PARTNERS OF CiLoCharging
Siemens: Optimization of integrated energy management
In the consortium, Siemens assumes the roles of the network coordinator and the leader of the integration of the charging infrastructure) and the work package “Integrative Optimization Approach” for the development activities and works closely with the responsible business unit SI (Smart Infrastructure) in the project.
Contact
Jürgen Götz
Component Engineer
Siemens
juergen.goetz@siemens.com
Fachhochschule Dortmund: Scenarios, use cases and systematic analysis
Creation of scenarios and use cases as well as the systematic analysis of the requirements for the project results, carried out using the CONSENS methodology and in coordination with the application partner DHL Freight.
Contact
Prof. Carsten Wolff
Professor of Computer Engineering
TU Dortmund
TU Munich: Simulation for charge management
Setting up a simulation environment for a load management system with the aim of optimizing the use of resources for a logistics fleet. The mobility simulator City Mobility Simulator (CityMoS) is used.
DHL Freight: Procurement and operation of electric trucks
Procurement and operation of electric trucks and the necessary charging infrastructure. In cooperation with the other project partners, the implementation and operation will be evaluated and the solutions will be further developed.
STTech: AI, machine learning and deep learning in the context of charging solutions.
Bring artificial intelligence, machine learning, and deep learning concepts and methods into CiLoCharging, as well as demonstrate their meaningful and beneficial use in this context.
Blog Topics
Cognition Factory: Evaluate and visualize camera data
Since the beginning of research on the digital twin, AI specialist Cognition Factory GmbH has focused on processing camera data. In the meantime Dr. Claus Lenz has deployed a large-scale platform
Digital real-time twin of traffic: ready for series production
Expand the test track, deploy new sensors, decentralize software architecture, fuse sensor data for 24/7 operation of a real-time digital twin, and make data packets public: TU Munich has decisively advanced the Providentia++ research project.
Elektrobit: Coining Test Lab to stationary data
Elektrobit lays the foundation for Big Data evaluations of traffic data. Simon Tiedemann on the developments in P++.