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Vermaschungsgrad der Verteilnetze in Deutschland (2021)

Weisenstein, Marco ; Wellßow, Wolfram

Dieses Dokument präsentiert und diskutiert die Ergebnisse einer Umfrage zum Vermaschungsgrad der Verteilnetze in Deutschland.

Inertialsensorik für Fahrerassistenzsysteme am Pedelec (2021)

Dauer, Felix

Mit dem Vorhandensein elektrischer Energie und moderner Sensorik an elektrisch unterstützten Fahrrädern eröffnen sich neue Möglichkeiten der Entwicklung von Fahrerassistenzsystemen am Pedelec zur Erhöhung der Sicherheit und des Fahrkomforts. Die Leistungsfähigkeit solcher Systeme kann durch die Nutzung von Inertialsensorik weiter gesteigert werden. Jedoch müssen solche Sensoren, vor allem bei sicherheitsrelevanten Assistenzsystemen, zuverlässige, robuste und plausible Sensordaten liefern. Hieraus ergibt sich das Thema dieser Arbeit: die Evaluation von Inertialsensorik für Fahrerassistenzsysteme am Pedelec anhand systematischer Untersuchung der Fahrdynamik. Durch simulative und experimentelle Untersuchungen der MEMS-Sensorik und der Fahrdynamik, basierend auf Testkatalogen, werden die Anforderungen an Inertialsensorik abgeleitet und die Störbarkeit der Drehrate analysiert. Dabei führt die Betrachtung verschiedener Sensortypen, Fahrszenarien und Anbaupositionen zu der Erkenntnis, dass bspw. die Anbauposition am Sattelrohr und in der Antriebseinheit besonders geeignet sind. Vor allem der betrachtete Automotive-MEMS-Sensor liefert auch bei potentiell kritischen Vibrationen bei einer Fahrt über Kopfsteinpflaster oder über Treppenstufen sowie bei Bremsenquietschen zuverlässig plausible Sensordaten. Zusätzlich zeigt eine Betrachtung der Auswirkungen von Sensorfehlern auf eine Datenfusion, d.h. der Berechnung der Raumwinkel, dass vor allem die Minimierung des Offset-Fehlers, bspw. durch eine Langzeitkorrektur, sinnvoll erscheint und resultierende Winkelfehler minimieren kann. Die Untersuchung der Fahrdynamik betrachtet insbesondere das Fahrszenario (kritische) Kurvenfahrt. Anhand der Fahrdaten zahlreicher Pedelec-Nutzer werden eine Methode zur Erkennung von Kurvenfahrten sowie theoretische Ansätze zur Vermeidung einer kritischen Kurvenfahrt durch einen aktiven Lenkeingriff realisiert.

Ein Beitrag zur Zustandsschätzung in Niederspannungsnetzen mit niedrigredundanter Messwertaufnahme (2020)

Brandalik, Robert

Durch den wachsenden Anteil an Erzeugungsanlagen und leistungsstarken Verbrauchern aus dem Verkehr- und Wärmesektor kommen Niederspannungsnetze immer näher an ihre Betriebsgrenzen. Da für die Niederspannungsnetze bisher keine Messwerterfassung vorgesehen war, können Netzbetreiber Grenzverletzungen nicht erkennen. Um dieses zu ändern, werden deutsche Anschlussnutzer in Zukunft flächendeckend mit modernen Messeinrichtungen oder intelligenten Messsystemen (auch als Smart Meter bezeichnet) ausgestattet sein. Diese sind in der Lage über eine Kommunikationseinheit, das Smart-Meter-Gateway, Messdaten an die Netzbetreiber zu senden. Werden Messdaten aber als personenbezogene Netzzustandsdaten deklariert, so ist aus Datenschutzgründen eine Erhebung dieser Daten weitgehend untersagt. Ziel dieser Arbeit ist es eine Zustandsschätzung zu entwickeln, die auch bei niedrigredundanter Messwertaufnahme für den Netzbetrieb von Niederspannungsnetzen anwendbare Ergebnisse liefert. Neben geeigneten Algorithmen zur Zustandsschätzung ist dazu die Generierung von Ersatzwerten im Fokus. Die Untersuchungen und Erkenntnisse dieser Arbeit tragen dazu bei, den Verteilnetzbetreibern bei den maßgeblichen Entscheidungen in Bezug auf die Zustandsschätzung in Niederspannungsnetzen zu unterstützen. Erst wenn Niederspannungsnetze mit Hilfe der Zustandsschätzung beobachtbar sind, können darauf aufbauende Konzepte zur Regelung entwickelt werden, um die Energiewende zu unterstützen.

Routing of strongly confined terahertz spoof surface plasmon polaritons on metasurfaces along straight and curved pathways with subwavelength width (2020)

Becker, Sven ; Fip, Tassilo ; Rahm, Marco

In search of new technologies for optimizing the performance and space requirements of electronic and optical micro-circuits, the concept of spoof surface plasmon polaritons (SSPPs) has come to the fore of research in recent years. Due to the ability of SSPPs to confine and guide the energy of electromagnetic waves in a subwavelength space below the diffraction limit, SSPPs deliver all the tools to implement integrated circuits with a high integration rate. However, in order to guide SSPPs in the terahertz frequency range, it is necessary to carefully design metasurfaces that allow one to manipulate the spatio-temporal and spectral properties of the SSPPs at will. Here, we propose a specifically designed cut-wire metasurface that sustains strongly confined SSPP modes at terahertz frequencies. As we show by numerical simulations and also prove in experimental measurements, the proposed metasurface can tightly guide SSPPs on straight and curved pathways while maintaining their subwavelength field confinement perpendicular to the surface. Furthermore, we investigate the dependence of the spatio-temporal and spectral properties of the SSPP modes on the width of the metasurface lanes that can be composed of one, two or three cut-wires in the transverse direction. Our investigations deliver new insights into downsizing effects of guiding structures for SSPPs.

Timing Performance Analysis of the Deterministic Ethernet Enhancements Time-Sensitive Networking (TSN) for Use in the Industrial Communication (2020)

Nsaibi, Seifeddine

Ethernet has become an established communication technology in industrial automation. This was possible thanks to the tremendous technological advances and enhancements of Ethernet such as increasing the link-speed, integrating the full-duplex transmission and the use of switches. However these enhancements were still not enough for certain high deterministic industrial applications such as motion control, which requires cycle time below one millisecond and jitter or delay deviation below one microsecond. To meet these high timing requirements, machine and plant manufacturers had to extend the standard Ethernet with real-time capability. As a result, vendor-specific and non-IEEE standard-compliant "Industrial Ethernet" (IE) solutions have emerged. The IEEE Time-Sensitive Networking (TSN) Task Group specifies new IEEE-conformant functionalities and mechanisms to enable the determinism missing from Ethernet. Standard-compliant systems are very attractive to the industry because they guarantee investment security and sustainable solutions. TSN is considered therefore to be an opportunity to increase the performance of established Industrial-Ethernet systems and to move forward to Industry 4.0, which require standard mechanisms. The challenge remains, however, for the Industrial Ethernet organizations to combine their protocols with the TSN standards without running the risk of creating incompatible technologies. TSN specifies 9 standards and enhancements that handle multiple communication aspects. In this thesis, the evaluation of the use of TSN in industrial real-time communication is restricted to four deterministic standards: IEEE802.1AS-Rev, IEEE802.1Qbu IEEE802.3br and IEEE802.1Qbv. The specification of these TSN sub-standards was finished at an early research stage of the thesis and hardware prototypes were available. Integrating TSN into the Industrial-Ethernet protocols is considered a substantial strategical challenge for the industry. The benefits, limits and risks are too complex to estimate without a thorough investigation. The large number of Standard enhancements makes it hard to select the required/appropriate functionalities. In order to cover all real-time classes in the automation [9], four established Industrial-Ethernet protocols have been selected for evaluation and combination with TSN as well as other performance relevant communication features. The objectives of this thesis are to (1) Provide theoretical, simulation and experimental evaluation-methodologies for the timing performance analysis of the deterministic TSN-standards mentioned above. Multiple test-plans are specified to evaluate the performance and compatibility of early version TSN-prototypes from different providers. (2) Investigate multiple approaches and deduce migration strategies to integrate these features into the established Industrial-Ethernet protocols: Sercos III, Profinet IRT, Profinet RT and Ethernet/IP. A scenario of coexistence of time-critical traffic with other traffic in a TSN-network proves that the timing performance for highly deterministic applications, e.g. motion-control, can only be guaranteed by the TSN scheduling algorithm IEEE802.1Qbv. Based on a requirements survey of highly deterministic industrial applications, multiple network scenarios and experiments are presented. The results are summarized into two case studies. The first case study shows that TSN alone is not enough to meet these requirements. The second case study investigates the benefits of additional mechanisms (Gigabit link-speed, minimum cycle time modeling, frame forwarding mechanisms, frame structure, topology migration, etc.) in combination with the TSN features. An implementation prototype of the proposed system and a simulation case study are used for the evaluation of the approach. The prototype is used for the evaluation and validation of the simulation model. Due to given scalability constraints of the prototype (no cut-through functionalities, limited number of TSN-prototypes, etc…), a realistic simulation model, using the network simulation tool OMNEST / OMNeT++, is conducted. The obtained evaluation results show that a minimum cycle time ≤1 ms and a maximum jitter ≤1 μs can be achieved with the presented approaches.

Programmnetzlisten: Ein formales Modell für die Verifikation von Hardwarenaher Software in Eingebetteten Systemen (2020)

Schmidt, Bernard

In dieser Arbeit wird ein formales Modell zur Beschreibung von hardwarenaher Software vorgestellt: Die Programmnetzliste. Die Programmnetzliste (PN) besteht aus Instruktionszellen die in einem gerichteten azyklischen Graph verbunden sind und dabei alle Ausführungspfade des betrachteten Programms beinhaltet. Die einzelnen Instruktionszellen repräsentieren eine Instruktion oder eine Instruktionssequenz. Die PN verfügt über eine explizite Darstellung des Programmablaufs und eine implizite Modellierung des Datenpfads und ist als Modell für die Verifikation von Software nutzbar. Die Software wird dabei auf Maschinencode-Level betrachtet. Die Modellgenerierung besteht aus wenigen und gut automatisierbaren Schritten. Als Grundlage dient ein – ggf. unvollständiger – Kontrollfluss Graph (CFG), der aus der Software generiert werden kann. Die Modellgenerierung besteht aus zwei Schritten. Der erste Schritt ist die Erzeugung des expliziten Programmablaufs, indem der CFG abgerollt wird. Dabei wird ein sogenannter Execution-Graph (EXG) erzeugt, der alle möglichen Ausführungspfade des betrachteten Programms beinhaltet. Um dieses Modell so kompakt wie möglich zu halten, werden unterschiedliche Techniken verwendet – wie das Zusammenführen gemeinsamer Pfade und das Erkennen von “toten” Verzweigungen im Programm, die an der entsprechenden Stelle niemals ausgeführt werden. Im Anschluss wird im zweiten Schritt der Execution-Graph in die Programmnetzliste (PN) übersetzt. Dabei werden alle Knoten im EXG durch eine entsprechende Instruktionszelle ersetzt. Die Kanten des Graphen entsprechen dabei dem Programmzustand. Der Programmzustand setzt sich aus den Variablen im Speicher wie auch dem Architekturzustand des unterliegenden Prozessors zusammen. Ergänzt wird der Programmzustand in der Programmnetzliste um ein sogenanntes Active-Bit, welches es ermöglicht den aktiven Pfad in der Netzliste zu markieren. Das ist notwendig, da die Software immer nur einen Pfad gleichzeitig ausführen kann, aber die PN alle möglichen Pfade beinhaltet. Auf der Programmnetzliste können dann mit Hilfe von Hardware Property Checkern basierend auf BMC oder IPC diverse Eigenschaften bewiesen werden. Zusätzlich wird die Programmnetzliste um die Fähigkeit zur Interruptmodellierung erweitert.

Prior-Knowledge Addition to Spatial and Temporal Classification Models with Demonstration on Hand Shape and Gesture Classification (2020)

Tewari, Aditya

The neural networks have been extensively used for tasks based on image sensors. These models have, in the past decade, consistently performed better than other machine learning methods on tasks of computer vision. It is understood that methods for transfer learning from neural networks trained on large datasets can reduce the total data requirement while training new neural network models. These methods tend not to perform well when the data recording sensor or the recording environment is unique from the existing large datasets. The machine learning literature provides various methods for prior-information inclusion in a learning model. Such methods employ methods like designing biases into the data representation vectors, enforcing priors or physical constraints on the models. Including such information into neural networks for the image frames and image-sequence classification is hard because of the very high dimensional neural network mapping function and little information about the relation between the neural network parameters. In this thesis, we introduce methods for evaluating the statistically learned data representation and combining these information descriptors. We have introduced methods for including information into neural networks. In a series of experiments, we have demonstrated methods for adding the existing model or task information to neural networks. This is done by 1) Adding architectural constraints based on the physical shape information of the input data, 2) including weight priors on neural networks by training them to mimic statistical and physical properties of the data (hand shapes), and 3) by including the knowledge about the classes involved in the classification tasks to modify the neural network outputs. These methods are demonstrated, and their positive influence on the hand shape and hand gesture classification tasks are reported. This thesis also proposes methods for combination of statistical and physical models with parametrized learning models and show improved performances with constant data size. Eventually, these proposals are tied together to develop an in-car hand-shape and hand-gesture classifier based on a Time of Flight sensor.

Incorporating Context Awareness in Cellular Networks to Enhance System Performance and User Mobility Support (2020)

Kuruvatti, Nandish P.

In today’s world, mobile communication has become one of the most widely used technologies corroborated by growing number of mobile subscriptions and extensive usage of mobile multimedia services. It is a key challenge for the network operators to accommodate such large number of users and high traffic volume. Further, several day-to-day scenarios such as public transportation, public events etc., are now characterized with high mobile data usage. A large number of users avail cellular services in such situations posing high load to the respective base stations. This results in increased number of dropped connections, blocking of new access attempts and blocking of handovers (HO). The users in such system will thus be subjected to poor Quality of Experience (QoE). Beforehand knowledge of the changing data traffic dynamics associated with such practical situations will assist in designing radio resource management schemes aiming to ease the forthcoming congestion situations. The key hypothesis of this thesis is that consideration and utilization of additional context information regarding user, network and his environment is valuable in designing such smart Radio Resource Management(RRM) schemes. Methods are developed to predict the user cell transitions, considering the fact that mobility of the users is not purely random but rather direction oriented. This is particularly used in case of traffic dense moving network or group of users moving jointly in the same vehicle (e.g., bus, train, etc.) to predict the propagation of high load situation among cells well in advance. This enables a proactive triggering of load balancing (LB) in cells anticipating the arrival of high load situation and accommodating the incoming user group or moving network. The evaluated KPIs such as blocked access attempts, dropped connections and blocked HO are reduced. Further, everyday scenario of dynamic crowd formation is considered as another potential case of high load situation. In real world scenarios such as open air festivals, shopping malls, stadiums or public events, several mobile users gather to form a crowd. This poses high load situation to the respective serving base station at the site of crowd formation, thereby leading to congestion. As a consequence, mobile users are subjected to poor QoE due to high dropping and blocking rates. A framework to predict crowd formation in a cell is developed based on coalition of user cell transition prediction, cluster detection and trajectory prediction. This framework is suitably used to prompt context aware load balancing mechanism and activate a small cell at the probable site of crowd formation. Simulations show that proactive LB reduces the dropping of users (23%), blocking of users (10%) and blocked HO (15%). In addition, activation of a Small Cell (SC) at the site of frequent crowd formation leads to further reductions in dropping of users (60%), blocking of users (56%) and blocked HO (59%). Similar to the framework for crowd formation prediction, a concept is developed for predicting vehicular traffic jams. Many vehicular users avail broadband cellular services on a daily basis while traveling. The density of such vehicular users change dynamically in a cell and at certain sites (e.g. signal lights), traffic jams arise frequently leading to a high load situation at respective serving base station. A traffic prediction algorithm is developed from cellular network perspective as a coalition strategy consisting of schemes to predict user cell transition, vehicular cluster/moving network detection, user velocity monitoring etc. The traffic status indication provided by the algorithm is then used to trigger LB and activate/deactivate a small cell suitably. The evaluated KPIs such as blocked access attempts, dropped connections and blocked HO are reduced by approximately 10%, 18% and 18%, respectively due to LB. In addition, switching ON of SC reduces blocked access attempts, dropped connections and blocked HO by circa 42%, 82% and 81%, respectively. Amidst increasing number of connected devices and traffic volume, another key issue for today’s network is to provide uniform service quality despite high mobility. Further, urban scenarios are often characterized by coverage holes which hinder service continuity. A context aware resource allocation scheme is proposed which uses enhanced mobility prediction to facilitate service continuity. Mobility prediction takes into account additional information about the user’s origin and possible destination to predict next road segment. If a coverage hole is anticipated in upcoming road, then additional resources are allocated to respective user and data is buffered suitably. The buffered data is used when the user is in a coverage hole to improve service continuity. Simulation shows improvement in throughput (in coverage hole) by circa 80% and service interruption is reduced by around 90%, for a non-real-time streaming service. Additionally, investigation of context aware procedures is carried out with a focus on user mobility, to find commonalities among different procedures and a general framework is proposed to support mobility context awareness. The new information and interfaces which are required from various entities (e.g., vehicular infrastructure) are discussed as well. Device-to-Device (D2D) communications commonly refer to the technology that enables direct communication between devices, hence relieving the base station from traffic routing. Thus, D2D communication is a feasible solution in crowded situations, where users in proximity requesting to communicate with one another could be granted D2D links for communication, thereby easing the traffic load to serving base station. D2D links can potentially reuse the radio resources from cellular users (known as D2D underlay) leading to better spectral utilization. However, the mutual interference can hinder system performance. For instance, if D2D links are reusing cellular uplink resources then D2D transmissions cause interference to cellular uplink at base station. Whereas, cellular transmissions cause interference to D2D receivers. To cope up with such issues, location aware resource allocation schemes are proposed for D2D communication. The key aim of such RA scheme is to reuse resources with minimal interference. The RA scheme based on virtual sectoring of a cell leads to approximately 15% more established links and 25% more capacity with respect to a random resource allocation. D2D transmissions cause significant interference to cellular links with which they reuse physical resource blocks, thereby hindering cellular performance. Regulating D2D transmissions to mitigate the aforementioned problem would mean sub-optimal exploitation of D2D communications. As a solution, post-resource allocation power control at cellular users is proposed. Three schemes namely interference aware power control, blind power control and threshold based power control are discussed. Simulation results show reductions in dropping of cellular users due to interference from D2D transmissions, improvement in throughput at base station (uplink) while not hindering the D2D performance.

Novel System Approach for a mm-range Precision Indoor Positioning System (2020)

Xiong, Renhai

Indoor positioning system (IPS) is becoming more and more popular in recent years in industrial, scientific and medical areas. The rapidly growing demand of accurate position information attracts much attention and effort in developing various kinds of positioning systems that are characterized by parameters like accuracy,robustness, latency, cost, etc. These systems have been successfully used in many applications such as automation in manufacturing, patient tracking in hospital, action detection for human-machine interacting and so on. The different performance requirements in various applications lead to existence of greatly diverse technologies, which can be categorized into two groups: inertial positioning(involving momentum sensors embedded on the object device to be located) and external sensing (geometry estimation based on signal measurement). In positioning systems based on external sensing, the input signal used for locating refers to many sources, such as visual or infrared signal in optical methods, sound or ultra-sound in acoustic methods and radio frequency based methods. This dissertation gives a recapitulative survey of a number of existence popular solutions for indoor positioning systems. Basic principles of individual technologies are demonstrated and discussed. By comparing the performances like accuracy, robustness, cost, etc., a comprehensive review of the properties of each technologies is presented, which concludes a guidance for designing a location sensing systems for indoor applications. This thesis will lately focus on presenting the development of a high precision IPS prototype system based on RF signal from the concept aspect to the implementation up to evaluation. Developing phases related to this work include positioning scenario, involved technologies, hardware development, algorithms development, firmware generation, prototype evaluation, etc.. The developed prototype is a narrow band RF system, and it is suitable for a flexible frequency selection in UHF (300MHz3GHz) and SHF (3GHz30GHz) bands, enabling this technology to meet broad service preferences. The fundamental of the proposed system classified itself as a hyperbolic position fix system, which estimates a location by solving non-linear equations derived from time difference of arrival (TDoA) measurements. As the positioning accuracy largely depends on the temporal resolution of the signal acquisition, a dedicated RF front-end system is developed to achieve a time resolution in range of multiple picoseconds down to less than 1 pico second. On the algorithms aspect, two processing units: TDoA estimator and the Hyperbolic equations solver construct the digital signal processing system. In order to implement a real-time positioning system, the processing system is implemented on a FPGA platform. Corresponding firmware is generated from the algorithms modeled in MATLAB/Simulink, using the high level synthesis (HLS) tool HDL Coder. The prototype system is evaluated and an accuracy of better than 1 cm is achieved. A better performance is potential feasible by manipulating some of the controlling conditions such as ADC sampling rate, ADC resolution, interpolation process, higher frequency, more stable antenna, etc. Although the proposed system is initially dedicated to indoor applications, it could also be a competitive candidate for an outdoor positioning service.

Planungsgrundsätze für Niederspannungsnetze unter Berücksichtigung regelbarer Ortsnetztransformatoren (2019)

Arnold, Maximilian

Die Versorgungsaufgaben für Niederspannungsnetze werden sich in den kommenden Jahrzehnten durch die weitere Verbreitung von Photovoltaikanlagen, Wärmepumpenheizungen und Elektroautomobilen gegenüber denen des Jahres 2018 voraussichtlich stark ändern. In der Praxis verbreitete Planungsgrundsätze für den Neubau von Niederspannungsnetzen sind veraltet, denn sie stammen vielfach in ihren Grundzügen aus Zeiten, in denen die neuen Lasten und Einspeisungen nicht erwartet und dementsprechend nicht berücksichtigt wurden. Der Bedarf für neue Planungsgrundsätze fällt zeitlich mit der Verfügbarkeit regelbarer Ortsnetztransformatoren (rONT) zusammen, die zur Verbesserung der Spannungsverhältnisse im Netz eingesetzt werden können. Die hier entwickelten neuen Planungsgrundsätze erfordern für ländliche und vorstädtische Versorgungsaufgaben (nicht jedoch für städtische Versorgungsaufgaben) den rONT-Einsatz, um die hohen erwarteten Leistungen des Jahres 2040 zu geringen Kosten beherrschen zu können. Eine geeignete rONT-Standardregelkennlinie wird angegeben. In allen Fällen werden abschnittsweise parallelverlegte Kabel mit dem Querschnitt 240 mm² empfohlen.

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