Harvesting energy from acoustic pressure fluctuations within hydraulic systems via excitation of piezoelectric stacks

Energy harvesting;Piezoelectrics;Acoustics;Hydraulics;Pressure ripple;Helmholtz resonator;Piezoelectric stacks;Ferroelectrics;Voltage multiplier;Power conditioning

Skow, Ellen A. ; Cunefare, Kenneth A. Mechanical Engineering Erturk, Alper Degertekin, F. Levent Ferri, Aldo A. Lynch, Christopher S. ; Cunefare, Kenneth A.

University:Georgia Institute of Technology

Department:Mechanical Engineering

关键词: Energy harvesting;    Piezoelectrics;    Acoustics;    Hydraulics;    Pressure ripple;    Helmholtz resonator;    Piezoelectric stacks;    Ferroelectrics;    Voltage multiplier;    Power conditioning;   

Others  :  https://smartech.gatech.edu/bitstream/1853/58652/1/SKOW-DISSERTATION-2017.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Hydraulic systems provide a unique opportunity to convert acoustic energy into electric energy due to the high intensity pressure ripple in the system. Hydraulic pressure energy harvesters (HPEHs) aim to provide a power source for powering or recharging wireless sensor networks on hydraulic systems through using an inherent byproduct of the pumps and actuators - the pressure ripple. HPEHs are able to connect to hydraulic systems via ports typically used for other sensors, such as for static pressure or temperature monitoring. HPEHs convert the pressure ripple into electricity by coupling the fluid fluctuations to a piezoelectric element, such as a stack or single crystal. The pressure ripple dominant frequencies are typically contained within the first or second harmonic of the pump operating frequency, which is usually in the 100s of Hz range, meaning the piezoelectric element is excited well below its resonance frequency. The combination of low-frequency excitation and high piezoelectric stack capacitance allow implementing an inductive load and resistive load in parallel with the piezoelectric stack to provide a passive resonant circuit. Using a soft PZT stack within a HPEH device and a parallel resistive load, a HPEH is able to provide 12.8 mW of AC power for a 202 kPa dynamic pressure amplitude, which corresponded to 0.31 µW/(kPa)^2 of power per squared dynamic pressure amplitude, which is sufficient to power sensors. Power needed for a wireless sensor transmitting data once every second is estimated to be 3.7 mW. This work introduces the HPEH devices, provides an electromechanical model, and investigates multiple methods to increase the power conversion efficiency and regulate the power output. There are three main parts of HPEH devices: (1) the mechanical coupling between the hydraulic fluid & piezoelectric element; (2) the piezoelectric material; and (3) an electrical circuit connected to the piezoelectric element. In regards to the mechanical coupling element, a Helmholtz resonator design is introduced and modeled for the coupling between a HPEH and the hydraulic system to provide pressure - and thus force - amplification to the piezoelectric element, resulting in a doubling of the normalized power response. For the piezoelectric material selection, a [011] cut lead indium niobate - lead magnesium niobate - lead titanate (PIN-PMN-PT) single crystal that goes through a phase transformation between ferroelectric rhombohedral and ferroelectric orthorhombic is presented as a higher power efficiency per cycle solution for HPEH devices, resulting in power output levels 100 times greater than soft PZT stacks tested. And finally for the electrical circuitry, this work provides a solution and model for power conditioning of low-voltage, low-frequency piezoelectric stack energy harvesting through the use of an inductive load in parallel with a voltage multiplier (VM), or cascade circuit. The inductive-VM circuit raised the AC voltage level from 0.59 Vrms to 2.4 VDC. A harmonic balance method model of the inductive-VM circuit is presented and provides an average error of 25%, with minimum error of less than 1%, and performed over 600 times faster than SPICE-based time domain transient analysis.