Statistical short-time analysis of electrochemical noise generated within a proton exchange membrane fuel cell

Abstract

Electrochemical noise analysis (ENA) technique has been performed for the diagnosis of proton exchange membrane fuel cell (PEMFC) under various operating conditions. The interest of electrochemical noise (EN) measurements relates with its non-invasive character and the possibility of online diagnosis of commercial fuel cells without interruption of the system. A new approach for the interpretation of electrochemical noise (EN) measurements has been proposed. This approach is based on internal intermittence of the recorded fluctuating signal (cell voltage). Namely, statistical descriptors in time domain (standard deviation, skewness, flatness), calculated for small time windows (short-time analysis), are rather unstable. This phenomenon can be called the internal intermittence of EN. Our experiments show that the level of internal intermittence is very sensitive to water management and increases drastically when a fuel cell meets either flooding or drying conditions. This conclusion has been confirmed using three statistical moments (standard deviation, skewness, and flatness), four different relative humidities, and three operation points (OCV, 2.5 A, 8 A). The level of internal intermittence can be detected easily by different ways and can be used for the characterization of possible faults of water management in practical applications as commercial fuel cell stacks. From a practical point of view, the measurement of the level of the internal intermittence is rather simple and avoids a time drift. In our knowledge, the internal intermittence of EN has not been used previously for studies of fuel cells. It will be interesting to apply this approach for other electrochemical systems and processes.