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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.

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 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.

Cooling is a critical factor for improving power density in electrical appliances, especially in integrated drives for mobile applications. However, the issue of distributed losses in electric machines can lead to hotspots and temperature gradients within the electric drive. Traditional cooling jackets use unidirectional flow without or with evenly distributed cooling structures. This often aggravates the issue of hotspots, resulting in thermal derating and thus limiting the operation range. As well, a non-demand oriented distribution of cooling structures leads to unnecessary pressure losses. This problem is addressed with a newly elaborated method for distributing cooling elements, i.e., pin fins with varying density distribution inside the cooling channel. Results from previous work, numerical simulations, and measurement data from a planar test bench are used. The approach segments the cooling channel by using a loss profile.

The functional extension of vibration reduction in continuous slip operation in modern wet-running clutch systems under dynamic excitation is being investigated by the authors. Therefore, a mixed virtual-physical validation environment has been developed using the IPEK X-in-the-Loop Framework and will be presented as part of this contribution. Thus, the validation environment enables the consideration of interactions with the residual systems, especially the residual drive train. In this contribution, the validation environment is used to investigate whether and how an attribute variation in the subsystem, respectively the tribological system, can provide improved vibration reduction without increased power dissipation due to damping but other reducing mechanisms favored. The results show significant differences in vibration reduction behavior whereas the power losses are almost the same between the investigated tribological system.

The increasing adoption of battery electric vehicles (BEVs), driven by the EU's target of no internal combustion engine vehicles from 2035 onwards, is driving significant changes in the automotive industry. However, the high degree of electrification and the unique low-speed acceleration behavior of BEVs therefore lead to new challenges. Measuring the drivetrain power and efficiency in a reproducible way and obtaining meaningful results is one of the challenges. To address this challenge, a novel test method is developed that offers a simple and preferably modification-free approach to drivetrain power and efficiency measurements for BEVs, allowing for efficient and reproducible testing. Different paths for determining the drivetrain power with varied measurement efforts are presented and evaluated. The test method is designed to provide reliable and accurate results for BEVs.

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.

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

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.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

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.

Vibration testing is often carried out for automotive components to meet guidelines based on their operational environments. This is an iterative process wherein design changes may need to be made depending on an intermediate model’s dynamic behavior. Predicting the behavior based on modifications in boundary conditions of a well-defined numerical model imparts practical insights to the component’s responses. To this end, application of a general method using experimental free-free condition frequency response functions of a structure is discussed in the presented work. The procedure is shown to be useful for prediction of responses when kinematic boundary conditions are applied, without the need for an actual measurement. This approach is outlined in the paper and is applied to datasets where dynamic modifications are made at multiple boundary nodes.

A gray-box optimization procedure based on evolutionary algorithms for the initial design of a suspension concept for four wheel independently driven and steered vehicles is developed. With the presented optimization method, the energy consumption together with state of the art knowledge about the parametrization and design of vehicle suspension systems leads to an optimization setup closely to real world requirements while the vehicle’s topology is exploited. To this, the modelling presented in [1] is considered as a geometric suspension model. Furthermore, to take advantage of the potential of such vehicles, an autonomous closed-loop setup with integrated motion control is utilized. During the optimization, the chassis parameters with the most impact on energy consumption and driving dynamics, namely camber, caster, scrub radius and the steering axis inclination (SAI) depending on a varying caster angle and SAI in relation to the steering angle, will be focused.

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.