Smart charging, where the charging of an electric vehicle battery is delayed or advanced in time based on energy costs, grid capacity or renewable contents, has a great potential for increasing the value of the electric vehicle to the owner, the grid and society as a whole. The Danish EDISON project has been launched to investigate various areas relevant to electric vehicle integration. As part of EDISON an electric vehicle aggregator has been developed to demonstrate smart charging of electric vehicles. The emphasis of this paper is the mathematical methods on which the EDISON aggregator is based. This includes an analysis of the problem of EV driving prediction and charging optimization, a description of the mathematical models implemented and an evaluation of the accuracy of such models. Finally, additional optimization considerations as well as possible future extensions will be explored. This paper hopes to contribute to the field of EV integration by coupling optimized EV charging coordination with the EV utilization predictions on which the former heavily relies.