With more and more electric vehicles driving on German roads, the challenge of how to support them with a satisfactory charging infrastructure becomes more pressing. Grid operators are faced with complex questions like: How can the energy needs of different vehicles from juggernauts to e-scooters be met? And how to predict and manage bottlenecks locally at charging stations?
Under the leadership of the Industrial Science and Technology Management (IAT) division at the University of Stuttgart, a group of partners including the Fraunhofer Institute for Industrial Engineering (IAO), are investigating these dynamics in a research project called KI-LAN. The aim is to develop smart charging solutions based on artificial intelligence (AI, or KI in German) and to garner operating information about parking stations with a high number of modular charging points.
The project will focus on two usage scenarios for charging stations: parking in urban areas during working hours and at events; and parking during working hours in rural municipalities. To this end, two charging stations have been set up at Wizemann-Areal in the city of Stuttgart and Marquardt GmbH in Rietheim-Weilheim, to provide a real world context.
The research partners want to develop a forecast-based charging management system that can manage different load scenarios and self-learning algorithms that can control charging processes.
"By storing intelligence in the charging process, we are able to expand the charging infrastructure without expanding the power grid. The more infrastructure there is, the more electric cars will soon be on the roads”, explains Marc Schmidt, project manager and scientist at the IAT in a . “This naturally promotes the acceptance of electromobility in society and can also establish electromobility as a sustainability concept suitable for the masses."