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Turbulence anisotropy has a great influence on mixture formation and flame propagation in internal combustion engines. However, the visualization of turbulence in simulations is not straightforward; traditional methods lack the ability to display the anisotropic properties in the engine geometry. Instead, they use invariant maps, and important information about the locality of the turbulence anisotropy is lost. This paper overcomes this shortcoming by visualizing the anisotropy directly in the physical domain. Componentality contours are applied to directly visualize the anisotropic properties of turbulence in the three-dimensional engine geometry. Using an RGB (red, green, blue) color map, the three limiting states of turbulence (one-component, axisymmetric two-component and isotropic turbulence) are displayed in the three-dimensional physical domain.

Virtual sensing, i.e., the method of estimating quantities of interest indirectly via measurements of other quantities, has received a lot of attention in various fields: Virtual sensors have successfully been deployed in intelligent building systems, the process industry, water quality control, and combustion process monitoring. In most of these scenarios, measuring the quantities of interest is either impossible or difficult, or requires extensive modifications of the equipment under consideration – which in turn is associated with additional costs. At the same time, comprehensive data about equipment operation is collected by ever increasing deployment of inexpensive sensors that measure easily accessible quantities. Using this data to infer values of quantities which themselves are impossible to measure – i.e., virtual sensing – enables monitoring and control applications that would not be possible otherwise.

The pedestrian model in PC-Crash is based on a multi-body system, where several bodies are interconnected by joints. Each of these bodies can have different properties to represent the different parts of the human body. The joint properties can be specified independently as well. The theoretical background of the pedestrian model has been introduced in SAE 1999-01-0445 and the model shows to give a good correlation of the gross movement of the pedestrian compared to crash test data. As there are many parameters, which can and have to be specified for the pedestrian model as input parameters, an in depth validation of the different parameters has to be done to validate this model. This paper describes in detail the validation process for the pedestrian model. A significant number of crash tests (approx. 30) was used as a basis to compare the results of the simulations and the real movement of the test subjects.

The upstream flow conditions and the use of tractive power to accelerate a vehicle are both sources of energy loss. The vehicle speed and the upstream flow conditions result in the oncoming wind vector experienced by the moving vehicle. The aim of the present work is to show a new approach to consider the chaotic and random behavior of surrounding flow conditions and their influence on driving performance. The approach is shown for the example of motorbike racing conditions. Special interest was put on a description of the flow conditions with respect to well know turbulent flow field parameters like the turbulent length scale or the turbulence intensity. Depending on where the flow conditions are measured, stationary in the earth reference frame, or on a moving vehicle, it is quite difficult to get a robust description of the flow field parameters. These parameters are used together with the Reynolds number to predict the aerodynamic behavior by correlation functions or maps.

The paper focuses on an optimization methodology, which uses Design of Experiments (DoE) methods to define component parameters of parallel hybrid powertrains such as number of gears, transmission spread, gear ratios, progression factor, electric motor power, electric motor nominal speed, battery voltage and cell capacity. Target is to find the optimal configuration based on specific customer targets (e.g. fuel consumption, performance targets). In the method developed here, the hybrid drive train configuration and the combustion engine are considered as fixed components. The introduced methodology is able to reduce development time and to increase output quality of the early system definition phase. The output parameters are used as a first hint for subsequently performed detailed component development. The methodology integrates existing software tools like AVL CRUISE [5] and AVL CAMEO [1].

This paper describes the development of a 0-D-sulfur poisoning model for a NOx storage catalyst (NSC). The model was developed and calibrated using findings and data obtained from a passenger car diesel engine used on testbed. Based on an empirical approach, the developed model is able to predict not only the lower sulfur adsorption with increasing temperature and therefore the higher SOx (SO2 and SO3) slip after NSC, but also the sulfur saturation with increasing sulfur loading, resulting in a decrease of the sulfur adsorption rate with ongoing sulfation. Furthermore, the 0-D sulfur poisoning model was integrated into an existing 1-D NOx storage catalyst kinetic model. The combination of the two models results in an “EAS Model” (exhaust aftertreatment system) able to predict the deterioration of NOx-storage in a NSC with increasing sulfation level, exhibiting higher NOx-emissions after the NSC once it is poisoned.

It is critical for gas and dual fuel engines to have improved transient characteristics in order that they can successfully compete with diesel engines. Testing of transient behavior as well as of different control strategies for the multi-cylinder engine (MCE) should already be done on the single cylinder engine (SCE) test bed during the development process. This paper presents tools and algorithms that simulate transient MCE behavior on a SCE test bed. A methodology that includes both simulation and measurements is developed for a large two-stage turbocharged gas engine. Simple and fast models and algorithms are created that are able to provide the boundary conditions (e.g., boost pressure and exhaust back pressure) of a multi-cylinder engine in transient operation in real-time for use on the SCE test bed. The main models of the methodology are discussed in detail.

CFD has been widely used to predict the flow behavior inside 2-stroke engines over the past twenty years. Usually a mass flow profile or a simple 0D model is used for the inlet boundary condition, which replaces the complete intake geometry, such as reed valve, throttle, and air box geometries. For a CFD simulation which takes into account the exact reed valve geometry, a simulation of all above mentioned domains is required, as these domains are coupled together and thus interact. As the high speed of the engine affects the opening dynamic and closure of the reed valve, the transient data from the crank case volume and the section upstream the reed valve have an important influence on the reed petal dynamic and therewith on the sucked fresh air mass of the engine. This paper covers a methodology for the transient CFD simulation of the reed petals of a 2-stroke engine by using a 2D model.

This paper introduces a research project on a spark ignition engine used in non-road applications. The aim is to illustrate the present situation as basis for comparison and to identify possible improvement potential in terms of performance, efficiency or exhaust and noise emissions. The study is carried out in two steps. First a standard walk-behind lawn mower is equipped with measuring instrumentation for recording the cutting forces and the engine variables during real world operation. The tests are carried out on three different lawn types and two different blade types are investigated. Consequently, in a second step the engine is analysed on the engine test bench in stationary and transient operating mode. A complete engine mapping is done regarding all relevant variables. Additionally to the outdoor tests, fuel consumption and engine out emissions are measured on the engine dynamometer. The recorded data enables a detailed analysis of the engine behaviour.

The development process of 2-stroke engines is characterized by limited CFD investigations in combination with long-term development phases on the test bench with high prototype costs. To reduce the costs and to realize shorter development time together with a higher prediction quality of the engine potential, a higher implementation level of 1D and 3D simulation tools into the development process is necessary. This publication outlines the 1D simulation methods in the layout phase of GDI combustion processes of 2-stroke engine categories. By means of conceptual investigations, the demands, the potential and the limits of 1D CFD simulation methodology are defined. Using a comparison between 1D and 3D or 1D/3D coupled simulation methods the limits of solely 1D simulation are shown. For advanced simulation tasks with a higher demand for prediction quality, the entire engine is simulated in 1D, whereas special parts of the engine design are simulated in a 3D model.

The present technical article deals with the modeling of dynamic tire forces, which are relevant during interactions of safety relevant Advanced Driver Assistance Systems (ADAS). Special attention has been paid on simple but effective tire modeling of semi-physical type. In previous investigations, experimental validation showed that the well-known first-order Kelvin-Voigt model, described by a spring and damper element, describes good suitability around fixed operation points, but is limited for a wide working range. When aiming to run vehicle dynamics models within a frequency band of excitation up to 8 Hz, these models deliver remarkable deviations from measured tire characteristics. To overcome this limitation, a nonlinear Maxwell spring-damper element was introduced which is qualified to model the dynamic hardening of the elastomer materials of the tire.

A worldwide decrease of legal limits for CO2 emissions and fuel economy led to stronger efforts for achieving the required reductions. The task is to evaluate technologies for CO2 reduction and to define a combination of such measures to ensure the targets. The challenge therefor is to find the optimal combination with respect to minimal costs. Individual vehicles as well as the whole fleet have to be considered in the cost analysis - which raises the complexity. Hereby, the focus of this work is the consideration and improvement of a new model series against the background of a fleet and the selection of measures. The ratio between the costs and the effect of the measures can be different for the each vehicle configuration. Also, the determination of targets depends whether a fleet or an individual vehicle is selected and has impact on the selection and optimization process of those measures.

Nowadays, investigating underhood airflow by using numerical simulation is a standard task in the development process of passenger cars and commercial vehicles. Numerous publications exist which deal with simulating the airflow through the engine compartment of road vehicles. However, hardly anything can be found which deals with off-road vehicles and nothing exists which focuses on snowmobiles. In the presented paper the airflow and the thermal conditions inside the engine compartment of a snowmobile are investigated by the usage of computational fluid dynamics (CFD) as well as experimental methods. Field tests at arctic conditions have been conducted on a serial snowmobile to measure temperatures inside the compartment and to gain realistic boundary conditions for the numerical simulation. Thermocouples (type K) were attached under the hood to measure exhaust, air, coolant and surface temperatures of several components at previously defined load cases.

In-cylinder flows in internal combustion engines are highly turbulent in nature. An important property of turbulence that plays a key role in mixture formation is anisotropy; it also influences ignition, combustion and emission formation. Thus, understanding the turbulence anisotropy of in-cylinder flows is critical. Since the most widely used two-equation Reynolds-averaged Navier-Stokes (RANS) turbulence models assume isotropic turbulence, they are not suitable for correctly capturing the anisotropic behavior of turbulence. However, large eddy simulation (LES) can account for the anisotropic behavior of turbulence. In this paper, the Reynolds stress tensor (RST) is analyzed to assess the predictive capability of RANS and LES with regard to turbulence anisotropy. The influence of mesh size on turbulence anisotropy is also looked into for multi-cycle LES.

Hydrogen nowadays is considered one promising energy carrier for future mobility scenarios. Its application as a fuel in ICEs greatly benefits from Direct Injection (DI) strategies, which help to reduce the disadvantages of PFI systems such as air displacement effects, knocking, backfiring and low power density. In SI-engines one appropriate way to increase efficiency is the reduction of wall heat losses by jet- and/or wall-guided mixture formation systems. In theory, Compression Ignition (CI) systems employing a diffusion type of combustion allow for a significant raise in compression ratio and, thus, are likely to excel the SI concept in terms of efficiency. The following paper deals with results obtained from investigations on H2 Compression-Ignition (H2-CI) combustion systems by employing both thermodynamic research engines and 3D CFD simulation.

Friction losses as well as lube oil consumption at the piston group are key factors for future engine downsizing concepts regarding to emissions and consumption. This means an early identification of friction losses and wear is essential within development. The main problem is that the wear assessment is based on long durability tests which are typically performed in a later phase. This may lead to the fact that an early optimized configuration with respect to friction can cause a potential wear problem later in the durability test program. Still ongoing trends in combustion engine engineering lead to both the minimized oil supply in the tribocontact piston bore interface and improved wear resistance. One is forced to the conclusion that understanding and quantifying wear will be a key driver for the future engine development process. The aim is a holistic concept that combines different methods to investigate wear and furthermore its combination with friction loss studies.

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).

Electric driving is generally limited to short distances in an emission sensible urban environment. In the present situation with high cost electric storage and long charging duration hybridization is the key to enable electric driving. In comparison to the passenger car segment, where numerous manufacturers are already producing and offering different hybrid configurations for their premium class models, the two wheeler sector is not yet affected by this trend. The main reason for the retarded implementation of this new hybrid technology is its high system costs, as they cannot be covered by a reasonable product price. Especially for the two wheeler class L1e, with a maximum speed of 45 km/h and an engine displacement of less than 50 cm₃, the cost factor is highly important and decisive for its market acceptance, because the majority of vehicles are still low-cost products equipped with simple carbureted 2-stroke engines.

Following the recent trend in the automotive industry, hybrid and pure electric powertrain systems are more and more preferred over conventional combustion powertrain systems due to their significant potential to reduce greenhouse-gas emissions. Although electric powertrains do not produce direct emissions during their operational time, the indirect emissions over their whole life cycle have to be taken into consideration. In this direction, the carbon footprint due to the electrification of the hand-held power tool industry needs to be examined in the preliminary design phase. In this paper, after defining the carbon footprint calculation framework, assumptions and simplifications used for the calculations, a direct comparison of the total carbon dioxide equivalent (CO2eq) emissions of three equivalent power and range powertrain systems - a combustion-driven, a hybrid-driven, and a cordless electric-driven - is presented.

In consideration of the fact that in extreme Enduro competitions two-stroke motorcycles are still dominating, the Institute of Internal Combustion Engines and Thermodynamics, Graz University of Technology, with a long tradition in two-stroke technology, has developed a new 300 cm3 two-stroke motorcycle engine. The 2-stroke LPDI (Low Pressure Direct Injection) technology was originally developed for the 50 cm3 Scooter and moped market in Europe. In 50 cm3 applications the LPDI technology fulfils the EURO 4 emission standard (2017) [1]. In a next step the LPDI technology was applied to a 250 cm3 Enduro engine demonstrator vehicle. Based on the results of the demonstrator, a complete new high performance 300 cm3 engine was developed. The development of this new engine will be described in this publication. Some interesting aspects of the layout with 3D-CFD methods and also 1D-CFD simulation to optimize the exhaust system by DoE methods are discussed in the paper.