REAL-TIME FREQUENCY TUNING OF KINETIC ENERGY HARVESTERS VIA SYSTEM MASS ADJUSTMENT

This research presents a method for real-time frequency tuning of piezoelectric kinetic energy harvesters through system-mass adjustment. Custom 3D-printed proof masses with cavity arrays were used to redistribute solid or liquid mass, enabling controlled modification of resonant frequency. Experimental studies using microparticles and liquids—including water, silicone oil, and sodium polytungstate—demonstrated an achievable tuning range of 115.27 Hz with sub-hertz resolution (< 0.1 Hz), confirming precise and repeatable frequency control. Finite-element modeling guided design optimization, while a microfluidic channel system enabled automated liquid filling for real-time operation. A MATLAB-based EH_Tuning application was developed to visualize and predict frequency responses. The combined computational and experimental results establish a scalable, energy-efficient approach for adaptive piezoelectric harvesters suited for Internet of Things and wireless sensor network applications.

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Publication Details

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UNM’s Digital Repository (University of New Mexico)
Published
2025-12-13
Primary Topic
Innovative Energy Harvesting Technologies
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article
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article

REAL-TIME FREQUENCY TUNING OF KINETIC ENERGY HARVESTERS VIA SYSTEM MASS ADJUSTMENT

Rahul Adhikari
UNM’s Digital Repository (University of New Mexico)
Innovative Energy Harvesting Technologies
article

REAL-TIME FREQUENCY TUNING OF KINETIC ENERGY HARVESTERS VIA SYSTEM MASS ADJUSTMENT

Rahul Adhikari
article en

Abstract

This research presents a method for real-time frequency tuning of piezoelectric kinetic energy harvesters through system-mass adjustment. Custom 3D-printed proof masses with cavity arrays were used to redistribute solid or liquid mass, enabling controlled modification of resonant frequency. Experimental studies using microparticles and liquids—including water, silicone oil, and sodium polytungstate—demonstrated an achievable tuning range of 115.27 Hz with sub-hertz resolution (< 0.1 Hz), confirming precise and repeatable frequency control. Finite-element modeling guided design optimization, while a microfluidic channel system enabled automated liquid filling for real-time operation. A MATLAB-based EH_Tuning application was developed to visualize and predict frequency responses. The combined computational and experimental results establish a scalable, energy-efficient approach for adaptive piezoelectric harvesters suited for Internet of Things and wireless sensor network applications.

UNM’s Digital Repository (University of New Mexico)
Affordable and clean energy
Openalex Percentile: Top 40%
Innovative Energy Harvesting Technologies
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