Hybrid piezoelectric-electromagnetic energy harvesting from ultra-low-frequency human motion via magnetic frequency up-conversion

Efficiently harvesting ultra-low-frequency vibration energy from human motion to power electronic devices remains challenging. This study presents a compact magnetically coupled energy harvester (MCEH) that integrates piezoelectric (PEH) and electromagnetic (EEH) modules through a shared reciprocating center magnet. The center magnet simultaneously produces electromagnetic induction and excites the piezoelectric cantilevers through nonlinear magnetic repulsion, enabling dual-path energy conversion and magnetic frequency up-conversion from excitation below 10 Hz. A coupled lumped-parameter electromechanical model was established and evaluated using numerical simulations and experiments, including frequency-response, load-matching, human-motion, and sensor-powering tests. At 6.5 Hz, the PEH reaches an RMS voltage of 3.56 V with magnetic coupling, versus only 0.0383 V for the no-center-magnet reference, showing an approximately 93-fold enhancement. Under the matched loads, the system delivers a total output of 1,147.88 μ W and a normalized power density of 31.89 μ W/ cm 3 . The prototype also powers a temperature-humidity sensor under the tested motion conditions, demonstrating the feasibility of the proposed approach for low-power wearable sensing.

Authors

Institutions

Publication Details

Journal
Journal of Vibration and Control
Published
2026-11-07
DOI
https://doi.org/10.1177/10775463261504874
Primary Topic
Innovative Energy Harvesting Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Hybrid piezoelectric-electromagnetic energy harvesting from ultra-low-frequency human motion via magnetic frequency up-conversion

Zhaoxi Wang, Minglei Han, Xu Yang, Weian Wang et al.
2 links
Journal of Vibration and Control
Innovative Energy Harvesting Technologies
article

Hybrid piezoelectric-electromagnetic energy harvesting from ultra-low-frequency human motion via magnetic frequency up-conversion

Zhaoxi Wang, Minglei Han, Xu Yang, Weian Wang, Yulai Yang, Xin Ma, Yixin Cui, Huixian Song
article en

Abstract

Efficiently harvesting ultra-low-frequency vibration energy from human motion to power electronic devices remains challenging. This study presents a compact magnetically coupled energy harvester (MCEH) that integrates piezoelectric (PEH) and electromagnetic (EEH) modules through a shared reciprocating center magnet. The center magnet simultaneously produces electromagnetic induction and excites the piezoelectric cantilevers through nonlinear magnetic repulsion, enabling dual-path energy conversion and magnetic frequency up-conversion from excitation below 10 Hz. A coupled lumped-parameter electromechanical model was established and evaluated using numerical simulations and experiments, including frequency-response, load-matching, human-motion, and sensor-powering tests. At 6.5 Hz, the PEH reaches an RMS voltage of 3.56 V with magnetic coupling, versus only 0.0383 V for the no-center-magnet reference, showing an approximately 93-fold enhancement. Under the matched loads, the system delivers a total output of 1,147.88 μ W and a normalized power density of 31.89 μ W/ cm 3 . The prototype also powers a temperature-humidity sensor under the tested motion conditions, demonstrating the feasibility of the proposed approach for low-power wearable sensing.

Journal of Vibration and Control
Jilin University (CN), Changchun University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 24%
Innovative Energy Harvesting Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon