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Proton-exchange membrane fuel cells (PEMFCs) are a clean power-generation technology that produces no direct carbon dioxide emissions during operation. Their performance and durability depend strongly on effective water management. Monitoring internal conditions during operation is essential to prevent flooding, in which excess liquid water accumulates within the cell, and membrane dry-out, in which the electrolyte membrane loses moisture.

Electrochemical impedance spectroscopy (EIS) is a widely used diagnostic technique that characterizes the cell's electrochemical response by applying a small alternating-current signal over a range of frequencies. However, conventional EIS measurements typically involve sequential measurements across a broad frequency range and can take several tens of seconds or longer to complete. This limits their suitability for monitoring rapidly changing operating conditions.

In a study appearing in the International Journal of Hydrogen Energy, researchers at University of Tsukuba reduced both the frequency range and the number of measurement points required for diagnosis.

The method uses only six measurement frequencies, compared with 41 in conventional EIS. Comparisons with conventional EIS results showed that a carefully balanced selection of frequencies that capture changes in impedance improved diagnostic accuracy relative to conventional frequency-selection approaches.

The researchers also developed an integrated program combining impedance measurement, data analysis and operational control. Using resistance parameters derived from impedance data as indicators of the cell's internal condition, the program automatically adjusted operating conditions. This approach enabled the detection and mitigation of electrolyte membrane dry-out and insufficient air supply within the cell.

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