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 - JOUR A1 - Hahn, Christoph A1 - Bednarz, Martin T1 - Economics of Polymer Electrolyte Membrane Fuel Cells JF - Tehnički glasnik N2 - Hydrogen is considered a key component of the renewable energy transition for the 21st century, with potential applications using fuel cells in the transportation sector, decentralized heating systems, and energy storage. However, the conversion from fossil fuels to hydrogen implies comprehensive research to address technological and socio economic challenges, enabling its widespread adoption. This paper discusses the economics of fuel cells. A cost analysis of the polymer electrolyte membrane fuel cells (PEMFC) is performed, and current market data and developments are presented. UR - https://doi.org/10.31803/tg-20250303145130 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250303145130 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59496 SN - 1848-5588 VL - 19 IS - si1 SP - 124 EP - 129 PB - University North CY - Koprivnica 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 - Behret, Valentino A1 - Kushtanova, Regina A1 - Fadl, Islam A1 - Weber, Simon A1 - Helmer, Thomas A1 - Palme, Frank ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Sensor Calibration and Data Analysis of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 2) N2 - Autonomous driving sensors face significant challenges under adverse weather conditions such as fog and rain, which can seriously degrade their performance and reliability. Existing datasets often lack the reproducible and measurable data needed to adequately quantify these effects. To address this gap, a new multimodal dataset (MuFoRa) has been collected under controlled adverse weather conditions at the CARISSMA facility, using a stereo camera and two solid-state LiDAR sensors. This dataset is used to quantitatively assess sensor degradation by measuring the entropy for images and the number of inliers for point clouds on a spherical target. These metrics are used to evaluate the impact on performance under varying conditions of fog (5 to 150 m visibility) and rain (20 to 100 mm/h intensity) at different distances (5 to 50 m). Additionally, two calibration target detection approaches - Deep-learning and Hough-based - are evaluated to achieve accurate sensor alignment. The contributions include the introduction of a new dataset focused on fog and rain, the evaluation of sensor degradation, and an improved calibration approach. This dataset is intended to support the development of more robust sensor fusion and object detection algorithms for autonomous driving. UR - https://doi.org/10.5220/0013310400003912 Y1 - 2025 UR - https://doi.org/10.5220/0013310400003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58088 SN - 978-989-758-728-3 SP - 622 EP - 631 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Kedilioglu, Oguz A1 - Nova, Tasnim Tabassum A1 - Landesberger, Martin A1 - Wang, Lijiu A1 - Hofmann, Michael A1 - Franke, Jörg A1 - Reitelshöfer, Sebastian ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - PrIcosa: High-Precision 3D Camera Calibration with Non-Overlapping Field of Views T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 2) N2 - Multi-camera systems are being used more and more frequently, from autonomous mobile robots to intelligent visual servoing cells. Determining the pose of the cameras to each other very accurately is essential for many applications. However, choosing the most suitable calibration object geometry and utilizing it as effectively as possible still remains challenging. Disadvantageous geometries provide only subpar datasets, increasing the need for a larger dataset and decreasing the accuracy of the calibration results. Moreover, an unrefined calibration method can lead to worse accuracies even with a good dataset. Here, we introduce a probabilistic method to increase the accuracy of 3D camera calibration. Furthermore, we analyze the effects of the calibration object geometry on the data properties and the resulting calibration accuracy for the geometries cube and icosahedron. The source code for this project is available at GitHub (Nova, 2024). UR - https://doi.org/10.5220/0013088700003912 Y1 - 2025 UR - https://doi.org/10.5220/0013088700003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58120 SN - 978-989-758-728-3 SP - 801 EP - 809 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Fadl, Islam A1 - Schön, Torsten A1 - Behret, Valentino A1 - Brandmeier, Thomas A1 - Palme, Frank A1 - Helmer, Thomas ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Environment Setup and Model Benchmark of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 3) N2 - Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, asse ssing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quantitative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain. UR - https://doi.org/10.5220/0013307900003912 Y1 - 2025 UR - https://doi.org/10.5220/0013307900003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58070 SN - 978-989-758-728-3 SP - 729 EP - 737 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Bayerl, Dominik A1 - Hutzelmann, Thomas A1 - Hof, Hans-Joachim T1 - Efficient Cross-Architecture Binary Function Embeddings through Knowledge Distillation T2 - Proceedings of the 11th ACM Cyber-Physical System Security Workshop N2 - Deep learning has recently been shown to be effective in various tasks related to static binary analysis. One important analysis task is the binary function similarity problem: Given the binary code of two functions compiled with different compilers, different settings, and different processor architectures, the goal is to decide whether the functions are semantically equivalent (i.e. "similar") or not. This problem has numerous applications for embedded systems, for example plagiarism detection, validation of compliance restrictions with usable software licenses, more efficient reverse engineering of existing binary codebases, or vulnerability scanning by detecting known vulnerable functions. In this paper, we propose a novel training scheme for the popular transformer neural network architecture to learn function embeddings directly from instruction listings. Unlike existing approaches, our solution explicitly considers the cross-architecture scenario: we propose a training method to adapt the model to different instruction set architectures (ISA) without having to train a new model from scratch, which allows the model to also be used efficiently for embedded systems, where there are a variety of different processor architectures. We show that our solution achieves a similarity classification accuracy of 89.6% on a dataset consisting of several real-world open source software projects. Finally, we conduct extensive experiments to demonstrate the effectiveness of knowledge distillation in increasing the computational efficiency of the embedding model. We demonstrate a reduction in the number of parameters from 87M to 23M, while still maintaining a classification accuracy of 87.8%. Our code and artifacts are available as open source. UR - https://doi.org/10.1145/3709017.3737709 Y1 - 2025 UR - https://doi.org/10.1145/3709017.3737709 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61584 SN - 979-8-4007-1413-9 SP - 43 EP - 51 PB - ACM CY - New York ER - TY - JOUR A1 - Weller, Julian A1 - Nalavade, Sumit A1 - Gmelch, Oliver A1 - Migenda, Nico A1 - Heuwinkel, Tim A1 - Dumitrescu, Roman T1 - Advanced Analytics in Smart Factories: Towards an actionable Taxonomy for Prescriptive Analytics Use Cases JF - Procedia CIRP N2 - Prescriptive analytics use cases support in the decision-making process and focus on providing actionable guidance (e.g. in the smart factory) based on a set of problems and possible solutions. Smart factories represent the core of Industry 4.0 and can greatly benefit from the implementation of advanced analytics use cases. Prescriptive analytics enables operational excellence in smart factories by providing actionable insights and decisions to (autonomously) steer and govern areas of a factory. Still, a widespread adoption of principles of prescriptive analytics is not reached, due to the complexity and interconnectivity of different use cases. Additionally, a lack of methodological support for developing prescriptive analytics use cases is observed. We support the adoption and ideation of prescriptive analytics use cases by providing a taxonomy for prescriptive analytics use cases in smart factories for researchers. To make the findings from the taxonomy actionable, we develop a concept on how to transform existing analytics use cases or use case ideas into prescriptive analytics use cases to support practitioners. We focus on the transformation of existing analytics use cases into prescriptive analytics use cases to lower the barrier to entry for the development of prescriptive use cases. The findings are based on the taxonomy development method by Nickerson. Our evaluation is supported by expert interviews as well as focus groups. UR - https://doi.org/10.1016/j.procir.2025.03.016 Y1 - 2025 UR - https://doi.org/10.1016/j.procir.2025.03.016 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61634 SN - 2212-8271 VL - 2025 IS - 134 SP - 229 EP - 234 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Rosbach, Emely A1 - Ammeling, Jonas A1 - Krügel, Sebastian A1 - Kießig, Angelika A1 - Fritz, Alexis A1 - Ganz, Jonathan A1 - Puget, Chloé A1 - Donovan, Taryn A1 - Klang, Andrea A1 - Köller, Maximilian C. A1 - Bolfa, Pompei A1 - Tecilla, Marco A1 - Denk, Daniela A1 - Kiupel, Matti A1 - Paraschou, Georgios A1 - Kok, Mun Keong A1 - Haake, Alexander F. H. A1 - de Krijger, Ronald R. A1 - Sonnen, Andreas F.-P. A1 - Kasantikul, Tanit A1 - Dorrestein, Gerry M. A1 - Smedley, Rebecca C. A1 - Stathonikos, Nikolas A1 - Uhl, Matthias A1 - Bertram, Christof A1 - Riener, Andreas A1 - Aubreville, Marc ED - Yamashita, Naomi ED - Evers, Vanessa ED - Yatani, Koji ED - Ding, Xianghua ED - Lee, Bongshin ED - Chetty, Marshini ED - Toups-Dugas, Phoebe T1 - "When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology T2 - CHI'25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems N2 - Artificial intelligence (AI)-based decision support systems hold promise for enhancing diagnostic accuracy and efficiency in computational pathology. However, human-AI collaboration can introduce and amplify cognitive biases, like confirmation bias caused by false confirmation when erroneous human opinions are reinforced by inaccurate AI output. This bias may increase under time pressure, a ubiquitous factor in routine pathology, as it strains practitioners’ cognitive resources. We quantified confirmation bias triggered by AI-induced false confirmation and examined the role of time constraints in a web-based experiment, where trained pathology experts (n=28) estimated tumor cell percentages. Our results suggest that AI integration fuels confirmation bias, evidenced by a statistically significant positive linear-mixed-effects model coefficient linking AI recommendations mirroring flawed human judgment and alignment with system advice. Conversely, time pressure appeared to weaken this relationship. These findings highlight potential risks of AI in healthcare and aim to support the safe integration of clinical decision support systems. UR - https://doi.org/10.1145/3706598.3713319 Y1 - 2025 UR - https://doi.org/10.1145/3706598.3713319 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58797 SN - 979-8-4007-1394-1 PB - ACM CY - New York 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 - TY - INPR A1 - Kammerlander, Calvin A1 - Kolb, Viola A1 - Luegmair, Marinus A1 - Scheermann, Lou A1 - Schmailzl, Maximilian A1 - Seufert, Marco A1 - Zhang, Jiayun A1 - Dalic, Denis A1 - Schön, Torsten T1 - Machine Learning Models for Soil Parameter Prediction Based on Satellite, Weather, Clay and Yield Data N2 - Efficient nutrient management and precise fertilization are essential for advancing modern agriculture, particularly in regions striving to optimize crop yields sustainably. The AgroLens project endeavors to address this challenge by develop ing Machine Learning (ML)-based methodologies to predict soil nutrient levels without reliance on laboratory tests. By leveraging state of the art techniques, the project lays a foundation for acionable insights to improve agricultural productivity in resource-constrained areas, such as Africa. The approach begins with the development of a robust European model using the LUCAS Soil dataset and Sentinel-2 satellite imagery to estimate key soil properties, including phosphorus, potassium, nitrogen, and pH levels. This model is then enhanced by integrating supplementary features, such as weather data, harvest rates, and Clay AI-generated embeddings. This report details the methodological framework, data preprocessing strategies, and ML pipelines employed in this project. Advanced algorithms, including Random Forests, Extreme Gradient Boosting (XGBoost), and Fully Connected Neural Networks (FCNN), were implemented and finetuned for precise nutrient prediction. Results showcase robust model performance, with root mean square error values meeting stringent accuracy thresholds. By establishing a reproducible and scalable pipeline for soil nutrient prediction, this research paves the way for transformative agricultural applications, including precision fertilization and improved resource allocation in underresourced regions like Africa. UR - https://doi.org/10.48550/arXiv.2503.22276 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.22276 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59345 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Song, Rui A1 - Liang, Chenwei A1 - Xia, Yan A1 - Zimmer, Walter A1 - Cao, Hu A1 - Caesar, Holger A1 - Festag, Andreas A1 - Knoll, Alois T1 - CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Driving N2 - Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic environments presents significant challenges in accurately rendering these scenes. In this paper, we introduce a novel 4D Gaussian Splatting (4DGS) approach, which incorporates context and temporal deformation awareness to improve dynamic scene rendering. Specifically, we employ a 2D semantic segmentation foundation model to self-supervise the 4D semantic features of Gaussians, ensuring meaningful contextual embedding. Simultaneously, we track the temporal deformation of each Gaussian across adjacent frames. By aggregating and encoding both semantic and temporal deformation features, each Gaussian is equipped with cues for potential deformation compensation within 3D space, facilitating a more precise representation of dynamic scenes. Experimental results show that our method improves 4DGS's ability to capture fine details in dynamic scene rendering for autonomous driving and outperforms other self-supervised methods in 4D reconstruction and novel view synthesis. Furthermore, CoDa-4DGS deforms semantic features with each Gaussian, enabling broader applications. UR - https://doi.org/10.48550/arXiv.2503.06744 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.06744 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58313 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 - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - 3D Extended Object Tracking based on Extruded B-Spline Side View Profiles N2 - Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on the observation that common road users are symmetrical on the right and left sides in the traveling direction, we focus on the side view profile of the object. In order to leverage of the development in 2D EOT and balance the number of parameters of a shape model in the tracking algorithms, we propose a method for 3D extended object tracking (EOT) by describing the side view profile of the object with B-spline curves and forming an extrusion to obtain a 3D extent. The use of B-spline curves exploits their flexible representation power by allowing the control points to move freely. The algorithm is developed into an Extended Kalman Filter (EKF). For a through evaluation of this method, we use simulated traffic scenario of different vehicle models and realworld open dataset containing both radar and lidar data. UR - https://doi.org/10.48550/arXiv.2503.10730 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2503.10730 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58331 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Yu, Qing A1 - Kiran, Iqra A1 - Ehrensberger, Moritz A1 - Streck, Luiza A1 - Roth, Thomas A1 - Jossen, Andreas A1 - Endisch, Christian A1 - Lewerenz, Meinert T1 - Assigning Calendar Aging during Open Circuit and Float Current Analysis to Anode and Cathode Aging Using Three-Electrode Cells JF - Journal of the Electrochemical Society N2 - Analyzing calendar aging by float current analysis, instead of solely repeating capacity tests, gains more insights into aging. However, the underlying mechanisms of the recharge current required to keep the voltage constant are not yet fully understood. Therefore, this study performs float current and additional open circuit voltage (OCV) tests on 3-electrode cells for four different voltages at 30 °C. By monitoring the potentials of the anode and the cathode over time individually, the aging rate on both electrodes and the present capacity can be calculated based on adjusting the electrode-specific OCV curves according to the voltage slippery theory. The electrode-specific aging and the capacity prediction show high agreement among both methods and the capacity tests at the end of the experiment. As a result, the capacity loss appears linear-like and is associated with the loss of active lithium mainly due to SEI formation on the anode. Additionally, a significant cathode voltage decay is observed especially for higher cell voltage. According to the literature, this is associated with cathode lithiation where the conductive salt is decomposed by inserting active lithium into the cathode masking SEI losses. Finally, OCV and float current analysis return comparable results and support present 2-electrode evaluation approaches. UR - https://doi.org/10.1149/1945-7111/ade295 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ade295 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60504 SN - 1945-7111 VL - 172 IS - 6 PB - IOP Publishing CY - Bristol ER - TY - CHAP A1 - Karpenahalli Ramakrishna, Chidvilas A1 - Mohan, Adithya A1 - Zeinaly, Zahra A1 - Belzner, Lenz ED - Rocha, Ana Paula ED - Steels, Luc ED - van den Herik, Jaap T1 - The Evolution of Criticality in Deep Reinforcement Learning T2 - Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) - Volume 3 N2 - In Reinforcement Learning (RL), certain states demand special attention due to their significant influence on outcomes; these are identified as critical states. The concept of criticality is essential for the development of effective and robust policies and to improve overall trust in RL agents in real-world applications like autonomous driving. The current paper takes a deep dive into criticality and studies the evolution of criticality throughout training. The experiments are conducted on a new, simple yet intuitive continuous cliff maze environment and the Highway-env autonomous driving environment. Here, a novel finding is reported that criticality is not only learnt by the agent but can also be unlearned. We hypothesize that diversity in experiences is necessary for effective criticality quantification which is majorly driven by the chosen exploration strategy. This close relationship between exploration and criticality is studied utilizing two different strategies namely the ex ponential ε-decay and the adaptive ε-decay. The study supports the idea that effective exploration plays a crucial role in accurately identifying and understanding critical states. UR - https://doi.org/10.5220/0013114200003890 Y1 - 2025 UR - https://doi.org/10.5220/0013114200003890 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57992 SN - 978-989-758-737-5 SP - 217 EP - 224 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Kugele, Stefan A1 - Schreyer, Lorenz A1 - Lamprecht, Martin ED - Koziolek, Anne ED - Lamprecht, Anna-Lena ED - Thüm, Thomas ED - Burger, Erik T1 - Cause-Effect Chain-Based Diagnosis of Automotive On-Board Energy Systems T2 - Software Engineering 2025: Proceedings N2 - This summary refers to the paper Cause-Effect Chain-Based Diagnosis of Automotive On-Board Energy Systems [KSL24]. This paper has been published in the Proceedings of the 18th European Conference on Software Architecture, ECSA 2024 in September 2024. UR - https://doi.org/10.18420/se2025-36 Y1 - 2025 UR - https://doi.org/10.18420/se2025-36 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57461 SN - 2944-7682 SP - 111 EP - 112 PB - Gesellschaft für Informatik CY - Bonn 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 - Axmann, Bernhard A1 - Pujar, Sanket T1 - Artificial Intelligence in Knowledge Management: Overview and Selection of Software for Automotive Reporting JF - Tehnički glasnik N2 - Knowledge Management is essential for modern organizations, enabling the systematic capture, organization, and sharing of knowledge to enhance decision-making and innovation. Traditional Knowledge Management tools, focused on document storage and retrieval, struggle with unstructured data and collaboration, necessitating advanced technological solutions, particularly those incorporating Artificial Intelligence. - Artificial Intelligence-driven Knowledge Management systems revolutionize data handling through automation, and real-time insights. This is particularly valuable in data-intensive industries like automotive, finance, and healthcare. In the automotive sector, annual reports provide critical insights but are complex and time-consuming to analyze and are a complex example and therefore a good test case. Annual reports of 5 major automotive companies BMW, Volkswagen group, Toyota Motors, General Motors and Tesla were selected as the testing dataset. Artificial Intelligence tools, using natural language processing and machine learning, streamline data extraction. - Despite their benefits, organizations face challenges in selecting the right Artificial Intelligence-driven Knowledge Management software due to a lack of standardized evaluation frameworks. This research applies a systematic methodology for assessing such software, considering usability, adaptability, cost-effectiveness, and data privacy compliance, specifically tailored to automotive reporting and gives recommendation for software tools. UR - https://doi.org/10.31803/tg-20250313154901 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250313154901 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59480 SN - 1848-5588 VL - 19 IS - si1 SP - 130 EP - 135 PB - University North CY - Koprivnica 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 - 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 - Vergnano, Alberto A1 - Pelizzari, Alessandro A1 - Giorgianni, Claudio A1 - Kovanda, Jan A1 - Zimmer, Alessandro A1 - Lopes da Silva, Joed A1 - Rezvanpour, Hamed A1 - Leali, Francesco T1 - Monitoring Occupant Posture Using a Standardized Sensor Interface with a Vehicle Seat JF - Designs N2 - Car safety can be enhanced by enabling the Airbag Control Unit (ACU) to adaptively deploy different charges based on the occupant’s position once the crash occurs. In this context, monitoring the occupant’s position using a sensorized seat integrated with an Inertial Measurement Unit (IMU) offers a practical and cost-effective solution. However, certain challenges still need to be addressed. The adoption of sensorized seats in research and vehicle set-up is still under consideration. This study investigates an interface device that can be reconfigured to suit almost any seat model. This reconfigurability makes it easily adaptable to new vehicles under development and applicable to any passenger seat in the vehicle. This paper details the device’s design, including its programming using calibration and monitoring features, which significantly improves its reliability compared to earlier prototypes. Extensive testing through real driving experiments with multiple participants demonstrated an accuracy range of 45–100%. The testing involved both drivers and passengers, showcasing the device’s ability to effectively monitor various in-car scenarios. UR - https://doi.org/10.3390/designs9020052 Y1 - 2025 UR - https://doi.org/10.3390/designs9020052 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59083 SN - 2411-9660 VL - 9 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Göbel, Jan-Philipp A1 - Peuckmann, Niklas A1 - Kundinger, Thomas A1 - Riener, Andreas T1 - Fusion of Driving Behavior and Monitoring System in Scenarios of Driving Under the Influence: An Experimental Approach JF - Applied Sciences N2 - Driving under the influence of alcohol (DUI) remains a leading cause of accidents globally, with accident risk rising exponentially with blood alcohol concentration (BAC). This study aims to distinguish between sober and intoxicated drivers using driving behavior analysis and driver monitoring system (DMS), technologies that align with emerging EU regulations. In a driving simulator, twenty-three participants (average age: 32) completed five drives (one practice and two each while sober and intoxicated) on separate days across city, rural, and highway settings. Each 30-minute drive was analyzed using eye-tracking and driving behavior data. We applied significance testing and classification models to assess the data. Our study goes beyond the state of the art by a) combining data from various sensors and b) not only examining the effects of alcohol on driving behavior but also using these data to classify driver impairment. Fusing gaze and driving behavior data improved classification accuracy, with models achieving over 70% accuracy in city and rural conditions and a Long Short-Term Memory (LSTM) network reaching up to 80% on rural roads. Although the detection rate is, of course, still far too low for a productive system, the results nevertheless provide valuable insights for improving DUI detection technologies and enhancing road safety. UR - https://doi.org/10.3390/app15105302 Y1 - 2025 UR - https://doi.org/10.3390/app15105302 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59467 SN - 2076-3417 VL - 15 IS - 10 PB - MDPI CY - Basel ER - TY - JOUR A1 - Agrawal, Shiva A1 - Bhanderi, Savankumar A1 - Elger, Gordon T1 - Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection JF - Sensors N2 - Mono RGB cameras and automotive radar sensors provide a complementary information set that makes them excellent candidates for sensor data fusion to obtain robust traffic user detection. This has been widely used in the vehicle domain and recently introduced in roadside-mounted smart infrastructure-based road user detection. However, the performance of the most commonly used late fusion methods often degrades when the camera fails to detect road users in adverse environmental conditions. The solution is to fuse the data using deep neural networks at the early stage of the fusion pipeline to use the complete data provided by both sensors. Research has been carried out in this area, but is limited to vehicle-based sensor setups. Hence, this work proposes a novel deep neural network to jointly fuse RGB mono-camera images and 3D automotive radar point cloud data to obtain enhanced traffic user detection for the roadside-mounted smart infrastructure setup. Projected radar points are first used to generate anchors in image regions with a high likelihood of road users, including areas not visible to the camera. These anchors guide the prediction of 2D bounding boxes, object categories, and confidence scores. Valid detections are then used to segment radar points by instance, and the results are post-processed to produce final road user detections in the ground plane. The trained model is evaluated for different light and weather conditions using ground truth data from a lidar sensor. It provides a precision of 92%, recall of 78%, and F1-score of 85%. The proposed deep fusion methodology has 33%, 6%, and 21% absolute improvement in precision, recall, and F1-score, respectively, compared to object-level spatial fusion output. UR - https://doi.org/10.3390/s25113422 Y1 - 2025 UR - https://doi.org/10.3390/s25113422 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59421 SN - 1424-8220 VL - 25 IS - 11 PB - MDPI CY - Basel ER - TY - JOUR A1 - Agricola, Barbara A1 - Palm, Frank A1 - Jägle, Eric A. A1 - Kerschenlohr, Annegret T1 - Influence of alloying elements on precipitation formation and mechanical properties of Al–Cr–Mo-Sc-Zr alloys during laser powder bed fusion at room and elevated temperatures JF - Journal of Materials Research and Technology N2 - Most of the high-strength aluminium alloys for Laser Powder Bed Fusion (L-PBF) in research are based on conventional hardenable Al–Cu, Al–Mg–Si and Al–Zn–Mg alloys that have issues with hot-cracking during the L-PBF process. This study investigates the effect of alloying elements on two novel Al–Cr–Mo-Sc-Zr alloys (Scancromal® variants) with a good, crack-free processability and strength-ductility combination. A layer thickness of 100 μm was used, highlighting the high productivity and good processability of Al–Cr alloys. Heat treatments and hardness measurements were conducted to investigate peak age heat treatment and revealed a relation between Sc/Zr-ratio and peak aged temperature. SEM observations of small precipitates at grain boundaries and fracture surfaces contributed to understanding the changing fracture mechanism from less ductile (2.4–10.2% elongation) to very ductile (14.1–19% elongation). Tensile tests at elevated temperatures and creep tests showed a positive effect of Cr and Mo on high temperature strength. High-temperature properties, especially creep results of Al–Cr alloys and Scalmalloy® (Al–Mg–Mn-Sc-Zr) are presented for the first time and emphasize the increased heat-resistance by Cr and Mo. The threshold stress, below which theoretically no creep should occur, of the presented Scancromal® variants is at least 5 times higher (142–189 MPa) compared to Scalmalloy® (28 MPa). A comprehensive comparison of the results to literature values of AlSi10Mg, other Al–Cr alloys and high temperature Al alloys gives valuable insight on how the aging response, microstructure, ductility and high-temperature strength of this type of alloy is influenced by its alloying elements. UR - https://doi.org/10.1016/j.jmrt.2025.04.255 Y1 - 2025 UR - https://doi.org/10.1016/j.jmrt.2025.04.255 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59137 SN - 2238-7854 VL - 2025 IS - 36 SP - 6632 EP - 6645 PB - Elsevier CY - Rio de Janeiro ER - TY - JOUR A1 - Gottwalt, Albin A1 - Kubaschinski, Paul A1 - Waltz, Manuela A1 - Tetzlaff, Ulrich T1 - Influence of shear cutting parameters on the edge properties and the fatigue behavior of non‐oriented electrical steel sheets JF - Materials Science & Engineering Technology N2 - The fatigue behavior of a fully processed, non‐oriented electrical steel sheet is investigated for different shear cutting parameters. Therefore, three cutting clearances (15 μm, 35 μm and 50 μm) in combination with two different punching tool wear states (sharp and worn) are compared regarding their mechanical properties. For this purpose, surface measurements, nanoindentation tests and stress‐controlled fatigue tests with a positive load ratio are performed for all six parameter sets. During shear cutting the material gets locally strain‐hardened and a deformed surface with micro‐notches is created. Compared to a polished reference condition, the fatigue strength of the shear‐cut sheets is severely deteriorated. However, the intensity of deterioration varies depending on the shear cutting parameters. For small cutting clearances, the highest fatigue life is observed for a sharp cutting tool. In contrast, for medium and high cutting clearances, samples that are cut with a worn tool achieve higher fatigue lives. Surface characteristics in the fracture zone, which act as a failure‐critical crack location, are considered as the main influencing factor. N2 - Das Ermüdungsverhalten eines vollständig schlussgeglühten, nicht kornorientierten Elektroblechs wird für verschiedene Parameterkombinationen während des Scherschneidens untersucht. Dazu werden drei Schnittspaltbreiten (15 μm, 35 μm und 50 μm) in Kombination mit zwei unterschiedlichen Verschleißzuständen der Stanzwerkzeugen (neuwertig und verschlissen) verglichen. Zu diesem Zweck werden für alle sechs Parametersätze Topographiemessungen, Nanohärtemessungen und spannungsgeregelte Ermüdungsversuche mit einem positiven Lastverhältnis durchgeführt. Die Schnittkanten sind als Folge des Scherschneidens lokal kaltverfestigt und es entsteht zudem eine raue Oberfläche mit Mikrokerben. Im Vergleich zu einem polierten Referenzzustand ist die Ermüdungsfestigkeit der schergeschnittenen Bleche dadurch verschlechtert. Die Intensität der Verschlechterung hängt jedoch von den Scherschneidparametern ab. Bei kleinen Schnittspalten wird die höchste Ermüdungslebensdauer für einen neuwertigen Schneidwerkzeug beobachtet. Im Gegensatz dazu erreichen Proben, die mit einem verschlissenen Werkzeug geschnitten werden, bei mittleren und großen Schnittspalten eine höhere Ermüdungslebensdauer. Die Oberflächenbeschaffenheit in der Bruchzone, die als versagenskritische Anrissposition wirkt, wird hierbei als Haupteinflussfaktor angesehen. T2 - Einfluss von Scherschneidparametern auf die Kanteneigenschaften und das Ermüdungsverhalten von nicht kornorientierten Elektroblechen UR - https://doi.org/10.1002/mawe.202400094 Y1 - 2025 UR - https://doi.org/10.1002/mawe.202400094 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59378 SN - 0933-5137 VL - 56 IS - 4 SP - 537 EP - 548 PB - Wiley CY - Weinheim ER - TY - JOUR A1 - Pace, Lisa A. A1 - Bruno, Carmen A1 - Schwarz, Jan Oliver T1 - Personas in scenario building: Integrating human-centred design methods in foresight JF - Futures N2 - This paper contributes to integrating human-centred design approaches in foresight. We emphasize design thinking as an approach that incorporates user-centred concepts and artefacts, enabling the creation and visualization of potential futures and mediating the exploration of new perspectives and areas of intervention for innovation. However, there is limited discussion in the foresight literature on the meaningful application of design approaches. We focus on the persona method and its roles and applications in scenario building. To be meaningful in scenario building, personas need to appropriately integrate users’ future needs, expectations and behaviours that shape and in turn are shaped by contexts that are yet to be realised. Based on an analysis of published case studies, the paper underscores the role of personas in fostering creative imagination, enhancing scenario engagement, and prospective sensemaking beyond their application as a storytelling vehicle in scenarios. We link persona characteristics and design to their roles in scenario building, allowing design and foresight practitioners the flexibility to tailor the persona approach to different contexts and critically assess the underlying limitations. From this, we provide recommendations for incorporating personas in scenario building and conclude with suggestions for future research. UR - https://doi.org/10.1016/j.futures.2025.103539 Y1 - 2025 UR - https://doi.org/10.1016/j.futures.2025.103539 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57730 SN - 1873-6378 VL - 2025 IS - 166 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schwarz, Jan Oliver A1 - Schropp, Theresa Constanze A1 - Wach, Bernhard A1 - Buder, Fabian T1 - Do internal foresight activities add value to decision-making? Insights from an empirical investigation JF - Futures N2 - In a large empirical investigation of 400 managers in large U.S. and European corporations, we shed light on the effects of internal strategic foresight activities for decision-making, asking whether and how firms’ internal foresight activities add value to their decision-making. Enabling and supporting strategy conversations is conceptualized here as a central activity of strategic foresight. Our empirical investigation demonstrates that internal foresight activities have a significant and positive effect on strategy conversations within a firm. Against the assumptions of previous research, however, we cannot confirm the positive influence of strategy conversations in general on challenging the status quo in a firm or the overall helpfulness of strategic foresight activities in the context of decision-making. Future research should delve deeper into organizational studies to gain a more nuanced understanding of the processes and factors influencing future-oriented decision-making, as well as identifying key enablers that facilitate these decisions. UR - https://doi.org/10.1016/j.futures.2025.103548 Y1 - 2025 UR - https://doi.org/10.1016/j.futures.2025.103548 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57703 SN - 0016-3287 VL - 2025 IS - 166 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Mohan, Nihesh A1 - Ahuir-Torres, Juan Ignacio A1 - Kotadia, Hiren R. A1 - Elger, Gordon T1 - Laser sintering of Cu particle-free inks for high-performance printed electronics JF - npj Flexible Electronics N2 - This study investigates laser sintering of Cu particle-free ink (Cu formate tetrahydrate—amino-2-propanol complex) as an alternative to conventional sintering in an oven (under inert/reducing atmosphere). Utilizing benefits of high-speed localized heating using laser, substrate damage can be prevented for low-melting substrates such as Polyethylene Terephthalate (PET). Firstly, a suitable sintering process window is achieved based on energy density for two different flexible polymeric susbtrates: Polyimide and PET using different laser parameters (laser power, scan rate and spot diameter). Subsequently, characterization of laser sintered traces are also made using different laser optic profiles (Gaussian and top hat). Different methodologies for fabrication of metallized Cu layer were also demonstrated. A very low bulk resistivity of 3.24 µΩcm (1.87 times of bulk Cu) was achieved on trace thickness of 0.85 ± 0.15 µm exhibiting good adherence to polymeric substrates. A promising fabrication process of low-cost and reliable flexible printed electronic devices is demonstrated. UR - https://doi.org/10.1038/s41528-025-00389-5 Y1 - 2025 UR - https://doi.org/10.1038/s41528-025-00389-5 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58266 SN - 2397-4621 VL - 9 IS - 1 PB - Springer CY - London ER - TY - JOUR A1 - Stöttner, Julia A1 - Hanzl, Christian A1 - Terbrack, Christoph A1 - Endisch, Christian T1 - Holistic evaluation and optimization of multilevel inverter designs for electric vehicle applications JF - Energy Reports N2 - To advance the development of multilevel inverters (MLIs) for electric vehicle applications, this study introduces novel asymmetric MLI (AMLI) configurations featuring buffer modules to enhance efficiency. A comprehensive comparative analysis of 125 distinct inverter systems is conducted, integrating five different microtopologies and 25 representative symmetrical MLI (SMLI) and AMLI systems. Unlike previous studies, this work employs a successive design process with a graph-based approach to systematically minimize conduction losses. Furthermore, experimental loss measurements ensure practical relevance. By applying Pareto optimization with cost, energy losses, and total harmonic distortion as objective functions, the study identifies the most promising MLI systems among all considered ones. While the cascaded H-bridge MLI emerges as the most cost-effective solution, specific SMLI configurations with 12 or 18 battery cells per module and AMLI designs featuring buffer modules exhibit lower inverter losses. In both cases, the incorporation of microtopologies that enable parallel operation leads to a remarkable reduction in inverter losses by more than 30 % compared to the least efficient MLI systems. Finally, a comparative assessment against a conventional B6-bridge SiC inverter highlights the significant advantages of these optimized MLI configurations in terms of efficiency and system performance. UR - https://doi.org/10.1016/j.egyr.2025.03.001 Y1 - 2025 UR - https://doi.org/10.1016/j.egyr.2025.03.001 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58297 SN - 2352-4847 VL - 2025 IS - 13 SP - 3561 EP - 3573 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kaufhold, Marc-André A1 - Mentler, Tilo A1 - Nestler, Simon A1 - Reuter, Christian T1 - The tension of usable safety, security and privacy JF - i-com: Journal of Interactive Media N2 - Local disasters such as the Ahr Valley flood in Germany, the international backdrop of the Russo-Ukrainian War, or the global impact of the COVID-19 pandemic place high demands on the people and organisations that are involved in these situations and contexts to save lives, mitigate damage, provide comfort, or organise reconstruction. Novel technologies are constantly making their way into everyday life, such as artificial intelligence, big data, decentralised networks, internet of things, or virtual reality. Their adaptation, acceptance, usability, usefulness, and legal framework conditions for safety-critical systems must be researched and tested thoroughly. In this special issue, we investigate the use of computer-based solutions in areas and situations of direct relevance to people’s lives and well-being (Usable Safety), as well as contributions to user-oriented resilience concepts of sociotechnical systems concerning potential attacks (Usable Security) and data protection mechanisms (Usable Privacy). UR - https://doi.org/10.1515/icom-2025-0009 Y1 - 2025 UR - https://doi.org/10.1515/icom-2025-0009 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58286 SN - 2196-6826 VL - 24 IS - 1 SP - 1 EP - 7 PB - De Gruyter CY - Berlin ER - TY - INPR A1 - Petrovska, Ana A1 - Erjiage, Guan A1 - Kugele, Stefan T1 - Defining Self-adaptive Systems: A Systematic Literature Review N2 - In the last two decades, the popularity of self-adaptive systems in the field of software and systems engineering has drastically increased. However, despite the extensive work on self-adaptive systems, the literature still lacks a common agreement on the definition of these systems. To this day, the notion of self-adaptive systems is mainly used intuitively without a precise understanding of the terminology. Using terminology only by intuition does not suffice, especially in engineering and science, where a more rigorous definition is necessary. In this paper, we investigate the existing formal definitions of self-adaptive systems and how these systems are characterised across the literature. Additionally, we analyse and summarise the limitations of the existing formal definitions in order to understand why none of the existing formal definitions is used more broadly by the community. To achieve this, we have conducted a systematic literature review in which we have analysed over 1400 papers related to self-adaptive systems. Concretely, from an initial pool of 1493 papers, we have selected 314 relevant papers, which resulted in nine primary studies whose primary objective was to define self-adaptive systems formally. Our systematic review reveals that although there has been an increasing interest in self-adaptive systems over the years, there is a scarcity of efforts to define these systems formally. Finally, as part of this paper, based on the analysed primary studies, we also elicit requirements and set a foundation for a potential (formal) definition in the future that is accepted by the community on a broader range. UR - https://doi.org/10.48550/arXiv.2505.17798 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2505.17798 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61576 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Ramic, Amra A1 - Kugele, Stefan T1 - A Systematic Mapping Study on Software Architecture for AI-based Mobility Systems N2 - Background: Due to their diversity, complexity, and above all importance, safety-critical and dependable systems must be developed with special diligence. Criticality increases as these systems likely contain artificial intelligence (AI) components known for their uncertainty. As software and reference architectures form the backbone of any successful system, including safety-critical dependable systems with learning-enabled components, choosing the suitable architecture that guarantees safety despite uncertainties is of great eminence. Aim: We aim to provide the missing overview of all existing architectures, their contribution to safety, and their level of maturity in AI-based safety-critical systems. Method: To achieve this aim, we report a systematic mapping study. From a set of 1,639 primary studies, we selected 38 relevant studies dealing with safety assurance through software architecture in AI-based safety-critical systems. The selected studies were then examined using various criteria to answer the research questions and identify gaps in this area of research. Results: Our findings showed which architectures have been proposed and to what extent they have been implemented. Furthermore, we identified gaps in different application areas of those systems and explained these gaps with various arguments. Conclusion: As the AI trend continues to grow, the system complexity will inevitably increase, too. To ensure the lasting safety of the systems, we provide an overview of the state of the art, intending to identify best practices and research gaps and direct future research more focused. UR - https://doi.org/10.48550/arXiv.2506.01595 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2506.01595 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61560 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Ngetuny, Joshua A1 - Baldauf, Tobias A1 - Zörner, Wilfried T1 - Optimizing Feedstock Selection for Sustainable Small-Scale Biogas Systems Using the Analytic Hierarchy Process JF - Energies N2 - Small-scale biogas systems can play a pivotal role in sustainable energy provision, particularly in developing countries. However, their dependence on livestock manure as the only feedstock poses challenges to their adoption and long-term viability. This often leads to insufficient biogas production and plant abandonment. This study proposes co-digestion of livestock manure with other farm residues to enhance the technical sustainability of small-scale biogas systems by ensuring adequate and consistent biogas production throughout the plant’s lifespan, minimizing the risks associated with reliance on a single feedstock. A novel feedstock selection approach is developed using the Analytic Hierarchy Process (AHP), a multicriteria decision-making method, to prioritize feedstocks based on adequacy, supply consistency, and logistical ease. AHP is chosen due to its capability to handle both quantitative and qualitative evaluation criteria. This approach is applied to the Fès-Meknès region of Morocco, which offers abundant livestock and crop residues alongside product utilization pathways. The prioritization and ranking of the potential feedstocks identified in the region reveals cattle manure as the top-ranked feedstock due to its consistent supply and ease of collection, followed by straw, valued for its storability and nutrient stability. Sheep, horse, and chicken manure ranked third, fourth, and fifth, respectively, while household food waste and fruit and vegetable residues, limited by seasonality and perishability, were ranked lower. Based on these findings, co-digestion of cattle manure and straw is proposed as a sustainable strategy for small-scale biogas plants in Fès-Meknès, addressing feedstock shortages, enhancing biogas production, and reducing plant abandonment. This approach strengthens technical sustainability and promotes the broader adoption of biogas technologies in developing countries. UR - https://doi.org/10.3390/en18071739 Y1 - 2025 UR - https://doi.org/10.3390/en18071739 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57915 SN - 1996-1073 VL - 18 IS - 7 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mohan, Nihesh A1 - Steinberger, Fabian A1 - Wächter, Sonja A1 - Erdogan, Hüseyin A1 - Elger, Gordon T1 - Additive Manufacturing for Automotive Radar Sensors Using Copper Inks and Pastes JF - Applied Sciences N2 - Radar sensors are critical for obstacle detection and navigation, especially for automated driving. Using the use-case “printing of heating coils on the inside of the front housing (primary radome)” needed for de-icing in winter, it is demonstrated that additive manufacturing (AM) can provide economic and functional benefits for manufacturing of the sensors. AM will allow significant cost reduction by eliminating parts and simplifying the manufacturing process. Different AM technologies for the coils were investigated, first, by applying the conductive traces by fused deposition modeling (FDM), and, second, by printing copper particle-free inks and pastes. The metal layers were electrically and mechanically characterized using a profilometer to measure the trace dimension and a four-point probe to measure the resistance. It was revealed that low-cost conductive filaments with low resistivity and current carrying capacity are commercially still not available. The best option sourced was a copper–polyester-based filament with 6000 µΩcm after printing. Therefore, low-cost particle-free copper inks and commercial copper flake paste were selected to print the heating coil. The Cu particle-free inks were amine-based Cu (II) formate complexes, where the Cu exists in an ionic form. Using contactless printing processes such as ink-jet printing or pneumatic dispensing, the traces could be deposited onto the low-melting temperature (225 °C) polymeric radome structure. After printing, the material needed to be sintered to form the conductive copper traces. To avoid damaging the polymer radome during sintering, two different processes were investigated: low-temperature (<150 °C) sintering in an oven for 30 min or fast laser sintering. The sintered Cu layers achieved the following specific electric resistivities when slowly sintered in the oven: paste 4 µΩcm and ink 8.8 µΩcm. Using laser sintering, the ink achieved 3.2 µΩcm because the locally high temperature provides better sintering. Also, the adhesion was significantly increased to (5 B). Therefore, laser sintering is the preferred technology. In addition, it allows fast processing directly after printing. Commercial equipment is available where printing and laser sintering is integrated. The potential of low-cost copper material and the integration in additive manufacturing of electronic systems using radar sensors as an example are demonstrated in this paper. UR - https://doi.org/10.3390/app15052676 Y1 - 2025 UR - https://doi.org/10.3390/app15052676 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58065 SN - 2076-3417 VL - 15 IS - 5 PB - MDPI CY - Basel ER - TY - JOUR A1 - Bednarz, Martin T1 - Die Casting or Sheet Metal Forming: A Comparison of Car Body Manufacturing in Times of the "Giga Press" JF - Tehnički glasnik N2 - Die casting as an alternative for sheet metal structures in car body design has been around for a few years. While the application of die cast body components by legacy automakers is rather limited, especially for mass market products, Tesla bases their mass-produced cars on a few extremely big die cast structure parts. The impact of this strategy makes it necessary to rethink car body manufacturing. In this study, published information and expert interviews are used to evaluate the strengths and weaknesses of the competing philosophies of car body manufacturing. UR - https://doi.org/10.31803/tg-20240510165209 Y1 - 2025 UR - https://doi.org/10.31803/tg-20240510165209 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57745 SN - 1848-5588 VL - 19 IS - 1 SP - 58 EP - 61 PB - University North CY - Koprivnica ER - TY - JOUR A1 - Güldali, Derya A1 - De Rose, Angela A1 - Mittag, Max A1 - Grübel, Benjamin A1 - Neuhaus, Holger A1 - Tetzlaff, Ulrich T1 - Interconnection of low-temperature metallization on silicon solar cells - The role of silver in tin-bismuth-based solder alloys JF - Solar Energy Materials and Solar Cells N2 - This study investigates the potential of tin-bismuth (SnBi) alloys micro-alloyed with silver (Ag) to enhance low-temperature (LT) soldering for photovoltaic (PV) modules. The primary focus is on addressing challenges such as intermetallic compound (IMC) formation, which can compromise mechanical strength and durability under thermal cycling, thereby improving the long-term stability of solder joints. A systematic investigation of the influence of the Ag amount is being conducted with the intention to find the optimal alloy composition for SnBi solder joints on LT metallization contacts. The objective is to provide a cost-effective, lead-free alternative for the interconnection of temperature-sensitive solar cells like silicon heterojunction (SHJ) cells. The findings illustrate that the addition of 0.4 %wt. Ag notably enhances the wettability and initial mechanical strength of the solder. An increase in the Ag content to 1.0 %wt. results in an excessive growth of IMC, which in turn leads to increased brittleness and potential long-term stability issues of the solder joint. Thermal cycling tests demonstrate that modules soldered with SnBiAg0.4 exhibited less than -5 % loss in power. This composition represents an optimal balance between performance and cost. These findings show the potential of SnBiAg0.4 as a suitable solder alloy regarding long-term stability and electrical performance for interconnection of LT metallization contacts of solar cells in PV module manufacturing. UR - https://doi.org/10.1016/j.solmat.2025.113488 Y1 - 2025 UR - https://doi.org/10.1016/j.solmat.2025.113488 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57982 SN - 1879-3398 VL - 2025 IS - 285 PB - Elsevier CY - Amsterdam 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 - JOUR A1 - Glaas, Saskia A1 - Pham, Huong A1 - Kuonath, Angela A1 - Frey, Dieter T1 - Thriving or Withdrawing: How Job Crafting and Disengagement Shape Responses to Daily Laissez-faire Leadership JF - Journal of Business and Psychology N2 - Although laissez-faire leadership is common in organizations and has been linked to detrimental effects on employees, little is known about its daily effects and how employees cope with this type of behavior. Drawing on the job demands-resources model and using a daily diary design, we examine the daily effects of laissez-faire leadership depending on followers’ coping styles, capturing both adaptive and maladaptive responses. Specifically, we argue that the negative effect of laissez-faire leadership on next-day performance via evening job satisfaction is mitigated on days that followers engage in job crafting, while it is amplified on days that followers engage in disengagement coping. We collected data twice a day over one working week in an experience sampling study with 127 employees (i.e., after work and before bedtime; 359 data points). Our findings revealed no direct effect of laissez-faire leadership. However, there was a positive indirect effect of laissez-faire leadership on next-day performance via evening job satisfaction on days when employees engaged in high levels of job crafting, supporting its hypothesized beneficial effect. Conversely, as hypothesized, a negative indirect effect was observed on days when disengagement coping was high. By identifying the mixed effects of laissez-faire leadership, this study offers a fresh perspective that challenges the dominant view of its uniformly negative consequences, revealing how its downstream effects vary within individuals depending on their daily coping strategies. UR - https://doi.org/10.1007/s10869-025-10056-1 Y1 - 2025 UR - https://doi.org/10.1007/s10869-025-10056-1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60822 SN - 1573-353X PB - Springer CY - New York ER - TY - JOUR A1 - Azzam, Mohamed A1 - Aydin, Atakhan A1 - Endisch, Christian A1 - Sauer, Dirk Uwe A1 - Lewerenz, Meinert T1 - Float Current Analysis for Lithium-Ion Battery Aging: Insights into SEI Growth and Cathode Lithiation with EIS and ICP OES JF - Journal of The Electrochemical Society N2 - This study investigates calendar-aging mechanisms in lithium-ion batteries, focusing on cathode lithiation due to decomposition of conductive salt and SEI growth, by correlating quantified float currents, capacity loss rates, and pulse resistances with changes in electrochemical impedance spectroscopy (EIS) spectra. Seven SamSung 25 R cells are aged at different float voltages with periodic EIS measurements at 30 °C. Using a pre-characterization cell, the internal processes via EIS are allocated across various states of charge and temperatures and GITT measurements are performed to derive scaling factors. GITT, float currents and capacity loss rate measurements at 30 °C enables the separation of SEI growth ISEI growth and cathode lithiation current ICL based on float current behavior across a temperature range of 5 °C to 50 °C. The distribution of relaxation times (DRT) method is employed to deconvolute overlapping electrochemical processes. EIS and DRT analyses showed significant changes in cathode charge transfer resistance and diffusion, confirming that cathode lithiation correlates substantially to elevated internal resistance at high cell voltages. The theory of ISEI growth and ICL is further supported using inductively coupled plasma atomic emission spectroscopy by quantifying elemental inventory changes and linking phosphorus release and lithium consumption to degradation mechanisms. UR - https://doi.org/10.1149/1945-7111/adef85 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/adef85 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60922 SN - 1945-7111 VL - 172 IS - 7 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Mehta, Kedar A1 - Zörner, Wilfried T1 - Optimizing Agri-PV System: Systematic Methodology to Assess Key Design Parameters JF - Energies N2 - Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. UR - https://doi.org/10.3390/en18143877 Y1 - 2025 UR - https://doi.org/10.3390/en18143877 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61136 SN - 1996-1073 VL - 18 IS - 14 PB - MDPI CY - Basel ER - TY - JOUR A1 - Laband, Dana Laureen A1 - Stöckl, Martin A1 - Mittreiter, Annedore A1 - Holzhammer, Uwe T1 - Barrier Analysis of Flexibilization of Cooling Supply Systems JF - Energies N2 - The present study examines the barriers that prevent cooling system flexibility from being optimized. In the context of an increasing reliance on renewable energy sources, the necessity for flexible energy utilization is becoming increasingly apparent. A survey and discussion groups were conducted with various stakeholders within the cooling value chain to obtain their experiences and insights regarding barriers to flexibilization. The findings point out that economic, technological, and regulatory barriers are the primary factors impeding the implementation of flexible solutions. In particular, high investment costs, complex technical implementation, a lack of information, and a complicated legal framework were identified as significant impediments. To enhance the flexibility of cooling systems, coordinated efforts are necessary to address these barriers. Practical examples, training, and the standardization and digitalization of processes could facilitate the widespread implementation of flexible cooling systems. UR - https://doi.org/10.3390/en18154133 Y1 - 2025 UR - https://doi.org/10.3390/en18154133 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61098 SN - 1996-1073 VL - 18 IS - 15 PB - MDPI CY - Basel ER - TY - JOUR A1 - Lützow, Laura A1 - Kochdumper, Niklas A1 - Althoff, Matthias T1 - Underapproximative Methods for the Order Reduction of Zonotopes JF - IEEE Control Systems Letters N2 - Zonotopes are a widely used set representation in set-based computations due to their compact representation size and their closure under many relevant set operations. However, certain set operations, such as the Minkowski sum, increase the zonotope order, which in turn increases the computational cost of further computations. To address this issue, various order reduction techniques have been proposed, most of which focus on overapproximating the original zonotope. While overapproximations are crucial for safety verification, some applications – such as reachset-conformant identification and backward reachability analysis – require underapproximations (also referred to as inner-approximations). Besides providing a comprehensive survey of existing underapproximative order reduction methods, we propose four novel reduction methods in this letter. We analyze the computational cost of all methods and evaluate the tightness of the resulting underapproximations through numerical experiments on more than 2000 randomly generated zonotopes. The results demonstrate that our proposed methods achieve a favorable balance between computational efficiency and approximation accuracy, making them well-suited for applications in control, estimation, and system identification. UR - https://doi.org/10.1109/LCSYS.2025.3577642 Y1 - 2025 UR - https://doi.org/10.1109/LCSYS.2025.3577642 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61157 SN - 2475-1456 VL - 9 SP - 1730 EP - 1735 PB - IEEE CY - New York ER - TY - CHAP A1 - Kochdumper, Niklas A1 - Foughali, Mohammed A1 - Habermehl, Peter A1 - Asarin, Eugene T1 - Robust Identification of Hybrid Automata from Noisy Data T2 - Proceedings of the 28th ACM International Conference on Hybrid Systems: Computation and Control, part of CPS-IoT Week N2 - In recent years, many different methods for identifying hybrid automata from data have been proposed. However, most of these methods consider clean simulator data, and consequently do not perform well for noisy data measured from real systems. We address this shortcoming with a new approach for the identification of hybrid automata that is specifically designed to be robust to noise. In particular, we propose a new high-level strategy consisting of the following three steps: clustering based on the dynamics identified from a local dataset, state space partitioning using decision trees, and conversion of the decision tree to a hybrid automaton. In addition, we introduce several new concepts for the realization of the single steps. For example, we propose an automated regularization of the dynamic models used for clustering via rank adaption, as well as a new variant of the Gini impurity index for decision tree learning, tailored toward hybrid systems where different dynamics can be active within the same state space region. As our experiments on 19 challenging benchmarks with different characteristics demonstrate, in addition to being robust to both process and measurement noise, our approach avoids the need for extensive hyper-parameter tuning and also performs well for clean data without noise. UR - https://doi.org/10.1145/3716863.3718030 Y1 - 2025 UR - https://doi.org/10.1145/3716863.3718030 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61207 SN - 979-8-4007-1504-4 PB - ACM CY - New York ER - TY - CHAP A1 - Schrage, Tobias A1 - Schuderer, Peter A1 - Franke, Jörg ED - Kohl, Holger ED - Seliger, Günther ED - Dietrich, Franz ED - Mur, Sebastián T1 - Process- and Material-Specific Modeling to Use in Simulation-Based and Resource-Oriented Decision Support Systems Using the Example of Calcium Silicate Brick Production Planning T2 - Sustainable Manufacturing as a Driver for Growth: Proceedings of the 19th Global Conference on Sustainable Manufacturing, December 4–6, 2023, Buenos Aires, Argentina N2 - As part of the fourth industrial revolution, data analysis and artificial intelligence are being integrated into production processes. In addition, energy consumption and CO2 costs are becoming decisive factors in the resource-oriented management of companies. For energy intensive and hybrid production processes a simulation-based decision support system (DSS) for production planning is validated and further developed for the sand lime brick industry to support the production planning process. The integration of empirical knowledge in the energy-intensive control of steam processes, in which quality-critical product parameters are set via thermodynamically complex relationships, is still part of current research approaches. In this paper, an approach for the mapping of an energetic system behavior in the energy-intensive and hybrid production processes will be discussed using the example of calcium silicate brick (CSB) production. Possibilities for using Discrete event simulation (DES) to increase the energy efficiency of steam processes are summarized and linked to formalized empirical knowledge in artificial Intelligence (AI) approaches. UR - https://doi.org/10.1007/978-3-031-77429-4_62 Y1 - 2025 UR - https://doi.org/10.1007/978-3-031-77429-4_62 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-55984 SN - 978-3-031-77429-4 SP - 562 EP - 568 PB - Springer CY - Cham ER - TY - JOUR A1 - Mehta, Kedar A1 - Wright, Andrew A1 - Brown, Neil A1 - Zörner, Wilfried T1 - Transitioning to Low-Carbon Heating: Decision-Making Approach for Cold Communities JF - Clean Energy N2 - Selecting a sustainable heat energy supply system for high-altitude, cold-climatic communities in developing countries is essential for both decision-makers and the scientific community. However, no comprehensive guide or framework exists to address this issue and decarbonize cold communities sustainably. This research aims to fill that gap by identifying and developing a methodology for selecting a suitable heat energy supply system, using Kyrgyzstan as a case study. The approach takes into account renewable energy sources, local conditions, and specific criteria necessary for designing a sustainable energy supply. The paper introduces a decision-making framework based on 17 criteria, covering geographical, environmental, economic, technical, and social aspects, derived from the opinions of over 20 experts. This framework serves as a guide for selecting and designing an appropriate heat energy supply system. Five heat supply options are analyzed in Kyrgyzstan’s high-altitude, cold rural setting to demonstrate the framework's potential. The analysis reveals that centralized district heating is the most suitable solution, scoring 79% for system selection. This methodology is partially or fully transferable to regions or countries with similar climates and local circumstances, offering a valuable resource for the development of sustainable heat energy solutions in cold, high-altitude communities. UR - https://doi.org/10.1093/ce/zkaf010 Y1 - 2025 UR - https://doi.org/10.1093/ce/zkaf010 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58214 SN - 2515-396X VL - 9 IS - 4 PB - Oxford University Press CY - Oxford ER - TY - CHAP A1 - Henß, Jörg A1 - Kugele, Stefan ED - Feichtinger, Kevin ED - Sonnleithner, Lisa ED - Hajiabadi, Hamideh T1 - 22nd Workshop on Automotive Software Engineering T2 - Software Engineering 2025 – Companion Proceedings N2 - Software-driven systems are becoming pivotal, underpinning the majority of innovations in contemporary automobiles. This workshop is poised to explore a plethora of topics pertinent to automotive software development. Attendees will engage in discourse on the most apt methodologies, techniques, and tools essential for navigating the foremost challenges faced by researchers and practitioners in the field. UR - https://doi.org/10.18420/se2025-ws-02 Y1 - 2025 UR - https://doi.org/10.18420/se2025-ws-02 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-57443 SN - 2944-7682 SP - 23 EP - 24 PB - Gesellschaft für Informatik CY - Bonn ER - TY - JOUR A1 - Weihmayr, Daniel A1 - Birkner, Christian A1 - Marzbani, Hormoz A1 - Jazar, Reza T1 - Data-Driven Vehicle Dynamics: Lever-Aging SINDy for Optimization-Based Vehicular Motion Planning JF - IEEE Access N2 - Motion planning remains a crucial challenge for the widespread adoption of autonomous vehicles. This paper presents a novel approach that integrates an empirical plant model within an optimization-based motion planning architecture. The model prioritizes performance and efficiency while maintaining interpretability. We introduce a methodology that utilizes a data-driven approach to derive an interpretable description of the evolution of vehicle states over time using sparse regression. This method allows effective learning from limited datasets, eliminating the need for extensive and expensive data collection. Our approach addresses the trade-off between performance and accuracy, enabling adaptation to diverse driving scenarios. We affirm the efficacy of our methodology via an extensive analysis, evaluating the independent prediction performance across diverse metrics. Additionally, we examine the overall tracking performance when incorporated into an optimization-based framework. Finally, we present a comparative analysis and discuss the subsequent impact on overall motion planning and decision-making in relation to a state-of-the-art single-track model. UR - https://doi.org/10.1109/ACCESS.2025.3594892 Y1 - 2025 UR - https://doi.org/10.1109/ACCESS.2025.3594892 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61981 SN - 2169-3536 VL - 13 SP - 136584 EP - 136597 PB - IEEE CY - New York ER - TY - JOUR A1 - Mehta, Kedar A1 - Zörner, Wilfried T1 - Crop selection in Agri-PV: international review based strategic decision-making model JF - Solar Compass N2 - Agri-Photovoltaics (Agri-PV) is well known for its dual land use, integrating solar energy generation with agricultural production. This not only optimizes land use but also enhances food and energy security. Since Agri-PV is closely linked with crop cultivation, it is not solely about energy generation but also requires careful consideration of crop suitability within Agri-PV installations. Despite its significance, there is limited information available to guide decision-making for crop selection in Agri-PV systems. Selecting suitable crops remains a complex challenge, as factors such as shading tolerance, water requirements, and economic viability vary across different geographical and climatic conditions. This study develops a novel, review-based decision support model for crop selection in Agri-PV systems, synthesizing international research and case studies to provide a structured framework for decision-making. The model is based on 12 main crop typologies and key parameters such as water use, shading adaptability, crop yield/economic potential, and space requirements, derived from 117 research articles and case studies from 25 countries. By leveraging insights from successful international implementations, the model provides a practical framework for policymakers, farmers, and energy planners to enhance the sustainability and efficiency of Agri-PV projects. Findings suggest that crop selection strategies must align with regional climate conditions and PV system design to maximize synergies between energy and food production. High-value crops that require less space and have higher shade tolerance are more suitable for small-scale or decentralized Agri-PV systems. Future research should focus on advanced modeling techniques, AI-driven optimization, and real-world pilot studies to further refine decision-making in Agri-PV deployment. This study contributes to the growing body of knowledge on Agri-PV systems by providing a novel crop suitability matrix for effective decision-making. UR - https://doi.org/10.1016/j.solcom.2025.100143 Y1 - 2025 UR - https://doi.org/10.1016/j.solcom.2025.100143 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62476 SN - 2772-9400 VL - 2025 IS - 16 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Mieruch, Sebastian A1 - Kreps, Gastón A1 - Chouai, Mohamed A1 - Reimers, Felix A1 - Vredenborg, Myriel A1 - Rabe, Benjamin A1 - Tippenhauer, Sandra A1 - Behrendt, Axel T1 - SalaciaML-2-Arctic - a deep learning quality control algorithm for Arctic Ocean temperature and salinity data JF - Frontiers in Marine Science N2 - We have extended a classical quality control (QC) algorithm by integrating a deep learning neural network, resulting in SalaciaML-2-Arctic , a tool for automated QC of Arctic Ocean temperature and salinity profile data. The neural network component was trained on the Unified Database for Arctic and Subarctic Hydrography (UDASH), which has been quality-controlled and labeled by expert oceanographers. SalaciaML-2-Arctic successfully reproduces human expertise by correcting misclassifications made by the classical algorithm, reducing False Negatives (samples incorrectly classified as “bad”) by 96% for temperature and 99% for salinity. When used in combination with a visual post-QC by human experts, it achieves a workload reduction of approximately 60% for temperature and 85% for salinity. All code and data required to reproduce the analysis or apply the method to other datasets are openly available via PANGAEA and GitHub. Moreover, SalaciaML-2-Arctic is accessible as a browser-based application at https://mvre.autoqc.cloud.awi.de, enabling its use without software installation or programming knowledge. UR - https://doi.org/10.3389/fmars.2025.1661208 Y1 - 2025 UR - https://doi.org/10.3389/fmars.2025.1661208 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62935 SN - 2296-7745 VL - 12 PB - Frontiers Media CY - Lausanne ER - TY - CHAP A1 - Schlosser, Alexander A1 - Schuderer, Peter A1 - Franke, Jörg ED - Kohl, Holger ED - Seliger, Günther ED - Dietrich, Franz ED - Vien, Ha Thuc T1 - Sustainability Assessment and Optimization in Construction Site: A Simulation-Based Approach T2 - Decarbonizing Value Chains: Proceedings of the 20th Global Conference on Sustainable Manufacturing (GCSM 2024), October 9–11, 2024, Ho Chi Minh City, Vietnam N2 - The construction industry is currently facing significant challenges. In order to address these challenges, the REMUS simulation model library for the construction industry is being developed. To this end, the physical modules are divided into stationary and mobile modules, as well as information objects. To create the simulation model and conduct the simulation experiment, a requirements cluster with the most important parameters of construction sites is created. The elements of sustainability—environmental, economy, and social aspects—are employed to assess the simulation results and to optimize the model. To this end, corresponding KPIs, methods, and procedures are delineated, which are documented during the various simulation experiments and evaluated subsequently. The equipment and environment exert an influence on the “economy”. This is reflected in the costs associated with the model components and their operation. The area of “environmental” is represented by the consumption of input materials. Alternative consumption and recovery concepts are implemented and compared here. The “social” aspect is represented by the human-machine collaboration. As part of the simulation experiments, the recorded variables are continuously adapted and refined. This process enables the simulation to improve the sustainability of the construction site environment. UR - https://doi.org/10.1007/978-3-031-93891-7_10 Y1 - 2025 UR - https://doi.org/10.1007/978-3-031-93891-7_10 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-62843 SN - 978-3-031-93891-7 SP - 82 EP - 90 PB - Springer CY - Cham ER - TY - JOUR A1 - Kiran, Iqra A1 - Azzam, Mohamed A1 - Endisch, Christian A1 - Butt, Nauman Zafar A1 - Lewerenz, Meinert T1 - Evaluation of Calendar Aging in Cells with Graphite: Silicon Anode Using Float Current Analysis Under the Influence of Voltage Hysteresis JF - Journal of The Electrochemical Society N2 - This study investigates the calendar aging of lithium-ion batteries with graphite-silicon anodes using float current analysis. While float current analysis is already a proven method for assessing aging in cells with graphite-based anodes, the presence of silicon introduces additional complexities due to its voltage hysteresis. We address this by comparing the results for the scaling factor separately for charge and discharge. The scaling factor is initially derived from charge and discharge GITT measurements on fresh cells, including an aging-induced shift among both electrode curves. This approach enables quantification of SEI growth ISEI growth, and cathode lithiation current ICL bridging measured results for float currents with capacity loss rate. As a result, the scaling factor during charge delivered the most meaningful results regarding fitted aging currents. By extending the estimation method based on the Arrhenius equation across temperatures from 5 °C to 50 °C, our model is validated against measured float currents, improving the predictive accuracy of long-term aging trends in silicon-containing anodes. Electrochemical impedance spectroscopy provided further insights into degradation mechanisms, revealing a strong correlation between cathode lithiation by salt decomposition and resistance increase at high voltages (⩾4.15 V), confirmed by pulse tests at 100% SOC showing a sharp resistance increase at elevated voltages. UR - https://doi.org/10.1149/1945-7111/ae0fe8 Y1 - 2025 UR - https://doi.org/10.1149/1945-7111/ae0fe8 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63053 SN - 1945-7111 VL - 172 IS - 10 PB - IOP Publishing CY - Bristol ER -