Tracking Of Maximum Electrical Power for a Piezoelectric Energy Harvesting System
Behnam Dadashzadeh1, Hadi Fekrmandi2

1Behnam Dadashzadeh, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
2Hadi Fekrmandi, Department of Mechanical Engineering, South Dakota School of Mines & Technology, Rapid City, USA.

Manuscript received on 06 August 2019. | Revised Manuscript received on 12 August 2019. | Manuscript published on 30 September 2019. | PP: 6465-6469 | Volume-8 Issue-3 September 2019 | Retrieval Number: B3492078219/2019©BEIESP | DOI: 10.35940/ijrte.B3492.098319
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Abstract: Recent global environmental challenges have urged researchers to work on renewable energy resources. One major category of these resources is piezoelectric materials. This paper presents dynamic modeling of a piezoelectric energy harvesting system and then presents two level methodology using artificial neural networks to reach its maximum power output. Simulation results show desirable performance of the system, which leads to output increasing and tracking of maximum power in a limited time.
Index Terms: Energy Harvesting, Maximum Power, Neural Networks, Piezoelectric.

Scope of the Article:
Energy Harvesting and Transfer for Wireless Sensor Networks