Multiobjective search for the management of a hybrid energy storage system

Self-optimizing mechatronic systems are a new class of technical systems which are able to autonomously reason about their objectives and to select appropriate behavior adaptations with regard to their current environment and changing requirements. Obviously, reasoning and changing the system's behavior during operation is a time critical task. Thus, it is usually not possible to explore all possible behaviors and evaluate them regarding various objectives. To reduce this effort, the set of nondominated solutions, the Pareto set, can be computed in advance and thus the effort of adapting the system behavior is reduced to a decision making process. This paper introduces a search based approach to approximate the Pareto set with a multi objective search algorithm. The algorithm is designed for the management of a hybrid energy storage module in a rail-bound vehicle where the two contradicting objectives of maximizing the power reserve to maintain robust against unexpected power peaks and minimizing the deterioration of the storages have to be optimized simultaneously.