05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access A dual‐layered anode buffer layer structure for all solid‐state batteries(2024) Lu, Yushi; Chang, Hansen Michael; Birke, Kai PeterOver the past few decades, lithium‐ion batteries have garnered considerable attention, especially for their use in electric vehicles (EVs). In recent years, solid‐state batteries have become increasingly popular due to their excellent safety features and potential for high energy density. However, solid‐state batteries with lithium metal anodes present challenges in terms of electrochemical reactivity and cost. To address these challenges, alternative anode systems such as the “anode‐free” approach are being explored. In this study, we introduced a dual‐layered anode comprising a primary layer of physically vapor‐deposited zinc and a secondary layer of carbon black, focusing on investigating the influence of varying thicknesses of the lithiophilic zinc layer on cell cycling performance. Among the three different zinc thicknesses chosen for this purpose - categorized as thin (286 nm), medium (1.802 μm), and thick (6.519 μm) - the dual‐layered anode buffer layer was analyzed in a single‐layer full pouch cell. An in‐depth investigation into the lithium‐zinc alloying behavior was conducted through post‐mortem analysis. From the results, we found that the combination of the zinc layer with the carbon black layer improved cell cycling performance in terms of discharge capacity retention compared to a single layer of either zinc or carbon black. The cycling performance of this dual‐layered anode could be further enhanced by optimizing the zinc layer thickness, likely due to the irreversible alloying step of zinc and lithium. Among the various thicknesses evaluated, the thin zinc layer (286 nm) combined with the carbon black layer demonstrated the most promising cycling performance in all solid‐state batteries.Item Open Access A bidirectional wireless power transfer system with integrated near-field communication for e-vehicles(2024) Ye, Weizhou; Parspour, NejilaThis paper presents the design of a bidirectional wireless power and information transfer system. The wireless information transfer is based on near-field technology, utilizing communication coils integrated into power transfer coils. Compared with conventional far-field-based communication methods (e.g., Bluetooth and WLAN), the proposed near-field-based communication method provides a peer-to-peer feature, as well as lower latency, which enables the simple paring of a transmitter and a receiver for power transfer and the real-time updating of control parameters. Using the established communication, control parameters are transmitted from one side of the system to another side, and the co-control of the inverter and the active rectifier is realized. In addition, this work innovatively presents the communication-signal-based synchronization of an inverter and a rectifier, which requires no AC current sensing in the power path and no complex algorithm for stabilization, unlike conventional current-based synchronization methods. The proposed information and power transfer system was measured under different operating conditions, including aligned and misaligned positions, operating points with different charging powers, and forward and reverse power transfer. The results show that the presented prototype allows a bidirectional power transfer of up to 1.2 kW, and efficiency above 90% for the power ranges from 0.6 kW to 1.2 kW was obtained. Furthermore, the integrated communication is robust to the crosstalk from the power transfer and misalignment, and a zero BER (bit error rate) and ultra-low latency of 15.36 µs are achieved. The presented work thus provides a novel solution to the synchronization and real-time co-control of an active rectifier and an inverter in a wireless power transfer system, utilizing integrated near-field-based communication.Item Open Access Optimising light electric vehicle capabilities through a new battery main switch topology with emphasis on battery heating(2025) Oehl, Joachim; Birke, Kai Peter (Prof. Dr.-Ing.)Item Open Access Generierung synthetischer Trainingsdaten zur Leistungssteigerung bei maschinellen Lernaufgaben in der Automatisierungstechnik(Düren : Shaker Verlag, 2026) Vietz, Hannes; Weyrich, Michael (Prof. Dr.-Ing. Dr. h. c.)Die Anwendung maschinell gelernter Algorithmen gewinnt in der Automatisierungstechnik zunehmend an Bedeutung, da sie datenbasierte Problemlösungen ermöglicht. Ein wesentlicher Engpass für den Einsatz leistungsfähiger Deep-Learning-Modelle im Feldeinsatz ist jedoch die Verfügbarkeit umfangreicher, gelabelter Trainingsdaten, deren Akquisition in der industriellen Praxis oft hohe Kosten und Betriebsanpassungen erfordert. Ein vielversprechender Ansatz zur Lösung dieses Problems liegt in der Nutzung synthetischer Daten, die das Training ohne den Zugang zu großen realen Datensätzen ermöglichen. Jedoch erzeugen derzeitige Verfahren häufig redundante Szenarien, und es bleibt unklar, welche spezifischen synthetischen Daten zur Verbesserung der Modellgüte beitragen. In dieser Dissertation wird ein Konzept zur leistungssteigernden Generierung synthetischer Daten entwickelt, das spezifisch darauf ausgerichtet ist, bestehende Schwächen in trainierten Modellen zu adressieren und deren Leistungsmetriken gezielt zu verbessern. Das iterative Konzept umfasst ein generatives neuronales Netz, eine Steuerungskomponente zur Optimierung der Datengenerierung sowie eine Entscheidungslogik, die bestimmt, ob ein generierter Datenpunkt für das Training verwendet werden sollte. Die Effektivität des Konzepts wird anhand von Anwendungsfällen aus der Automatisierungstechnik demonstriert: Der MNIST-Datensatz zur Handschrifterkennung dient als kontrollierte Umgebung zur Bewertung der Fähigkeit des Generators, realitätsnahe, interpretierbare Bilddaten zu erzeugen; ein datengetriebenes 5G-Positionsbestimmungssystem wird genutzt, um die Übertragbarkeit des Konzepts auf eine industrielle Produktionsumgebung zu belegen, wobei eine signifikante Verbesserung der Modellgenauigkeit und Generalisierung gezeigt wird; der dritte Anwendungsfall untersucht die optische Objektdetektion in einer Industrieumgebung ohne verfügbare öffentliche Datensätze und zeigt das Potenzial des Konzepts, spezifische industrielle Anforderungen zu adressieren. Die Evaluierung zeigt, dass das vorgestellte Konzept in der Lage ist, realistische und gezielte Trainingsdaten zu generieren, die die Robustheit und Leistungsfähigkeit neuronaler Netze im Kontext maschinellen Lernens und industrieller Automatisierung signifikant erhöhen können. In allen Anwendungsfällen führte der Einsatz der synthetisch generierten Daten zu einer substantiellen Verbesserung der Modellgüte, was das Potenzial des Ansatzes für praktische Anwendungen in der Automatisierungstechnik unterstreicht.Item Open Access Analytic free-energy expression for the 2D-Ising model and perspectives for battery modeling(2023) Markthaler, Daniel; Birke, Kai PeterAlthough originally developed to describe the magnetic behavior of matter, the Ising model represents one of the most widely used physical models, with applications in almost all scientific areas. Even after 100 years, the model still poses challenges and is the subject of active research. In this work, we address the question of whether it is possible to describe the free energy A of a finite-size 2D-Ising model of arbitrary size, based on a couple of analytically solvable 1D-Ising chains. The presented novel approach is based on rigorous statistical-thermodynamic principles and involves modeling the free energy contribution of an added inter-chain bond DAbond(b, N) as function of inverse temperature b and lattice size N. The identified simple analytic expression for DAbond is fitted to exact results of a series of finite-size quadratic N N-systems and enables straightforward and instantaneous calculation of thermodynamic quantities of interest, such as free energy and heat capacity for systems of an arbitrary size. This approach is not only interesting from a fundamental perspective with respect to the possible transfer to a 3D-Ising model, but also from an application-driven viewpoint in the context of (Li-ion) batteries where it could be applied to describe intercalation mechanisms.Item Open Access Additively manufactured transverse flux machine components with integrated slits for loss reduction(2022) Kresse, Thomas; Schurr, Julian; Lanz, Maximilian; Kunert, Torsten; Schmid, Martin; Parspour, Nejila; Schneider, Gerhard; Goll, DagmarLaser powder bed fusion (L-PBF) was used to produce stator half-shells of a transverse flux machine from pure iron (99.9% Fe). In order to reduce iron losses in the bulk components, radially extending slits with a nominal width of 150 and 300 µm, respectively, were integrated during manufacturing. The components were subjected to a suitable heat treatment. In addition to a microscopic examination of the slit quality, the iron losses were also measured using both a commercial and a self-developed measurement setup. The investigations showed the iron losses can be reduced by up to 49% due to the integrated slits and the heat treatment.Item Open Access Laser doping for silicon solar cells : modeling and application(2024) Hassan, Mohamed; Werner, Jürgen H. (Prof. Dr. rer. nat. habil.)In meiner Dissertation geht es um die Simulation des Laserdotierungsprozess der Oberfläche des Siliziumwafers um hoch effizienten Solarzellen herzustellen. Die Simulation ermöglicht die genaue Vorhersage der Dimensionen eines dotierten Bereiches. Das hat ermöglicht, nicht nur die Abhängigkeit des ergebenden Schichtleitwerts von der benutzten Rastergeschwindigkeit des Laserstrahls auf die Siliziumoberfläche zu verstehen, sondern auch der Schichtleitwert einer laserdotierten Schicht basierend auf ein einfaches geometrisches Modell vorherzusagen.Item Open Access Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes(2026) Ecker, Veronika; Yang, Bin; Gatidis, Sergios; Küstner, ThomasAging is a complex, multifactorial process, influencing disease risk and overall health. While chronological age (CA) is widely used in clinical practice, it fails to capture individual aging trajectories. Current approaches to estimate biological age (BA) often focus on single organs or predefined clinical biomarkers, limiting comprehensive assessment. We introduce a novel, purely imaging-driven deep learning framework for organ-specific BA estimation across seven organ systems. Our uncertainty-aware ResNet-based models autonomously learned aging-related features from imaging data in 70,000 UK Biobank participants, eliminating manual feature selection biases. Training on a healthy cohort, where CA approximates BA, allows learning normative aging patterns. When applied to a broader cohort, deviations from typical aging indicate older or younger BA. Our findings demonstrate the feasibility of BA estimation, even in organs with subtle aging features. While aging is largely heterogeneous across organs, we also identified correlations in aging patterns. We further showed that accelerated aging is prognostic of mortality and health outcomes, offering insights for personalized assessments.Item Open Access Software product line testing : a systematic literature review(2024) Agh, Halimeh; Azamnouri, Aidin; Wagner, StefanA Software Product Line (SPL) is a software development paradigm in which a family of software products shares a set of core assets. Testing has a vital role in both single-system development and SPL development in identifying potential faults by examining the behavior of a product or products, but it is especially challenging in SPL. There have been many research contributions in the SPL testing field; therefore, assessing the current state of research and practice is necessary to understand the progress in testing practices and to identify the gap between required techniques and existing approaches. This paper aims to survey existing research on SPL testing to provide researchers and practitioners with up-to-date evidence and issues that enable further development of the field. To this end, we conducted a Systematic Literature Review (SLR) with seven research questions in which we identified and analyzed 118 studies dating from 2003 to 2022. The results indicate that the literature proposes many techniques for specific aspects (e.g., controlling cost/effort in SPL testing); however, other elements (e.g., regression testing and non-functional testing) still need to be covered by existing research. Furthermore, most approaches are evaluated by only one empirical method, most of which are academic evaluations. This may jeopardize the adoption of approaches in industry. The results of this study can help identify gaps in SPL testing since specific points of SPL Engineering still need to be addressed entirely.Item Open Access Not all features are equal: feature selection based on deep learning(2025) Liao, Yiwen; Yang, Bin (Prof. Dr.-Ing)