Artificial intelligence based optimization for vibration energy harvesting applications
| Autor: | Jiri Kurfurst, Zdenek Hadas, Cestmir Ondrusek, Vladislav Singule |
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| Rok vydání: | 2012 |
| Předmět: |
Physics::Biological Physics
Engineering business.industry Electric potential energy Vibration energy harvesting New energy Control engineering Mechatronics Condensed Matter Physics Computer Science::Digital Libraries Electronic Optical and Magnetic Materials Vibration Resonator Hardware_GENERAL Hardware and Architecture Artificial intelligence Electronics Electrical and Electronic Engineering business GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) Energy harvesting |
| Zdroj: | Microsystem Technologies. 18:1003-1014 |
| ISSN: | 1432-1858 0946-7076 |
| DOI: | 10.1007/s00542-012-1432-1 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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