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Reliable estimation of pumping and friction losses in modern combustion engines allows better control strategies aiming at optimal fuel consumption and emissions. Sophisticated simulation tools enable detailed simulation of losses based as well on physical and thermodynamic laws as well as on design data. Models embedded in these tools however are not real-time capable and cannot be implemented into the programs of the electronic control units (ECU's). In this paper an approach is presented that estimates the pumping and friction losses of a combustion engine with variable valve train (VVT). Particularly the pumping losses strongly depend on the control of variable valve train by ECU. The model is based on a combination of a globally physical structure embedding data driven sub models based on test bed measurements. Losses are separated concerning different component groups (bearings, pistons, etc.).

In internal combustion engines operating in Controlled Auto Ignition (CAI) mode, combustion phasing and heat-release rate is controlled by stratification of fuel, fresh air, and hot internally recirculated exhaust gases. Based on the Representative Interactive Flamelet (RIF) model, a two-dimensional flamelet approach is developed. As independent parameters, firstly the fuel mixture fraction and secondly the mixture fraction of internally recirculated exhaust gases are considered. The flamelet equations are derived from the transport equations for species mass fraction and total enthalpy, employing an asymptotic analysis. A subsequent coordinate transformation leads to the phase space formulation of the two-dimensional flamelet equations. By the use of detailed chemical reaction mechanisms, the effects of dilution, temperature, and chemical species composition due to the internally recirculated exhaust gases are represented.

The integration of safety-critical and major power-consuming electrical systems presents a challenge for the development of future automotive electrical networks. Both reliability and performance must be enhanced in order to guarantee the power supply to essential electrical consumers at a sufficient degree of power quality. Often, in order to cope with these requirements, merely an upgrade of the existing wiring harness design is used, resulting in additional complexity, weight, and cost [3]. A characterization of the wiring harness and its electrical consumers facilitates a systematic optimization approach aimed at designing new automotive power networks [1, 5]. Measurement and analysis methods to characterise the thermal behaviour of the wiring harness have been presented and discussed in a previous paper [4] This paper presents and compares two methods aimed at modeling the electrical behavior of consumers at various voltages and temperatures.

The development of battery electric vehicle drives comes along with comprehensive and time-consuming finite element methods and extensive measurement campaigns. The drive efficiency has drawn great attention from engineers and customers, because it influences the size of the drive, the cooling measures and the vehicle range. Indirect efficiency acquisition accomplished by comparing inward and outward power, has a low accuracy which arises from a relatively small difference between inward and outward power of highly efficient drives. Therefore the indirect efficiency acquisition is insufficient to evaluate advanced development measures.

Both the electrical portion of the powertrain and the rising number of auxiliary systems will considerably increase the electrical power requirements in future vehicles. In addition, multiple voltage supply levels will enhance the complexity of the electrical distribution system (EDS), while strict cost, weight, packaging, and safety constraints must be upheld, posing serious design challenges in terms of robustness, reliability and energy efficiency. Currently, a self-contained integral test or evaluation of the EDS is normally not applied. For such a purpose, quantitative quality criteria are introduced here which allow a comparative assessment of an EDS by addressing the dynamic and static stability of the supply voltage, the reliability of the fusing system, and the ability to provide the required electrical power. The presented approach uses both precisely-defined test scenarios and a comprehensive EDS test bench.

The optimum design of an electrical distribution system (EDS) is based on the profound understanding and measurement of its thermal behavior, because this determines wire diameter and insulation material, has a major impact on the fusing strategy, and enables minimizing technical risk. Current methods of calculation require an extensive database, whereas the temperature measurements at selected points with normal sensors allow neither the precise rating of the actual insulation temperature within a wire bundle, nor the determination of the thermal impact of load currents. The presented approach is based on both a new measurement method and on a related evaluation algorithm. A common automotive wire is applied as a sensing device using its resistance temperature coefficient as the measurement principle.

A reduced kinetic reaction mechanism for the autoignition of dimethyl ether is presented in this paper. Dimethyl ether has proven to be one of the most attractive alternatives to traditional fossil fuels for compression ignition engines. It can either be produced from biomass or from fossil oil. For dimethyl ether, Fischer et al. (Int. J.Chem. Kinet. 32 ( 12 ) (2000) 713-740) proposed a detailed reaction mechanism consisting of 79 species and 351 elementary reactions. In the present work, this detailed mechanism is systematically reduced to 31 species and 49 reactions. The reduced mechanism is discussed in detail with special emphasis on the high temperature thermal decomposition of dimethyl ether and on the fuel specific depleting reactions, which produce the methoxymethyl radical. In addition, a reaction pathway analysis for low temperature combustion is applied, where hydroperoxy-methylformate is found to be the dominating parameter for the low temperature regime.

The increasing power and safety requirements of electrical systems present a challenge for future automotive electrical networks. However, the modeling of use-profiles and the overall power consumption of electrical systems proves to be difficult as the number of potential on/off combinations of the loads is tremendous. Furthermore, the operation of some loads is correlated or depends upon the operating conditions. Thus, simple worst-case calculations applied to this complexity often lead to an over-specification of components. The proposed approach is based on the probabilities of loads being in the on-state and their respective interdependencies with each other and with boundary conditions such as time of day. Applying basic statistics and a new iterative algorithm, it allows the calculation of the probability of consumed total power for a given set of boundary conditions and of, very importantly, its expected continuous period.

For the prevention of technical risks and the optimum design of an electrical distribution system, considerable efforts have been made to implement thermal models of wires, bundles, and electromechanical components in order to improve thermal analysis. Unfortunately, in most cases, important input parameters such as the position of a wire within a bundle or the profiles of the currents are unknown. This leads to the use of worst-case scenarios, frequently providing unrealistic results and uneconomic over-dimensioning. The proposed approach is based on the thermal simulation of a large number of randomly-generated bundle configurations for given profiles of currents. Thus one gets a temperature distribution, allowing a much more precise analysis compared to a simple worst-case calculation. By applying the same method to various current profiles, one gets temperature distributions for each wire as a function of a normalized total bundle current.

The integration of safety-critical and major power-consuming electrical systems presents a challenge for the development of future vehicle power nets. Reliability and performance of the electrical network must be enhanced in order to guarantee the power supply to essential electrical consumers at a sufficient degree of power quality. This paper presents a test bench for automotive electrical networks based on a hardware-in-the-loop (HiL) platform. The test bench is used to assess the power and temperature behavior of the wiring harness and the connected power consumers. This characterisation facilitates the development of new tailored automotive electrical networks to meet the increased requirements while efficiently using the available resources.

The influence of different fuels and injection pressures on the flame lift-off length (LOL), as well as the combustion structure under quiescent conditions in a heated high-pressure vessel were experimentally investigated using OH chemiluminescence measurements. This data was used to validate the newly developed G-equation coupled with MRIF (G-MRIF) model, which was designed to describe the lifted Diesel combustion process. The achieved results are very promising and could be used as a tool to apply this combustion mode into Diesel engines. Furthermore these measurements were used to validate the approach of a new combustion model, which was developed using former OH chemiluminescence measurements by the authors. Based on this approach the LOL is mainly determined by auto-ignition and therefore highly dependent on the cetane number. This model is presented in more detail within this work.

Both the integration of safety-critical electrical systems and the increasing power requirements in vehicles present a challenge for electrical distribution systems in terms of reliability, packaging, weight, and cost. In this regard, the wire protection device is a key element, as it determines the reliability of the short circuit detection, the immunity against false tripping, and the wire diameters. Currently, in most cases, thermal fuses are used, due to their low cost and robust design. However, the description of their tripping behavior based only on steady-state currents is insufficient for the increasingly complex current profiles in vehicles. Thus, to achieve an optimum dimensioning of a fuse-wire combination, a profound understanding of the thermal behavior of both components under dynamic load conditions is mandatory. However, the FEM tools used for the thermal design of fuses are relatively slow, require huge calculation resources, and must be well-parameterized.

The impact of the design of automotive electrical distribution systems (EDS) is becoming more and more significant with the continuous integration of new safety-relevant functions and the substitution of mechanical systems having reached a high degree of robustness. The introduction of hybrid and electric vehicles amplify this trend and lead to the design of even more complex electrical networks with multiple voltage levels and new challenges. To assess electrical power systems with respect to their ability to supply the involved electrical consumers in various driving and consuming situations at a high level of reliability and voltage stability simulation studies, bench testing and driving tests are conducted. However, a sustained strategy to define relevant consuming and driving situations in order to test the EDS under consistent loading conditions is missing.

Within the scope of the development of autonomous vehicles, the mandatory reliability requirements of the electrical power supply, and consequently of the electrical distribution system (EDS), are increased considerably. In addition, the overall rising number of electrical functions leads to significantly higher electrical power demands, while strict cost, weight and packaging constraints must be upheld. Current developments focus on adding redundancies, enhancing physical robustness, or dimensioning critical components. New approaches address predictive power management, better diagnostic capabilities, and, the subject of this paper, alternative topologies and architectures [1]. These are derivations of the conventional tree structure, as well as ring- or linear-bus-based zonal architectures, which feature in part distributed storage devices or semiconductor switches that rearrange the power paths in case of a fault [2,3].

The modern engine design process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. The introduction of predictive real-time simulation tools that represent the entire powertrain can likely contribute to improving the efficiency of the calibration process. Engine models, which are purely based on physical first principles, are usually not capable of real-time applications, especially if the simulation is focused on cold start and warm-up behavior. However, the initial data definition for the ECU using a Hardware-in-the-Loop (HiL)-Simulator requires a model with both real-time capability and sufficient accuracy. The use of artificial intelligence systems becomes necessary, e.g. neural networks. Methods, structures and the realization of a hybrid real-time model are presented in this paper, which combines physical and neural network models.

A main focus of development in modern SI engine technology is variable valve timing, which implies a high potential of improvement regarding fuel consumption and emissions. Variable opening, period and lift of inlet and outlet valves enable numerous possibilities to alter gas exchange and combustion. However, this additional variability generates special demands on the calibration process of specific engine control devices, particularly under cold start and warm-up conditions. This paper presents procedures, based on Hardware-in-the-Loop (HiL) simulation, to support the classical calibration task efficiently. An existing approach is extended, such that a virtual combustion engine is available including additional valve timing variability. Engine models based purely on physical first principles are often not capable of real time execution. However, the definition of initial parameters for the ECU requires a model with both real time capability and sufficient accuracy.

The thermal behavior of wires within the electrical distribution system (EDS) has a strong impact on the conductor cross section, the type of insulation, the derating, and the fusing system, and therefore on weight, cost, and reliability. Consequently, significant efforts have been made to develop sound static and dynamic thermal models for single wires and wire bundles. However, these models are based on the simplifying assumption that the object is completely surrounded by air, where, with the exception of free convection, airflow can be neglected, and where no interaction with other objects is considered. The approach presented in this paper takes into account the actual environment and routing within a vehicle, where some objects such as metal sheets can be considered as heat sinks and other objects, e.g. a motor block, as heat sources.

So far, the effect of injection rate shaping on the diesel combustion in small-bore DI diesel engines has not been extensively investigated, especially at high part load conditions with high EGR rates. The benefit of injection rate shaping is already verified for heavy duty engines at high load conditions with and without EGR. For this investigation, single cylinder engine investigations were conducted at the VKA / RWTH Aachen University. In order to meet the future NOx legislation limits like US-Tier2Bin5 it is crucial to reduce NOx especially at the high load points of the certification cycles, as FTP75 or US06. For the single cylinder investigations two part load points were chosen, which have relevance for the mentioned certification cycles. The experimental work focuses on different rate shapes as rectangular (Common-Rail type), ramp and boot shape at high EGR rates.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

The purpose of this study is to investigate the effect of spray-bowl interaction on combustion, and pollutants formation at one specific high-load point of a single-cylinder small-bore diesel engine through computational analysis. The simulations are performed using Representative Interactive Flamelet (RIF) model with detailed chemical kinetics. Detailed chemistry-based soot model is used for the prediction of soot emissions. The simulations are performed for five different injection timings. Model-predicted cylinder pressure and exhaust emissions are validated against the measured data for all the injection timings. A new method - Two-part analysis - is then applied to investigate the spray-bowl interaction. Two-part analysis splits the volume of the combustion chamber into two, namely the piston bowl and the squish volume. Through analysis, among others the histories of soot, carbon monoxide (CO) and nitric oxide (NO ) emissions inside both volumes are shown.