Experimental design and genetic algorithm optimization of a fuzzy-logic supervisor for embedded electrical power systems
The embedded power systems are nowadays developing at high pace. Hybrid-electric vehicles, full-electric vehicles, airplanes, ships, high-speed trains, all share a common point - the embedded electrical power system. This paper aims to present an optimization methodology of a fuzzy-logic supervision strategy. The optimization objectives are to minimize the DC-link voltage variations, and to increase the system efficiency by reducing the dissipated power. For that, a methodology involving the experimental design and genetic algorithm will be presented. The simulation and experimental results are validating the proposed procedure. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.
experimental design genetic algorithm optimization embedded electrical power system energy storage fuzzy logic