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The ongoing energy transition will have a profound impact on future mobility, with electrification playing a key role. Battery electric vehicles (EVs) are the dominant technology, relying on the conversion of alternating current (AC) from the grid to direct current (DC) to charge the traction battery. This process involves power electronic components such as rectifiers and DC/DC converters operating at high switching frequencies in the kHz range. Fast switching is essential to minimize losses and improve efficiency, but it might also generate electromagnetic interferences (EMI). Hence, electromagnetic compatibility (EMC) testing is essential to ensure reliable system operations and to meet international standards. During DC charging, the AC/DC conversion takes place off-board in the charging station, allowing for better cooling and larger components, resulting in increased power transfer, currently up to 350 kW.

There is a growing need for low-emissions concepts due to stricter emission regulations, more stringent homologation cycles, and the possibility of a ban on new engines by 2035. Of particular concern are the conditions during a cold start, when the Three-Way Catalyst is not yet heated to its light-off temperature. During this period, the catalyst remains inactive, thereby failing to convert pollutants. Reducing the time needed to reach this temperature is crucial to comply with the more stringent emissions standards. The post oxidation by means of secondary air injection, illustrated in this work, is a possible solution to reduce the time needed to reach the above-mentioned temperature. The strategy consists of injecting air into the exhaust manifold via secondary air injectors to oxidize unburned fuel that comes from a rich combustion within the cylinder.

Modern automotive development evolves beyond artificial intelligence for highly automated driving, and toward an interconnected manifold of data-driven development processes. Widely used analytical system modelling struggles with rising system complexity, invoking approaches through data-driven system models. We consider these as key enablers for further improvements in accuracy and development efficiency. However, literature and industry have yet to thoroughly discuss the relevance and methods along the vehicle development cycle. We emphasize the importance of data-driven system models in their distinct types and applications along the developing process, from pre-development to fleet operation. Data-driven models have proven in other works to be fast approximators, of high accuracy and adaptive, in contrast to physics-based analytical approaches across domains.

Predictive physical modeling is an established method used in the development process for automotive components and systems. While accurate predictions can be issued after tuning model parameters, long computation times are expected depending on the complexity of the model. As requirements for components and systems continuously increase, new optimization approaches are constantly being applied to solve multidimensional objectives and resulting conflicts optimally. Some of those approaches are deemed not feasible, as the computational times for required single predictions using conventional simulation models are too high. To address this issue it is proposed to use data-driven model such as neural networks. Previous efforts have failed due to sparse data sets and resulting poor predictive ability. This paper introduces an AI Toolchain used for data-driven modeling of combustion engine components. Two methods for generating scalable and fully variable datasets will be shown.

For the NOx removal from diesel exhaust, the selective catalytic reduction (SCR) and lean NOx traps are established technologies. However, these procedures lack efficiency below 200 °C, which is of importance for city driving and cold start phases. Thus, the present paper deals with the development of a novel low-temperature deNOx strategy implying the catalytic NOx reduction by hydrogen. For the investigations, a highly active H2-deNOx catalyst, originally engineered for lean H2 combustion engines, was employed. This Pt-based catalyst reached peak NOx conversion of 95 % in synthetic diesel exhaust with N2 selectivities up to 80 %. Additionally, driving cycle tests on a diesel engine test bench were also performed to evaluate the H2-deNOx performance under practical conditions. For this purpose, a diesel oxidation catalyst, a diesel particulate filter and a H2 injection nozzle with mixing unit were placed upstream to the full size H2-deNOx catalyst.

The introduction of real driving emissions cycles and increasingly restrictive emissions regulations force the automotive industry to develop new and more efficient solutions for emission reductions. In particular, the cold start and catalyst heating conditions are crucial for modern cars because is when most of the emissions are produced. One interesting strategy to reduce the time required for catalyst heating is post-oxidation. It consists in operating the engine with a rich in-cylinder mixture and completing the oxidation of fuel inside the exhaust manifold. The result is an increase in temperature and enthalpy of the gases in the exhaust, therefore heating the three-way-catalyst. The following investigation focuses on the implementation of post-oxidation by means of scavenging in a four-cylinder, turbocharged, direct injection spark ignition engine. The investigation is based on detailed measurements that are carried out at the test-bench.

Intensified emission regulations as well as consumption demands lead to an increasing significance of unburned hydrocarbon (UHC) emissions for diesel engines. On the one hand, the quantity of hydrocarbon (HC) raw emissions is important for emission predictions as well as for the exhaust after treatment. On the other hand, HC emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the HC molecules. Due to these reasons, a simulation model for predicting HC raw emissions was developed for diesel engines based on a phenomenological two-zone model. The HC model takes three main sources of HC emissions of diesel engines into account: Firstly, it contains a sub-model that describes the fuel dribble out of the injector after the end of injection. Secondly, HC emissions from cold peripheral zones near cylinder walls are determined in another sub-model.

In order to optimize spray layouts of commonly used high-pressure injectors for gasoline direct injection (GDI) engines featuring multi-hole valve seats, a detailed understanding of the cause-effect relation between inner spray hole geometries and inner flow conditions, initializing the process of internal mixture formation, is needed. Therefore, a novel measurement setup, capable of determining spray hole individual mass flow rates, is introduced and discussed. To prove its feasibility, a 2-hole configuration is chosen. The injected fuel quantities are separated mechanically and guided to separate pressure tight measurement chambers. Each measurement chamber allows for time resolved mass flow rate measurements based on the HDA measurement principle (German: “Hydraulisches Druck-Anstiegsverfahren”).

State-of-the-art avionics systems are standardized, e.g. the computing system of the flying vehicle is composed of pre-defined and pre-qualified modules of a standardized avionics platform. Integrated Modular Avionics (IMA) is the most popular representative, but not the only one. Two challenges of standardized avionics platform are system design and configuration. Since the high numbers of functions, modules, and constraints for modern air vehicles, bringing up the optimal system architecture is a difficult job if carried out manually. The subsequent process of creating millions of configuration parameters is time consuming and error prone. Both issues are similar and are, in general, processable by algorithms. Algorithms proved to provide significant support for current system design issues and might be mandatory in future, when avionics become self-organizing and the design and configuration are derived by the platform itself.

The development and qualification of distributed and highly safety-critical avionics systems implicate high efforts and risks. The resulting costs usually limit implementations like fly-by-wire systems to the military or commercial airliner domains. The aim of previous and ongoing research at the Institute of Aircraft Systems at University of Stuttgart is the reduction of these costs and therefore open up their benefits, inter alia, to general aviation, remotely piloted or unmanned aircraft. An approach for an efficient development is the application of a platform based development which supports the reuse of software and hardware components. The Flexible Platform adopts this approach. It is accompanied by a tool suite which automates the design and parameter instantiation, documentation generation and the generation of verification artifacts for a platform instance. This paper presents the approach for the requirement document generation compliant to ARP4754A and DO-178C.

Aircraft cabin systems, especially cabin management systems (CMS) have to cope with frequent cabin changes during their lifecycle. This includes not only layout rearrangements and technological upgrades during the service, but also extensive CMS customizations and product variations before aircraft delivery. Therefore it is inevitable for the CMS to be highly changeable and offer an easy and agile change process. Today's CMS solutions face this challenge with configurable system architectures. Although such architectures offer a vast change domain, they usually come with time consuming and error prone change processes. This paper introduces an adaptive avionics software architecture that enables the CMS to cope with cabin changes highly automatically and with minimal human interactions. The adaptation is performed during an on ground organization phase, in which system changes are detected and evaluated by the CMS itself.

As known de-icing methods use a high amount of energy or environmentally harmful chemicals, research has focused lately on passive de-icing by functional surfaces with an improved removal of ice (de-icing) or a reduced formation of it (anti-icing). Inspired by the Lotus plant leaf, a “superhydrophobic” surface can be produced by the combination of a hierarchical micro/nanoscale roughness and a hydrophobic surface coating. By a hot stamping process we have generated differently shaped microstructures (cylinders, ellipses) on polyurethane (PU) films which were afterwards coated by a plasma enhanced chemical vapor deposition (PECVD) process with thin, hydrophobic fluorocarbon films. This combination of methods could be a process for the production of large area functionalized films. PU films are suitable for outdoor use, because they are resistant against erosion and UV radiation. The films can be glued to different geometries and can easily be exchanged if damaged.

In the automotive industry, the model-based approach is increasingly establishing itself as a standard paradigm for developing control unit software. Just as code reviews are widespread in classical software development as a quality assurance measure, models also have to undergo a stringent review procedure – particularly if they serve as a starting point for automatic implementation by code generators. In addition to these model reviews, the generated production code is reviewed later in the development process by performing auto code reviews. This article will present procedures for and give an account of experiences with model and code reviews which have been adapted to the model-based development process.

The EU SPARC Project (Secure Propelled Vehicle with Advanced Redundant Control) has developed a new system architecture that enables effective application of driver assisted systems in an X-by-wire powertrain. A major challenge in the conception of such a system is development of a reliable electrical energy supply. A simulation is the most important tool for enabling the fundamental aspects to work, as for example, a dimensioning of the powernet. This article explains our approach in this SPARC simulation. We provide suggestions through examples of how to find simulation solutions for powernet dimensioning, as well as for the conception and validation of energy management strategies.

This paper investigates the potential of using FEA poro-elastic Biot elements for the modeling carpet-like trim systems in a simplified setup. A comparison between FEA computations and experiments is presented for two layer (mass-spring) trim systems placed on a test-rig consisting in a 510×354×1.6 mm flat steel plate clamped in a stiff frame excited at its base. Results are presented for a given heavy layer with two different poro-elastic materials: one foam and one fibrous material. The investigations included accelerometer measurements on the steel plate, laser-doppler vibrometer scans of the heavy layer surface, sound pressure measurements in free field at a distance of 1 meter above the plate, as well as sound pressure in a closed rectangular concrete-walled cavity (0.5×0.6×0.7 m) put on top of the test-rig. Computations were carried out using a commercial FEA software implementing the Biot theory for poro-elastic media.

Whereas the verification of non-safety-related, embedded software typically focuses on demonstrating that the implementation fulfills its functional requirements, this is not sufficient for safety-relevant systems. In this case, the control software must also meet application-specific safety requirements. Safety requirements typically arise from the application of hazard and/or safety analysis techniques, e.g. FMEA, FTA or SHARD. During the downstream development process it must be shown that these requirements cannot be violated. This can be achieved utilizing different techniques. One way of providing evidence that violations of the safety properties identified cannot occur is to thoroughly test each of the safety requirements. This paper introduces Evolutionary Safety Testing (EST), a fully automated procedure for the safety testing of embedded control software.

Because of the rapidly increasing amount of electronic components and busses in a vehicle, the use of gateways in Electronic Control Units (ECUs) becomes more important. The upcoming question is how to design an optimal gateway. This paper describes a method for designing an optimal automotive gateway in an FPGA by using Evolutionary Algorithms (EAs). The complete gateway functionality is diagrammed in a specification graph which consists of a function graph and an architecture graph. The function graph describes the complete functionality of the gateway. The architecture graph shows the variety of the different implementation options of the mapped function graph. Each gateway task in the function graph can be realized either in a parallel way (different kinds of hardware implementations) or in a sequential way (software on a microprocessor core).

Increasing vehicle complexity, broader vehicle variety, and global vehicle projects are a major challenge to all global vehicle manufacturers. Common vehicle projects not only require a common E/E-architecture in order to share components, but also a common diagnostic strategy. On-board and off-board strategies have been developed to achieve this goal. This paper will explain the importance of ISO-standardization, common networking & diagnostic architectures and standardized access to vehicle electronics. Also the need for a common diagnostic process chain throughout engineering, manufacturing and service, and the need for harmonized vehicle standards between passenger cars and heavy duty trucks will be addressed.

In open jet wind tunnels with high blockage ratios a sharp rise in drag is observed for models approaching the nozzle exit plane. The physical background for this rise in drag will be analyzed in the paper. Starting with a basic analysis of the dependencies of the effect on model and wind tunnel properties, the key parameters of the problem will be identified. It will be shown using a momentum balance and potential flow theory that interaction between model and nozzle exit can result in significant tunnel-induced gradients at the model position. In a second step, a CFD-based investigation is used to show the interaction between nozzle exit and a bluff body. The results cover the whole range between open jet and closed wall test section interaction. The model starts at a large distance from the nozzle, then moves towards the nozzle, enters the nozzle and is finally completely inside the nozzle.

EMC Emission Measurements are usually carried out in frequency domain with measuring receivers and spectrum analyzers in frequency domain. The advantage is the sensitivity of the measurement by pre-selecting the input signal. The time consumption of such a frequency scan is significant high. Modern oscilloscopes cover the needed frequency range and with additional signal processing the sensitivity can be significant improved. Therefore modern time domain EMC emission techniques are a time and cost effective alternative to traditional frequency range measurement. Further more the “real” signal is being monitored which allows the design engineer to trace the source of the emission much better than with frequency range methods.