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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.

The absence of combustion engine noise pushes increasingly attention to the sound generation from other, even much weaker, sources in the acoustic design of electric vehicles. The present work focusses on the numerical computation of flow induced noise, typically emerging in components of flow guiding devices in electro-mobile applications. The method of Large-Eddy Simulation (LES) represents a powerful technique for capturing most part of the turbulent fluctuating motion, which qualifies this approach as a highly reliable candidate for providing a sufficiently accurate level of description of the flow induced generation of sound. Considering the generic test configuration of turbulent pipe flow, the present study investigates in particular the scope and the limits of incompressible Large-Eddy Simulation in predicting the evolution of turbulent sound sources to be supplied as source terms into the acoustic analogy of Lighthill.

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.

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.

Small displacement two-stroke engines are widely used as affordable and low-maintenance propulsion systems for motorcycles, scooters, hand-held power tools and others. In recent years, considerable progress regarding emission reduction has been reached. Nevertheless, a further improvement of two-stroke engines is necessary to cover protection of health and environment. In addition, the shortage of fossil fuel resources and the anthropogenic climate change call for a sensual use of natural resources and therefore, the fuel consumption and engine efficiency needs to be improved. With the application of suitable analyses methods it is possible to find improving potential of the working processes of these engines. The thermodynamic loss analysis is a frequently applied method to examine the working process and is universally adaptable.

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.

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.

The main target for the development of power sport engines is and will be in future the increase of the power-to-weight ratio. However, the reduction of carbon dioxide emissions is getting more and more important as future legislation and increasing customer demands ask for lower fuel consumption. One possible technology for CO₂ reduction which is widely used in automotive applications is downsizing by reducing the engine capacity and increasing the specific power by charging strategies. Focusing on power sport applications, like motorcycles, the automotive downsizing technologies cannot be transferred without major modifications. The essential difference to automotive applications is the extraordinary response behavior of today's motorcycles, as well as the large engine speed spread. Additionally, packaging and cost reasons exclude the direct transfer of highly complex automotive technology, like two-stage charging, cam-phasing, etc., to motorcycle applications.

Energy politics and environmental circumstances demand novel strategies for private transport. Several studies have shown that one of these possibilities can be an electric vehicle with a range extender - REX. Today these REX engines are under way as derivation from modern internal combustion engines. As the need for an optimized usage of energy will further increase in the future, alternative energy converter systems have to be investigated. For DENSO, as supplier of components, it is of strong interest how the basic layout of these concepts could look like. This is necessary in order to be prepared for the specific needs of these concepts in terms of auxiliaries, electric / electronic components as well as for the cabin climate & various control strategies. In these REX-concepts all energies have to be considered. A sophisticated usage of energy inside a REX vehicle is required which leads to the investigation of a combined heat and power usage on-board.

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.

State of the art technologies of 2 and 4 stroke engines have to fulfill severe future exhaust emission regulations, with special focus on the aspects of rising performance and low cost manufacturing, leading to an important challenge for the future. In special fields of applications (e.g. mopeds, hand held or off-road equipment) mainly engines with simple mixture preparation systems, partially without exhaust gas after treatment are used. The comparison of 2 and 4 stroke concepts equipped with different exhaust gas after treatment systems provides a decision support for applications in a broad field of small capacity engine classes.

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.

An efficient and economic method to increase the performance of four stroke engines can be accomplished by utilizing the crankcase supercharging method. The lubrication of the movable parts in the crankcase by mixing the intake air with lubricant leads to a high oil consumption and disadvantages in the emission characteristics. This paper describes parts of a research project with the goal to develop a supercharged four–stroke engine with a closed loop lubrication system for the crank train and the cylinder head. The thermodynamic layout and the development of an oil separating system have been carried out with the help of simulation tools and development work on a flow test bench.

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.

The release of the “Regulation No. 168/2013” for the approval and market surveillance of two- or three-wheel motorcycles and quadricycles of the European Union started a new challenge for the motorcycle industry. One goal of the European Union is to achieve emission parity between passenger cars (EURO 6) and motorcycles (EURO 5) in 2020. The hybridization of motorcycle powertrains is one way to achieve these strict legislation limits. In the automotive sector, hybridization is well investigated and has already shown improvements of fuel consumption, efficiency and emission behavior. Equally, motorcycle applications have a high potential to improve efficiency and to meet customer needs as fun to drive as well. This paper describes a methodical approach to analyze conventional motorcycles regarding the energy and power demand for different driving cycles and driving conditions. Therefore, a dynamic or forward vehicle simulation within MATLAB Simulink is used.

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.

In hybrid electric vehicles (HEV), the operation strategy strongly influences the available system power, as well as local exhaust emissions. Predictive operation strategies rely on knowledge of future traction-force demands. This predicted information can be used to balance the battery’s state of charge or the engine’s thermal system in their legal operation limits and can reduce peak loads. Assuming the air and rolling drag-coefficient to be constant, the desired vehicle velocity, vehicle-mass and longitudinal driving resistances determine the vehicle’s traction-force demand. In this paper, a novel methodology, combining a history-based prediction algorithm for estimating future traction-force demands with the parameter identification of road grade angle and vehicle mass, is proposed. It is solely based on a route-history database and internal vehicle data, available on its on-board communication and measuring systems.