Quantitative assessment of voltage nonuniformity in 20 cell PEMFC stack for degradation mapping and health monitoring

Proton Exchange Membrane Fuel Cells (PEMFCs) are widely regarded as a leading technology for sustainable energy conversion due to their high efficiency, compact structure, and zero-emission characteristics. However, the long-term performance and reliability of PEMFC stacks are often limited by internal inconsistencies, especially voltage nonuniformity among individual cells. This spatial variation in cell voltage reflects underlying degradation phenomena such as membrane dehydration, localized flooding, and catalyst deterioration, which can accelerate aging and lead to early failure. Although voltage uniformity is critical for system stability, it has not been sufficiently quantified under realistic operating conditions, restricting its application in predictive diagnostics. In this study, we propose a quantitative framework to assess voltage nonuniformity in a 350 cm2, 20-cell PEMFC stack under varying current loads. We define four statistical measures: the coefficient of variation (CV), range ratio, skewness, and kurtosis. These indicators are used to describe the scale and shape of voltage dispersion and are further normalized and combined into a single Voltage Nonuniformity Index (VNI) to enable integrated evaluation. The results show that nonuniformity increases with current density, especially beyond the mid-load range where voltage distributions become more asymmetric and peaked. These patterns highlight the responsiveness of the proposed indicators to electrochemical imbalance and temperature gradients under dynamic operation. By combining several statistical features into a single evaluation scheme, the framework provides a multidimensional view of intra-stack behavior. This enhances the ability to detect early-stage degradation and supports real-time monitoring and control. This study contributes to a better understanding of voltage distribution patterns in PEMFC systems and offers practical guidance for improving stack design, operating strategies, and health management.