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Real world operating scenarios have a major influence on emissions and fuel consumption. To reduce climate-relevant and environmentally harmful gaseous emissions and the exploitation of fossil resources, deep understanding concerning the real drive behavior of mobile sources is needed because emissions and fuel consumption of e.g. passenger cars, operated in real world conditions, considerably differ from the officially published values which are valid for specific test cycles only [1]. Due to legislative regulations by the European Commission a methodology to measure real drive emissions RDE is well approved for heavy duty vehicles and automotive applications but may not be adapted similar to two-wheeler-applications. This is due to several issues when using the state of the art portable emission measurement system PEMS that will be discussed.

The development of future internal combustion engines and fuels is influenced by decreasing energy resources, restriction of emission legislation and increasing environmental awareness of humanity itself. Alternative renewable fuels have, in dependency on their physical and chemical properties, on the production process and on the raw material, the potential to contribute a better well-to-wheel-CO2-emission-balance in automotive and nonautomotive applications. The focus of this research is the usage of alcohol fuels, like ethanol and 2-butanol, in motorcycle high power engines. The different propulsion systems and operation scenarios of motorcycle applications in comparison to automobile applications raise the need for specific research in this area.

Millions of small displacement single-cylinder engines are used for the propulsion of scooters, motorcycles, small boats and others. These SI-engines represent the basis of an affordable mobility in many countries, but at the same time their efficiency is quite low. Today, the limited fossil fuel resources and the anthropogenic climate require a sustainable development of combustion engines, the reduction of fuel consumption being an important factor. A variety of different strategies (turbo-charging, cylinder deactivation, direct injection, etc.) are investigated here to increase the efficiency of multi-cylinder engines. In the case of small displacement single-cylinder engines, other strategies are required because of their special design and the high pressure on costs. In the context of this paper different layout parameters which have an influence on the working process are investigated, with the aim of increasing the efficiency of small displacement single-cylinder engines.

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.

Virtual sensing refers to the processing of desired physical data based on measured values. Virtual sensors can be applied not only to obtain physical quantities which cannot be measured or can only be measured at an unreasonable expense but also to reduce the number of physical sensors and thus lower costs. In the field of spark ignited internal combustion engines, the virtual sensing approach may be used to predict the cylinder pressure signal (or characteristic pressure values) based on the acceleration signal of a knock sensor. This paper presents a method for obtaining the cylinder pressure signal in the high-pressure phase of an internal combustion engine based on the measured acceleration signal of a knock sensor. The approach employs a partial differential equation to represent the physical transfer function between the measured signal and the desired pressure. A procedure to fit the modeling constants is described using the example of a large gas engine.

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.

To achieve high power output and good efficiency and to comply with increasingly stricter emission standards, modern combustion engines require a more complex engine design, which results in a higher number of control parameters. As the measurement effort and the number of sensors for engine development at the test bed continue to increase, it is becoming nearly impossible for the test bed engineer to manually check measurement data quality. As a result, automated methods for analysis and plausibility checks of measurement data are necessary in order to find faults as soon as they occur and to obtain test results of the highest possible quality. This paper presents a methodology for automated fault diagnosis on engine test beds. The methodology allows reliable detection of measurement faults as well as the identification of the root cause of faults.

Charge dilution by lean-burn is one way to increase the efficiency of spark ignition engines while reducing NOx emissions. This work focuses on increasing the flammability of lean mixtures inside a passive pre-chamber spark plug by elevating its temperature with the help of a controllable hot surface integrated into the pre-chamber. Thus, an extension of the lean limit under part load is aimed for. A pre-chamber spark plug prototype with an integrated, controllable glow plug was developed, called Hot Surface Assisted Spark Ignition (HSASI). Experimental investigations were conducted on a single-cylinder engine at the Karlsruhe University of Applied Sciences. Operating modes with an active glow plug (HSASI) and a non-active glow plug were compared. The lean limit for both operation modes were determined under part load. NOx, CO and THC emissions were measured for different air-fuel equivalence ratios λ. The lean limit is extended by more than 0.1 in λ at low loads with HSASI operation.

A transient behavior investigation of a hybrid hand-held tool is carried out on near real load conditions, through a hybrid experimental and simulative study. As this study focuses on handheld tools with a varied or transient load operation like chainsaws and brush cutters, a use of a blower tool as a test-carrier and a throttle body implementation on its blower air pipe adds a controllable braking mechanism. This allows for driving varied load cycles without the need of a testbench. Experimental investigation takes place at both start-up, shut-down and load conditions and for different drive control and commutation modes of electric motor. The controller characterization and parameter selection are done. After the load cycles are driven on the test-carrier, the characterizing data are transferred to the MATLAB and Simulink simulation model to correct and calibrate its transient behavior.

Increasing demands regarding the efficiency and emissions of internal combustion engines will require higher peak firing pressures and increased indicated mean effective pressures in the future. Adaptation of these parameters will result in higher thermal and mechanical loads that act on core engine components. To meet the future requirements, it is essential to make changes to the design of the tribological system, which is composed of the piston, piston rings, liner and lube oil, while maintaining the robustness and reliability of the engine and its components. Modification of the tribological system requires in-depth knowledge of wear and friction. This paper presents the setup of a model of the tribological system (piston, piston rings, liner and lube oil) of a large gas engine in the commercial software AVL EXCITE™ Piston&Rings as well as its calibration and validation with data obtained from a test bed.

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.

As alternative to electrification or carbon free fuels such as hydrogen, CO2-neutral fuels have been researched aiming to decrease the impact of fossil energy sources on the environment. Despite the potential benefit of capturing CO2 emission after combustion for own fuel production, the so-called eFuels also benefit by using a green source of energy during their fabrication. Among all the possibilities for eFuels, alcohols, ethers (such as MTBE and ETBE) and alternative hydrocarbons have shown positive impacts regarding emission reduction and performance when compared to standard gasoline. Previously in [1] and [2], synthetic fuels and methanol blends were tested at steady state conditions in order to verify advantages and drawbacks relative to gasoline, for power-sport motorcycles.

The objective of this experimental investigation was to analyze the effect of various exhaust gas aftertreatment technologies on particulate number emissions (PN) of an MPFI EU5 motorcycle. Specifically, three different aftertreatment strategies were compared, including a three-way-catalyst (TWC) with LS structure as the baseline, a hybrid catalyst with a wire mesh filter, and an optimized gasoline particulate filter (GPF) with three-way catalytic coating. Experimental investigations using the standard test cycle WMTC performed on a two-wheeler chassis dynamometer, while the inhouse particulate sampling system was utilized to gather information about size-dependent filtering efficiency, storage, and combustion of nanoparticles. The particulate sampling and measuring system consist of three condensation particle counters (CPCs) calibrated to three different size classes (SPN4, SPN10, SPN23).

Currently, emission regulations for the LVs using standard spark ignited ICEs considering only gaseous pollutants, just as CO, HC and NOx. Following the upcoming legislation for personal vehicles sector, the LVs might also include limits of PN and PM. Regarding fuel injection strategies, the MPFI which was previously excluded from particulate control will be incorporated into the new regulation [1]. In terms of social harm, there will be a necessity to reduce engine particulate emissions, as they are known for being carcinogenic substances [2, 3, 4]. Generally, the smaller the particulate diameter, the more critical are the damages for human health therefore, the correct determination of PN and particulate diameter is essential. Beside future challenges for reducing and controlling particulates, the reduction of fossil fuel usage is also an imminent target, being the replacement by eFuels one of the most promising alternatives.

Increasingly stringent emission regulations force manufacturers of two wheelers to develop low emission motorcycle concepts. Especially for small two-stroke engines with symmetrical port timing structure, causing high HC-emissions due to scavenge losses, this is a challenging demand that can only be met with alternative mixture formation strategies and by intensifying the use of modern development tools. Changing from EU4 to EU5, emission legislation will not only have an impact on the improvement of internal combustion but will also drastically change the after-treatment system. Nowadays, small two-stroke engines make use of a simple carburetor for external mixture preparation. The cylinders are scavenged by air/fuel mixtures. Equipped with exhaust gas after-treatment systems, such as secondary air with two or three catalytic converters, the emission limits for EURO 4 homologation can be achieved with carbureted engines.

Based on the fundamental analysis of the two-stroke process (SETC 2005-32-0098) and the development of a stratified scavenged small capacity two-stroke engine (SETC 2006-32-0065), a further approach to achieve low emissions in this engine category is the main subject of this publication. The principles of the system are described by design activities, results of the 3D-CFD simulation and the visualization of the spray in the cylinder. The benefit of this system on exhaust emissions is demonstrated by engine test bench as well as chassis dynamometer results. The achievable reduction of exhaust emissions, especially with an applied oxidation catalytic converter, is remarkable and the potential to fulfill future emission limits has already been demonstrated.

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.

In an era characterized by the rapid proliferation and advancement of AI-based technologies across various domains, the spotlight is placed on the integration of these technologies into trustworthy autonomous systems. The integration into embedded systems necessitates a heightened focus on dependability. This paper combines the findings from the TEACHING project, which delves into the foundations of humanistic AI concepts, with insights derived from an expert workshop in the field of dependability engineering. We establish the body of knowledge and key findings deliberated upon during an expert workshop held at an international conference focused on computer safety, reliability and security. The dialogue makes it evident that despite advancements, the assurance of dependability in AI-driven systems remains an unresolved challenge, lacking a one-size-fits-all solution.

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.

Brake wear particles are recognized as one of the dominant sources of road transport particulate matter emissions and are linked to adverse health effects and environmental impact. The UNECE mandated the Particle Measurement Program to address this issue, by developing a harmonized sampling and measurement methodology for the investigation of brake wear particles on a brake dynamometer (dyno). However, although the brake dyno approach with tightly controlled test conditions offers good reproducibility, a multitude of changing vehicle and surrounding conditions make real-driving emissions measurement a highly relevant task. Here we show two different prototypes for on-road particle measurement with minimal impact of the measurement setup on the emission behavior, tested on a brake dyno.