High Performance Magnetic Mass‐Enhanced Triboelectric‐Electromagnetic Hybrid Vibration Energy Harvester Enabling Totally Self‐Powered Long‐Distance Wireless Sensing

Author:

Xi Ziyue1,Yu Hongyong1,Du Hengxu1,Yang Hengyi1,Wang Yawei2,Guan Mengyuan1,Wang Zhaoyang1,Wang Hao1,Du Taili1,Xu Minyi1ORCID

Affiliation:

1. Dalian Key Lab of Marine Micro/Nano Energy and Self‐powered Systems Marine Engineering College State Key Laboratory of Maritime Technology and Safety Dalian Maritime University Dalian 116026 China

2. Internet of Things Thrust The Hong Kong University of Science and Technology (Guangzhou) Nansha Guangzhou Guangdong 511400 China

Abstract

AbstractWireless sensor networks play a significant role in various fields, and it is promising to construct a totally self‐powered wireless sensor network by harvesting unused mechanical vibration energy. Here, a magnetic mass‐enhanced triboelectric‐electromagnetic hybrid nanogenerator (MM‐HNG) is proposed for harvesting mechanical vibration energy. The additional magnets generate magnetic fields for electromagnetic power generation. As an additional mass effectively increases the membrane's amplitude, thereby enhancing the output performance of the MM‐HNG. The peak power density of TENG in the MM‐HNG reaches 380.4 W m−3, while the peak power density of EMG achieves 736 W m−3, which can charge a 0.1 F capacitor rapidly. In addition, a totally self‐powered wireless sensing system is constructed, with the integrated microcontroller unit (MCU), which detects and processes various sensing parameters and controls wireless transmission. The system features rapid transmission speeds and an extensive transmission range (up to 1 km), and its effectiveness has been validated in a practical application aboard an actual ship. The results illustrate the MM‐HNG's broad applicability across various Internet of Things (IoT) scenarios, including smart machinery, smart transportation, and smart factories.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3