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Author Ippolito, L. ♦ Loia, V. ♦ Siano, P.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2003
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Genetic algorithms ♦ Load flow ♦ Energy management ♦ Hybrid electric vehicles ♦ Power demand ♦ Internal combustion engines ♦ Electric motors ♦ Power supplies ♦ Fuzzy control ♦ Fuzzy systems
Abstract Most of the features of the future hybrid electric vehicles are enabled by a new energy flow management unit designed to split the instantaneous power demand between the internal combustion engine and the electric motor, ensuring both an efficient power supply and a reduced emission. Classic approaches that rely on static thresholds, optimized on a fixed drive cycle, cannot face the high dynamicity and unpredictability of real-life drive conditions. The proposed approach exploits a fuzzy clustering criterion that combined with a genetic algorithm, permits to achieve better results, both in terms of a reduced computational effort and an improved efficiency of the control system over various driving cycles.
Description Author affiliation: Dipt. di Ingegneria dell'Informazione ed Ingegneria Elettrica, Salerno Univ., Fisciano, Italy (Ippolito, L.)
ISBN 078037729X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2003-06-25
Publisher Place Turkey
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 394.25 kB
Page Count 5
Starting Page 115
Ending Page 119


Source: IEEE Xplore Digital Library