Database Systems and Information Management

moreEVS - The Multi-Domain Modeling and Optimization of Integrated Renewable Energy and Urban Electric Vehicle Systems

The number of electric vehicles (EVs) in urban areas is expected to increase rapidly in the following years. The German Federal Government has set as a target one million EVs on the road by 2020. With over 200,000 EVs sold in 2015, the People’s Republic of China is the current market leader. In contrast to Germany, the Chinese government has committed to a target of 4.6 million EVs on the road by 2020. Thus, an elective-vehicle charging strategy needs to be developed to address the integration of EVs into smart grids. Otherwise, the rapid growth could trigger serious strains on power quality during peak demand and increase grid maintenance costs. Simultaneously, the large-scale integration of renewable energy sources in distribution networks is also expected to increase the share of volatile renewable energy generation, thus introducing further complexity into the former strictly top-down energy supply infrastructure.

In this research project, DIMA will address the challenge of conducting large-scale data analysis efficiently and pair renewable energy power sources with EVs, to facilitate charging. The moreEVS project enables state-of-the-art research to be conducted in energy demand modeling, battery quality management, grid infrastructure for renewable energy, and largescale data management.


Project Duration: 05/12/2018 - 31/12/2021

Project Partners:

  1. The National Engineering Laboratory for Electric Vehicles at the Beijing Institute of Technology,
  2. The Electric Power System Institute at Tsinghua University,
  3. The Methods for Product Development and Mechatronics Group at TU Berlin,
  4. The Sustainable Electric Networks and Sources of Energy Group at TU Berlin.

Funding Agencies: The moreEVS Project is part of a bilateral initiative for joint Sino-German research projects. The German project partners are funded by the German Research Foundation (DFG) and the Chinese project partners are funded by the National Natural Science Foundation of China (NSFC).