Skip to main content

d-E-mand

The development of an area-wide charging infrastructure and digital services for all kind of electric vehicle is of crucial importance for the transition to widespread electric vehicle usage. These services aim to ensure the energy supply for all electric vehicle users especially in situations with increased charging demand, e.g., local events.

The aim of the project is to create a foundation for small businesses to build on in order to create novel services in the context of increased spatio-temporal charging demand of electric vehicles.

Description

This project aims at creating a foundation for small businesses and startups that aim to address the increased demand of spatio-temporal electric vehicle charging capacity and to open new business fields in this area. Furthermore, the projects aims to create analytics interfaces for larger companies that enable the prediction of charging demand and optimization of energy supply.  These solutions will contribute to handle the increased demand of charging infrastructure in the context of local events or high traffic load as well as lowering the overall load of the energy infrastructure.

The project is divided into three parts that contribute to solve the considered problem.
Building on comprehensive data that is gathered within the project, novel AI based methods that are capable of predicting the short- and long-term charging demand of electric vehicles will be developed. A cloud based service platform that will serve as the central point of data integration will be developed. The results of the analyses and prediction models will be provided to business stakeholders as smart services. Specific applications that are tailored to the needs of the user of the platform (fleet owners, charging infrastructure provider), e.g. dashboards, will be developed. Smartphone based applications that provide information about the availability of charging infrastructure as well as declaring individual charging demand will be developed for private customers.

Team
Research area
Intelligent Access to Information
Begin
End