Acoustical modeling and analysis of proton-exchange membrane fuel cell stack anode exhaust gas from the perspective of ultrasound testing

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Abstract Proton-exchange membrane fuel cells are widely utilized in transportation and stationary power generation applications due to their high energy conversion efficiency, substantial power density, and zero emissions. To address the requirements for internal status monitoring and hydrogen purge management in the hydrogen supply subsystem of automotive fuel cell systems, this paper proposes an innovative online monitoring scheme for real-time measurement of the anode exhaust mixture concentration from the fuel cell stack, utilizing an ultrasonic flowmeter. This scheme offers high measurement accuracy, short sampling intervals, simple configuration, and low cost. An acoustic analysis model of the anode exhaust gas was developed to systematically evaluate the influence of environmental parameters such as temperature, pressure, and humidity on the ultrasonic flowmeter’s measurement. Additionally, an ultrasonic flowmeter prototype was constructed based on this acoustic model, and the accuracy of its flow rate and concentration measurements was validated using standard gases. The results indicate that, without a humidity sensor, the absolute error in hydrogen concentration can reach 7 vol%, while the absolute error in nitrogen concentration can exceed 11 vol%. Therefore, integrating additional sensors is essential for improving the accuracy of concentration calculations for the anode exhaust gas components. The relative error in flow measurement with the ultrasonic flowmeter prototype is consistently below 5%, and the absolute error in concentration measurements is less than 1%, reflecting the effectiveness and feasibility of the proposed method. Furthermore, this paper outlines a calculation method for converting sensor feedback into the mass flow rates of individual gas components in the mixture. This work offers a novel theoretical and practical framework for enhancing real-time internal status monitoring and hydrogen purge management in fuel cell systems, which is expected to significantly improve the reliability, stability, and fuel economy of automotive fuel cell systems in the future.