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Practical bottlenecks associated with commercialization of Lithium-air cells include capacity limitation and low cycling efficiency. The origin of such losses can be traced to complex electrochemical side reactions and reactant mass transport losses[1]. The efforts to minimize such losses include exploration of various electrolytes with additives[2], and cell component geometry and material design. Given the wide range of options for such materials, it is almost impractical to experimentally setup and characterize all those cells. Consequently, modeling and simulation studies are efficient alternatives to analyze spatially and temporally resolved cell behavior for various combinations of materials[3]. In this study, with the help of a two-dimensional multi physics model, we have focused on the effect of electrode and electrolyte interaction (electrochemistry), choice of electrolyte (species transport), and electrode geometry (electrode design) on the performance of a lithium-air button cell. Figure1a shows the schematics of the 2D axisymmetric computational domain. A comparative analysis of five different electrolytes was performed while focusing on the 2D distribution of local current density and the concentration of electro-chemically active species in the cell, that is, O2and Li+. Using two different cathode configurations, namely, flooded electrode and gas diffusion electrode (GDE)[4] at different cathode thickness, the effect of cell geometry and electrolyte saturation on cell performance was explored. Further, a detailed discussion on electrode volume utilization (cf. Figure1b) is presented via changes in the active volume of cathode that produces 90% of the total current with the cell current density for different combinations of electrolyte saturations and cathode thickness.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
The insufficient lifetime of lithium-ion batteries is one of the major cost driver for mobile applications. The battery pack in vehicles is one of the most expensive single components that practically must be excluded from premature replacement (i.e., before the life span of the other components end). Battery degradation is a complex physicochemical process that strongly depends on operating condition and environment. We present a simulation-based analysis of lithium-ion battery degradation during operation with a standard PHEV test cycle. We use detailed multiphysics (extended Newman-type) cell models that allow the assessment of local electrochemical potential, species and temperature distributions as driving forces for degradation, including solid electrolyte interphase (SEI) formation [1]. Fig. 1 shows an exemplary test cycle and the predicted resulting spatially-averaged SEI formation rate. We apply a time-upscaling approach to extrapolate the degradation analysis over long time scales, keeping physical accuracy while allowing end-of-life assessment [2]. Results are presented for lithium-ion battery cells with graphite/LFP chemistry. The behavior of these cells in terms of degradation propensity, performance, state of charge and other internal states is predicted during long-term cycling. State of health (SOH) is quantified as capacity fade and internal resistance increase as function of operation time.
Message co chairmen
(2017)
The Bluetooth community is in the process to develop mesh technology. This is highly promising as Bluetooth is widely available in Smart Phones and Tablet PCs, allowing an easy access to the Internet of Things. In this paper work, we investigate the performance of Bluetooth enabled mesh networking that we performed to identify the strengths and weaknesses. A demonstrator for this protocol has been implemented by using the Fruity Mesh protocol implementation. Extensive test cases have been executed to measure the performance, the reliability, the power consumption and the delay. For this, an Automated Physical Testbed (APTB), which emulates the physical channels has been used. The results of these measurements are considered useful for the real implementation of Bluetooth; not only for home and building automation, but also for industrial automation.
Elastic constants of components are usually determined by tensile tests in combination with ultrasonic experiments. However, these properties may change due to e.g. mechanical treatments or service conditions during their lifetime. Knowledge of the actual material parameters is key to the determination of quantities like residual stresses present in the medium. In this work the acoustic nonlinearity parameter (ANP) for surface acoustic waves is examined through the derivation of an evolution equation for the amplitude of the second harmonic. Given a certain depth profile of the third-order elastic constants, the dependence of the ANP with respect to the input frequency is determined and on the basis of these results, an appropriate inversion method is developed. This method is intended for the extraction of the depth dependence of the third-order elastic constants of the material from second-harmonic generation and guided wave mixing experiments, assuming that the change in the linear Rayleigh wave velocity is small. The latter assumption is supported by a 3D-FEM model study of a medium with randomly distributed microcracks as well as theoretical works on this topic in the literature.
Zerstörungsfreie Verfahren zur Messung von Eigenspannungen erfordern, abhängig vom gewählten Verfahren, die Kenntnis gewisser Kopplungskonstanten. Im Falle von Ultraschallmessverfahren sind das neben den elastischen Konstanten zweiter Ordnung (SOEC) vor allem die Konstanten dritter Ordnung (TOEC). Elastische Konstanten fester, metallischer Bauteile werden in der Regel in Zugversuchen bestimmt. Zur Ermittlung der TOEC werden diese mit Ultraschallmessmethoden kombiniert. Durch äußere Einflüsse, wie etwa mechanische Nachbehandlungen der zu untersuchenden Bauteile können sich diese Konstanten jedoch ändern und müssen folglich direkt am veränderten Material bestimmt werden. Mithilfe von Simulationen wird die Ausbreitung der zweiten Harmonischen und der nichtlinear erzeugten Oberflächenwellen in Wellenmischexperimenten analysiert und der akustische Nichtlinearitätsparameter (ANP) bzw. der Kopplungsparameter aus der Amplitudenentwicklung berechnet. Insbesondere wird untersucht, welchen Einfluss ein gegebenes Tiefenprofil der TOEC auf den ANP hat (Vorwärtsproblem) und inwiefern sich aus den Messungen des ANP auf ein vorliegendes Tiefenprofil der TOEC schließen lässt (inverses Problem). Außerdem wird diskutiert, welchen Einfluss lokale Änderungen der SOEC auf den ANP haben können und wie groß diese Änderungen sein dürfen, um die TOEC dennoch bestimmen zu können. Die Untersuchungen hierzu wurden auf der Basis eines 3D-FEM Modells mit zufällig orientierten Mikrorissen durchgeführt. Die numerischen Rechnungen zeigen dabei auch eine gute Übereinstimmung mit einem aus der Literatur bekannten und für dieses Problem erweiterten, analytischen Modell. Neben der rissinduzierten Nichtlinearität kann bei diesem auch die Gitternichtlinearität berücksichtigt werden.
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.
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.
Heart rhythm model and simulation of electrophysiological studies and high-frequency ablations
(2017)
Background: The simulation of complex cardiologic structures has the potential to replace clinical studies due to its high efficiency regarding time and costs. Furthermore, the method is more careful for the patients’ health than the conventional ways. The aim of the study was to create an anatomic CAD heart rhythm model (HRM) as accurate as possible, and to show its usefulness for cardiac electrophysiological studies (EPS) and high-frequency (HF) ablations.
Methods: All natural heart components of the new HRM were based on MRI records, which guaranteed electronic functionality. The software CST (Computer Simulation Technology, Darmstadt) was used for the construction, while CST’s material library assured genuine tissue properties. It should be applicable to simulate different heart rhythm diseases as well as various diffusions of electromagnetic fields, caused by electrophysiological conduction, inside the heart tissue.
Results: It was achievable to simulate normal sinus rhythm and fourteen different heart rhythm disturbance with different atrial and ventricular conduction delays. The simulated biological excitation of healthy and sick HRM were plotted by simulated electrodes of four polar right atrial catheter, six polar His bundle catheter, ten polar coronary sinus catheter, four polar ablation catheter and eight polar transesophageal left cardiac catheter (Fig.). Accordingly, six variables were rebuilt and inserted into the anatomic HRM in order to establish heart catheters for ECG monitoring and HF ablation. The HF ablation catheters made it possible to simulate various types of heart rhythm disturbance ablations with different HF ablation catheters and also showed a functional visualisation of tissue heating. The use of tetrahedral meshing HRM made it attainable to store the results faster accompanied by a higher degree of space saving. The smart meshing function reduced unnecessary high resolutions for coarse structures.
Conclusions: The new HRM for EPS simulation may be additional useful for simulation of heart rhythm disturbance, cardiac pacing, HF ablation and for locating and identification of complex fractioned signals within the atrium during atrial fibrillation HF ablation.