Electromobility research project successfully completed
Results announced at the MENDEL closing event
Dirk Weißer, INIT's Head of Research, gave a lecture on general challenges of e-mobility.
Braunschweig/Karlsruhe 17 July 2019
A pleasing finish to a successful research project: The results of the MENDEL project were announced in a series of presentations and a live demonstration at an event to mark the project’s completion held in Braunschweig on July 4th, 2019. The MENDEL project – short for ‘Minimizing the load on Electrical Networks by charging Electric-buses’ – was initiated in January 2016 with the objective of reducing capital and operating costs associated with electromobility solutions. Numerous partners from research and industry came together to collaborate on the project, including AVT-Stoye, Fraunhofer IML, GEVAS software, ifak e.V., the German Aerospace Center (DLR), and INIT – which led the consortium. The results are impressive.
In the Smart Grid subproject, the partners developed software solutions to enable smart planning and control of e-bus charging in the power grid. Software was developed to determine the optimal charging infrastructure for opportunity charging (charging en route) in a bus network by analyzing infrastructure data from the electricity provider and schedule information. Based on this information, another software then optimizes vehicle blocks and scheduling of charging. The allotted charging time can also be adapted ad-hoc where required. For example, if the Intermodal Transport Control System (ITCS) registers a critically low charge, the vehicles' charging at a given stop can be extended or shortened to reduce the strain on the power grid.
Priority for e-buses
The ITS subproject focused on reducing variable operating costs. Significant savings can be achieved by reducing energy-intensive starting procedures. To this end, a central public transport prioritization system has been developed that takes charge levels and planned charging times into account. This is enabled by the ITCS’s backend-to-backend connection to the new CCALL component in the local authority’s traffic management system, which manages central registration of vehicle approaches and prioritization. This makes it possible to control traffic signal priority in real time taking into account data coming from public transport systems and specific e-buses in particular, e.g. current state of charge, delays, and occupancy. In practice it means that, for example, an e-bus with a critical charging level is given traffic signal priority to get it through intersections as quickly as possible. The on-board computer also provides the driver with precise real-time information on the distance to the next traffic light and predicts when the lights will next turn green. At the same time, a smartphone app also allows transport companies from surrounding regions to use public transport prioritization once they enter a city where these systems exist.
Demonstrating the software prototypes
The software of this subproject was set up in the DLR’s Application Platform for Intelligent Mobility (AIM) test environment and successfully tested in the Braunschweig urban area. Visitors were able to watch a live demonstration of the software at the closing event. They were impressed by the software prototypes demonstrating the successful integration of Smart Grid and ITS components to form a cohesive system. Particular attention was paid to the interfaces during the development of all software prototypes. Where possible, the project partners used standard interfaces, or expanded them to incorporate e-mobility-related data. INIT’s R&D manager, Manuel Quinting, believes that the intense three-and-a-half year collaboration has paid off: “MENDEL has shown how information, communication and network technology will run large electric bus fleets of tomorrow reliably and economically.”
Head of Department Corporate Marketing INIT SE Germany Phone: +49 721 6100 113 Fax: +49 721 6100 399
These cookies are necessary to enable the basic functions of our website. We store personal page settings and your language settings.
To further improve our website, we collect anonymous data for statistics and analysis. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages of our website in order to optimize our content.
Third-party content – e.g. Vimeo or YouTube videos – can be embedded and displayed. To further improve our communication, we collect anonymous statistical data.