Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

Planning the Charging Infrastructure for Electric Vehicles in Cities and Regions

Planning the charging infrastructure for electric vehicles (EVs) is a new challenging task. This book treats all involved aspects: charging technologies and norms, interactions with the electricity system, electrical installation, demand for charging infrastructure, economics of public infrastructure provision, policies in Germany and the EU, external effects, stakeholder cooperation, spatial planning on the regional and street level, operation and maintenance, and long term spatial planning

Modelling the Development of a Regional Charging Infrastructure for Electric Vehicles in Time and Space

This article presents a dynamic spatial model of the development of a charging infrastructure for electric vehicles in the German metropolitan region of Stuttgart. The model consists of several sub-models whose functioning and interactions are explained in detail. The first sub-model simulates the time-spatial development of electric vehicle ownership. The output of this module is used by the second component that determines the resulting demand for charging stations. To quantify this demand, the necessary utilisation of charging stations to allow for the profitability of the infrastructure is calculated. A final processing step simulates the mobility of EVs throughout the Region Stuttgart, and thus allows allocating the need for charging stations in space. We used our model to generate several scenarios of the development of a charging infrastructure in the Region Stuttgart until 2020. The main finding of this work is that the number of public charging stations needed for the region in the long run is quite low. If too many charging stations are installed the infrastructure will be under-utilized and thus cannot be operated economically. The simulation runs show that the installation of public charging infrastructure should be focused on the few biggest urban centres of the region. The scenarios also show that publicly accessible charging stations form only a minor part of the overall number of charging stations. Additionally, it can be seen that the exponential growth of electric vehicle ownership, with very few vehicles at the beginning, but large gains after a few years, requires high flexibility from stakeholders involved in the implementation of charging infrastructure for electric vehicles

Semantic evidential grid mapping using monocular and stereo cameras

Accurately estimating the current state of local traffic scenes is one of the key problems in the development of software components for automated vehicles. In addition to details on free space and drivability, static and dynamic traffic participants and information on the semantics may also be included in the desired representation. Multi-layer grid maps allow the inclusion of all of this information in a common representation. However, most existing grid mapping approaches only process range sensor measurements such as Lidar and Radar and solely model occupancy without semantic states. In order to add sensor redundancy and diversity, it is desired to add vision-based sensor setups in a common grid map representation. In this work, we present a semantic evidential grid mapping pipeline, including estimates for eight semantic classes, that is designed for straightforward fusion with range sensor data. Unlike other publications, our representation explicitly models uncertainties in the evidential model. We present results of our grid mapping pipeline based on a monocular vision setup and a stereo vision setup. Our mapping results are accurate and dense mapping due to the incorporation of a disparity- or depth-based ground surface estimation in the inverse perspective mapping. We conclude this paper by providing a detailed quantitative evaluation based on real traffic scenarios in the KITTI odometry benchmark dataset and demonstrating the advantages compared to other semantic grid mapping approaches

Semantic Evidential Grid Mapping Using Monocular and Stereo Cameras

Accurately estimating the current state of local traffic scenes is one of the key problems in the development of software components for automated vehicles. In addition to details on free space and drivability, static and dynamic traffic participants and information on the semantics may also be included in the desired representation. Multi-layer grid maps allow the inclusion of all of this information in a common representation. However, most existing grid mapping approaches only process range sensor measurements such as Lidar and Radar and solely model occupancy without semantic states. In order to add sensor redundancy and diversity, it is desired to add vision-based sensor setups in a common grid map representation. In this work, we present a semantic evidential grid mapping pipeline, including estimates for eight semantic classes, that is designed for straightforward fusion with range sensor data. Unlike other publications, our representation explicitly models uncertainties in the evidential model. We present results of our grid mapping pipeline based on a monocular vision setup and a stereo vision setup. Our mapping results are accurate and dense mapping due to the incorporation of a disparity- or depth-based ground surface estimation in the inverse perspective mapping. We conclude this paper by providing a detailed quantitative evaluation based on real traffic scenarios in the KITTI odometry benchmark dataset and demonstrating the advantages compared to other semantic grid mapping approaches

Chaperone assisted recombinant expression of a mycobacterial aminoacylase in Vibrio natriegens and Escherichia coli capable of N-lauroyl-L-amino acid synthesis

Abstract Background Aminoacylases are highly promising enzymes for the green synthesis of acyl-amino acids, potentially replacing the environmentally harmful Schotten-Baumann reaction. Long-chain acyl-amino acids can serve as strong surfactants and emulsifiers, with application in cosmetic industries. Heterologous expression of these enzymes, however, is often hampered, limiting their use in industrial processes. Results We identified a novel mycobacterial aminoacylase gene from Mycolicibacterium smegmatis MKD 8, cloned and expressed it in Escherichia coli and Vibrio natriegens using the T7 overexpression system. The recombinant enzyme was prone to aggregate as inclusion bodies, and while V. natriegens Vmax™ could produce soluble aminoacylase upon induction with isopropyl β-d-1-thiogalactopyranoside (IPTG), E. coli BL21 (DE3) needed autoinduction with lactose to produce soluble recombinant protein. We successfully conducted a chaperone co-expression study in both organisms to further enhance aminoacylase production and found that overexpression of chaperones GroEL/S enhanced aminoacylase activity in the cell-free extract 1.8-fold in V. natriegens and E. coli. Eventually, E. coli ArcticExpress™ (DE3), which co-expresses cold-adapted chaperonins Cpn60/10 from Oleispira antarctica, cultivated at 12 °C, rendered the most suitable expression system for this aminoacylase and exhibited twice the aminoacylase activity in the cell-free extract compared to E. coli BL21 (DE3) with GroEL/S co-expression at 20 °C. The purified aminoacylase was characterized based on hydrolytic activities, being most stable and active at pH 7.0, with a maximum activity at 70 °C, and stability at 40 °C and pH 7.0 for 5 days. The aminoacylase strongly prefers short-chain acyl-amino acids with smaller, hydrophobic amino acid residues. Several long-chain amino acids were fairly accepted in hydrolysis as well, especially N-lauroyl-L-methionine. To initially evaluate the relevance of this aminoacylase for the synthesis of N-acyl-amino acids, we demonstrated that lauroyl-methionine can be synthesized from lauric acid and methionine in an aqueous system. Conclusion Our results suggest that the recombinant enzyme is well suited for synthesis reactions and will thus be further investigated