整流器(神经网络)
最大功率点跟踪
功率(物理)
最大功率原理
控制理论(社会学)
悬挂(拓扑)
最大化
工程类
计算机科学
电压
操作点
电子工程
电气工程
控制(管理)
人工神经网络
随机神经网络
微观经济学
循环神经网络
量子力学
同伦
人工智能
逆变器
经济
机器学习
物理
数学
纯数学
作者
Luigi Costanzo,Teng Lin,Weihan Lin,Alessandro Lo Schiavo,M. Vitelli,Lei Zuo
标识
DOI:10.1109/tie.2020.3009584
摘要
An electronic interface for the maximization of the power extraction from train suspension energy harvesters is presented in this article. It is made up of a passive rectifier and a dc-dc converter equipped with a digital control unit that implements a novel maximum power point tracking technique. It can settle the voltage at the rectifier output to its optimal value, despite the time-varying train suspension vibrations. By exploiting the measurement of the generator speed, the proposed technique is able to almost instantaneously reach the maximum power point, allowing a power extraction higher than the widely used perturb and observe algorithm. Moreover, the proposed technique is equipped with an adaptive control for ensuring the power maximization despite the tolerances and time-variability of the system parameters. Experimental results validate the theoretical analysis and confirm the superior performance of the proposed interface.
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