Online Diagnosis Method of Water Management Faults Based on Hybrid-Frequency Electrochemical Impedance Spectroscopy for PEMFC

To swiftly accomplish online fault diagnosis of water management for proton exchange membrane fuel cell (PEMFC), an online diagnosis method of water management faults based on hybrid-frequency electrochemical impedance spectroscopy is proposed. First, guided by the principle of time-frequency signal processing, the online diagnosis of water management faults is conducted via the full-frequency band electrochemical impedance spectroscopy and the characteristic information of the abscissa coordinates at the intersection of high and low frequencies in electrochemical impedance spectroscopy. Subsequently, an online diagnosis method of water management faults based on hybrid-frequency electrochemical impedance spectroscopy is proposed to enhance the diagnostic speed. To validate the effectiveness and feasibility of the proposed method, a test platform is established, and numerous tests and analyses are conducted on PEMFC under diverse operating conditions. Experimental results demonstrate that the proposed method can accurately and swiftly identify various faults of water management in PEMFC, achieving a diagnostic accuracy of 95.56%, with a diagnostic duration of approximately 4 s.

I. Introduction

As the scale of rail transit networks expands and passenger volumes escalate, the rail transit systems, which are powered by traditional electricity and internal combustion engines, are no longer sufficient to meet the global demand for energy efficiency and environmental protection [1]. The proton exchange membrane fuel cell (PEMFC) is a power device that directly converts chemical energy from hydrogen gas into electrical energy. Due to its advantages of high power density, high efficiency, low operating temperatures, and being pollution-free, PEMFC is widely utilized in various fields, such as aviation, stationary power plants, hybrid electric vehicles, and rail transportation vehicles, among others, promoting the green transformation of rail transit [2], [3], [4], [5]. Nevertheless, PEMFC is a nonlinear, multiphysical, and multiscale system. It is susceptible to performance deterioration resulting from failures, such as flooding and membrane drying, induced by factors, including internal water content, water ingress, temperature, and humidity [6], [7]. To ensure high-performance operation of PEMFC, it is imperative to conduct online fault diagnosis, acquire real-time internal status information, identify the root cause of the fault, and implement suitable protective measures. Currently, online fault diagnosis primarily relies on external parameters, such as output voltage, current, and operating temperature, while internal status information of PEMFC remains inaccessible [8]. Therefore, it is paramount to develop a rapid and precise online fault diagnosis method for PEMFC, enabling real-time monitoring of internal status information and prompt identification of fault types.