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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.

Discussions about the optimal technology of propulsion systems for future ground vehicles have been raising over the last few years. Several options include different types of technologies. However, those who are advocating conventional internal combustion engines are faced with the fact that fossil fuels are limited. Others favor hydrogen fuel as the solution for the future, either in combination with combustion engines or as an energy carrier for fuel cells. In any case, the production and storage of hydrogen is an ongoing challenge of numerous research works. Finally, there are battery-electric or hybrid propulsion systems in use, gaining more and more popularity worldwide. Ongoing advances in power electronics help to improve control systems within automotive applications. New developed or designed components enable more efficient system architectures and control.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

Worldwide increasing energy consumption, decreasing energy resources and continuous restriction of emission legislation cause a rethinking in the development of internal combustion engines and fuels. Alternative renewable fuels, so called bio-fuels, have the potential to contribute to environmentally friendly propulsion systems. This study concentrates on the usage of alcohol fuels like ethanol, methanol and butanol in non-automotive high power engines, handheld power tools and garden equipment with the focus on mixture formation and cold start capability. Although bio-fuels have been investigated intensely for the use in automotive applications yet, the different propulsion systems and operation scenarios of nonautomotive applications raise the need for specific research. A zero dimensional vaporization model has been set up to calculate the connections between physical properties and mixture formation.

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.

Due to current progresses in the field of driver assistance systems and the continuously growing electrification of vehicle drive trains, the evaluation of driver behavior has become an important part in the development process of modern cars. Findings from driver analyses are used for the creation of individual profiles, which can be permanently adapted due to ongoing data processing. A benefit of data-based dynamic control systems lies in the possibility to individually configure the vehicle behavior for a specific driver, which can contribute to increasing customer acceptance and satisfaction. In this way, an optimization of the control behavior between driver and vehicle and the resulting mutual system learning and -adjustment hold great potential for improvements in driving behavior, safety and energy consumption.

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.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

This study deals with the experimental investigation of the mechanical properties of a lithium-ion pouch cell and its modelling in an explicit finite element simulation code. One can distinguish between ‘macroscopic’ and ‘microscopic’ modelling approaches. In the ‘macroscopic’ approach, one material model approximates the behaviour of multiple inner cell layers. In the ‘microscopic’ approach, which is used in the present study, all layers and their interactions are modelled separately. The cell under study is a pouch-type lithium-ion cell with a liquid electrolyte. With its cell chemistry, design, size and capacity it is usable for automotive applications and can be assembled into traction batteries. One cell sample was fully discharged and disassembled, and its components (anode, cathode, separator and pouch) were examined and measured by electron microscopy. Components were also tensile tested.

When vehicle to vehicle collisions are analyzed using a discrete kinetic time forward simulation, several simulation runs have to be performed, to find a solution, where post impact trajectories and rest positions correspond with the real accident. This paper describes in detail a method to vary the pre-impact parameters automatically and to evaluate the simulation results. In a first step the different pre-impact parameters are discussed. Their influence on the impact and the post impact movement is shown. Furthermore the necessary specifications to define the post crash movement are presented. The necessity to define tire marks and rest positions of the vehicles involved is outlined. An effective evaluation criteria is derived, which is used to calculate a simulation error. This error is then used as a target function to control the optimization process. Two different optimization strategies are presented.

Research and development engineers have paid much attention to coupling commercial tools for examining complex systems, recently. The purpose of this paper is to demonstrate an automated coupling of a CFD program with a commercial thermal radiation tool. Based on a previous work the coupling behaviour of a parallelized CFD code is being demonstrated. The automation thus speeds up the calculation procedure even for transient simulations not relying on codes of just one vendor. The simulation is then compared with measurements of temperatures of an actual SUV and conclusions are drawn.

In the automotive industry well-established different simulation tools targeting different needs are used to mirror the physical behavior of domain specific components. To estimate the overall system behavior coupling of these components is necessary. As systems become more complex, simulation time increases rapidly by using traditional coupling approaches. Reducing simulation time by still maintaining accuracy is a challenging task. Thus, a coupling methodology for co-simulation using adaptive macro step size control is proposed. Convergence considerations of the used algorithms and scheduling of domain specific components are also addressed. Finally, the proposed adaptive coupling methodology is examined by means of a cross-domain co-simulation example describing a hybrid electric vehicle. Considerable advantages in terms of simulation time reduction are presented and the trade-off between simulation time and accuracy is depicted.

Experimental investigations on engine test beds represent a significant cost in engine development. To reduce development time and related costs, it is necessary to check the quality of measurements automatically whenever possible directly on the test bed to allow early detection of faults. A fault diagnosis system should provide information about the presence, cause and magnitude of an inconsistency in measurement. The main challenge in developing such a system is to detect the fault quickly and reliably. However, only faults that have actually occurred should be detected because the user will only adopt a system that provides accurate results. This paper presents a methodology for automated fault diagnosis at engine test beds, starting with an explanation of the general procedure. Next, the methods applied for fault detection are introduced.

In order to fulfill future regulations regarding emissions and CO2 reduction, the small engine market inclines to migrate from carburetor systems to cleaner, more efficient electronic ignition controls and electronic fuel injection systems. When implementing such mechatronic systems in small engine applications, one has to consider specific boundary conditions like the lack of relevant sensors, limited possibilities in terms of space and of course the necessity to keep the costs as low as possible. Especially in the non-road mobile machinery (NRMM) segment, the absence of sensors makes it difficult to apply standard electronic control systems, which are based on engine related input signals provided by sensors. One engine related signal, which is even provided by the simplest engine setup, is some form of the crankshaft speed since it is essential for the functionality of the engine.

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.

Vehicles driven by electric or hybrid technologies have the advantage that a high torque potential can be used from the start, hence the initial vehicle acceleration is higher compared to conventional propulsion concepts [1]. The speed-torque characteristic of electric machines is nearly ideal for the use in automotive applications and electrical machines can be controlled with a high efficiency. The aim of the present work is the examination of different sensor technologies, which are used in such automotive applications to measure the rotor position of electric motors. The project includes the assessment and evaluation of different sensor technologies, e.g. resolver, eddy current sensors and sensors based on magneto-resistive effects. The quality of the sensor angular measurement depends on different parameters, for example misalignment in planar direction, longitudinal direction, tilt angle, temperature, rotational speed and supply voltage.

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.

For a broad acceptance of electric vehicles, the trade-off between all electric range and battery cost respectively weight represents the most important challenge. The all electric range obtained under real world conditions most often deviates significantly from the nominal value which is measured under idealized conditions. Under extreme conditions - slow traffic and demanding requirements for cabin heating or cooling - the electrical range might become less a question of spatial distance but even more of total operation time. Whereas with conventional powertrain, high flexibility of the total driving range can be obtained without sacrificing cost, with a pure battery vehicle this results in extreme high cost and weight of the energy storage. Therefore the difference between the typical daily driving range (e.g. in Germany 80-90% is below 50 km) and the minimum total range requested by most customers for acceptance of battery vehicles (200- 250 km), becomes essential.

Volatile oil prices and increased environmental sensitivity together with political concerns have moved the attention of governments, automobile manufacturers and customers to alternative power trains. From the actual point of view the most promising concepts for future passenger cars are based on the conversion of electrical into mechanical energy. In-wheel motors are an interesting concept towards vehicle electrification that provides also high potentials to improve vehicle dynamics and handling. Beside aspects concerning the electric system (e.g. motor type, energy storage, and control strategy), there are also some open questions related with the mechanical design of in-wheel motor driven vehicles that need to be solved before series production.

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].