Micro-current excitation for efficient diagnosis of membrane electrode assemblies in fuel cell stacks: Error analysis and method optimization

• Identify ohmic resistance and update excitation model for precision upgrading. • Conduct systematic error analysis concerning decoupling algorithm and stack state. • Originally reveal condition sensitivity for identifying MEA inconsistency. • Validate adaptability to single excitation for a great advance in test efficiency. • Contribute to validity and reliability of MCE in stack-level MEA diagnosis. The inconsistency of membrane electrode assemblies (MEAs) greatly restricts the development of high-performance and long-lifetime fuel cell stacks. Micro-current excitation (MCE) method has promising prospects in consistency evaluation due to its capacity in MEA component diagnosis at the stack level. In this study, the ohmic resistance is identified with the initial voltage jump characteristic upon MCE and then introduced into the excitation-response model for precision upgrading. A detailed error analysis is then conducted concerning the decoupling algorithm, the simplified model, and the stack state, demonstrating the significance of error revision for degraded stacks. Based on the updated method, the condition sensitivity of inconsistency identification is further investigated, involving the operating temperature, the gas humidity, and the gas flow rate. It is essential to ensure the same hydration state of fuel cells for simultaneous component inconsistency diagnosis. Heating and minor gas humidification are sufficient and necessary. The MCE is proven to be very sensitive to the N 2 flow rate in the cathode. An extremely low N 2 flow rate enables a relatively uniform gas distribution and hydrogen adsorption saturation, and is thus recommended. Finally, the updated MCE is validated to adapt to a single excitation for inconsistency diagnosis, which means great progress in test efficiency.