TY - CHAP A1 - Eder, Lukas A1 - Löw, Jakob A1 - Hof, Hans-Joachim T1 - Charging Communication Sniffing and Man-in-the-Middle Attacks T2 - Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems N2 - In recent years an increasing amount of electric vehicle fast charging stations have been built to meet the growing demand from rising electric vehicle numbers. The standard for fast charging communication in europe is ISO 15118. In theory the standard includes security controls for authentication and transport encryption. In reality difficulties with implementing those security controls as well as insecure design within the standard lead to multiple possible attack vectors compromising the confidentiality and authenticity of charging communication sessions. The goal of this research is to present different approaches towards performing sniffing and man-in-the-middle attacks against charging communication. We also provide a novel approach, which does not rely on race conditions and thus is more reliable than previous approaches. UR - ttps://doi.org/10.1145/3679240.3734648 Y1 - 2025 UR - ttps://doi.org/10.1145/3679240.3734648 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60183 SN - 979-8-4007-1125-1 SP - 799 EP - 804 PB - ACM CY - New York ER - TY - JOUR A1 - Morales Torricos, Pablo A1 - Berg, Sascha A1 - Figgemeier, Egbert A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - The important role of lithiation-induced pressure change on apparent aging of lithium-ion batteries during accelerated cyclic aging tests JF - Journal of Energy Storage N2 - In assessing the lifespan of lithium-ion batteries in laboratory conditions, the measured capacity declines during accelerated cyclic aging tests but increases when the cells are left idle. This recoverable capacity loss, known in literature as apparent aging, results from an inhomogeneous lithium distribution in the anode appearing in dV/dQ and capacity difference analysis. This study explores the origin of the apparent aging by correlating lithium distribution in the anode and recoverable capacity loss, with the lithiation induced pressure change and generated electrolyte motion during cycling. To this end, we compressed five commercial pouch lithium-ion cells (NMC/Gr) with holder stiffnesses ranging from 0.9 to 15.4 MPa/mm and offset pressure from 289 to 681 kPa and subjected them to continuous cyclic aging tests. While offset pressure had no significant impact, we observed, that holder stiffnesses over 3.3 MPa/mm induces an apparent capacity loss, which is recoverable by 35 % during a resting phase. The root cause is the so-called electrolyte motion induced salt inhomogeneity (EMSI), driven by continuous high current cycling and electrolyte motion, which is intensified by higher holder stiffness but not by offset pressure. These insights are crucial for improving the accuracy of accelerated aging tests and enhancing battery lifespan predictions. UR - https://doi.org/10.1016/j.est.2025.117323 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.117323 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60173 SN - 2352-1538 VL - 2025 IS - 131, Part A PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Devillers, Hugo A1 - Kurtenacker, Matthias A1 - Membarth, Richard A1 - Lemme, Stefan A1 - Kenzel, Michael A1 - Yazici, Ömercan A1 - Slusallek, Philipp ED - Knoll, Aaron ED - Peters, Christoph T1 - No More Shading Languages: Compiling C++ to Vulkan Shaders T2 - High-Performance Graphics - Symposium Papers N2 - Graphics APIs have traditionally relied on shading languages, however, these languages have a number of fundamental defects and limitations. By contrast, GPU compute platforms offer powerful, feature-rich languages suitable for heterogeneous compute. We propose reframing shading languages as embedded domain-specific languages, layered on top of a more general language like C++, doing away with traditional limitations on pointers, functions, and recursion, to the benefit of programmability. This represents a significant compilation challenge because the limitations of shaders are reflected in their lower-level representations. We present the Vcc compiler, which allows conventional C and C++ code to run as Vulkan shaders. Our compiler is complemented by a simple shading library and exposes GPU particulars as intrinsics and annotations. We evaluate the performance of our compiler using a selection of benchmarks, including a real-time path tracer, achieving competitive performance compared to their native CUDA counterparts. UR - https://doi.org/10.2312/hpg.20251167 Y1 - 2025 UR - https://doi.org/10.2312/hpg.20251167 UR - https://diglib.eg.org/handle/10.2312/hpg20251167 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60151 SN - 978-3-03868-291-2 PB - The Eurographics Association CY - Goslar ER - TY - CHAP A1 - Wildgrube, Fabian A1 - Ehrett, Pete A1 - Trojahn, Paul A1 - Membarth, Richard A1 - Beckmann, Bradford A1 - Baumeister, Dominik A1 - Chajdas, Matthäus T1 - GPUs All Grown-Up: Fully Device-Driven SpMV Using GPU Work Graphs T2 - ISCA ´25: Proceedings of the 52nd Annual International Symposium on Computer Architecture N2 - Sparse matrix-vector multiplication (SpMV) is a key operation across high-performance computing, graph analytics, and many more applications. In these applications, the matrix characteristics, notably non-zero elements per row, can vary widely and impact which algorithm performs best. Thus, Graphics Processing Unit (GPU) SpMV algorithms often rely on costly preprocessing to determine what per-row algorithm to select to achieve high performance. In this work we combine SpMV preprocessing and the subsequent per-row processing on the GPU by leveraging the novel “Work Graphs” GPU programming model—initially designed for graphics applications—for dynamic on-device self-scheduling. Work Graphs allow for fine-grain dataflow execution of individual workgroups using emerging hardware and firmware support. As soon as preprocessing has generated sufficient work, workgroups of individual processing kernels are self-scheduled and executed, interleaved with those of other kernels. This improves cache locality and eliminates host interaction altogether. Across a suite of 59 sparse matrices, the best of various novel Work Graphs SpMV implementations outperforms state-of-the-art rocSPARSE “LRB” for a single SpMV by up to 7.19 × (mean: 3.35 ×, SD: 1.89). Furthermore, it achieves much more stable performance across various sparsity patterns than the rocSPARSE CSR-General algorithm, and even beats the advanced rocSPARSE CSR-Adaptive algorithm for up to 92 consecutive SpMV calculations. In addition, compared to rocSPARSE LRB, it reduces code complexity by 75%. Its memory footprint for supporting data structures is a fixed ∼ 25 MiB independent of matrix size, compared to rocSPARSE LRB’s data structures that scale with matrix size to hundreds of megabytes. Overall, this work showcases the performance potential of emerging dynamic on-device scheduling techniques for GPU compute applications. UR - https://doi.org/10.1145/3695053.3731060 Y1 - 2025 UR - https://doi.org/10.1145/3695053.3731060 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58868 SN - 979-8-4007-1261-6 SP - 1777 EP - 1791 PB - ACM CY - New York ER - TY - JOUR A1 - Gaedicke, Sonja A1 - Haubold, Rebekka A1 - Klages, Anna-Lisa A1 - Rhein, Christian A1 - Schwertel, Tamara A1 - Tietje, Olaf T1 - Conference Report: Mapping Situational Analysis—An International Conference JF - Forum Qualitative Sozialforschung / Forum: Qualitative Social Research (FQS) N2 - In this conference report we provide insights into some of the key topics presented at the first international conference on situational analysis in Germany, held in November 2024 in Magdeburg. Central issues discussed include collaborations and feminist perspectives in practice for power-sensitive knowledge production, nonhumans and how they can be included in situational analysis through all types of mappings as well as methodical and methodological questions regarding mapping processes, interdisciplinary mapping, and the conceptualization of space in and through situational analysis. Adele CLARKE and her work were honored and celebrated at the conference. UR - https://doi.org/10.17169/fqs-26.2.4424 Y1 - 2025 UR - https://doi.org/10.17169/fqs-26.2.4424 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59992 SN - 1438-5627 VL - 26 IS - 2 PB - Freie Universität Berlin CY - Berlin ER - TY - CHAP A1 - Rauscher, Andreas A1 - Stenzel, Peer A1 - Endisch, Christian T1 - Investigation of Factors Influencing the End-of-Line Partial Discharge Testing of Electrical Machines T2 - 2025 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD) UR - https://doi.org/10.1109/WEMDCD61816.2025.11014117 Y1 - 2025 UR - https://doi.org/10.1109/WEMDCD61816.2025.11014117 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Sequeira, Gerald Joy A1 - Inderst, Maximilian A1 - Xhiku, Redjon A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - Sigmoid-Based Method for Longitudinal Crash Pulse Prediction in Intelligent Vehicles T2 - 2024 IEEE International Conference on Vehicular Electronics and Safety (ICVES) UR - https://doi.org/10.1109/ICVES61986.2024.10927899 Y1 - 2025 UR - https://doi.org/10.1109/ICVES61986.2024.10927899 SN - 979-8-3503-8727-8 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Lobo, Silas A1 - Festag, Andreas A1 - Facchi, Christian T1 - Adaptive Message Prioritization: How to Prioritize VRU Awareness Messages in a Congested V2X Network T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10919704 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10919704 SN - 979-8-3315-0592-9 SP - 423 EP - 430 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Wachtel Granado, Diogo A1 - Tasabat, Sinan A1 - Rothmeier, Thomas A1 - Cristófoli Duarte Silva, Letícia A1 - Huber, Werner T1 - Exploring Synthetic Radar Data and Deep Learning for Road User Classification in Autonomous Vehicles T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10919565 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10919565 SN - 979-8-3315-0592-9 SP - 2021 EP - 2026 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Wachtel Granado, Diogo A1 - Trevisol, Heitor Derder A1 - Rothmeier, Thomas A1 - Nassu, Bogdan Tomoyuki A1 - Huber, Werner T1 - Navigating on Adverse Weather: Enhancing LiDAR-Based Detection with the DBSPRY Dataset T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10920224 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10920224 SN - 979-8-3315-0592-9 SP - 4034 EP - 4039 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Brühl, Tim A1 - Shanmuganathan, Aravind Kumar A1 - Ewecker, Lukas A1 - Schwager, Robin A1 - Sohn, Tin Stribor A1 - Vaculin, Ondrej A1 - Hohmann, Sören T1 - Consideration of Safety Aspects in a Camera-Aided, Radar-Based Free Space Detection T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10920194 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10920194 SN - 979-8-3315-0592-9 SP - 3997 EP - 4004 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Rothmeier, Thomas A1 - Dal Vesco Hoger, Mayara A1 - Nassu, Bogdan Tomoyuki A1 - Huber, Werner A1 - Knoll, Alois T1 - Out of the Box: Weather Augmentation for Enhanced Detection in Bad Visibility Conditions T2 - 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC58415.2024.10919529 Y1 - 2025 UR - https://doi.org/10.1109/ITSC58415.2024.10919529 SN - 979-8-3315-0592-9 SP - 1410 EP - 1417 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Bilal, Mühenad A1 - Podishetti, Ranadheer A1 - Großmann, Daniel A1 - Bregulla, Markus T1 - Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System JF - IEEE Access N2 - In this study, we introduce the ToolSurface-144 dataset, which is presented here for the first time. It comprises four subsets – Full R, Full S, Top R, and Top S – each containing 144 tool classes captured under varying illumination conditions and fields of view. A newly developed, patented imaging approach was employed to acquire the data. It is compared with conventional diffuse ring illumination to assess its effectiveness in evaluating state-of-the-art convolutional neural networks. This enabled a more targeted investigation of the role of global shape characteristics such as silhouettes versus localized features like the tool face, cutting edges, and delicate geometrical structures under different training strategies. In this study, we evaluate six state-of-the-art convolutional neural networks—AlexNet, DenseNet161, EfficientNet-B0, ResNet152, ResNet50, and VGG16—using three training strategies: fine-tuning, freezing of pre-trained layers, and training from scratch. The results show that EfficientNet-B0 consistently achieved the highest classification accuracy in nearly all experiments and data sets. Especially using the fine-tuning training strategy, the model achieved 99% accuracy in tool classification. ResNet50 benefited greatly from fine-tuning and freezing, achieving a significant increase in performance compared to training from scratch. In contrast, ResNet152, AlexNet, and VGG16 consistently showed poor classification performance, indicating difficulties regarding learning and generalisation. The results show that diffuse illumination and complete tool views provide the best classification conditions, while restricted image sections with homogeneous illumination negatively affect model performance. Among the evaluated training strategies, fine-tuning proved the most efficient training method for developing CNN models for tool classification. UR - https://doi.org/10.1109/ACCESS.2025.3574785 Y1 - 2025 UR - https://doi.org/10.1109/ACCESS.2025.3574785 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59669 SN - 2169-3536 VL - 13 SP - 96400 EP - 96422 PB - IEEE CY - New York ER - TY - JOUR A1 - Schreiber, Markus A1 - Lin, Yilei A1 - Sommer, Alessandro A1 - Wassiliadis, Nikolaos A1 - Morales Torricos, Pablo A1 - Rogge, Marcel A1 - Lewerenz, Meinert A1 - Grosu, Cristina A1 - Endisch, Christian A1 - Jossen, Andreas A1 - Lienkamp, Markus T1 - Apparent vs. true battery aging: Impact of various load characteristics on accelerated aging tests JF - Journal of Energy Storage N2 - Vehicle applications involve highly dynamic and variable operating conditions. These result from changing driving profiles and diverse driving behaviors. To accelerate battery aging tests, experiments are often based on constant load cycles. While efficient, this approach distorts the natural degradation behavior of the cells. This study compares cell aging under real-world and laboratory load conditions. For this purpose, we compare realistic driving profiles measured in a test vehicle in the field with synthetic constant power cycles. Average discharge power and charging sequences are kept identical for comparability. Results show that constant power cycles cause stronger cell aging than dynamic loads. Differential voltage analysis indicates more lithium inventory loss and active material loss at the negative electrode under static loads. Static loading also leads to strong inhomogeneity in the negative electrode and altered charge transfer and diffusion kinetics, as shown by impedance data. After 15 months of rest, the cells recovered up to 52 of lost capacity and 66 of the resistance increase. Impedance assessment and differential voltage analysis confirm the recovery and rehomogenization of the negative electrode. These findings show that conventional accelerated tests are strongly influenced by relaxation and load dynamics. As a result, their applicability to specific use cases, such as automotive applications, is strongly limited . Therefore, andraditional test strategies require reconsideration and redesign. UR - https://doi.org/10.1016/j.est.2025.116924 Y1 - 2025 UR - https://doi.org/10.1016/j.est.2025.116924 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59653 SN - 2352-1538 VL - 2025 IS - 127 PB - Elsevier CY - Amsterdam ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model N2 - Extended Object Tracking (EOT) exploits the high resolution of modern sensors for detailed environmental perception. Combined with decentralized fusion, it contributes to a more scalable and robust perception system. This paper investigates the decentralized fusion of 3D EOT using a B-spline curve based model. The spline curve is used to represent the side-view profile, which is then extruded with a width to form a 3D shape. We use covariance intersection (CI) for the decentralized fusion and discuss the challenge of applying it to EOT. We further evaluate the tracking result of the decentralized fusion with simulated and real datasets of traffic scenarios. We show that the CI-based fusion can significantly improve the tracking performance for sensors with unfavorable perspective. UR - https://doi.org/10.48550/arXiv.2504.18708 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.18708 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59648 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Wan, Lei A1 - Zhao, Jianxin A1 - Wiedholz, Andreas A1 - Bied, Manuel A1 - Martinez de Lucena, Mateus A1 - Jagtap, Abhishek Dinkar A1 - Festag, Andreas A1 - Fröhlich, Antônio A1 - Keen, Hannan Ejaz A1 - Vinel, Alexey T1 - A Systematic Literature Review on Vehicular Collaborative Perception – A Computer Vision Perspective UR - https://doi.org/10.48550/arXiv.2504.04631 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.04631 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Kalyanasundaram, Abinav A1 - Chandra Sekaran, Karthikeyan A1 - Stäuber, Philipp A1 - Lange, Michael A1 - Utschick, Wolfgang A1 - Botsch, Michael T1 - Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation N2 - Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor system are often constrained by cost. For instance, measuring critical quantities such as the Vehicle Sideslip Angle (VSA) poses significant commercial challenges using current optical sensors. This paper addresses these limitations by focusing on the development of high-performance virtual sensors to enhance vehicle state estimation for active safety. The proposed Uncertainty-Aware Hybrid Learning (UAHL) architecture integrates a machine learning model with vehicle motion models to estimate VSA directly from onboard sensor data. A key aspect of the UAHL architecture is its focus on uncertainty quantification for individual model estimates and hybrid fusion. These mechanisms enable the dynamic weighting of uncertainty-aware predictions from machine learning and vehicle motion models to produce accurate and reliable hybrid VSA estimates. This work also presents a novel dataset named Real-world Vehicle State Estimation Dataset (ReV-StED), comprising synchronized measurements from advanced vehicle dynamic sensors. The experimental results demonstrate the superior performance of the proposed method for VSA estimation, highlighting UAHL as a promising architecture for advancing virtual sensors and enhancing active safety in autonomous vehicles. UR - https://doi.org/10.48550/arXiv.2504.06105 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.06105 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59578 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Himmels, Chantal A1 - Buchner, Claudia A1 - Schmitz, Jan A1 - Parduzi, Arben A1 - Riener, Andreas T1 - Validity of Driver Assistance Systems in Driving Simulators: A Comparative Study of Real-World Driving and Two Simulator Environments JF - International Journal of Human–Computer Interaction UR - https://doi.org/10.1080/10447318.2025.2495120 Y1 - 2025 UR - https://doi.org/10.1080/10447318.2025.2495120 SN - 1044-7318 VL - 41 IS - 23 SP - 15197 EP - 15214 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Knollmeyer, Simon A1 - Caymazer, Oğuz A1 - Großmann, Daniel T1 - Document GraphRAG: Knowledge Graph Enhanced Retrieval Augmented Generation for Document Question Answering Within the Manufacturing Domain JF - Electronics N2 - Retrieval-Augmented Generation (RAG) systems have shown significant potential for domain-specific Question Answering (QA) tasks, although persistent challenges in retrieval precision and context selection continue to hinder their effectiveness. This study introduces Document Graph RAG (GraphRAG), a novel framework that bolsters retrieval robustness and enhances answer generation by incorporating Knowledge Graphs (KGs) built upon a document’s intrinsic structure into the RAG pipeline. Through the application of the Design Science Research methodology, we systematically design, implement, and evaluate GraphRAG, leveraging graph-based document structuring and a keyword-based semantic linking mechanism to improve retrieval quality. The evaluation, conducted on well-established datasets including SQuAD, HotpotQA, and a newly developed manufacturing dataset, demonstrates consistent performance gains over a naive RAG baseline across both retrieval and generation metrics. The results indicate that GraphRAG improves Context Relevance metrics, with task-dependent optimizations for chunk size, keyword density, and top-k retrieval further enhancing performance. Notably, multi-hop questions benefit most from GraphRAG’s structured retrieval strategy, highlighting its advantages in complex reasoning tasks. UR - https://doi.org/10.3390/electronics14112102 Y1 - 2025 UR - https://doi.org/10.3390/electronics14112102 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59524 SN - 2079-9292 VL - 14 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Greßhake, Lukas A1 - Bosch, Stephan A1 - Tutunaru, Robin A1 - Holzhammer, Uwe T1 - What do you mean by ‘(un-)suitable’? Analysing the diversity of social acceptance towards the deployment of renewable energies in different landscapes JF - Journal of Land Use Science N2 - Local energy transitions are shaped by diverse stakeholder perspectives on land use, reflecting competing values, knowledge systems, and political views. This study applies the landscape services framework to systematically assess renewable energy (RE) suitability across different landscapes, capturing both ecological and socio-cultural dimensions. Through stakeholder surveys in two German regions and statistical comparative analysis, we reveal how suitability perceptions vary significantly: (1) between stakeholder groups (e.g. conservationists vs. developers), (2) across regions (industrial vs. ecological-cultural contexts), and (3) even within groups sharing similar objectives. Key findings show strong preference for RE development in industrial and agricultural zones (‘acceptance corridors’) and opposition in ecologically sensitive areas, though with notable regional exceptions. The landscape services approach proves effective in mapping these conflicts and consensus areas, providing actionable insights for spatially sensitive RE planning. Our results underscore the need to complement technical siting criteria with structured assessments of social landscape values to enable just and locally accepted energy transitions. UR - https://doi.org/10.1080/1747423X.2025.2499280 Y1 - 2025 UR - https://doi.org/10.1080/1747423X.2025.2499280 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59512 SN - 1747-4248 SN - 1747-423X VL - 20 IS - 1 SP - 117 EP - 150 PB - Taylor & Francis CY - London ER -