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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.

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.

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 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.

Usually the power output of 50 cm₃ two wheelers is higher than necessary to reach the maximum permitted vehicle speed, making engine power restriction necessary. This publication deals with different power restriction strategies for four-stroke engines and their effect on exhaust emissions. Alternative power limitation strategies like EGR and leaning were investigated and compared with the common method of spark advance reduction to show the optimization potential for this certain engine operation conditions. From these tests, a substantial set of data showing the pros and cons in terms of emissions, combustion stability and fuel economy could be derived for each speed limiting technique.

This paper presents a project undertaken by Ricardo and the Energy Efficient Motorsport (EEMS) working group in the UK. The purpose of this project is to develop a method to encourage fuel efficiency in motorsport and enable vehicles running different types of fuels to race on a competitive basis without having to set up a complex set of rules for every application and while maintaining exciting racing for both teams and spectators. Motorsport technologies typically focus on maximum vehicle performance as their prime criteria for optimisation. In this respect they have begun to diverge from the primary technological goal of road car development, which is now focussed around improvement of efficiency and fuel economy.

With the aim of reducing CO2 emissions, several solutions exist presenting different performances and costs. Hybrid electric vehicle is one of the most efficient solutions and lead to fuel consumption and CO2 emissions reduction of 10 to 60 % compared to conventional vehicle and depending on the level of hybridisation and the considered speed cycle. In the context of the European project Hi-CEPS (Highly integrated Combustion Electric Propulsion System), several thermal management solutions have been investigated with the aim of increasing the global vehicle efficiency and tackling hybrid-vehicle-specific cabin comfort challenges such as cabin heating. Intermittent operation of the engine in a hybrid electric vehicle (Stop & Start, pure electric vehicle mode) has detrimental effects on engine and cabin warm-up.

In the course of the last few years a continuous increase of the injection pressure level of gasoline direct injection systems appeared. Today's systems use an injection pressure up to 200bar and the trend shows a further increase for the future. Although several benefits go along with the increased injection pressure, the disadvantages such as higher system costs and higher energy demand lead to the question of the lowest acceptable injection pressure level for low cost GDI combustion systems. Lowering injection pressure and costs could enable the technological upgrading from MPFI to GDI in smaller engine segments, which would lead to a reduction of CO2 emission. This publication covers the investigation of a low pressure GDI system (LPDI) with focus on small and low cost GDI engines. The influence of the injection pressure on the fuel consumption and emission behavior was investigated using a 1.4l series production engine.

The advantages of 2-stroke engines, high power and low weight, are in conflict with their disadvantages, high emissions and bad fuel economy. As these disadvantages are caused by the scavenging process, a reason for the problem can be analyzed by using three dimensional computational fluid dynamics simulation (3D CFD simulation). The scavenging losses can be dramatically reduced with a high pressure fuel injection strategy. The purpose of this strategy is to prevent a fuel concentration in the incoming charge and to reduce the fuel concentration inside the exhaust system. These advantages can only be successfully exploited with the application of an optimal injection strategy. This paper covers a spray study for a gasoline direct injection (GDI) high performance 2-stroke engine using the commercial CFD Code Fluent.

This paper reports on an investigation into the potential for a thermoelectric generator (TEG) to improve the fuel economy of a mild hybrid vehicle. A simulation model of a parallel hybrid vehicle equipped with a TEG in the exhaust system is presented. This model is made up by three sub-models: a parallel hybrid vehicle model, an exhaust model and a TEG model. The model is based on a quasi-static approach, which runs a fast and simple estimation of the fuel consumption and CO2 emissions. The model is validated against both experimental and published data. Using this model, the annual fuel saving, CO2 reduction and net present value (NPV) of the TEG’s life time fuel saving are all investigated. The model is also used as a flexible tool for analysis of the sensitivity of vehicle fuel consumption to the TEG design parameters. The analysis results give an effective basis for optimization of the TEG design.

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.

Excitement, image and emotion are key attributes for cars, particularly those with higher power ratings. Engine sound has traditionally acted as the car’s voice, conveying these attributes to the driver and passengers along with the brand image. Engine sound also underpins the dynamic driving experience by giving instant feedback about how a car is operating, enhancing the connection between driver and vehicle. For decades, the automotive industry has engineered engine sound to achieve these benefits, thereby defining the ‘language’ of car sound. Electric vehicles deliver strong and responsive performance but naturally lack the acoustic feedback that internal combustion engines provide. While this gives advantages in terms of comfort and environmental noise, the benefits of engine sound are lost. Carefully controlled acoustic feedback inside the car’s cabin brings tangible and valuable benefits both for the dynamic driving experience and to convey the brand image.

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].