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In the near future, emissions legislation will become more and more restrictive for direct injection SI engines by adopting a stringent limitation of particulate number emissions in late 2017. In order to cope with the combustion system related challenges coming along with the introduction of this new standard, Hitachi Automotive Systems Ltd., Hitachi Europe GmbH and IAV GmbH work collaboratively on demonstrating technology that allows to satisfy EU6c emissions limitations by application of Hitachi components dedicated to high pressure injection (1). This paper sets out to describe both the capabilities of a new high pressure fuel system improving droplet atomization and consequently mixture homogeneity as well as the process of utilizing the technology during the development of a demonstrator vehicle called DemoCar. The Hitachi system consists of a fuel pump and injectors operating under a fuel pressure of 30 MPa.

The spray-guided combustion process offers a high potential for fuel savings in gasoline engines in the part load range. In this connection, the injector and spark plug are arranged in close proximity to one another, as a result of which mixture formation is primarily shaped by the dynamics of the fuel spray. The mixture formation time is very short, so that at the time of ignition the velocity of flow is high and the fuel is still largely present in liquid form. The quality of mixture formation thus constitutes a key aspect of reliable ignition. In this article, the spray characteristics of an outward-opening piezo injector are examined using optical testing methods under pressure chamber conditions and the results obtained are correlated with ignition behaviour in-engine. The global spray formation is examined using high-speed visualisation methods, particularly with regard to cyclical fluctuations.

In order to reduce the negative health effects associated with engine pollutants, environmental problems caused by combustion engine emissions and satisfy the current strict emission standards, it is essential to better understand and simulate the emission formation process. Further development of emission model, improves the accuracy of the model-based optimization approach, which is used as a decisive tool for combustion system development and engine-out emission reduction. The numerical approaches for emission simulation are closely coupled to the combustion model. Using a detailed emission model, considering the 3D mixture preparation simulation including, chemical reactions, demands high computational effort. Phenomenological combustion models, used in 1D approaches for model-based system optimization can deliver heat release rate, while using a two-zone approach can estimate the NOx emissions.

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.

The homogeneous Diesel combustion is a way to effect a soot and nitrogen oxide (NOx) free Diesel engine operation. Using direct injection of Diesel fuel, the mixture typically ignites before it is fully homogenized. In this study a homogeneous mixture is prepared outside of the combustion chamber by a Cool Flame Vaporizer. At first the specification of the vaporizer is given in this paper. To determine the composition of the vaporizer gas an analysis using gas chromatography/mass spectroscopy (GC/MS) was made. The results give an idea of the effects on engine combustion. Followed by, the vaporizer was adapted to a single-cylinder Diesel engine. To adapt the engine's configuration regarding compression ratio and inlet temperature range a zero dimensional engine process simulation software was utilized. The engine was run in different operating modes.

The newest legislative trends enforce a significant decrease in CO2 emissions for commercial vehicles. For instance, in Europe a drop in fleet consumption of 15% and 30% is set as target by the regulation by 2025 and 2030. The use of carbon-neutral fuels offers possibilities regarding net-zero CO2 emissions - although not yet considered by the rules. Another challenging aspect is the drastic tightening of NOx emissions limits for future legislations, which is approved or being discussed both for the United States and for the EU. The current work describes the potentials of an innovative fuel, marketed as Gane fuel regarding performance, efficiency and emission behavior. First, the properties of the developed fuel are described: Gane is made from methanol blended with water and is tailored for diffusive combustion. The fuel blending is so defined to fulfill the combustion requirements.

The strong demand for diesel fuel is producing a surplus of gasoline fractions in Europe. Despite new vehicles using less energy, the rising volume of traffic will lead to more diesel being consumed. European legislation demands that renewable fuels cover 10% of energy consumed in the transport sector. The present strategy of dividing biofuels in equal shares between diesel and gasoline does not help to improve this situation. It seems reasonable not only to add FAME but also ethanol to diesel. Unfortunately, fuel blends containing ethanol cannot be used in existing cars without hardware modifications. This is because of ethanol's characteristics and well-known from the experience gathered with gasoline cars. As such, the first part of this study investigates material compatibility, focusing on corrosion and changes to the mechanical properties of the materials used in diesel engines.

Battery simulation by a DSP-controlled high current power supply is used to improve repeatability and comparability of starting tests, especially at low temperatures. The simulator's algorithm calculates the internal resistance of the battery by a timely constant resistor and a variable resistor representing the actual discharge history. The output voltage of the simulator is set as a function of internal resistor and load current with temperature and state of charge as setup parameter. The simulator was evaluated in cold start testing in comparison to real batteries. As a result, batteries are simulated with high repeatability. Deviations to real battery behavior are in the range of test to test deviations using real batteries.

The software design of this new engine control unit is based on a unique and homogenous torque structure. All input signals are converted into torque equivalents and a torque coordinator determines their influence on the final torque delivered to the powertrain. The basic torque structure is independent on the type of fuel and can be used for gasoline, diesel, or CNG injection systems. This allows better use of custom specific algorithms and facilitates reusability, which is supported by the graphical design tool that creates all modules using automatic code generation. Injection specific algorithms can be linked to the software by simply setting a software switch.

Introducing new exhaust-gas aftertreatment concepts at mass production level places exacting demands on the overall development process - from defining process engineering to developing and calibrating appropriate control-unit algorithms. Strategies for operating and controlling exhaust-gas aftertreatment components, such as oxidation and selective catalytic reduction catalysts (DOC and SCR), diesel particulate filters (DPF) and SCR on DPF systems (SCR/DPF), have a major influence on meeting statutory exhaust-emission standards. Therefore it is not only necessary to consider the physical behavior of individual components in the powertrain but also the way in which they interact as the basis for ensuring efficient operation of the overall system.

The protection of pedestrians from injuries by accidental collision is a primary focus of the automotive industry and of government legislation [1]. In this area, scientists and developers are faced with a multitude of requirements. Complex scenes are to be analyzed. The wide spectrum of where pedestrians and cyclists appear on the road, weather, and light conditions are just examples. Data fusion of raw or preprocessed signals for several sensors (cameras, radar, lidar, ultrasonic) need to be considered as well. Accordingly, algorithms are very complex. When moving from prototypic environments to embedded systems, additional constraints must be considered. Limited system resources drive the need to simplify and optimize for technical and economic reasons. With all these constraints, how can the safety functions be safe-guarded? This submission considers scene-based methods for the development of vehicle functions from prototype to series production focusing on functional safety.

In this paper a practical methodology for automated tuning of simulation models is introduced, which is widely and successfully adapted in IAV. For this, stochastic optimization algorithms (like Genetic Algorithms or Particle Swarm Optimization), and appropriate algorithms for optimization tasks with very long computation time (e.g. Adaptive Surrogate-Model Optimization or Adaptive Hybrid Strategies) are used in combination with commercial and internal simulation tools. Often it is necessary to evaluate several contradictory objectives at the same time which leads to multi-criterion optimization. Effective post processing methods (mathematical decision aids) are used to select the best compromises for the problem. As a practical example, this automated tuning methodology is applied to an engine performance simulation model developed in GT-Power.

The precision of direct fuel injection systems of combustion engines is crucial for the further reduction of emissions and fuel consumption. It is influenced by the dynamic behavior of the fuel system, in particular the injection valves and the common rail pressure. As model based control strategies for the fuel system could substantially improve the dynamic behavior, an accurate model of the common rail injection system for gasoline engines - consisting of the main components high-pressure pump, common rail and injection valves - that could be used for control design is highly desirable. Approaches for developing such a model are presented in this paper. For each key component, two models are derived, which differ in temporal resolution and number of degrees of freedom. Experimental data is used to validate and compare the models. The data was generated on a test bench specifically designed and built for this purpose.

Conventional methods of physicochemical models require various experts and a high measurement demand to achieve the required model accuracy. With an additional request for faster development time for diagnostic algorithms, this method has reached the limits of economic feasibility. Machine learning algorithms are getting more popular in order to achieve a high model accuracy with an appropriate economical effort and allow to describe complex problems using statistical methods. An important point is the independence from other modelled variables and the exclusive use of sensor data and actuator settings. The concept has already been successfully proven in the field of modelling for exhaust gas aftertreatment sensors. An engine-out nitrogen oxide (NOX) emission sensor model based on polynomial regression was developed, trained, and transferred onto a conventional automotive electronic control unit (ECU) and also proves real-time capability.

Mixture formation in gasoline direct-injection engines is largely determined by the quality of injection. Injection systems with a wide range of layouts are used today in enhancing spray quality. As parameters, the pressure and temperature of injected fuel play a crucial part in defining quality. The effect increasing pressure has on the quality of spray is basically known. So are ways of applying this process to gasoline fuel. The effect of massively increasing the temperature of injected fuel - to the point of reaching supercritical conditions - in contrast, is not known in any detail. For this reason, the following paper focuses attention on examining the fundamental influence of increasing fuel temperature from 25 °C to 450 °C on the spray behavior of a high-pressure injector with a GDI nozzle. Combining relevant levels of pressure and temperature, discussion also turns to supercritical fuel conditions and their effects on spray behavior.

Hydrogen engines offer the possibility of a carbon neutral transportation - a focal point of current propulsion development activities especially for EU and US future concepts. From today's point of view, hydrogen can play an important role in this regard as it is a carbon-free fuel, no CO2 emissions are produced during its combustion process. Besides, it can be well used for lean burn combustion leading to very low NOx emissions, a key benefit in combination with an optimized after-treatment system for future ultra-low NOx legislations of heavy-duty (HD) engines. Comprehensive investigations using experimental tests and model-based development approach are performed using a six cylinder HD hydrogen engine featuring PFI (port fuel injection) aiming the definition of a high efficiency hydrogen engine concept.

The future emission standards, including real driving emissions (RDE) measurements are big challenges for engine and after-treatment development. Also for development of a robust control system, in real driving emissions cycles under varied operating conditions and climate conditions, like low ambient temperature as well as high altitude are advanced physical-based algorithms beneficial in order to realize more precise, robust and efficient control concepts. A fast-running novel physical-based ignition delay model for diesel engine combustion simulation and additionally, for combustion control in the next generation of ECUs is presented and validated in this study. Detailed chemical reactions of the ignition processes are solved by a n-heptane mechanism which is coupled to the thermodynamic simulation of in-cylinder processes during the compression and autoignition phases.

The development and calibration of exhaust aftertreatment (EAT) systems for the most diverse applications of diesel powertrain concepts requires EAT models, capable of performing concept analysis as well as control and OBD system development and calibration. On the concept side, the choice of an application-specific EAT layout from a wide technology selection is driven by a number of requirements and constraints. These include statutory requirements regarding emissions of criteria pollutants and greenhouse gases (GHG), technical constraints such as engine-out emissions and packaging, as well as economic parameters such as fuel consumption, and EAT system and system development costs. Fast and efficient execution of the analysis and multi-criteria system optimization can be done by integrating the detailed EAT models into a total system simulation.