Nonlinear Dynamic Performance of Low‐Frequency Vibration Energy Harvesting Systems Based on an Adjustable Rhombic Inertia Amplifier and Gear‐Adjustable Device

Harvesting energy from vibrations at different frequencies is a prominent research topic. This article proposes adjusting the effective stiffness of the system by modulating the rotation angle of gears, thereby enabling more efficient energy harvesting under varying vibration conditions. The gear assembly is connected to a large mass block, with two spring‐connected mass blocks attached to either side of the lower rhombic link. For the system incorporating gear adjustment and an inertia amplifier, equations of motion are derived. Subsequently, plots are generated for the root mean square value of induced voltage, bifurcation diagrams of displacement versus excitation amplitude at different initial angles of the inertia amplifier, and coexistence attractor diagrams. Phase trajectory variations under different initial conditions are also investigated. By adjusting the gear rotation angle, the distribution of chaotic regions and the effective range for energy harvesting are modified. Results demonstrate that this device facilitates efficient adaptation to varying vibration energy collection conditions. Modifying the initial angle of the inertia amplifier and the gear rotation angle significantly optimizes energy harvesting efficiency.

Authors

Institutions

Publication Details

Journal
Energy Technology
Published
2026-02-01
DOI
https://doi.org/10.1002/ente.202502485
Primary Topic
Innovative Energy Harvesting Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nonlinear Dynamic Performance of Low‐Frequency Vibration Energy Harvesting Systems Based on an Adjustable Rhombic Inertia Amplifier and Gear‐Adjustable Device

Xinzong Wang, Ao Zhang, Hui Li, Xiaofang Kang et al.
Energy Technology
Innovative Energy Harvesting Technologies
article

Nonlinear Dynamic Performance of Low‐Frequency Vibration Energy Harvesting Systems Based on an Adjustable Rhombic Inertia Amplifier and Gear‐Adjustable Device

Xinzong Wang, Ao Zhang, Hui Li, Xiaofang Kang, Shaojie Ma
article en

Abstract

Harvesting energy from vibrations at different frequencies is a prominent research topic. This article proposes adjusting the effective stiffness of the system by modulating the rotation angle of gears, thereby enabling more efficient energy harvesting under varying vibration conditions. The gear assembly is connected to a large mass block, with two spring‐connected mass blocks attached to either side of the lower rhombic link. For the system incorporating gear adjustment and an inertia amplifier, equations of motion are derived. Subsequently, plots are generated for the root mean square value of induced voltage, bifurcation diagrams of displacement versus excitation amplitude at different initial angles of the inertia amplifier, and coexistence attractor diagrams. Phase trajectory variations under different initial conditions are also investigated. By adjusting the gear rotation angle, the distribution of chaotic regions and the effective range for energy harvesting are modified. Results demonstrate that this device facilitates efficient adaptation to varying vibration energy collection conditions. Modifying the initial angle of the inertia amplifier and the gear rotation angle significantly optimizes energy harvesting efficiency.

Energy TechnologyVol. 14(2)
Anhui Jianzhu University (CN), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 52%
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.