A high-power non-contact Magnetic Conversion-Enhanced Wind Energy Harvester for self-powered iot nodes and real-time wind speed sensing

被引:1
作者
Li, Yunfei [1 ,2 ]
Huang, Manjuan [2 ]
Tang, Tianyi [1 ,2 ]
Mei, Mingqi [2 ]
Zhao, Heng [2 ]
Zha, Fusheng [1 ]
Sun, Lining [1 ,2 ]
Liu, Huicong [2 ]
机构
[1] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
[2] Soochow Univ, Sch Mech & Elect Engn, Jiangsu Key Lab Embodied Intelligence Robot Techno, Suzhou 215006, Peoples R China
基金
中国国家自然科学基金;
关键词
Wind energy harvesting; Self-powered environmental monitoring sensor nodes; Self-sensing system; Non-contact magnetic conversion-enhanced mechanism;
D O I
10.1016/j.nanoen.2025.111293
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Harnessing wind energy to power Internet of Things (IoT) sensor nodes is a critical step toward advancing sustainable environmental monitoring. Traditional wind energy harvesters (WEHs) often suffer from low rotational speeds and insufficient output, limiting their application in autonomous monitoring systems. In this work, we present a non-contact magnetic conversion-enhanced wind energy harvester (MCE-WEH) that combines efficient energy harvesting with self-sensing capabilities to overcome these limitations. At the core of the system is a magnetic conversion enhancement (MCE) mechanism. By arranging a specific number of soft magnetic materials beneath the driving magnets, it induces faster periodic variations in the magnetic field acting on the driven magnets, thereby accelerating their motion and enabling non-contact power transmission. When wind rotates the blades, the MCE mechanism amplifies the rotational frequency by 4:1 and transfers motion to the electromagnetic generator (EMG) without physical contact. This approach significantly improves low-frequency wind energy utilization while reducing mechanical wear and enhancing system reliability. The EMG delivers up to 1.6 W at a wind speed of 9.5 m/s, sufficient to power commercial environmental sensors and high-power communication modules. Moreover, the system integrates a self-powered wind speed sensing mechanism. Leveraging the strong linear relationship (R-2 = 0.995) between the output frequency of the triboelectric nanogenerator (TENG) and wind speed, the system enables accurate real-time wind monitoring under low-to-medium wind conditions. Together, these features provide a robust platform for autonomous, multi-parameter environmental monitoring in remote and harsh environments such as terrain-effect wind zones and air-sea interface regions.
引用
收藏
页数:13
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