Experimental design and genetic algorithm optimization of a fuzzy-logic supervisor for embedded electrical power systems

Stefan Breban, Christophe Saudemont, Sébastien Vieillard and Benoît Robyns

Mathematics and Computers in Simulation (MATCOM), 2013, vol. 91, issue C, 91-107

Abstract: 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.

Keywords: Embedded electrical power system; Energy storage; Fuzzy logic; Optimization; Experimental design; Genetic algorithm (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:91:y:2013:i:c:p:91-107

DOI: 10.1016/j.matcom.2012.06.003

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