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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.

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.

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.

State-of-the-art powertrain concepts with automatic transmission must comply with increasingly stringent legislation on emissions and fuel consumption while fulfilling or surpassing customers' expectations as to driveability. In this respect, automated manual transmissions (AMT) and automated shift transmissions (AST) must compete with conventional automatic transmissions (AT) and continuously variable transmissions (CVT). In order to exploit the theoretical advantages of ASTs and put them into practice, complex ECU functions are needed to coordinate engine and transmission. Adaptive control, sophisticated clutch management and an intelligent shifting strategy allow shifting quality and shifting points to be simultaneously optimized to the effect that performance and comfort are increased while fuel consumption is reduced.

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.

Modern engines are intended to work at high efficiency and at the same time have low emissions. Since modern engines operate with nearly stoichiometric air/fuel mixtures to reduce nitrogen oxides, one of the most critical emissions is carbon monoxide and its prediction is therefore essential for today's engine design. The concept of the presented model is to combine the two-zone thermodynamic model and CHEMKIN software to predict the carbon monoxide emissions from a gasoline direct injection engine with good computational efficiency and low calculation time. The model calculation was divided into two parts. The first part is the two-zone model which can also predict the CO concentration for the exhaust condition by using the chemical equilibrium concentration. The second part is the kinetic model, which uses input data from the two-zone model and starts the calculation shortly before the end of combustion.

Under the persistent pressure to further reduce fuel consumption worldwide, it is necessary to advance the processes that influence the efficiency of gasoline engines. In doing so, harnessing the entire potential of fully variable mechanical valve trains will involve targeting efforts on optimizing all design parameters. A new type of valve timing system is used to portray thermodynamic and mechanical as well as electronic aspects of developing fully variable mechanical valve timing and lift systems

A physico-chemical model of a Cu-zeolite SCR/DPF-system involving NH₃ storage and SCR reactions as well as soot oxidation reactions with NO₂ has been developed and validated based on fundamental experimental investigations on synthetic gas test bench. The goal of the work was the quantitative modeling of NOx and NH₃ tailpipe emissions in transient test cycles in order to use the model for concept design analysis and the development of control strategies. Another focus was put on the impact of soot on SCR/DPF systems. In temperature-programmed desorption experiments, soot-loaded SCR/DPF filters showed a higher NH₃ storage capacity compared to soot-free samples. The measured effect was small, but could affect the NH₃ slip in vehicle applications. A bimodal desorption characteristic was measured for different adsorption temperatures and heating rates.

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.

The low-NOx standard for heavy-duty trucks proposed by the California Air Resources Board will require rapid warm-up of the aftertreatment system (ATS). Several different aftertreatment architectures and technologies, all based on selective catalytic reduction (SCR), are being considered to meet this need. One of these architectures, the close-coupled SCR (ccSCR), was evaluated in this study using two different physics-based, 1D models; the simulations focused on the first 300 seconds of the cold-start Federal Test Procedure (FTP). The first model, describing a real, EuroVI-compliant engine equipped with series turbochargers, was used to evaluate a ccSCR located either i) immediately downstream of the low-pressure turbine, ii) in between the two turbines, or iii) in a by-pass around the high pressure turbine.

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.

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.

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.

After the realization of very low exhaust gas emissions and corresponding OBD requirements to fulfill Euro VI and Tier 4 legislation, the focus in heavy-duty powertrain development is on the reduction of fuel consumption and thus CO₂ emissions again. Besides this, the total vehicle operation costs play another major role. A holistic view of the overall powertrain system including the combustion process, exhaust gas aftertreatment, energy recuperation and energy storage is necessary in order to obtain the best possible system for a given application. A management system coordinating the energy flow between the different subsystems while guaranteeing low exhaust emissions plays a major part in operating such complex architectures under optimal conditions.

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.

For the NOx removal from diesel exhaust, the selective catalytic reduction (SCR) and lean NOx traps are established technologies. However, these procedures lack efficiency below 200 °C, which is of importance for city driving and cold start phases. Thus, the present paper deals with the development of a novel low-temperature deNOx strategy implying the catalytic NOx reduction by hydrogen. For the investigations, a highly active H2-deNOx catalyst, originally engineered for lean H2 combustion engines, was employed. This Pt-based catalyst reached peak NOx conversion of 95 % in synthetic diesel exhaust with N2 selectivities up to 80 %. Additionally, driving cycle tests on a diesel engine test bench were also performed to evaluate the H2-deNOx performance under practical conditions. For this purpose, a diesel oxidation catalyst, a diesel particulate filter and a H2 injection nozzle with mixing unit were placed upstream to the full size H2-deNOx catalyst.

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.

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 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.