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Summary of the 8th Workshop on Metallization and Interconnection for Crystalline Silicon Solar Cells
(2019)
This article gives a summary of the 8th Metallization and Interconnection workshop and attempts to place each contribution in the appropriate context. The field of metallization and interconnection continues to progress at a very fast pace. Several printing techniques can now achieve linewidths below 20 μm. Screen printing is more than ever the dominating metallization technology in the industry, with finger widths of 45 μm in routine mass production and values below 20 μm in the lab. Plating technology is also being improved, particularly through the development of lower cost patterning techniques. Interconnection technology is changing fast, with introduction in mass production of multiwire and shingled cells technologies. New models and characterization techniques are being introduced to study and understand in detail these new interconnection technologies.
We present an innovative decision support system (DSS) for distribution system operators (DSO) based on an artificial neural network (ANN). A trained ANN has the ability to recognize problem patterns and to propose solutions that can be implemented directly in real time grid management. The principle functionality of this ANN based optimizer has been demonstrated by means of a simple virtual electrical grid. For this grid, the trained ANN predicted the solution minimizing the total line power dissipation in 98 percent of the cases considered. In 99 percent of the cases, a valid solution in compliance with the specified operating conditions was found. First ANN tests on a more realistic grid, calibrated with household load measurements, revealed a prediction rate between 88 and 90 percent depending on the optimization criteria. This approach promises a faster, more cost-efficient and potentially secure method to support distribution system operators in grid management.
We present an alternative approach to grid management in low voltage grids by the use of artificial intelligence. The developed decision support system is based on an artificial neural network (ANN). Due to the fast reaction time of our system, real time grid management will be possible. Remote controllable switches and tap changers in transformer stations are used to actively manage the grid infrastructure. The algorithm can support the distribution system operators to keep the grid in a safe state at any time. Its functionality is demonstrated by a case study using a virtual test grid. The ANN achieves a prediction rate of around 90% for the different grid management strategies. By considering the four most likely solutions proposed by the ANN, the prediction rate increases to 98.8%, with a 0.1 second increase in the running time of the model.
Das hier vorgestellte Netzoptimierungstool kann dem Verteilnetzbetreiber bei einem Störfall im Netz in Echtzeit eine Lösung zur Steuerung seiner Betriebsmittel vorschlagen. Dadurch kann das bestehende Netz optimal genutzt werden und ein kostenintensiver Netzausbau im Mittel- und Niederspannungsnetz verringert oder sogar verhindert werden. Als Grundlage für den Netzoptimierer dient ein künstliches neuronales Netz (KNN). Zum Training des KNN wurden Störfälle generiert, die auf reellen Erzeugungs- und Lastprofilen aus dem CoSSMic-Projekt basieren [1]. Für jeden Störfall wurde aus allen möglichen und sinnvollen Netzkonfigurationen eine optimierte Netztopologie anhand von Lastflussberechnungen ermittelt. Durch die Variation der Stufenschalter der Transformatoren und der Stellungen aller installierten Schalter im Netz wurde berechnet, wie der Stromfluss gelenkt werden muss, damit keines der Betriebsmittel die zulässigen Belastungsgrenzen mehr überschreitet. Für ein virtuelles Testnetz konnte mit einem trainierten KNN zu 90 Prozent die optimale Lösung des jeweiligen Störfalls erkannt werden. Durch die Anwendung der N-Best Methode konnte die Vorhersagewahrscheinlichkeit auf annähernd 99 Prozent erhöht werden.
Path planning and collision avoidance for safe autonomous vessel navigation in dynamic environments
(2017)
This thesis deals with the object tracking problem of multiple extended objects. For instance, this tracking problem occurs when a car with sensors drives on the road and detects multiple other cars in front of it. When the setup between the senor and the other cars is in a such way that multiple measurements are created by each single car, the cars are called extended objects. This can occur in real world scenarios, mainly with the use of high resolution sensors in near field applications. Such a near field scenario leads a single object to occupy several resolution cells of the sensor so that multiple measurements are generated per scan. The measurements are additionally superimposed by the sensor’s noise. Beside the object generated measurements, there occur false alarms, which are not caused by any object and sometimes in a sensor scan, single objects could be missed so that they not generate any measurements.
To handle these scenarios, object tracking filters are needed to process the sensor measurements in order to obtain a stable and accurate estimate of the objects in each sensor scan. In this thesis, the scope is to implement such a tracking filter that handles the extended objects, i.e. the filter estimates their positions and extents. In context of this, the topic of measurement partitioning occurs, which is a pre-processing of the measurement data. With the use of partitioning, the measurements that are likely generated by one object are put into one cluster, also called cell. Then, the obtained cells are processed by the tracking filter for the estimation process. The partitioning of measurement data is a crucial part for the performance of tracking filter because insufficient partitioning leads to bad tracking performance, i.e. inaccurate object estimates.
In this thesis, a Gaussian inverse Wishart Probability Hypothesis Density (GIW-PHD) filter was implemented to handle the multiple extended object tracking problem. Within this filter framework, the number of objects are modelled as Random Finite Sets (RFSs) and the objects’ extent as random matrices (RM). The partitioning methods that are used to cluster the measurement data are existing ones as well as a new approach that is based on likelihood sampling methods. The applied classical heuristic methods are Distance Partitioning (DP) and Sub-Partitioning (SP), whereas the proposed likelihood-based approach is called Stochastic Partitioning (StP). The latter was developed in this thesis based on the Stochastic Optimisation approach by Granström et al. An implementation, including the StP method and its integration into the filter framework, is provided within this thesis.
The implementations, using the different partitioning methods, were tested on simulated random multi-object scenarios and in a fixed parallel tracking scenario using Monte Carlo methods. Further, a runtime analysis was done to provide an insight into the computational effort using the different partitioning methods. It emphasized, that the StP method outperforms the classical partitioning methods in scenarios, where the objects move spatially close. The filter using StP performs more stable and with more accurate estimates. However, this advantage is associated with a higher computational effort compared to the classical heuristic partitioning methods.
The Universal Serial Bus (USB) is a worldwide standard for communication between peripherals. Nowadays USB interfaces are integrated in almost every device. It will be used to connect peripherals and computers. USB devices communicate between pieces of hardware, i.e., cable, plug and socket. Thus, there exists different standardized communication protocols depending on the application. In case of different communication protocols, it is necessary to verify them, that devices, no matter of country, can communicate to each other.
The verifying process is very important in order that companies can sell products with such interfaces and their designated logo, to guaranty a certain standard, which is provided all over the world. Devices have to complete various test procedures to get certified. Otherwise a company is not allowed to use logos ore designations, i.e., USB or information about data rates, i.e., SuperSpeed. Furthermore, successfully completed test procedures prove that a device works properly based on a professional method.
The Human-Machine-Interface (HMI) device family from the company Marquardt Verwaltungs GmbH, is using the USB interface for service and data exchange purposes. The service application is realized through a Virtual COM Port (VCP), based on the Communication Device Class (CDC) of USB. On the other side they want to use the Media Transfer Protocol (MTP) based on the Still Image Capture Device class for data exchange between the HMI device and a computer. Of course, the integrated circuit, which implements the USB interface on the circuit board of the HMI device has to be verified, too. The verification will be performed through an external company. In contrast, the communication protocols do not need a verification but must be examined. The identification of an USB class in an operating system does neither guaranty a proper functionality nor comply with a professional scientific method.
To accelerate the development of a project as well as to reduce the production costs, it is a significant advantage to own a test environment. Microsoft provides the possibility to verify devices on Windows operating systems. Therefor they invented the Windows Certification Program, which contains software that can be used for verification purposes. One of them is the Windows Hardware Certification Kit (HCK) we want to set up and set the HMI device under test, to examine the implementation of MTP.
Thus, it is possible to use the HCK test setup during a development process to examine a current implementation without a big effort, i.e., cooperation with an external company or similarly approaches, which delays the whole development process by far.
Techniken zur Energiewende - studentische Fachkonferenz im Masterstudiengang Elektrische Systeme
(2013)
Die studentische Fachkonferenz im Rahmen des Seminars im Masterstudiengang Elektrische Systeme in der Fakultät für Elektrotechnik und Informationstechnik wird zum sechsten Mal veranstaltet.
Alle Studierenden erarbeiten unter dem vorgegebenen Rahmenthema eigene Beiträge, recherchieren, ergänzen, stellen die aktuellen Erkenntnisse zu wissenschaftlichen Publikationen zusammen.
Die Energiewende ist seit einigen Jahren ein heiß diskutiertes Thema. Die dezentrale Energieversorgung
unter Anwendung erneuerbarer Quellen, insbesondere Wind- und Solarkraft, ist langfristig gesehen die
einzige Antwort auf die Ausbeutung der Erde und Zerstörung der Umwelt durch Gewinnung nichtregenerativer
Energien, insbesondere Öl, Erdgas und Uran. Allerdings gibt es noch viele Bereiche, die intensive wissenschaftliche und entwicklungstechnische Arbeiten benötigen. Wie aus dem Titel durch Verwendung des Wortes „zur“ anstatt „der“ schon erkennbar, werden in dieser Fachtagung weniger die Techniken betrachtet, die schon zum Einsatz kommen, sondern zukünftige Techniken, die gedanklich auf Papier gebracht wurden, oder inzwischen das Stadium der Machbarkeitsstudie erreicht haben.
Das Thema Energiewende beinhaltet ein sehr breites Feld von Techniken. Daher haben sich die Teilnehmer
auf nur wenige, wichtige Gebiete konzentriert: Regenerative Energiegewinnung, Elektromobilität,
Speichertechnologien und Smart Grid. Durch das intensive Befassen mit diesen Themen haben sich die
Studierenden zum ersten Mal richtig mit den Problemen der Energiewende vertraut gemacht. Sie haben
dabei erkannt, dass für die Ingenieure der Fachrichtungen Elektrotechnik und Informationstechnik überaus
vielfältige, spannende und auch aus gesellschaftspolitischer Sicht notwendige und lohnende Aufgaben auf
sie warten.
This diploma thesis is devoted to the design and analysis of a radar signal enabling an object classification capability in surveillance radar systems based on high-resolution radar range profiles. It picks up the research results from Kastinger (2006), who investigated classification algorithms for high-resolution radar range profiles, and Meier (2007), who programmed a MATLAB toolbox for the evaluation of radar signals. A classical, brief, introduction to radar fundamentals is given (Chapter 1) as well as the motivation for this thesis and certain basic parameters used. After high-resolution radar range profiles are discussed with special focus on surveillance radar systems (Chapter 2), the results of Kastinger (2006) are picked up (Chapter 3) as far as necessary for the following chapters of this thesis. Following the chapters on radar basics, high-resolution radar range profiles and classification, basic and advanced radar signals are discussed and analysed, especially their range resolution and sidelobe levels (Chapter 4). This includes linear frequency-modulated pulses and nonlinear frequency-modulated pulses as well as phase-coded pulses, coherent trains of identical pulses, and stepped-frequency waveforms. Their analysis is based on Meier's MATLAB toolbox. In Chapter 5 we will bring up additional points that have to be considered in radar system design for implementing a classification capability, before this thesis ends with an overall conclusion (Chapter 6).