A decentralized charge management for electric vehicles using a genetic algorithm: Case study and proof-of-concept in Java and FPGA

Genetic algorithms are a common option to solve optimization problems. In this paper a decentralized approach to calculate a charging schedule for electric vehicles based on a genetic algorithm is presented. It is predicted, that the number of battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV) will increase to 5 million vehicles by the year of 2020. The increase of electric vehicles will have an impact on the existing power infrastructure, especially at specific times of day. Equipping all electric vehicles with a power controlling unit (PCU) in a so-called consumer grid, and connect the PCUs to each other, will allow to calculate an optimized schedule. This schedule ensures that all electric vehicles are charged and that a given maximum power peak will not be exceeded. First, the proposed approach was implemented in a Java program and its performance was evaluated for different scenarios. Afterwards, a VHDL (Very High Speed Integrated Circuit Hardware Description Language) implementation was created and verified by using simulation and FPGAs (Field Programmable Gate Array).