Synthetic assessment of self-powered energy-harvesting including robustness evaluation
We have developed a smart energy harvester that generates electrical energy from multi-modal vibrations. The harvester consists of a digital processor and a piezoelectric sensor, which allows the application of a technical method to improve the energy-conversion efficiency. The method is implemented...
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The Japan Society of Mechanical Engineers
2015
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oai:doaj.org-article:465b3134a2074ec09af057513bc9121d2021-11-26T06:30:10ZSynthetic assessment of self-powered energy-harvesting including robustness evaluation2187-974510.1299/mej.14-00549https://doaj.org/article/465b3134a2074ec09af057513bc9121d2015-09-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/2/5/2_14-00549/_pdf/-char/enhttps://doaj.org/toc/2187-9745We have developed a smart energy harvester that generates electrical energy from multi-modal vibrations. The harvester consists of a digital processor and a piezoelectric sensor, which allows the application of a technical method to improve the energy-conversion efficiency. The method is implemented by measuring the vibration displacements, processing the data digitally, and adequately regulating electric switches. These operations are managed by a built-in digital processor. The driving power for the digital processor is satisfied with a part of the energy harvested from structural vibrations. Thus, the harvester operates flexibly with the digital processor to enhance electrical energy generation, and requires neither batteries nor an external power supply. We refer to the proposed device as a self-powered energy harvester. An advantage of digital processing is that observations by a Kalman filter can be used to estimate modal structural vibrations. In addition to reducing sensor noise, the digital filter extracts modal values from the measured displacement data. Here, we describe the basic configuration of the proposed harvester and demonstrate energy harvesting from multi-modal vibrations for a structure with 2 degrees of freedom (DOF). We assess the internal energy consumption of self-powered control devices, such as the digital processor and DC/DC converter. In addition, we show the robustness of the proposed harvester by conducting a harvesting experiment with electrical noise. The results demonstrate that the self-powered energy harvester generates more electrical energy from 2DOF vibrations than does a conventional harvester, and accurately operates under noisy conditions.Yuta YAMAMOTOKenji YOSHIMIZUKanjuro MAKIHARAThe Japan Society of Mechanical Engineersarticleenergy harvestingpiezoelectricmulti-modal vibrationdigital controlself-poweredMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 2, Iss 5, Pp 14-00549-14-00549 (2015) |
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energy harvesting piezoelectric multi-modal vibration digital control self-powered Mechanical engineering and machinery TJ1-1570 |
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energy harvesting piezoelectric multi-modal vibration digital control self-powered Mechanical engineering and machinery TJ1-1570 Yuta YAMAMOTO Kenji YOSHIMIZU Kanjuro MAKIHARA Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
description |
We have developed a smart energy harvester that generates electrical energy from multi-modal vibrations. The harvester consists of a digital processor and a piezoelectric sensor, which allows the application of a technical method to improve the energy-conversion efficiency. The method is implemented by measuring the vibration displacements, processing the data digitally, and adequately regulating electric switches. These operations are managed by a built-in digital processor. The driving power for the digital processor is satisfied with a part of the energy harvested from structural vibrations. Thus, the harvester operates flexibly with the digital processor to enhance electrical energy generation, and requires neither batteries nor an external power supply. We refer to the proposed device as a self-powered energy harvester. An advantage of digital processing is that observations by a Kalman filter can be used to estimate modal structural vibrations. In addition to reducing sensor noise, the digital filter extracts modal values from the measured displacement data. Here, we describe the basic configuration of the proposed harvester and demonstrate energy harvesting from multi-modal vibrations for a structure with 2 degrees of freedom (DOF). We assess the internal energy consumption of self-powered control devices, such as the digital processor and DC/DC converter. In addition, we show the robustness of the proposed harvester by conducting a harvesting experiment with electrical noise. The results demonstrate that the self-powered energy harvester generates more electrical energy from 2DOF vibrations than does a conventional harvester, and accurately operates under noisy conditions. |
format |
article |
author |
Yuta YAMAMOTO Kenji YOSHIMIZU Kanjuro MAKIHARA |
author_facet |
Yuta YAMAMOTO Kenji YOSHIMIZU Kanjuro MAKIHARA |
author_sort |
Yuta YAMAMOTO |
title |
Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
title_short |
Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
title_full |
Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
title_fullStr |
Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
title_full_unstemmed |
Synthetic assessment of self-powered energy-harvesting including robustness evaluation |
title_sort |
synthetic assessment of self-powered energy-harvesting including robustness evaluation |
publisher |
The Japan Society of Mechanical Engineers |
publishDate |
2015 |
url |
https://doaj.org/article/465b3134a2074ec09af057513bc9121d |
work_keys_str_mv |
AT yutayamamoto syntheticassessmentofselfpoweredenergyharvestingincludingrobustnessevaluation AT kenjiyoshimizu syntheticassessmentofselfpoweredenergyharvestingincludingrobustnessevaluation AT kanjuromakihara syntheticassessmentofselfpoweredenergyharvestingincludingrobustnessevaluation |
_version_ |
1718409773837189120 |