Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems
Large amplitude inter-well oscillations in bi-stable energy harvesters made them a proper energy harvesting choice due to high energy generation. However, the co-existence of the chaotic attractor in these harvesters could essentially decrease their efficiency. In this paper, an algorithm for detect...
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| Format: | Article |
| Language: | English |
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Shahrood University of Technology
2021-01-01
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| Series: | Renewable Energy Research and Applications |
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| Online Access: | http://rera.shahroodut.ac.ir/article_1962_e5ac0f18be5a6d920c5a4bca873a0f48.pdf |
| _version_ | 1818469984242761728 |
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| author | M. Mohammadpour Seyed M. M. Modarres-Gheisari P. Safarpour R. Gavagsaz-Ghoachani M. Zandi |
| author_facet | M. Mohammadpour Seyed M. M. Modarres-Gheisari P. Safarpour R. Gavagsaz-Ghoachani M. Zandi |
| author_sort | M. Mohammadpour |
| collection | DOAJ |
| description | Large amplitude inter-well oscillations in bi-stable energy harvesters made them a proper energy harvesting choice due to high energy generation. However, the co-existence of the chaotic attractor in these harvesters could essentially decrease their efficiency. In this paper, an algorithm for detecting chaos in bi-stable energy harvesters based on a data-gathering algorithm and estimating the largest Lyapunov exponent is investigated. First, a simple model of axially loaded non-linear energy harvesters is derived. This model is derived using the Euler-Bernoulli beam theory and the Assumed Mode method considering the Von-Karman non-linear strain-displacement equation. The harvester's numerical simulation results are used to test the algorithm's efficiency and accuracy in identifying chaotic response. The results showed the algorithm's success in detecting chaos in such systems with minimum possible calculation cost. The effect of noise on the algorithm's performance has been investigated, and the results showed the excellent robustness of the algorithm to noise. It can diagnose the harvester's chaotic or harmonic behavior with noise-contaminated data, with 10 percent noise density. The comparison between this algorithm and Wolf's method showed relatively less computation time, up to 80 percent, to detect chaos with reasonable accuracy. |
| first_indexed | 2024-04-13T21:31:52Z |
| format | Article |
| id | doaj.art-b14fb3973b7d499abb9e0dc3c93d08ae |
| institution | Directory Open Access Journal |
| issn | 2717-252X 2676-7430 |
| language | English |
| last_indexed | 2024-04-13T21:31:52Z |
| publishDate | 2021-01-01 |
| publisher | Shahrood University of Technology |
| record_format | Article |
| series | Renewable Energy Research and Applications |
| spelling | doaj.art-b14fb3973b7d499abb9e0dc3c93d08ae2022-12-22T02:29:08ZengShahrood University of TechnologyRenewable Energy Research and Applications2717-252X2676-74302021-01-0121718010.22044/rera.2020.10240.10411962Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting SystemsM. Mohammadpour0Seyed M. M. Modarres-Gheisari1P. Safarpour2R. Gavagsaz-Ghoachani3M. Zandi4Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.Large amplitude inter-well oscillations in bi-stable energy harvesters made them a proper energy harvesting choice due to high energy generation. However, the co-existence of the chaotic attractor in these harvesters could essentially decrease their efficiency. In this paper, an algorithm for detecting chaos in bi-stable energy harvesters based on a data-gathering algorithm and estimating the largest Lyapunov exponent is investigated. First, a simple model of axially loaded non-linear energy harvesters is derived. This model is derived using the Euler-Bernoulli beam theory and the Assumed Mode method considering the Von-Karman non-linear strain-displacement equation. The harvester's numerical simulation results are used to test the algorithm's efficiency and accuracy in identifying chaotic response. The results showed the algorithm's success in detecting chaos in such systems with minimum possible calculation cost. The effect of noise on the algorithm's performance has been investigated, and the results showed the excellent robustness of the algorithm to noise. It can diagnose the harvester's chaotic or harmonic behavior with noise-contaminated data, with 10 percent noise density. The comparison between this algorithm and Wolf's method showed relatively less computation time, up to 80 percent, to detect chaos with reasonable accuracy.http://rera.shahroodut.ac.ir/article_1962_e5ac0f18be5a6d920c5a4bca873a0f48.pdfenergy harvestingbi-stabilitychaoslargest lyapunov exponent |
| spellingShingle | M. Mohammadpour Seyed M. M. Modarres-Gheisari P. Safarpour R. Gavagsaz-Ghoachani M. Zandi Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems Renewable Energy Research and Applications energy harvesting bi-stability chaos largest lyapunov exponent |
| title | Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems |
| title_full | Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems |
| title_fullStr | Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems |
| title_full_unstemmed | Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems |
| title_short | Identifying Chaotic Behavior in Non-linear Vibration Energy Harvesting Systems |
| title_sort | identifying chaotic behavior in non linear vibration energy harvesting systems |
| topic | energy harvesting bi-stability chaos largest lyapunov exponent |
| url | http://rera.shahroodut.ac.ir/article_1962_e5ac0f18be5a6d920c5a4bca873a0f48.pdf |
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