Assessing the Possibility of Implementing Distributed Diagnostic Systems for Hydrogen Fuel Cells Using Local and Global Telecommunication Networks

Abstract

The development of effective methods and means for diagnosing hydrogen fuel cells during their operation is an urgent task, since their implementation will improve the energy characteristics and stability of operation by detecting incorrect operating modes and malfunctions at the early stages of development. This problem can be solved by using various approaches based on the analysis of impedance, relaxation or fluctuation-noise characteristics. All of these methods require the implementation of rather complex computational procedures and the accumulation of fairly large amount of statistical data, which makes it difficult to implement diagnostic devices on inexpensive embedded microprocessor tools. To overcome this drawback, this work proposes the use of distributed diagnostic systems with high-performance server devices connected to local modules via global or local telecommunication networks. Such an implementation will significantly simplify the requirements for local diagnostic modules and reduce their cost, but this raises the question of the efficiency of making diagnostic decisions by such systems.The work carried out, is a study of delays in making diagnostic and control decisions when using remote server devices for signal processing. It has been shown that the use of such systems makes it possible to achieve delays of less than one second even when using intercontinental communication lines. It should be noted that in applications critical to time delays, the distance between the client and server systems should be reduced. The advantages of the proposed implementation of a diagnostic system for electrochemical energy sources are the possibility of simplifying local measurement systems installed on individual sources, the possibility of accelerating signal processing through the use of more productive computing tools and the accumulation of statistical data.