Publication detail

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

HADAŠ, Z. ONDRŮŠEK, Č. KURFÜRST, J.

Original Title

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

English Title

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

Type

conference paper

Language

en

Original Abstract

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.

English abstract

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.

Keywords

Vibration Power Generator, Optimization. Genetic Algorithm, SOMA

RIV year

2009

Released

18.11.2009

Publisher

Springer-Verlag Berlin Heidelberg

Location

Berlin

ISBN

978-3-642-05021-3

Book

Recent Advancecs in Mechatronics 2008-2009

Edition

1

Edition number

1

Pages from

245

Pages to

250

Pages count

6

Documents

BibTex


@inproceedings{BUT29379,
  author="Zdeněk {Hadaš} and Čestmír {Ondrůšek} and Jiří {Kurfűrst}",
  title="Optimization of Vibration Power Generator Parameters Using Self-Organizing Migrating Algorithm",
  annote="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.",
  address="Springer-Verlag Berlin Heidelberg",
  booktitle="Recent Advancecs in Mechatronics 2008-2009",
  chapter="29379",
  edition="1",
  howpublished="print",
  institution="Springer-Verlag Berlin Heidelberg",
  year="2009",
  month="november",
  pages="245--250",
  publisher="Springer-Verlag Berlin Heidelberg",
  type="conference paper"
}