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The distribution of the magnetic field generated by an electromagnetic device can provide insights into their operational condition. This paper focuses on diagnosing electrolyzers through magneto-tomography, a method which involves mapping the magnetic field generated by electrical devices. Since current density and magnetic field are directly linked, this study can characterize the normal and abnormal operation of an electrolyzer. To achieve this, a two-dimensional (2-D) Biot–Savart model in polar coordinates is developed. To validate this model for electrolyzer diagnostics, an experimental setup was established to replicate the electrolyzer operation. The purely analytical model was successfully validated, with the average difference between the analytical results and experimental measurements established. The model validation is performed by comparing the experimental data to the theoretical results, and it is observed that the difference does not exceed 5%. [ABSTRACT FROM AUTHOR]

In this paper, a meticulous modeling approach is proposed not only for a fuel cell stack itself but also for all auxiliary components that collectively form the fuel cell system. This comprehensive modeling approach encompasses a wide range of components, including, but not limited to, the hydrogen recirculation pump and the air compressor. Each component is thoroughly analyzed and modeled based on the detailed specifications provided by suppliers. This involves considering factors such as efficiency, operating parameters, response times, and interactions with other system elements. By integrating these detailed models, a holistic understanding of the entire fuel cell system's performance can be attained. Such an approach enables engineers and designers to simulate various operating scenarios, predict system behavior under different conditions, and optimize the system design for maximum efficiency and reliability. Moreover, it allows for informed decision-making throughout the system's development, deployment, and operational phases, ultimately leading to more robust and effective energy systems. The model validation is performed by comparing experimental data to theoretical results, and the observed difference does not exceed 3%. [ABSTRACT FROM AUTHOR]