On the Reduced-order Modeling of Energy Harvesters

This work addresses the accuracy and convergence of reduced-order models (ROMs) of energy harvesters. Two types of energy harvesters are considered, a magnetostrictive rod in axial vibrations and a piezoelectric cantilever beam in traverse oscillations. Using generalized Hamilton’s principle, the partial differential equations (PDEs) and associated boundary conditions governing the motion of these harvesters are obtained. The eigenvalue problem is then solved for the exact eigenvalues and modeshapes. Furthermore, an exact expression for the steady-sate output power is attained by direct solution of the PDEs. Subsequently, the results are compared to a ROM attained following the common Rayleigh—Ritz procedure. It is observed that the eigenvalues and output power near the first resonance frequency are more accurate and has a much faster convergence to the exact solution for the piezoelectric cantilever-type harvester. In addition, it is shown that the convergence is governed by two dimensionless constants, one that is related to the electromechanical coupling and the other to the ratio between the time constant of the mechanical oscillator and the harvesting circuit. Using these results, some interesting conclusions are drawn in regards to the design values for which the common single-mode ROM is accurate. It is also shown that the number of modes necessary for convergence should be obtained at maximum electric loading for the piezoelectric harvester and at minimum electric loading in the magnetostrictive case.

[1]  Daniel J. Inman,et al.  Estimation of Electric Charge Output for Piezoelectric Energy Harvesting , 2004 .

[2]  D. Guyomar,et al.  Piezoelectric Energy Harvesting Device Optimization by Synchronous Electric Charge Extraction , 2005 .

[3]  Daniel J. Inman,et al.  A Distributed Parameter Electromechanical Model for Cantilevered Piezoelectric Energy Harvesters , 2008 .

[4]  Lei Wang,et al.  Energy harvesting by magnetostrictive material (MsM) for powering wireless sensors in SHM , 2007, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[5]  Loreto Mateu,et al.  Review of energy harvesting techniques and applications for microelectronics (Keynote Address) , 2005, SPIE Microtechnologies.

[6]  Y. Shu,et al.  Analysis of power output for piezoelectric energy harvesting systems , 2006 .

[7]  L. Meirovitch Analytical Methods in Vibrations , 1967 .

[8]  Joseph A. Paradiso,et al.  Energy scavenging for mobile and wireless electronics , 2005, IEEE Pervasive Computing.

[9]  Marilyn Wun-Fogle,et al.  Characterization of Terfenol-D for magnetostrictive transducers , 1990 .

[10]  R. D. Greenough,et al.  The stress dependence of k/sub 33/, d/sub 33/, lambda and mu in Tb/sub 0.3/Dy/sub 0.7/Fe/sub 1.95/ , 1992 .

[11]  Alison B. Flatau,et al.  Characterization of energy harvesting potential of Terfenol-D and Galfenol , 2005, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[12]  Thiago Seuaciuc-Osório,et al.  Effect of bias conditions on the optimal energy harvesting using magnetostrictive materials , 2008, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[13]  D. Inman,et al.  A Review of Power Harvesting from Vibration using Piezoelectric Materials , 2004 .

[14]  Shadrach Roundy,et al.  On the Effectiveness of Vibration-based Energy Harvesting , 2005 .

[15]  Wei-Hsin Liao,et al.  Sensitivity Analysis and Energy Harvesting for a Self-Powered Piezoelectric Sensor , 2005 .

[16]  Du Toit,et al.  Modeling and design of a MEMS piezoelectric vibration energy harvester , 2005 .

[17]  Daniel J. Inman,et al.  Issues in mathematical modeling of piezoelectric energy harvesters , 2008 .