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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.

As the late combustion phase in SI engines is of high importance for a further reduction of fuel consumption and especially emissions, the impacts of unburnt mass, located in a small volume with a relatively large surface near the wall and in the top land volume, is of high relevance throughout the range of operation. To investigate and quantify the respective interactions, a state of the art Mercedes-Benz single cylinder research SI-engine was equipped with extensive measurement technology. To detect the axial and radial temperature distribution, several surface thermocouples were applied in two layers around the top land volume. As an additional reference, multiple surface thermocouples in the cylinder head complement the highly dynamic temperature measurements in the boundary zones of the combustion chamber.

The development and calibration of modern combustion engines is challenging in the area of continuously tightening emission limits and the necessity for meeting real driving emissions regulations. A focus is on the knowledge of the internal engine processes and the determination of pollutants formations in order to predict the engine emissions. A physical model-based development provides an insight into hardly measurable phenomena properties and is robust against changing input data. With increasing modeling depth the required computing capacities increase. As an alternative to physical modeling, data-driven machine learning methods can be used to enable high-performance modeling accuracy. However, these are dependent on the learned data. To combine the performance and robustness of both types of modeling a hybrid application of data-driven and physical models is developed in this paper as a grey box model for the exhaust emission prediction of a commercial vehicle diesel engine.

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.

The low-NOx standard for heavy-duty trucks proposed by the California Air Resources Board will require rapid warm-up of the aftertreatment system. Several different engine technologies are being considered to meet this need. In this study, a 1-D engine model was first used to evaluate several individual control strategies capable of increasing the exhaust enthalpy and decreasing the engine-out NOX over the initial portion of the cold start FTP cycle. The additional fuel consumption resulting from these strategies was also quantified with the model. Next, several of those strategies were combined to create a hypothetical aftertreatment warm-up mode for the engine. The model was then used to evaluate potential benefits of an air gap manifold (AGM) and two different turbine by-pass architectures. The detailed geometry of the AGM model was taken into account, having been constructed from a real prototype design.

Specific shifting of load points is an important approach in order to reduce the fuel consumption of gasoline engines. A potential measure is cylinder deactivation, which is used as a study example. Currently CO2 savings of new concepts are evaluated by dynamic cycles simulations. The fuel consumption during driving cycles is calculated based on consumption-optimized steady-state engine maps. Discrete load point shifts occur as shifts within maps. For reasons of comfort shifts require neutral torque. The work of deactivated cylinders must be compensated by active cylinders within one working cycle. Due to the larger time constant of the air path the air charge must be increased or decreased in order to deactivate or activate cylinders without affecting the torque. A working-cycle-resolved, continuously variable parameter is prerequisite for process control. Manipulation of ignition timing enables a reduction of efficiency and gained work.

Further tightening of NOx emission standards as well as CO2 emission limits for commercial vehicles are currently under discussion. In the on-road market, lowering NOx emissions up to 90%, down to 0.02 g/bhp-hr, has been proposed by CARB and is evaluated by US EPA. Testing for in-service conformity using a portable emission measurement system (PEMS) is currently under review in the US. In Europe, CO2 emission limits are anticipated and a CO2 monitoring program is ongoing. PEMS legislation has been recently tightened and further restrictions can be expected. Stage V legislation has been introduced in Europe and it is foreseeable that further tightening of off-road standards will take place in the future. This study deals with virtual development and evaluation of future engine and exhaust aftertreatment (EAT) technology solutions to fulfill the diverse future emission requirements with emphasis on off-road applications.

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.

Advanced SI engines for passenger cars often use the cylinder deactivation technology for dethrottling and thus achieving a reduction of fuel consumption. The gas exchange valves of the deactivated cylinders are closed permanently by a zero lift of the cams. The solutions for cylinder deactivation can vary in the kind of gas composition included in the deactivated cylinders: charge air, exhaust gas or vacuum. All these strategies have in common the frequent loss of captured charge mass from cycle to cycle. Their two-stroke compression-expansion cycle additionally intensifies this phenomenon. Thus, a significant decrease of the minimum cylinder pressure can cause an undesired entry of lubricant into the combustion chamber. The idea was to ventilate the generally deactivated cylinders frequently to compensate the loss of captured cylinder charge mass. The task was to keep the minimum cylinder pressure above a certain limit to prevent the piston rings from a failure.

A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing.

A promising combustion technology for DISI downsizing engines is the Miller cycle. It is based on an early intake valve closing for the separation of effective and geometric compression ratio. Therefore IAV has prepared a turbocharged DISI test engine with a high geometric compression ratio. This engine is equipped with the Schaeffler “UniAir” variable valve train in order to investigate a variable Miller cycle valve timing in the turbocharged map area. The goal is to investigate whether and how a rapidly variable Miller cycle can influence the knocking behavior. Therefore its potential for a SI knock control can be evaluated. The investigated parameters in a steady-state engine dyno mode were the intake valve closing timing, the intake camshaft phasing and the ignition timing. A variable intake valve closing Miller cycle strategy, a variable intake camshaft phasing Miller cycle strategy and a state-of-the- art ignition timing strategy have been investigated.

Standard compressor and turbine maps obtained from steady-state test bench measurements are not sufficient for assessing transient turbocharger behavior. This also makes them inappropriate for gauging combustion-engine response and fuel consumption. Nor do they allow for the widely differing operating conditions which, apart from aerodynamics, have a major influence on heat transfer and turbocharger efficiency. This paper looks at a more complex approach of modeling the turbocharger as well developing appropriate measurement methods (“advanced turbocharger model”). This includes non-destructive measurements under various heat transfer conditions to define the turbocharger's adiabatic behavior needed to describe charge-air pressure increase in the compressor and engine exhaust gas backpressure from the turbine for transient engine operation.

Zero-dimensional heat release rate models have the advantage of being both easy to handle and computationally efficient. In addition, they are capable of predicting the effects of important engine parameters on the combustion process. In this study, a zero-dimensional combustion model based on physical and chemical sub-models for local processes like injection, spray formation, ignition and combustion is presented. In terms of injection simulation, the presented model accounts for a phenomenological nozzle flow model considering the nozzle passage inlet configuration and an approach for modeling the characteristics of the Diesel spray and consequently the mixing process. A formulation for modeling the effects of intake swirl flow pattern, squish flow and injection characteristics on the in-cylinder turbulent kinetic energy is presented and compared with the CFD simulation results.

Recent years have witnessed a dramatic increase in global ethanol production, while cellulosic feedstock or the algae-based production approach make more sustainable ethanol production foreseeable in many countries. The ethanol produced will increasingly penetrate the markets not only as blending component, but also as main fuel component, boosting demand for flex-fuel vehicles. One of the main challenges for flex-fuel vehicles is the cold start due to the poor vapor pressure of ethanol. This is detrimental to starting capability in DISI engines in particular, with increased cylinder wall wetting causing higher oil dilution. The most efficient solution for DISI engines is a smart injection strategy, enabling fuel vaporization during injection in the compression stroke. But this requires optimum injection parameters such as injection timing, split ratio and rail pressure.

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.

Global warming is a climate phenomenon with world-wide ecological, economic and social impact which calls for strong measures in reducing automotive fuel consumption and thus CO2 emissions. In this regard, turbocharging and the associated designing of the air path of the engine are key technologies in elaborating more efficient and downsized engines. Engine performance simulation or development, parameterization and testing of model-based air path control strategies require adequate performance maps characterizing the working behavior of turbochargers. The working behavior is typically identified on test rig which is expensive in terms of costs and time required. Hence, the objective of the research project “virtual Exhaust Gas Turbocharger” (vEGTC) is an alternative approach which considers a physical modeled vEGTC to allow a founded prediction of efficiency, pressure rise as well as pressure losses of an arbitrary turbocharger with known geometry.

There is an enormous effort to implement safety functionality into battery systems to prevent any accidents with the poisonous and inflammable ingredients of the electrolytes and electrode materials. But not only the safety regulation for lithium ion batteries will be different in comparison to the home electronics application, also the operating strategy must be different to guaranty the required lifetime in the automotive industry up to 10-12 years. This paperwork will show an approach to get offline (on test benches) and/or online (installed inside the car) information regarding the current healthy and state inside the cell. As an approach modeling of physical effects by the help of electro impedance spectroscopy (EIS) will be applied.

The startability of SI engines, especially of DISI engines, is the greatest challenge when using ethanol blended fuels. The development of a suitable injection strategy is therefore the main engineering target when developing an ethanol engine with direct injection. In order to limit the test efforts of such a program, a vaporization model has been created that provides the quantity of vaporized fuel depending on pressure and on start and end, respectively number and split relation of injections. This model takes account of the most relevant fuel properties such as density, surface tension and viscosity. It also considers the interaction of the spray with cylinder liner, cylinder head and piston. A comparison with test results shows the current status and the need for action of this simulation model.

Flow fields and fuel distribution play a critical role in developing the combustion process inside the cylinders of piston engines. This has prompted the development of measurement and diagnostic capabilities including laser techniques like Doppler Global Velocimetry (DGV). The paper provides an overview of the basics of DGV and the type of results that can be obtained. It also includes a short comparison to Particle Image Velocimetry (PIV) which is a popular alternative method. Furthermore, it is shown that DGV can be used simultaneously in combination with droplet distribution visualization inside cylinders based on Mie scattering.

Mixture formation in the combustion chamber is of paramount significance for diesel combustion processes. Particularly in inhomogeneous combustion processes with internal mixture formation, the course of combustion and composition of combustion products are heavily influenced by charge motion and material transport during the compression phase and during combustion itself. Charge motion is normally quantified in steady-state flow testing. This model-based test takes place under idealized conditions. This means that with a permanently open valve and constant pressure differential over the inlet port, a steady-state flow of air is established in the simulated cylinder. The influence of piston movement is neglected. The test delivers integral characteristic flow figures, such as swirl number, flow number and tumble number.