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Autonomous Driving is being utilized in various settings, including indoor areas such as industrial halls. Additionally, LIDAR sensors are currently popular due to their superior spatial resolution and accuracy compared to RADAR, as well as their robustness to varying lighting conditions compared to cameras. They enable precise and real-time perception of the surrounding environment. Several datasets for on-road scenarios such as KITTI or Waymo are publicly available. However, there is a notable lack of open-source datasets specifically designed for industrial hall scenarios, particularly for 3D LIDAR data. Furthermore, for industrial areas where vehicle platforms with omnidirectional drive are often used, 360° FOV LIDAR sensors are necessary to monitor all critical objects. Although high-resolution sensors would be optimal, mechanical LIDAR sensors with 360° FOV exhibit a significant price increase with increasing resolution.

The UN R155 regulation is the first automotive cyber security regulation and has made security a mandatory approval criterion for new vehicle types. This establishes internationally harmonized security requirements for market approval. As a result, the application of the regulation presents manufacturers and suppliers with the challenge of demonstrating compliance. At process level the implementation of a Cyber Security Management System (CSMS) is required while at product level, the Threat Assessment and Risk Analysis (TARA) forms the basis to identify relevant threats and corresponding mitigation strategies. Overall, an issued type approval is internationally recognized by the member states of the UN 1958 Agreement. International recognition implies that uniform assessment criteria are applied to demonstrate compliance and to decide whether security efforts are sufficient.

The electrification of vehicles marks the introduction of new products to the automotive market and a continued effort to optimize their performance. The electric motor is an important component with which a further optimization of efficiency, power density and cost can be achieved. Additional benefits can be realized in the laminated core. This paper presents an innovative method to produce laminated stacks by a chain of processes different from conventional ways. The process chain presents a sequence of precision blanking, buffering, heat treatment and gluing. The effect of these processes is compared with existing solutions that typically contain some individual features but usually not the combination that enhances the overall effect. The heat treatment decreases residual stresses from previous process steps and reduces power losses in the laminated core. Depending on the design, benefits around 20% are found.

Given the rapid advancement of connected and automated transportation, its applications have significantly increased. They are being studied worldwide to shape the future of mobility. Key promises are a more comfortable, efficient and socially adapted kind of mobility. As part of the EU Horizon2020 project SHared automation Operating models for Worldwide adoption (SHOW), the Karlsruhe Test Site in the Test Area Autonomous Driving Baden-Württemberg (TAF-BW) addresses aspects of scalability to overcome challenges, which have so far hindered market penetration of this future-oriented kind of mobility. The explored services, including passenger and cargo transport, are closely linked to the daily travel requirements of road users, particularly in peri-urban areas, to cover the last mile of their journeys, connecting them to public transport.

The idea of keeping a vehicle safe and secure throughout its whole life cycle, as well as having the opportunity to add functionality after initial delivery, is the key motivation behind automotive software updates. Today, safety or security issues that appear after vehicle delivery need to be resolved by starting a recall campaign. These campaigns require the vehicle user to visit a car repair workshop to get an update. Over The Air (OTA) software updates, being location-independent, can pave the way for higher update frequencies and more efficiency regarding customer satisfaction, resource consumption as well as safety and security. In this paper we analyze requirements for OTA software updates phrased in various standards and regulations as well as in existing development and type approval processes. Prevailing challenges for OTA updates are extracted to identify necessary activities and artifacts within the procedure.

The rapidly growing amount of software in cars reshapes the automotive industry. The software has a significant influence on the production lines, due to the time required to flash it onto the vehicle and its capabilities to test vehicle functions during production. In this paper we identify the main pain points regarding software in the manufacturing process by performing a structured analysis on the experiences made at a major car manufacturer over last two years. Consequently, the paper analyses the possible approaches to address the challenges.

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

For electric vehicles the ability for regenerative braking reduces the use of friction brakes. Particularly on the rear axle of vehicles with reduced dynamic requirements such as urban vehicles, this can offer a potential for downsizing or, in extreme cases, even the elimination of the friction brakes on the rear axle. Due to the fact that the rear axle service brakes also represent the typical parking brake location in SoA (State-of-Art) vehicles, a rigorous rethinking of the parking brake concept is necessary to incorporate safe vehicle standstill management for such novel brake system topology. This research study introduces a novel parking brake design that covers SoA but also legal requirements while retaining potentials associated with the elimination of the rear service brakes such as cost and packaging.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

Software-in-the-Loop (SiL) test environments are the ideal virtual platforms for enabling continuous-development, -integration, -testing -delivery or -deployment commonly referred as Continuous-X (CX) of the complex functionalities in the current automotive industry. This trend especially is contributed by several factors such as the industry wide standardization of the model exchange formats, interfaces as well as architecture definitions. The approach of frontloading software testing with SiL test environments is predominantly advocated as well as already adopted by various Automotive OEMs, thereby the demand for innovating applicable methods is increasing. However, prominent usage of the existing monolithic architecture for interaction of various elements in the SiL environment, without regarding the separation between functional and non-functional test scope, is reducing the usability and thus limiting significantly the cost saving potential of CX with SiL.

Thermal management has always played a significant role in reducing emissions and improving the fuel efficiency of the internal combustion engines (ICEs). With a momentous influence on the thermal behavior of the engines, the cooling system has a considerable impact on ICE performance. In this scenario, a method based on artificial neural network (ANN) of the cooling system was proposed in this work. Specific modeling methods were adopted for the various operating conditions and flow circuits of the cooling system. To describe these varied dynamic characteristics, four ANN sub-models were established to simulate the system at different temperature stages. As a closed-loop system, the temperature of the cooling system can be regarded as a result of all the experienced operating points. Therefore, integral parameters describing the trajectory of the system were selected as the input of the ANNs.

As an important means of engine development and optimization, modelbuilding plays an increasingly important role in reducing carbon dioxide emissions of the internal combustion engines (ICEs). However, due to the non-linearity and high dimension of the engine system, a large amount of data is required to obtain high model accuracy. Therefore, a modelling approach combining the experimental data and prior knowledge was proposed in this study. With this method, an artificial neural network (ANN) model simulating the engine brake specific fuel consumption (BSFC) was established. With mean square error (MSE) and Kullback-Leibler divergence (KLD) serving as the fitness functions, the 86 experimental samples and constructed physical models were used to optimize the ANN weights through genetic algorithms.

The fuel economic and emission performance of an innovative electric hybrid vehicle (HEV), Dualhybrid, with two internal combustion engines (ICEs) under cold start conditions was studied. Sub-models including powertrain, lubrication and cooling system as well as exhaust system were built and integrated into the models of Dualhybrid and two other reference models: Base model and Fullhybrid model. Coupled lubrication and the exhaust systems of the two ICEs are proposed. The effect of the combination of oil heating and electric heating on the fuel consumption of Dualhybrid was investigated. The results show that the coupled lubricating system of Dualhybrid is beneficial to improve the fuel economy in cold start. The method of hybrid heating can provide a sufficient heating power of the cabin in the initial stage of cold start without declining the fuel economic performance significantly.

The start of combustion in a spark-ignited engine is highly dependent upon the conditions between the two spark plug electrodes at ignition. In addition to the air-to-fuel ratio in this gap, the gas flow is seen as most critical. In a combustion engine with a standard spark plug that protrudes into the combustion chamber, this gas flow is mainly dependent upon the tumble, swirl, or squish that is developed by the cylinder head and the piston movement. However, the air movement in the pre-chamber depends on the orientation of the orifices towards the main combustion chamber (MCC). This implies a less complex manipulation of local velocity in the electrode gap. This paper focuses on the effect of different pre-chamber designs on spark deflection by the inflowing gas. Therefore, a test rig was developed using the spark plug thread in the cylinder head of a motored engine.

Acoustics and vibrations are amongst the foremost indicators in perceiving the quality of drive units. Analyzing these factors is vital for improve the performances of electro-mechanical systems. This paper deals with the study of vibro-acoustic behavior concerning the drivetrain components using system modeling and Finite Element calculations. A generic simulation methodology within system modeling is proposed enabling the vibro-acoustic simulation of electro-mechanical drivetrains. Excitations for these systems mostly arise from the electric motor and mechanical gears. The paper initially depicts the system model for gear whining considering the associated nonlinearities of the mesh. The results obtained from the gear mesh submodel, together with the excitations resulting from the motor, aid in the comprehension of the forces at the bearings and of the vibrations at the housings.

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”).

The gradual global tightening of emission legislation for particulate matter emissions requires the development of new gasoline engine exhaust aftertreatment systems. For this reason, the development of gasoline direct injection engines aims at the reduction of particulate emissions by application of a Gasoline Particulate Filter (GPF). The regeneration temperature of GPF depend on soot reactivity towards oxidation and therefore on particle properties. In this study, the soot reactivity is correlated with nanostructural characteristics of primary gasoline particles as a function of specific engine injection parameters. The investigations on particle emissions were carried out on a turbocharged 4-cylinder GDI-engine that allows the variation of injection parameters. The emitted engine soot particles have been in-situ characterized towards their number and size distribution using an engine exhaust particle sizer (EEPS).

Service-oriented architectures (SOAs) are well-established solutions in the IT industry. Their use in the automotive domain is still on the way. Up to now, the automotive domain has taken advantage of service-oriented architectures only in the area of infotainment and not for systems with hard real-time requirements. However, applying SOA to such systems has just started but is missing suitable design and verification methodologies. In this context, we target to include the notion of model-based design to address fail-operational systems. As a result, a model-based approach for the development of fail-operational systems based on dynamic reconfiguration using a service-oriented architecture is illustrated. For the evaluation, we consider an example function of an automatically controlled braking system and analyze the reconfiguration time when the function fails.

Large Eddy Simulations (LES) and tracer-based Laser-Induced Fluorescence (LIF) measurements were performed to study the dynamics of fuel wall-films on the piston top of an optically accessible, four-valve pent-roof GDI research engine for a total of eight operating conditions. Starting from a reference point, the systematic variations include changes in engine speed (600; 1,200 and 2,000 RPM) and load (1000 and 500 mbar intake pressure); concerning the fuel path the Start Of Injection (SOI=360°, 390° and 420° CA after gas exchange TDC) as well as the injection pressure (10, 20 and 35 MPa) were varied. For each condition, 40 experimental images were acquired phase-locked at 10° CA intervals after SOI, showing the wall-film dynamics in terms of spatial extent, thickness and temperature.

Safety-critical embedded software has to satisfy stringent quality requirements. One such requirement, imposed by all contemporary safety standards, is that no critical run-time errors must occur. Runtime errors can be caused by undefined or unspecified behavior of the programming language; examples are buffer overflows or data races. They may cause erroneous or erratic behavior, induce system failures, and constitute security vulnerabilities. A sound static analyzer reports all such defects in the code, or proves their absence. Sound static program analysis is a verification technique recommended by ISO/FDIS 26262 for software unit verification and for the verification of software integration. In this article we propose an analysis methodology that has been implemented with the static analyzer Astrée. It supports quick turn-around times and gives highly precise whole-program results.