Multi-Objective Optimization of System of Systems Architectures for Vehicle to Infrastructure Applications using an Evolutionary Algorithm

In future, Electric vehicles (EV) will play a key role for an affordable and sustainable mobility in urban areas. Today, Electric Vehicles are often associated with a limitation of the usual mobility. Original Equipment Manufacturers try to reduce the drawbacks and to generate added values by connecting EVs with other individual systems, like Household Components, Photovoltaic Systems, and Home Energy Storage Systems, which builds a connected Smart Home. This correspondents to the concepts of System of Systems (SoS) and Vehicle to Infrastructure (V2I) applications. Due to a high number of variants of constituent systems, the overall development of such connected systems gets a combinatorial optimization problem. Today's engineering methods don't address the challenges of finding the optimal SoS architecture. This paper presents a new engineering methodology for searching, assessing, and optimizing the SoS architecture for V2I applications. The new methodology is based on a Non-Dominating Sorting Genetic Algorithm II for an intelligent exploring of the trade space for finding optimal configurations of constituent systems and their interfaces. Therefore, a bitwise representation of SoS architectures is introduced. The methodology is validated at a real data set.