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Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.

Cybersecurity assumes a major role in the context of the automotive domain, where both existing and forthcoming regulations are heightening the need for robust security engineering. A significant milestone in advancing cybersecurity within the automotive industry is the release of the first international standard for automotive cybersecurity ISO/SAE 21434:2021 ‘Road Vehicles — Cybersecurity Engineering’. A recently published type approval regulation for automotive cybersecurity (UN R155) is also tailored for member countries of the UNECE WP.29 alliance. Thus, the challenges for embedded automotive systems engineers are increasing while frameworks, tools and shared concepts for cybersecurity engineering and training are scarce.

Amid the increasing demand for higher efficiency in combustion driven handheld tools, the recent developments in electric machine technology together with the already existing benefits of small combustion engines for these applications favor the investigation of potential advantages in hybrid powertrain tools. This concept-design study aims to use a fully parametric, system-level simulation model with exchangeable blocks, created with a power-loss approach in Matlab and Simulink, in order to examine the potential of different hybrid configurations for different tool load cycles. After the model introduction, the results of numerous simulations for 36 to 100 cc engine displacement will be presented and compared in terms of overall system efficiency and overall powertrain size. The different optimum hybrid configurations can show a reduction up to 30 % in system’s brake specific fuel consumption compared to the baseline combustion engine driven model.

To get an overview of the emission situation in the field of small non-road mobile machinery powered by various types of SI engines, the Association for Emissions Control by Catalyst (AECC), together with the Institute for Internal Combustion Engines and Thermodynamics (IVT) of Graz University of Technology, conducted a customized test program. The main goal for this campaign was to derive information regarding the emissions of regulated gaseous components (following European Directive 97/68/EC) as well as particulate matter. With regard to the big variety of different engines that are available on the European and North-American market, the most representative ones had to be chosen. This resulted in a pool of test devices to cover different engine working principles (2-Stroke and 4-Stroke), technological standards (low-cost and professional tools) and different emissions control strategies (advanced combustion and exhaust gas aftertreatment).

The European emission legislation for two-wheeler vehicles driven by engines of ≤ 50 cm₃ is continuously developing. One of the most important issues in the near future will be the finalization of the European Commission's proposals for future steps in the emissions regulations as well as the verification of the impacts of current standards on the market. To have a basis for the discussion about these topics, the Association for Emissions Control by Catalyst (AECC) with the Institute for Internal Combustion Engines and Thermodynamics of Graz University of Technology (IVT) carried out an extensive test program to show the actual emission situation of state-of-the-art mopeds including mass and number of particulate matter as well as unregulated gaseous components. One of the main goals of these tests was to measure exhaust emissions without any modifications to the engines of standard production vehicles available on the European market.

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.

During recent years the accident simulation program PC-Crash was developed. This software simulates vehicle movement before, during and after the impact, using 3D vehicle and scene models. When reconstructing car accidents, quite often questions arise regarding occupant movement and loading. Especially important is the influence of different types of restraint systems on the occupant. MADYMO® is a software tool which was developed by TNO in the Netherlands and which is well known in the automotive industry for the simulation of occupant movement. It allows the simulation of all kinds of modern restraint systems such as airbags and seatbelts with and without pretensioners. As the software is used in the automotive industry quite extensively, a huge validated database of dummy and human models is available. Since MADYMO® demands the setup of quite complicated input files, its use normally requires a high level of expertise.

These days a new generation of hybrid electric vehicles (HEV) are penetrating the global vehicle market - the plug-in hybrid electric vehicles (PHEVs). Compared to conventional HEVs, PHEVs have additional significant potential. They are able to improve fuel efficiency and reduce local emissions due to higher battery capacities, and they can be recharged from external outlets. Energy management has a major impact on the PHEVs performance. In this publication, an innovative operation strategy for PHEVs is presented. This is due to the fact that both increasing fuel efficiency and enhancing the vehicle's longitudinal performance requires a fine balance between the consumption of fossil and electric energy. The new operation strategy combines advanced predictive and adaptive algorithms. In contrast to the charge-sustaining strategy of HEVs, the charge-depleting mode for PHEVs is more appropriate.

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.

Increasing demands for safety, security, and certifiability of embedded automotive systems require additional development effort to generate the required evidences that the developed system can be trusted for the application and environment it is intended for. Safety standards such as ISO 26262 for road vehicles have been established to provide guidance during the development of safety-critical systems. The challenge in this context is to provide evidence of consistency, correctness, and completeness of system specifications over different work-products. One of these required work-products is the hardware-software interface (HSI) definition. This work-product is especially important since it defines the interfaces between different technologies. Model-based development (MBD) is a promising approach to support the description of the system under development in a more structured way, thus improving resulting consistency.

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.

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.

Drivetrain electrification is increasing in the kart racing sector since noise emissions are an important factor in urban areas. To improve range, it has become necessary to optimize the rolling resistance of kart racing tires. This paper introduces a parameter study for small bias-ply tires which are used in kart racing and investigates the effect of these parameters on rolling resistance. In recent literature, rolling resistance is mostly examined in radial passenger car tires. Most testing devices are limited to rim sizes from ten inches upwards. In this study, a test rig was developed with focus on low cost and small rim sizes. This self-developed test rig was validated through a comparison with an approved test rig according to ISO 18164 standard. A parameter study was conducted to investigate the effect of changes in the construction of the tire. These changes affect the warp count of the carcass fabric and the crown angle of the different plies.

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.

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.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

Car driver’s behavior and its influence on driving characteristics play an increasing role in the development of modern vehicles, e.g. in view of efficient powertrain control and implementation of driving assistance functions. In addition, knowledge about actual driving style can provide feedback to the driver and support efficient driving or even safety-related measures. Driving patterns are caused not only by the driver, but also influenced by road characteristics, environmental boundary conditions and other traffic participants. Thus, it is necessary to take the driving circumstances into account, when driving patterns are studied. This work proposes a methodology to cluster and evaluate driving patterns under consideration of vehicle-related parameters (e.g. acceleration and jerk) in combination with additional influencing factors, e.g. road style and inclination. Firstly, segmentation of the trip in distance series is performed to generate micro cycles.

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.

The production of electric vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. In comparison to conventional materials such as aluminum, ply wood structures exhibit beneficial damping properties. The loss factor of plywood structures with a thickness below 20 mm ranges from 0.013 to 0.032. Comparable aluminum structures however exhibit only a fraction of this loss factor with a range between 0.002 and 0.005.

Nowadays, politicians are forced by air pollution prevention to demand zero emission vehicles (ZEV) in the form of pure electric vehicles. The poor capacity to weight factor of actual batteries compared to any kind of liquid or gaseous hydro-carbon fuel is the main reason for the retarded implementation of ZEV. Solutions offered by automobile manufacturers are mild to full hybrid powertrains based on the well established ICE platform. The difficulty of those approaches of electrification is to compete with the performance and benefit costumers expect from standard automobiles. Pure electric vehicles are rare and often disappointing regarding range and/or performance. Additionally the costs for such vehicles, which are mainly driven by the battery prices, are comparatively high, impeding their market entrance and acceptance. Low price electric city scooters are actually offered as pure electric vehicles in a wide variety of different models.