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Mit dem Klimaschutzgesetz 2021 wurden von der Bundesregierung die Klimaschutzvorgaben verschärft und die Treibhausgasneutralität bis 2045 als Ziel verankert. Zur Erreichung dieses ambitionierten Ziels ist es notwendig, im Bereich der Mobilität weitgehend von Verbrennungsmotoren mit fossilen Kraftstoffen auf Elektromobilität mit regenerativ erzeugtem Strom umzusteigen. Dabei ist die zügige Bereitstellung einer ausreichenden Ladeinfrastruktur für die Elektrofahrzeuge eine große Herausforderung. Neben der Installation einer ausreichend großen Zahl von Ladepunkten selbst besteht die Herausforderung darin, diese in das bestehende Verteilungsnetz zu integrieren bzw. das Verteilungsnetz so auszubauen, dass weiter ein sicherer Netzbetrieb gewährleistet werden kann. Dabei sind insbesondere Lösungen gefragt, bei denen der Ausbau der Ladeinfrastruktur und der Netzbetriebsmittel durch intelligentes Management des Ladens so gering wie möglich gehalten wird, indem vorhandene oder neu zu installierender Hardware möglichst effizient genutzt wird.
Hier setzte das Projekt „Intelligente Ladeinfrastruktur für Elektrofahrzeuge auf dem Parkplatz der Hochschule Offenburg (INTLOG)“ (Projektlaufzeit 15.11.2020 – 30.09.2022) an. Inhalt des Projekts war es, einen Ladepark für den Parkplatz der Hochschule Offenburg mit 20 Ladepunkten à 11 kW und somit einer Gesamtladeleistung von 220 kW an einen vorhandenen Ortsnetztransformator mit 200 kW Nennleistung anzuschließen, der aber bereits von anderen Verbrauchern genutzt wurde. Das übergeordnete Ziel war es also, eine Ladeinfrastruktur von maßgeblichem Umfang in die bestehende Netzinfrastruktur ohne zusätzlichen Ausbau zu integrieren.
Dabei wurden zukunftsweisende Technologien genutzt und weiterentwickelt sowie teilweise in Praxis, im Labor und in der Computersimulation demonstriert.
eLetter zu "Illusory movement perception improves motor control for prosthetic hands" von Paul D. Marasco et al., veröffentlicht in Science Translational Medicine, Vol. 10, No. 432 (DOI: 10.1126/scitranslmed.aao6990)
The automatic processing of handwritten forms remains a challenging task, wherein detection and subsequent classification of handwritten characters are essential steps. We describe a novel approach, in which both steps - detection and classification - are executed in one task through a deep neural network. Therefore, training data is not annotated by hand, but manufactured artificially from the underlying forms and yet existing datasets. It can be demonstrated that this single-task approach is superior in comparison to the state-of-the-art two task approach. The current study focuses on hand-written Latin letters and employs the EMNIST data set. However, limitations were identified with this data set, necessitating further customization. Finally, an overall recognition rate of 88.28% was attained on real data obtained from a written exam.
Die Entwicklung der Cyber-Bedrohungslandschaft zwingt Unternehmen zur Auseinandersetzung mit neuen funktionalen Herausforderungen. Da sich die Angriffsoberflächen genauso dynamisch verändern wie die Taktiken und Techniken, sollte die Corporate Governance für ein integratives Cyber-Risikomanagement sorgen, um das Cybersicherheitsmanagement differenziert einzubetten. Dadurch leistet die Corporate Governance einen Beitrag zur Steigerung der Cyber-Resilienz.
Additive manufacturing processes have evolved rapidly in recent years and now offer a wide range of manufacturing technologies and workable materials. This range from plastics and metals to paper and even polymer plaster composites. Due to the layer by layer structure of the components the additive processes have in comparison with conventional manufacturing processes the advantage of freedom of design, that means the simple implementation of complex geometries. Moreover, the additive processes provide the advantage of reduced consumption of resources, since essentially only the material is consumed, which is required for the actual component, since no waste in the form of chips is produced. In order to use these advantages, the potentials of additive manufacturing and the requirements of sustainable design must already be observed in the product development process. So the design of the components and products must be made so as little as possible construction and supporting material is required for the generative production and therefore little resources are consumed. Also, all steps of the additive manufacturing process must be considered properly, that includes the post processing. This allows components be designed so that for instance the effort for removing the support structure is considerably reduced. This leads to a significant reduction in manufacturing time and thus energy consumption. The implementation of these potentials in product development can be demonstrated by means of a multiple-stages model. A case study shows how this model is applied in the training of Master students in the field of product development. In a workshop the students work as a group while implementing the task of developing a miniature racing car under the rules of sustainable design in compliance with the boundary conditions for an additive manufacturing. In this case, Fused Deposition Modelling FDM using plastics as a building material is applied. The results show how the students have dealt with the different requirements and how they have implemented them in product development and in the subsequent additive manufacturing.
Integration of BACNET OPC UA-Devices Using a JAVA OPC UA SDK Server with BACNET Open Source Library
(2014)
Blockchain frameworks enable the immutable storage of data. A still open practical question is the so called "oracle" problem, i.e. the way how real world data is actually transferred into and out of a blockchain while preserving its integrity. We present a case study that demonstrates how to use an existing industrial strength secure element for cryptographic software protection (Wibu CmDongle / the "dongle") to function as such a hardware-based oracle for the Hyperledger blockchain framework. Our scenario is that of a dentist having leased a 3D printer. This printer is initially supplied with an amount of x printing units. With each print action the local unit counter on the attached dongle is decreased and in parallel a unit counter is maintained in the Hyperledger-based blockchain. Once a threshold is met, the printer will stop working (by means of the cryptographically protected invocation of the local print method). The blockchain is configured in such a way that chaincode is executed to increase the units again automatically (and essentially trigger any payment processes). Once this has happened, the new unit counter value will be passed from the blockchain to the local dongle and thus allow for further execution of print jobs.
Wireless Sensor Networks (WSN) have emerged as interesting topic in the research community due to its manifold applications. One of the main challenges of this field is the energy consumption of the nodes, which typically is quite restricted due to the required lifetime of such WSNs. To solve that problem several energy-saving MAC protocols have been developed so far. One of them recently presented by the authors is the so-called SmartMAC as an extension to the IEEE802.15.4 standard. In this paper, we present the implementation details of the porting of the SmartMAC protocol to the discrete event network simulator NS3. We develop this module for NS3 to simulate the performance, multi node execution, and multi node configuration. Along with this model, we also present an energy model for the evaluation of the energy consumption. The current implementation in NS3 is based on the LR-WPAN (Low-Rate Wireless Personal Area Networks) as specified by the IEEE802.15.4 (2006) standard. The simulation results show that the SmartMAC with its sleep and wake-up mechanisms for the transceivers, is significantly more efficient than the current NS3 MAC (Medium Access Control) scheme.