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In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, also the battery and the electric motors have to be cooled. Currently, scroll compressors are widely used in the automotive industry, which generate one pressure pulse per revolution due to their discontinuous compression principle. This results in speed-dependent pressure fluctuations as well as higher-harmonic pulsations that arise from reflections. These fluctuations spread through the refrigeration cycle and cause the vibration excitation of refrigerant lines and heat exchangers. The sound transmission path in the air conditioning heat exchanger integrated in the dashboard is particularly critical. Various silencer configurations can be used to dampen these pulsations.

Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

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 emissions gained significant relevance with the upcoming Euro7 type approval within the European Union for brake emission measurement on the test bed. While the controlled brake test bed approach provides consistent results, real-driving emission (RDE) measurements are needed to better understand actual emission behavior due to varying vehicle and environmental conditions. The EU has already announced its interest in RDE testing. Here we present the results of an RDE brake wear sampling system with minimal thermal impact, where particles are only sampled from one side of the brake disc, characterized on a laboratory sampling system. The investigations aim to validate symmetric particle release and to confirm that doubling the measured RDE results effectively represents the reference emissions on the test bed.

In battery electric vehicles (BEV), thermal management is a key technique to improve efficiency and lifetime. Currently, manufacturers use different cooling concepts with numerous architectures. This work describes the development of a co-simulation framework to optimize BEV thermal management on system level, using advanced simulation methodologies also on component level, merging simulation and testing. Due to interactions between multiple conditioning circuits, thermal management optimization requires an overall vehicle approach. Thus, a full vehicle co-simulation of a BEV is developed, combining 1D thermal management software KULI and MATLAB/Simulink. Within co-simulation, the precise modeling of vehicle’s subsystems is important to predict thermal behavior and to calculate dynamic heating and cooling demands as well as exchanged energy flows with the thermal management system.

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).

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.

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.

A new artificial intelligence (model order reduction) / finite element coupled approach will be presented for the risk assessment of battery fire during a car crash event. This approach combines standard crash finite element for the main car body with a reduced order model for the battery. Simulation is today used by automotive engineering teams to design lightweight vehicle bodies fulfilling vehicle safety regulations. Legislation is rapidly evolving to accommodate the growing electrical vehicle market share and is considering additional battery safety requirements. The focus is on avoiding internal short circuit due to internal damage within a cell which may result in a fire hazard. Assessing short circuit risk in CAE at the vehicle level is complex as there involves phenomena at different scales. The vehicle deforms on a macroscale level during the impact event.

A reduction in CO2 emissions and consequently fuel consumption is essential in the context of future greenhouse gas limits. With respect to the thermodynamic loss analysis of an internal combustion engine, a gap between the net indicated thermal efficiency and the brake thermal efficiency is recognizable. This share is caused by friction losses, which are the focus of this research project. The parasitic loss reduction potential by replacing the mechanical water pump with an electric coolant pump is discussed in the course of this work. This is not a novel approach in light duty vehicles, whereas in commercial vehicles a rigid drive of all auxiliaries is standard. Taking into account an implementation of a 48-V power system in the short or medium term, an electrification of auxiliary components becomes feasible. The application of electric coolant pumps on an Euro VI certified 6-cylinder in-line heavy-duty diesel engine regarding fuel economy was thus performed.

The concept of a loop scavenged two-stroke engine, controlling the intake and exhaust port by the moving piston, is a proven way to realize a simple and cheap combustion engine. But without any additional control elements for the gas exchange this concept quickly reaches its limits for current emission regulations. In order to fulfil more stringent emission and fuel consumption limits with a two-stroke engine, one of the most important measures is to avoid scavenging losses of fuel and oil. Additionally, it is necessary to follow a lambda = 1 concept for a 3-way exhaust gas after-treatment. Therefore, using internal mixture preparation systems in combination with different concepts to control the gas exchange process, the two-stroke engine could become a choice for automotive applications, especially as a Range Extender in a Plugin Hybrid Electric Vehicle (PHEV).

Small displacement two-stroke engines are cheap and low-maintenance propulsion systems and commonly used in scooters, recreation vehicles and handheld power-tools. The restriction by emission legislation and the increasing environmental awareness of end users as well as decreasing energy resources cause a rethinking in the development of propulsion systems and fuels in these fields. Despite recent improvements of electric powertrains, two stroke engines are the challenged propulsion system in high performance handheld power tools at the moment. The reasons are the extraordinary high power to weight ratio of two-stroke engines, the high energy density of liquid fuels and the reliability of the product with respect to extreme ambient conditions. Nevertheless, further improvements on emissions and fuel consumption of small displacement two-stroke engines can be realized.

In a variety of applications, two-stroke engines assert their usage as a propulsion unit, for examples in off-road vehicles, scooters, hand-held power tools and others. The outstanding power to weight ratio is the key advantage for two-stroke engines. Furthermore, two-stroke engines convince with high durability and low maintenance demand. However, an increasing environmental awareness, the protection of health and the shortage of fossil resources are the driving factors to further enhance the internal combustion process of two-stroke engines. The reduction of emissions and fuel consumption with a constant power level is focused on. Developments deal with the optimization of the combustion process itself or the enhancement of the exhaust gas aftertreatment. Especially in very small two-stroke engines an exhaust gas aftertreatment system is rarely applied, due to disadvantages regarding component temperatures and product costs.

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.

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.

The pulse-echo method of non-destructive ultrasonic material testing is modeled by an iterative coupling scheme combining analytical and numerical methods in different domains. The approach offers significant advantages in terms of computational efficiency compared to volumetric mesh-based numerical models if the distance between transducer and specimen is large compared to the wavelength in the coupling medium. Excitation and results are given in the time domain while computations are performed in the frequency domain and are compatible with usual FEM solvers for linear elasticity. Due to the use of interpolated phase-shifted transfer functions only a small number of frequency lines is required in comparison to a direct Fourier transform of signals. The method is illustrated alongside a typical application on a steel structure embedded in water.

Friction losses as well as lube oil consumption at the piston group are key factors for future engine downsizing concepts regarding to emissions and consumption. This means an early identification of friction losses and wear is essential within development. The main problem is that the wear assessment is based on long durability tests which are typically performed in a later phase. This may lead to the fact that an early optimized configuration with respect to friction can cause a potential wear problem later in the durability test program. Still ongoing trends in combustion engine engineering lead to both the minimized oil supply in the tribocontact piston bore interface and improved wear resistance. One is forced to the conclusion that understanding and quantifying wear will be a key driver for the future engine development process. The aim is a holistic concept that combines different methods to investigate wear and furthermore its combination with friction loss studies.

For many applications, such as scooters, hand-held power tools and many off-road vehicles, two-stroke engines are used as a preferred propulsion unit. These engines convince by a good power to weight ratio, a high durability and low maintenance technology and are therefore the first choice in this field of application. In general, already much development effort has been expended to improve those systems. However, an increasing environmental awareness, the protection of health and the shortage of fossil resources are the driving factors to further enhance the internal combustion process of those adapted two-stroke engines. The current focus here is on the reduction of emissions and fuel consumption with an at least constant power output. An approach to address an improvement of engine efficiency can be covered by applying a lean combustion burn mode.

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.