Publication detail
Artificial intelligence based optimization for vibration energy harvesting applications
HADAŠ, Z. KURFÜRST, J. ONDRŮŠEK, Č. SINGULE, V.
Czech title
Artificial intelligence based optimization for vibration energy harvesting applications
English title
Artificial intelligence based optimization for vibration energy harvesting applications
Type
journal article in Web of Science
Language
en
Original abstract
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.
Czech abstract
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.
English abstract
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.
Keywords in Czech
Vibration energy harvester, energy harvesting, optimization, SOMA, artificial intelligence
Keywords in English
Vibration energy harvester, energy harvesting, optimization, SOMA, artificial intelligence
RIV year
2012
Released
07.02.2012
Publisher
Springer Berlin / Heidelberg
Location
Berlín
ISSN
0946-7076
Volume
18
Number
7-8
Pages from–to
1003–1014
Pages count
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"
}