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Artificial intelligence based optimization for vibration energy harvesting applications

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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.

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Acknowledgments

The present work has been supported by European Regional Development Fund in the framework of the research project NETME Centre under the Operational Programme Research and Development for Innovation. Reg. Nr. CZ.1.05/2.1.00/01.0002, id code: ED0002/01/01, project name: NETME Centre–New Technologies for Mechanical Engineering.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering, Brno University of Technology, Technicka 2896/2, 61669, Brno, Czech Republic

    Zdenek Hadas & Vladislav Singule

  2. Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 8, 61600, Brno, Czech Republic

    Jiri Kurfurst & Cestmir Ondrusek

Authors
  1. Zdenek Hadas
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  2. Jiri Kurfurst
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  3. Cestmir Ondrusek
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  4. Vladislav Singule
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Correspondence to Zdenek Hadas.

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Hadas, Z., Kurfurst, J., Ondrusek, C. et al. Artificial intelligence based optimization for vibration energy harvesting applications. Microsyst Technol 18, 1003–1014 (2012). https://doi.org/10.1007/s00542-012-1432-1

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  • DOI: https://doi.org/10.1007/s00542-012-1432-1

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