of common rail (CR) diesel injectors deteriorate combustion performance. This is of particular relevance when it comes to complying with emission legislation and demonstrates the need for detecting and compensating aging effects during operation. The first objective of this paper is to analyze the influence of worn nozzles on the injection rate. Therefore, measurements of commercial solenoid common rail diesel injectors with different nozzles are carried out using an injection rate analyzer of the Bosch type. Furthermore, a fault model for typical aging effects in the nozzle of the injector is presented together with two methods to detect and identify these effects. Both methods are based on a multi-domain simulation model of the injector. The needle lift, the control piston lift and the pressure in the lower feed line are used for the fault diagnosis.

For development of new engines a ‘general purpose ECU’ for spark ignition engines with up to 12 cylinders has been developed. As part of this ECU a DSP (Digital Signal Processor)-based measurement unit for high frequency combustion analysis has been integrated. In this paper, details about this signal processing platform are given. The DSP-unit has 24 analog input channels. 12 channels are used for cylinder pressure measurement; the other 12 channels are general purpose ones. For example, they can be used for ionic current analysis. Additional digital inputs allow measurement of crank speed and crank speed variations. This is an important topic for misfire detection as part of the OBD regulations.