Detail publikace

Optimization of Vibration Power Generator Parameters Using Self-Organizing Migrating Algorithm

HADAŠ, Z. ONDRŮŠEK, Č. KURFÜRST, J.

Originální název

Optimization of Vibration Power Generator Parameters Using Self-Organizing Migrating Algorithm

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper deals with a self-organizing migrating algorithm (SOMA) for an optimization of vibration power generator parameters. The vibration power generator is an energy harvesting device, which is capable of harvest electrical en-ergy from an ambient mechanical vibration. The generator consists of a precise mechanical part, electro-mechanical converter and electronics. It creates a com-plex mechatronic system, where parameters of individual parts are mutually af-fected. For effective harvesting of energy all parameters have to be tuned up opti-mally to nature of an excited vibration and required output power. A generator model can be used for optimization study of maximal output power and minimiza-tion of generator volume. Main problem is complexity of this system and number of parameters in mutual feed back of this mechatronic system. Thus the SOMA is applied to the optimization problem of the vibration power generator.

Klíčová slova

Vibration Power Generator, Optimization. Genetic Algorithm, SOMA

Autoři

HADAŠ, Z.; ONDRŮŠEK, Č.; KURFÜRST, J.

Rok RIV

2009

Vydáno

18. 11. 2009

Nakladatel

Springer-Verlag Berlin Heidelberg

Místo

Berlin

ISBN

978-3-642-05021-3

Kniha

Recent Advancecs in Mechatronics 2008-2009

Edice

1

Číslo edice

1

Strany od

245

Strany do

250

Strany počet

6

BibTex

@inproceedings{BUT29379,
  author="Zdeněk {Hadaš} and Čestmír {Ondrůšek} and Jiří {Kurfűrst}",
  title="Optimization of Vibration Power Generator Parameters Using Self-Organizing Migrating Algorithm",
  booktitle="Recent Advancecs in Mechatronics 2008-2009",
  year="2009",
  series="1",
  number="1",
  pages="245--250",
  publisher="Springer-Verlag Berlin Heidelberg",
  address="Berlin",
  isbn="978-3-642-05021-3"
}