275003 research outputs found
Sort by
Scalability and durability, or: Is modular the new durable? The case of smartphones
No full text20123
Realistic parameters for dynamic simulation of composite cables using a damped Cosserat rod model
No full text391399Digital prototyping presents one of today’s biggest chances in boosting efficiency of product development in automotive industry. Handling flexible parts, such as cables and hoses, is a big challenge in this context. The software IPS Cable Simulation addresses this topic and solves the problem for a wide field of applications. To obtain reliable simulation results, a basic set of parameters describing the effective mechanical properties of the flexible parts is an essential part of the model. The development of the MeSOMICS measurement machine represents a practical solution to this need for experimental data. Additional challenges are related to dynamic simulations of vehicles in operation mode. To solve these, we introduced the durability and dynamics module as an extension to the established software. This leads to an extended set of required parameters. In order to obtain these dynamic parameters, two different experimental setups have been realized. The experiments investigate damped torsional and bending oscillations, and yield parameters that can conveniently be treated as effective viscous properties within the framework of our software
100 kHz water window soft X-ray high-order harmonic generation through pulse self-compression in an antiresonant hollow-core fiber
No full textMacro Economic and Ecological Aspects of Cell Production in Europe 2030
No full textFactory announcements for battery production are increasing in number as European demand for battery cells grows. Using a Monte Carlo simulation (108 projects as of October 2025) with risk factors for individual projects, the predicted theoretical production capacity for lithium-ion batteries in Europe will rise to 1.1-1.5 TWh, enabling a real production output of 0.8-1.0 TWh by 2030. Our analysis suggests necessary cumulative investments in battery cell gigafactories of 36–139 billion euros by 2030. The industrial output of LIB cells in 2030 will have a value of 35-99 billion euros, of which the market size of battery production is around 6-17 billion euros. Furthermore, 43,000-174,000 direct jobs could be created, with the strongest impacts seen in Eastern Europe by the end of the decade. The raw material demand generated by this industry rises steeply: lithium will rise from 14 kt in 2025 to 47-133 kt, and nickel from 83 kt to 226-640 kt by 2030, implying continued import dependencies. The energy demand of European cell production will be 8.4-19.9 TWh in 2030. Furthermore, CO2 emissions of cell production will be 1.6 to 3.7 Mt CO2-eq in 2030. The volume of production scrap is estimated at 160-398 kt in 2030, creating near-term demand for recycling capacities.111
Development of robust sensor packages for autonomous underwater vehicles
No full text470475New generations of robots are designed to support humans with a variety of partially or fully automated services. Such flexible and mobile service robots cooperate with humans or even act completely independent. To achieve this, it is necessary to significantly improve their capabilities in terms of environment perception, data processing and movement. At the same time, they must meet the highest standards of reliability and safety. Innovative electronics enable the necessary improvements and thus appropriate robot behavior. The aim of the Bionic RoboSkin project is to enhance the possibilities of a robot platform that is capable of autonomously navigating its respective environment by means of a flexible bionic sensor skin. The sensor platform is an autonomous underwater vehicle [AUV] that is based on the bionic principles of a Manta Ray [1, 2, 3]. The newly developed sensor skin consists of a textile composite as a carrier for sensor elements and provides moisture-resistant electrical connections for energy supply and communication. The integrated sensor modules enable both the detection of touch and approach and the exploration of the environment. The functionality of the sensor skin is targeting two service robotics applications: autonomous surveying of underwater structures (e.g. inspection of pipelines) and semi-autonomous geo-exploration in difficult-to-access areas (e.g. monitoring in tunnel construction). As a result, the paper presents the concept of a modular packaging platform for the use in a harsh marine environment. The technologies used for the miniaturization of the sensor module by PCB embedding and for outer housing development will be discussed in detail and a strong focus is put on packaging material properties in sub-marine conditions
How phase-out policies strengthen Europe's automotive industry
No full textDie Europäische Union hat die Automobilindustrie verpflichtet, den Verkauf von neuen Benzin- und Dieselfahrzeugen bis 2035 schrittweise einzustellen. In der öffentlichen Debatte wird vermehrt die Befürchtung geäußert, dass diese ambitionierten CO2- Flottengrenzwerte für Neuwagen schlecht fürs Geschäft sind. Besonders in Deutschland, das stark von seiner Automobilindustrie abhängt, werden entsprechende Sorgen immer häufiger artikuliert. Jüngste Untersuchungen zeigen jedoch, dass eine Kehrtwende beim Ausstieg aus dem Verbrennungsmotor der angeschlagenen europäischen Automobilindustrie mehr schaden als nützen würde. Denn die Zielvorgaben helfen den Unternehmen, im globalen Innovationswettlauf zu bestehen. In diesem Policy Brief wird erläutert, warum eine glaubwürdige politische Ausstiegsstrategie die europäische Automobilindustrie stärkt, anstatt sie zu schwächen. Darüber hinaus werden zusätzliche Maßnahmen vorgestellt, die die Politik ergreifen könnte, um die internationale Wettbewerbsfähigkeit der europäischen Automobilindustrie zu stärken
Modelling Photon-pair Generation in Nanoresonators Using Quasinormal Mode Expansions
No full textWe model SPDC in dielectric nanoresonators based on quasinormal modes (QNMs). Using QNMs, the process reduces to a few interacting modes, providing intuition and enabling the design of nanoscale SPDC sources with complex functionalities
Towards the development of the cybersecurity concept according to ISO/SAE 21434 using model-based systems engineering
No full text486491Cyber-physical systems (CPS), such as autonomous vehicles, are intelligent and networked. Close collaboration between stakeholders from different disciplines is necessary right from the start of development. In the automotive sector in particular, the collaboration of the car manufacturer extends to several suppliers. The increasing complexity in the design of such CPSs makes interdisciplinary and cross-company collaboration more difficult. Here, requirements specifications serve as a support for communication. A lack of overall understanding of such CPSs and their numerous interfaces jeopardizes the assurance of safety-relevant security. ISO/SAE 21434, which applies to the automotive industry, requires the creation of a cybersecurity concept at the beginning of the product development process. The problem is that ISO/SAE 21434 only prescribes WHAT must be done, but does not define HOW this is supposed to be done methodically.Existing methods are not applicable to the concept phase without extensive tailoring, according to the challenges I identified in this paper and the literature review I conducted. Furthermore, I present four papers I have written and four papers I plan to write, which serve as building blocks for the required overall method. Finally, I explain how I plan to evaluate my approach
FeatInv: Spatially resolved mapping from feature space to input space using conditional diffusion models
No full textInternal representations are crucial for understanding deep neural networks, such as their properties and reasoning patterns, but remain difficult to interpret. While mapping from feature space to input space aids in interpreting the former, existing approaches often rely on crude approximations. We propose using a conditional diffusion model-a pretrained high-fidelity diffusion model conditioned on spatially resolved feature maps-to learn such a mapping in a probabilistic manner. We demonstrate the feasibility of this approach across various pretrained image classifiers from CNNs to ViTs, showing excellent reconstruction capabilities. Through qualitative comparisons and robustness analysis, we validate our method and showcase possible applications, such as the visualization of concept steering in input space or investigations of the composite nature of the feature space. This approach has broad potential for improving feature space understanding in computer vision models.Online Firs
Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility
No full textThe automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehicles’ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicle’s technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehicles’ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.