一种利用可逆PEM燃料电池的新型浮力控制装置

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9155
J. Yazji, Hamza Zaidi, Luke Thomas Torres, C. Leroy, A. Keow, Zheng Chen
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引用次数: 3

摘要

浮力控制装置是水下有效操纵ROV的关键。许多方法已经被用来解决这个问题,例如压缩空气镇流器,它可以吸收水并使用压缩空气排出水,以及使用高密度泡沫板,可以添加或移除以增加或减少浮力。本文提出了一种新的浮力控制方法,该方法利用可逆聚合物电解质膜(PEM)燃料电池的电解和反电解能力来调节小型车辆的体积和深度。利用这两个过程有助于通过反电解过程恢复系统消耗的一些能量,也有助于建立一个全封闭的系统,即不需要任何水或气体流向周围。解释了该装置的建模,并设计了一个比例导数(PD)控制器,以使用单个传感器测量在一定深度控制它。实验验证了控制器的性能。
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A Novel Buoyancy Control Device Using Reversible PEM Fuel Cells
Buoyancy control devices are essential to maneuver ROV effectively underwater. Many approaches have been used to tackle this problem such as compressed air ballast which can take in water and eject it using compressed air and the use of high-density foam plates that can be added or removed to increase or decrease the buoyancy. Presented in this paper is a novel approach for buoyancy control, which utilizes the electrolysis and reverse electrolysis capabilities of a reversible polymer electrolyte membrane (PEM) fuel cell to adjust the volume of a small vehicle, and change its depth. Making use of the two processes helps restore some of the energy consumed by the system through the process of reverse electrolysis and also for building a fully-closed system, that is, one that does not require any water or gas flow to the surrounding. Modeling of the device is explained and a proportional-derivative (PD) controller is designed to control it at a certain depth using a single sensor measurement. Experiments validate the controller performance.
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来源期刊
Mechatronic Systems and Control
Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.40
自引率
66.70%
发文量
27
期刊介绍: This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.
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