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With increasing flexible AC transmission system (FACTS) devices in operation, like the most versatile unified power flow controller (UPFC), the AC/DC transmission flexibility and power system stability have been suffering unprecedented challenge. This paper introduces the user-defined modeling (UDM) method into the UPFC dynamic modeling process, to deal with the challenging requirements of power system operation. This has also been verified using a leading-edge stability analysis software named DSATools TM in the IEEE-39 bus benchmark system. The characteristics of steady-state and dynamic responses are compared and analyzed under different conditions. Furthermore, simulation results prove the feasibility and effectiveness of the proposed UPFC in terms of both the independent regulation of power flow and the improvement of transient stability.
One of the challenges in humanoid robotics is motion control. Interacting with humans requires impedance control algorithms, as well as tackling the problem of the closed kinematic chains which occur when both feet touch the ground. However, pure impedance control for totally autonomous robots is difficult to realize, as this algorithm needs very precise sensors for force and speed of the actuated parts, as well as very high sampling rates for the controller input signals. Both requirements lead to a complex and heavy weight design, which makes up for heavy machines unusable in RoboCup Soccer competitions.
A lightweight motor controller was developed that can be used for admittance and impedance control as well as for model predictive control algorithms to further improve the gait of the robot.
Heart rhythm model and simulation of electrophysiological studies and high-frequency ablations
(2017)
Background: Target of the study was to create an accurate anatomic CAD heart rhythm model, and to show its usefulness for cardiac electrophysiological studies and high-frequency ablations. The method is more careful for the patients’ health and has the potential to replace clinical studies due to its high efficiency regarding time and costs.
Methods: All natural heart components of the new HRM were based on MRI records, which guaranteed electronic functionality. The software CST 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 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. 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.
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.
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.
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.
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.
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.
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.
Message co chairmen
(2017)
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.
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.
Computing Aggregates on Autonomous, Self-organizing Multi-Agent System: Application "Smart Grid"
(2017)
Decentralized data aggregation plays an important role in estimating the state of the smart grid, allowing the determination of meaningful system-wide measures (such as the current power generation, consumption, etc.) to balance the power in the grid environment. Data aggregation is often practicable if the aggregation is performed effectively. However, many existing approaches are lacking in terms of fault-tolerance. We present an approach to construct a robust self-organizing overlay by exploiting the heterogeneous characteristics of the nodes and interlinking the most reliable nodes to form an stable unstructured overlay. The network structure can recover from random state perturbations in finite time and tolerates substantial message loss. Our approach is inspired from biological and sociological self-organizing mechanisms.
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.
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset where, a subspace is the subset of dimensions of the data. But exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, thus, parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage, firstly, the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation has shown linear speedup. Secondly, we are developing an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
In medical applications wireless technologies are not widely spread. Today they are mainly used in non latency-critical applications where reliability can be guaranteed through retransmission protocols and error correction mechanisms. By using retransmission protocols within the disturbed shared wireless channel latency will increase. Therefore retransmission protocols are not sufficient for removing latency-critical wired connections within operating rooms such as foot switches. Todays research aims to improve reliability through the physical characteristics of the wireless channel by using diversity methods and more robust modulation. In this paper an Architecture for building up a reliable network is presented. The Architecture offers the possibility for devices with different reliability, latency and energy consumption requirements to participate. Furthermore reliability, latency and energy consumption are scalable for every single participant.