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Passive hybridization of battery cell and photovoltaic cell: modeling and experimental validation
(2017)
Muli-scale thermos-electrochemical modelling of aging mechanisms in an LFP/graphite lithium-ion cell
(2017)
The paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. In comparison with the engineers, the students often demonstrate lower motivation in learning systematic inventive techniques, like for example TRIZ methodology, and prefer random brainstorming for idea generation. The quality of obtained solutions also depends on the level of completeness of the problem analysis, which is more complex and time consuming in the case of interdisciplinary systems. The paper briefly describes one-semester-course of 60 hours in new product development with the Advanced Innovation Design Approach and TRIZ methodology, in which a typical industrial innovation process for one selected interdisciplinary mechatronic product is modelled.
Modelling and Simulation of Microscale Trigeneration Systems Based on Real- Life Experimental Data
(2017)
For the shift of the energy grid towards a smarter decentralised system flexible microscale trigeneration systems will play an important role due to their ability to support the demand side management in buildings. However to harness their potential modern control methods like model predictive control must be implemented for their optimal scheduling and control. To implement such supervisory control methods, first, simple analytical models representing the behaviour of the components need to be developed. At the Institute of Energy System Technologies in Offenburg we have built a real-life microscale trigeneration plant and present in this paper the models based on experimental data. These models are qualitatively validated and their application in the future for the optimal scheduling problem is briefly motivated.
The collection of selected papers of the TRIZ Future Conference 2017 is in open access and is included to the Innovator, the journal of the European TRIZ Assocation.
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.
Microscale trigeneration systems are highly flexible in their operation and thus offer the technical possibility for peak load shifting in building demand side management. However to harness their potential modern control methods such as model predictive control must be implemented for their optimal scheduling. In literature the need for experimental investigation of microscale trigeneration systems to identify typical characteristics of the components and their interactions has been identified. On a real-life setup control specific information of the components is collected and lessons learnt during commissioning of the equipment is shared. The data is analysed to draw the vital characteristics of the system and it will be used for creating models of the components that can be utilised for optimal control.
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].
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.