整流器(神经网络)
电气工程
电压
材料科学
升压变换器
能量收集
功率(物理)
功率密度
工程类
计算机科学
物理
随机神经网络
量子力学
机器学习
循环神经网络
人工神经网络
作者
Huifang Liu,Chongdong Cao,Xingwei Sun,Luyao Zhao,Cong Chen
出处
期刊:AIP Advances
[American Institute of Physics]
日期:2020-11-01
卷期号:10 (11)
被引量:9
摘要
A magnetostrictive vibration energy harvester based on an iron–gallium alloy composite cantilever beam is developed, and its capability is optimized from the aspects of bias magnetic field and the number of active layers. To solve the issue of low and irregular output voltage, it designs a converter suitable for a low-power harvester to make full use of the generated electric energy. A set of AC–DC converters with two working modes is designed by using the multiple voltage rectification method, which is able to directly drive low power load or store energy to supply power to higher power load. Through theoretical simulation and experiment, the converter’s characteristics, such as rectifier and filter characteristics, energy storage, and release process are systematically studied and tested. 1 V AC output voltage of the harvester is able to be converted into 5 V DC voltage after being processed by the converter. The proposed harvester provides an excellent vibration harvesting capacity that the AC normalized power density (power density per volume and acceleration) reaches 7.4 mW/(cm3/g). The harvesting system with the two-mode converter has achieved a high normalized DC output power vs AC input voltage of 630 µW/V. We have applied the harvester and converter for a low power electronic meter, which can work normally and display the time, temperature, and humidity in the laboratory. In addition, we have also applied the harvesting system for a higher power (1.2 W) electric fan with a universal serial bus (USB) port. After battery charging and IP5306 voltage boosting, the harvester meets the normal operation requirements of an electric fan with a USB port and it is able to operate normally.
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