Detail publikace
Artificial intelligence based optimization for vibration energy harvesting applications
HADAŠ, Z. KURFÜRST, J. ONDRŮŠEK, Č. SINGULE, V.
Český název
Artificial intelligence based optimization for vibration energy harvesting applications
Anglický název
Artificial intelligence based optimization for vibration energy harvesting applications
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
en
Originální abstrakt
This paper deals with optimization studies based on artificial intelligence methods. These modern optimization methods can be very useful for design improving of an electromagnetic vibration energy harvester. The vibration energy harvester is a complex mechatronic device which harvests electrical energy from ambient mechanical vibrations. The harvester design consists of a precise mechanical resonator, electromagnetic converter and electronics. The optimization study of such complex mechatronic device is complicated however artificial intelligence methods can be used for set up of optimal harvester parameters. Used optimization strategies are applied to optimize the design of the electro-magnetic vibration energy harvester according to multi-objective fitness functions. Optimization results of the harvester are summarized in this paper. Presented optimization algorithms can be used for a design of new energy harvesting systems or for improving on existing energy harvesting systems.
Český abstrakt
This paper deals with optimization studies based on artificial intelligence methods. These modern optimization methods can be very useful for design improving of an electromagnetic vibration energy harvester. The vibration energy harvester is a complex mechatronic device which harvests electrical energy from ambient mechanical vibrations. The harvester design consists of a precise mechanical resonator, electromagnetic converter and electronics. The optimization study of such complex mechatronic device is complicated however artificial intelligence methods can be used for set up of optimal harvester parameters. Used optimization strategies are applied to optimize the design of the electro-magnetic vibration energy harvester according to multi-objective fitness functions. Optimization results of the harvester are summarized in this paper. Presented optimization algorithms can be used for a design of new energy harvesting systems or for improving on existing energy harvesting systems.
Anglický abstrakt
This paper deals with optimization studies based on artificial intelligence methods. These modern optimization methods can be very useful for design improving of an electromagnetic vibration energy harvester. The vibration energy harvester is a complex mechatronic device which harvests electrical energy from ambient mechanical vibrations. The harvester design consists of a precise mechanical resonator, electromagnetic converter and electronics. The optimization study of such complex mechatronic device is complicated however artificial intelligence methods can be used for set up of optimal harvester parameters. Used optimization strategies are applied to optimize the design of the electro-magnetic vibration energy harvester according to multi-objective fitness functions. Optimization results of the harvester are summarized in this paper. Presented optimization algorithms can be used for a design of new energy harvesting systems or for improving on existing energy harvesting systems.
Klíčová slova česky
Vibration energy harvester, energy harvesting, optimization, SOMA, artificial intelligence
Klíčová slova anglicky
Vibration energy harvester, energy harvesting, optimization, SOMA, artificial intelligence
Rok RIV
2012
Vydáno
07.02.2012
Nakladatel
Springer Berlin / Heidelberg
Místo
Berlín
ISSN
0946-7076
Ročník
18
Číslo
7-8
Strany od–do
1003–1014
Počet stran
12
BIBTEX
@article{BUT89532,
author="Zdeněk {Hadaš} and Jiří {Kurfűrst} and Čestmír {Ondrůšek} and Vladislav {Singule},
title="Artificial intelligence based optimization for vibration energy harvesting applications",
year="2012",
volume="18",
number="7-8",
month="February",
pages="1003--1014",
publisher="Springer Berlin / Heidelberg",
address="Berlín",
issn="0946-7076"
}