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In this work, the effect of low air relative humidity on the operation of a polymer electrolyte membrane fuel cell is investigated. An innovative method through performing in situ electrochemical impedance spectroscopy is utilised to quantify the effect of inlet air relative humidity at the cathode side on internal ionic resistances and output voltage of the fuel cell. In addition, algorithms are developed to analyse the electrochemical characteristics of the fuel cell. For the specific fuel cell stack used in this study, the membrane resistance drops by over 39 % and the cathode side charge transfer resistance decreases by 23 % after increasing the humidity from 30 % to 85 %, while the results of static operation also show an increase of ∼2.2 % in the voltage output after increasing the relative humidity from 30 % to 85 %. In dynamic operation, visible drying effects occur at < 50 % relative humidity, whereby the increase of the air side stoichiometry increases the drying effects. Furthermore, other parameters, such as hydrogen humidification, internal stack structure, and operating parameters like stoichiometry, pressure, and temperature affect the overall water balance. Therefore, the optimal humidification range must be determined by considering all these parameters to maximise the fuel cell performance and durability. The results of this study are used to develop a health management system to ensure sufficient humidification by continuously monitoring the fuel cell polarisation data and electrochemical impedance spectroscopy indicators.
Critical quantitative evaluation of integrated health management methods for fuel cell applications
(2024)
Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system.
In der wasserbaulichen Forschung werden neben klassischen Messinstrumenten zunehmend kamerabasierte Verfahren genutzt. Diese erlauben neben der Bestimmung von Fließgeschwindigkeiten auch die Detektion der freien Wasseroberfläche oder zeitliche Vermessung von Kolken. Durch die hohen räumlichen und zeitlichen Auflösungen, welche neueste Kamerasensoren liefern, können neue Erkenntnisse in turbulenten, komplexen Strömungen gewonnen werden. Auch in der Praxis können diese Verfahren mit geringem Aufwand wichtige Daten liefern.
Direct sampling method via Landweber iteration for an absorbing scatterer with a conductive boundary
(2024)
In this paper, we consider the inverse shape problem of recovering isotropic scatterers with a conductive boundary condition. Here, we assume that the measured far-field data is known at a fixed wave number. Motivated by recent work, we study a new direct sampling indicator based on the Landweber iteration and the factorization method. Therefore, we prove the connection between these reconstruction methods. The method studied here falls under the category of qualitative reconstruction methods where an imaging function is used to recover the absorbing scatterer. We prove stability of our new imaging function as well as derive a discrepancy principle for recovering the regularization parameter. The theoretical results are verified with numerical examples to show how the reconstruction performs by the new Landweber direct sampling method.
We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.
Bald eine Dekade ist es her, dass diese annähernd mantraartig wiederholte Phrase Unternehmen zur Umsetzung datenschutzrechtlicher Vorgaben incentivierte. Was ist davon geblieben? Nur wenige in Deutschland verhängte Bußgelder erreichten Millionenhöhe. Hintergrund ist (auch) das deutsche Ordnungswidrigkeitenrecht, welches in einem Spannungsverhältnis zu den Vorgaben der DS-GVO steht. Ein Bußgeldbescheid der Berliner Datenschutzaufsicht gegen die Deutsche Wohnen sollte Auslöser eines langen, fortdauernden Rechtsstreits werden. Auf Vorlage des KG hatte der EuGH in der Rechtssache C-807/21 („Deutsche Wohnen“) erstmals Gelegenheit, sich zur Frage der Bußgeldhaftung zu positionieren.
Seit Ende 2022 prägt das Schlagwort „Künstliche Intelligenz“ (KI) nicht nur den rechtswissenschaftlichen Diskurs. Die allgemeine Verfügbarkeit von generativen KI-Modellen, allen voran die großen Sprachmodelle (Large Language Models, kurz: LLM) wie ChatGPT von OpenAI oder Bing AI von Microsoft, erfreuen sich größter Beliebtheit: LLM sind in der Lage, auf Grundlage statistischer Methoden – eine entsprechende Schnittstelle (Interface) vorausgesetzt – auch technisch wenig versierten Nutzern verständliche Antworten auf ihre Fragen zu liefern. Dabei werden nicht nur umfassend Nutzerdaten verarbeitet, sondern auch auf weitere personenbezogene Daten zugegriffen sowie neue Daten erzeugt. Der Beitrag geht der Frage nach, welche spezifischen datenschutzrechtlichen Herausforderungen sich für Unternehmen beim Einsatz solcher LLM stellen.