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Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
Wie man die Vorlesung "Technische Mechanik 1 - Statik" für alle Beteiligten dynamisch gestaltet
(2017)
Lehrende nehmen vielfältige Veränderungen, insbesondere bei Studienanfängern wahr: Vorkenntnisse, Aufnahme- und Konzentrationsfähigkeit werden zunehmend heterogener. In der Vorlesung „Technische Mechanik 1“ wurde darauf konstruktiv reagiert, indem der Ablauf und die Struktur verändert wurden. Aufgaben und ihre Lösungen stehen im Mittelpunkt des Unterrichts. Neben der Lehrenden als aktiv Handelnde wird jeder Studierende im Lauf des Semesters in den Ablauf integriert und muss individuelle Lösungen der verteilten Aufgaben präsentieren. Im Vergleich entwickeln die Studierenden durch „Lernen am Modell“ dadurch ihre methodischen und fachlichen Fähigkeiten weiter. Um den Studierenden die Relevanz der behandelten Themenbereiche zu verdeutlichen wurden spezielle Aufgaben mit einem lebensweltlichem Bezug entwickelt. Befragungen zeigen, dass die Studierenden von den vielfältigen interaktiven Lernangeboten profitieren und die entwickelten Kompetenzen auch auf andere Lernsituationen übertragen.
Process engineering focuses on the design, operation, control and optimization of chemical, physical and biological processes and has applications in many industries. Process Intensification is the key development approach in the modern process engineering. The proposed Advanced Innovation Design Approach (AIDA) combines the holistic innovation process with the systematic analytical and problem solving tools of the theory of inventive problem solving TRIZ. The present paper conceptualizes the AIDA application in the field of process engineering and especially in combination with the Process Intensification. It defines the AIDA innovation algorithm for process engineering and describes process mapping, problem ranking, and concept design techniques. The approach has been validated in several industrial case studies. The presented research work is a part of the European project “Intensified by Design® platform for the intensification of processes involving solids handling”.
Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
Viele hochbeanspruchte Bauteile müssen zur Erfüllung ihres konstruktiven Zwecks mit Durchdringungskerben versehen werden. Infolge der gegenseitigen Wechselwirkung gelten für die Kerbwirkung dieser Art von Mehrfachkerben andere Gesetzmäßigkeiten als bei Einzelkerben. Die Weiterentwicklung der Lehre von der Tragfähigkeitsberechnung höchstbeanspruchter Maschinenelemente macht es notwendig, sich mit der Durchdringungskerbwirkung eingehend zu befassen. Thum und Svenson [1] entwickelten im Jahr 1949 ein Näherungsverfahren zur Abschätzung der Formzahl an einem zugbelasteten Stab mit Durchdringungskerben. In vielen Lehrbüchern findet dieses Verfahren Anwendung. Aus heutiger Sicht erscheint die Eignung der aus diesem Ansatz erzielten Ergebnisse als dringend überprüfungswürdig. Das thum’sche Verfahren wird unter die Lupe genommen. Der hier vorliegende Beitrag präsentiert mit Hilfe der Finiten-Elemente-Methode (FEM) neue Untersuchungsergebnisse an zugbeanspruchten Stäben mit Halbkreisnut und überlagerter Querbohrung. Diese ergaben, dass die Berechnung nach [1] Lücken aufweist. Ihr Ansatz stellt für den heutigen Entwicklungsstand eine mit zu großen Abweichungen behaftete Näherungshypothese dar.
This paper describes the Sweaty II humanoid adult size robot trying to qualify for the RoboCup 2017 adult size humanoid competition. Sweaty came 2nd in RoboCup 2016 adult size league. The paper describes the main characteristics of Sweaty that made this success possible, and improvements that have been made or are planned to be implemented for RoboCup 2017.
Technology and computer applications influence our daily lives and questions arise concerning the role of artificial intelligence and decision-making algorithms. There are warning voices, that computers can, in theory, emulate human intelligence-and exceed it. This paper points out that a replacement of humans by computers is unlikely, because human thinking is characterized by cognitive heuristics and emotions, which cannot simply be implemented in machines operating with algorithms, procedural data processing or artificial neural networks. However, we are going to share our responsibilities with superior computer systems, which are tracking and surveying all of our digital activities, whereas we have no idea of the decision-making processes inside the machines. It is shown that we need a new digital humanism defining rules of computer responsibilities to avoid digital totalism and comprehensive monitoring and controlling of individuals within the planet Earth.
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products (e.g., fuel cells, metal/air cells, electrolyzers) offer an additional observable, that is, the gas pressure. The dynamic coupling of current and/or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. This sensitivity can be exploited for model parameterization and validation. A general analysis of EPIS is presented, which shows the necessity of model-based interpretation of the complex EPIS shapes in the Nyquist plot (cf. Figure). We then present EPIS simulations for two different electrochemical cells: (1) a sodium/oxygen battery cell and (2) a hydrogen/air fuel cell. We use 1D or 2D electrochemical and transport models to simulate current excitation/pressure detection or pressure excitation/voltage detection. The results are compared to first EPIS experimental data available in literature [2,3].