Open AccessTracking Of Maximum Electrical Power for a Piezoelectric Energy Harvesting System
Author(s) -
Behnam Dadashzadeh*,
Hadi Fekrmandi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3492.098319
Subject(s) - energy harvesting , renewable energy , tracking (education) , power (physics) , piezoelectricity , maximum power principle , computer science , work (physics) , electric potential energy , electricity generation , artificial neural network , energy (signal processing) , energy system , control engineering , electrical engineering , engineering , photovoltaic system , mechanical engineering , artificial intelligence , mathematics , physics , psychology , pedagogy , statistics , quantum mechanics
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.