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Power maximization from resonant electromagnetic vibration harvesters feeding bridge rectifiers
Author(s) -
Costanzo Luigi,
Lo Schiavo Alessandro,
Vitelli Massimo
Publication year - 2019
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2574
Subject(s) - rectifier (neural networks) , inductor , electromagnetic coil , capacitor , vibration , power (physics) , figure of merit , dissipative system , power factor , electrical engineering , h bridge , energy (signal processing) , engineering , acoustics , physics , electronic engineering , computer science , voltage , optoelectronics , stochastic neural network , quantum mechanics , machine learning , inverter , recurrent neural network , artificial neural network
Summary In this paper, it is shown that, for resonant electromagnetic vibration energy harvesters (REVEH) feeding diode bridge rectifiers, it is possible to quantify how close the ideal load condition is to the actual load condition. For this purpose, a new figure of merit, the REVEH exploitation factor (REF), is introduced. The higher the REF, the higher the REVEH exploitation. Moreover, by using the REF, a suitable technique for increasing the extracted power in a frequency region of interest is investigated. This is the frequency region where a significant energy content of the input vibrations is present. The investigated technique is based on the proper insertion of additional non‐dissipative components (capacitors or inductors) between the REVEH coil and the bridge rectifier. Experimental results confirm the validity of the theoretical analysis.