Prediction based charging management for full electric vehicles in a mobility-on demand-concept using local renewable energy

Abstract

Unavoidably, the aim of ecologically sustainable driving leads to the use of full electric vehicles (FEV) and a charging process based on renewable energy. Ecologically sustainable charging, however, faces a diverse range of challenges. First of all the additional integration of renewable energy sources into the distribution and regional grids requires an expansion of grid infrastructure. In addition the FEV represents a high-power load inside the electrical grid; this may cause overloads and deviations from the preset voltage band. The management system in [1] was developed to address the problem of the high-power load as well as to maximize the usage of already available renewable energy. This paper details a charging management system which is based on [1] and incorporates the prediction of available renewable energy inside the electric grid. The management system also considers the special challenges presented by a mobility-on-demand-concept, above all the permanent availability of mobility. First results show that the developed prediction based management system is capable to raise the percentage of renewable charging energy in comparison to a dump charging as well as to the charging management presented in [1].