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Trim materials are often used for vibroacoustic energy absorption purposes within vehicles. To estimate the sound impact at a driver’s ear, the substructuring approach can be applied. Thus, transfer functions are calculated starting from the acoustic source to the car body, from the car body to the trim and, finally, from the trim to the inner cavity where the driver is located. One of the most challenging parts is the calculation of the transfer functions from the car body inner surface to the bottom trim surface. Commonly, freely laying mass-spring systems (trims) are simulated with a fixed boundary and interface phenomena such as friction, stick-slip or discontinuities are not taken into consideration. Such an approach allows for faster simulations but results in simulations strongly overestimating the energy transfer, particularly in the frequency range where the mass-spring system’s resonances take place.

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.

Charge dilution in gasoline engines reduces NOx emissions and wall heat losses by the lower combustion temperature. Furthermore, under part load conditions de-throttling allows the reduction of pumping losses and thus higher engine efficiency. In contrast to lean burn, charge dilution by exhaust gas recirculation (EGR) under stoichiometric combustion conditions enables the use of an effective three-way catalyst. A pre-chamber spark plug with hot surface-assisted spark ignition (HSASI) was developed at the UAS Karlsruhe to overcome the drawbacks of charge dilution, especially under part load or cold start conditions, such as inhibited ignition and slow flame speed, and to even enable a further increase of the dilution rate. The influence of the HSASI pre-chamber spark plug on the heat release under EGR dilution and stoichiometric conditions was investigated on a single-cylinder gasoline engine.

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).

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 a result of the ever-increasing application of cyber-physical components in the automotive industry, cybersecurity has become an urgent topic. Adapting technologies and communication protocols like Ethernet and WiFi in connected vehicles yields many attack scenarios. Consequently, ISO/SAE 21434 and UN R155 (2021) define a standard and regulatory framework for automotive cybersecurity, Both documents follow a risk management-based approach and require a threat modeling methodology for risk analysis and identification. Such a threat modeling methodology must conform to the Threat Analysis and Risk Assessment (TARA) framework of ISO/SAE 21434. Conversely, existing threat modeling methods enumerate isolated threats disregarding the vehicle’s design and connections. Consequently, they neglect the role of attack paths from a vehicle’s interfaces to its assets.

The current European fleet of vehicles is ageing and lifetime mileages are rising proportionally. Consequently, a substantial fraction of the vehicle fleet is currently operating at mileages well beyond current durability legislation (≤ 160,000 km). Emissions inventories and models show substantial increases in emissions with increasing mileage, but knowledge of the effect of emissions control system deterioration at very high mileages is sparse. Emissions testing has been conducted on matched pairs (or more) of diesel and gasoline (and CNG) vehicles, of low and high mileage, supplementing the results with in-house data, in order to explore high mileage emission deterioration factors (DF). The study isolated, as far as possible, the effect of emissions deterioration with mileage, by using nominally identical vehicle models and controlling other variables.

To increase reliability and the maintenance interval of an internal combustion engine while operating it with the lowest possible emissions, spark plug wear must be reduced. In this context, information about the spark plug center and the ground electrode temperature is key. Several measurement devices have been developed that measure the temperature of spark plug electrodes. The great challenge is to measure the temperature of the center electrode; on the one hand, the measurement device must be insulated and capable of withstanding the high voltage of the ignition system, and on the other hand, the device should not influence the ignition system. All previously studied devices presented in this paper have in common that major reconstruction of the ignition system and/or spark plugs whose design is very different from the standard engine spark plug were necessary.

Due to climatic movements and politics, there is no doubt that a stricter emission legislation will soon face the two-wheeler sector and their manufacturers with new challenges. Additional to the already limited pollutants, a limitation of particulate number will probably also be introduced, which means that there is an urgent need for action in exhaust gas after treatment and particulate reduction systems. For natural aspirated, port injected engines, as used in two-wheeler-technologies, conventional systems already established in passenger cars are not necessarily applicable. Moreover, the emission spectrum is fundamentally different from passenger car engines due to the better homogenization of they typically used MPFI engine types. Adapting conventional particulate filter technologies to the finer particles of MPFI engines would result in a disproportionately larger exhaust backpressure.

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.

The latest generation of internal combustion engines may emit significant levels of sub-23 nm particles. The main objective of the Horizon 2020 “DownToTen” project was to develop a robust methodology and provide policy recommendations towards the particle number (PN) emissions measurements in the sub-23 nm region. In order to achieve this target, a new portable exhaust particle sampling system (PEPS) was developed, being capable of measuring exhaust particles down to at least 10 nm under real-world conditions. The main design target was to build a system that is compatible with current PMP requirements and is characterized by minimized losses in the sub-23 nm region, high robustness against artefacts and high flexibility in terms of different PN modes investigation, i.e. non-volatile, volatile and secondary particles.

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.

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.

The replacement of safety-critical mechanical components with electro-mechanical systems has led to the fact that safety aspects play a central role in development of embedded automotive systems. Recently, consumer demands for connectivity (e.g., infotainment, car-2-car or car-2-infrastructure communication) as well as new advances toward advanced driver assistance systems (ADAS) or even autonomous driving functions make cybersecurity another key factor to be taken into account by vehicle suppliers and manufacturers. Although these can capitalize on experiences from many other domains, they still have to face several unique challenges when gearing up for specific cybersecurity challenges. A key challenge is related to the increasing interconnection of automotive systems with networks (such as Car2X). Due to this connectivity, it is no longer acceptable to assume that safety-critical systems are immune to security risks.

The enhancement of efficiency will play a more and more important role in the development of future (small) internal combustion engines. In recent years, the Atkinson (or Extended Expansion) cycle, realized over the crank drive, attracted increasing attention. Several OEMs have investigated this efficiency-increasing principle in the whole range from small engines up to automotive engines until now. In prior publications, the authors outlined the remarkable efficiency potentials of an Extended Expansion (EE) cycle. However, for an internal combustion engine, a smooth running performance as well as low vibrations and noise emissions are relevant aspects. This is especially true for an Extended Expansion engine realized over the crank drive. Therefore, design measures concerning friction and NVH need to be taken to enable possible series production status. Basically, these measures strongly depend on the reduction of the free mass forces and moments.

Dual fuel combustion processes, which burn varying ratios of natural gas and diesel, are an attempt to reach high efficiencies similar to diesel engines while exploiting the CO2 savings potential of natural gas. As shown in earlier studies, the main challenge of this combustion process is the high emission of unburned hydrocarbons during low load operation. Many publications have focused on a layout which utilizes port injection of natural gas and a direct injection of diesel to initiate combustion. However, previous studies indicated that a sequential direct injection of both fuels is more promising. It enables charge stratification of natural gas and air, whereby a remarkable reduction of the unburned hydrocarbon emissions was observed. This work develops this approach further, utilizing a low pressure direct injection of natural gas.

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.

The enhancement of efficiency will play a more and more important role in the development of future (small) internal combustion engines. In recent years, the Atkinson cycle, realized over the crank drive, has attracted increasing attention. Several OEMs have been doing investigations on this efficiency-increasing principle with in the whole range from small engines up to automotive ones. In previous publications, the authors stated that an indicated efficiency of up to 48% could be reached with an Atkinson cycle-based engine. However, these studies are based on 1D-CFD simulation. To verify the promising simulation results, a prototype engine, based on the Atkinson principle, was designed and experimentally tested. The aim of the present study is to evaluate and validate the (indicated) engine efficiency gained by experimental tests compared to the predicted simulation results. In order to investigate part load behavior, several valve timing strategies were also developed and tested.