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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]

An original non-invasive methodology of the fuel cell diagnosis is proposed to identify different positions of the faults in Proton Exchange Membrane Fuel Cell (PEMFC) stacks from external magnetic field measurements. The approach is based on computing the external magnetic field difference between normal and faulty PEMFC operating conditions. To evaluate the external magnetic field distribution, in this paper, we propose an improved design of the magnetic field analyzer. This analyzer amplifies the magnetic field around the cell to perform an accurate detection of the fault position. Moreover, the main contribution of this work is represented by conceiving and implementing a 3D multi-physical current distribution emulator of a proton exchange membrane fuel cell. The new concept of a proton exchange membrane fuel cell emulator has been specially designed to emulate the magnetic field of a real fuel cell stack. This emulator concept is also beneficial for a new model of the fuel cell, which implies a multi-physical coupling between electrochemical electric conduction and the generated magnetic field. Finally, finally, the numerical model and the emulator have been involved in the realization of numerical simulations and experimental analysis to prove the ability of the system to detect and localize 3D faults. [ABSTRACT FROM AUTHOR]

Despite its high energy density and zero-carbon emissions, the path to large commercialization for Proton Exchange Membrane Fuel Cell (PEMFC) systems faces challenges related to cost reduction, efficiency enhancement, and durability improvement. One key strategy to address these hurdles is the development of reliable control algorithms that ensure operation at the Maximum Efficiency Point (MEP) of PEMFC systems. This optimization is essential for achieving high efficiency, a crucial factor for PEMFC technology commercial viability. This work explores the experimental design, implementation, and evaluation of Maximum Efficiency Point Tracking (MEPT) control algorithms for a PEMFC system. The investigated methods span across five distinct categories: conventional, data-driven, metaheuristics, online model identification, and filter-based approaches. To assess these methods, a real-time small-scale PEMFC system test bench was built. The setup consists of 200 W open-cathode PEMFC, industrial step-up DC–DC converter, programmable load and a cost-effective measurement and monitoring unit. Merits and demerits of each method are then discussed based on different performance metrics such as tracking speed, hydrogen consumption and power stress. Comparative analysis of the results reveals that, while all the algorithms achieved a maximum electrical efficiency of about 48%, data-driven methods exhibited a superior trade-off between performance metrics. This ultimately leads to improved PEMFC durability. • Enhancing PEMFC system efficiency through the implementation of MEPT control. • A detailed design of a small-scale experimental demonstration PEMFC test bench. • Comparative analysis of MEPT techniques based on multi-index performance metrics. • Data-driven methods provide the best trade-off for improving PEMFC durability. [ABSTRACT FROM AUTHOR]

Electric trains equipped with efficient electric motors and powered by high-capacity hydrogen fuel cells are a choice of the global transportation industry to accelerate the global transition to a low-carbon transportation system. The operation of distinct vehicle types in varying geographical regions is characterized by unique features. Concurrently, the continually fluctuating demand for electricity necessitates the utilization of fuel cells in conjunction with energy storage devices. Thus, this study centers on examining the role of the PEMFC-supercapacitor direct hybridization system within the authentic driving profile of the subway in the Bangkok metropolitan region. The supercapacitor within the hybridization system serves as an energy management device, enhancing the durability of fuel cells when subjected to diverse load demands associated with train propulsion. In order to validate this hypothesis, an MRT (Mass Rapid Transit) protocol was formulated to emulate and serve as the load demand for the investigation, and then the PEMFC-supercapacitor direct hybridization system was operated using the created profile. Subsequently, the hybridization system undergoes electrochemical characterizations and fuel cell performance tests for diagnostic purposes. Empirical findings validated that the supercapacitor operates as a filter, generating a stable voltage response to varying load requirements, and possesses the capability to assimilate energy originating from regenerative braking. The integration of supercapacitors in stabilizing the operational parameters of proton exchange membrane fuel cells (PEMFCs) has markedly prolonged their operational lifespan. This assertion is substantiated by voltage signal analysis, which demonstrated a negligible increase in surface resistance of merely 0.23%, as depicted by Nyquist plots. Furthermore, cyclic voltammetry revealed that the system attained a peak electrochemical surface area (ECSA) of 0.0089 (106 cm2/mg of Pt). The information presented in this article constitutes data that has been minimally explored in existing research. Specifically, the study concentrates on the practical driving pattern of electric trains. Consequently, experimental results were deemed advantageous for the advancement of heavy-duty electric vehicles. [Display omitted] • Exploring the relationship between the utilization of an energy storage device as a SC and energy generation as a PEMFC. • Establishing a connection between the authentic current profile of an MRT metro system and an accelerated stress test. • Examining the electrochemical reactions within fuel cells, drawing upon operational data from the transportation sector. [ABSTRACT FROM AUTHOR]

This article addresses a new approach to non-invasive diagnostics of proton exchange membrane fuel cells. More specifically, it deals with the detection of several faults generated by inappropriate operating conditions using an original non-invasive methodology based on the measurement of the external magnetic field around the fuel cell stack, thanks to a specially designed ferromagnetic circuit analyzer. A large experimental campaign has been released on a fuel cell stack associated with this magnetic circuit analyzer for normal and faulty fuel cell operating conditions at different current values. These experiments provide a vector of the measured magnetic field at different positions around the fuel cell stack. Each experiment was labeled based on accurate electric and fluidic measurements realized on a laboratory fuel cell test bench. These magnetic field measurements were used as original variables for a data-driven diagnostics approach involving two steps: feature extraction and classification. Finally, the high accuracy given by this diagnostic methodology proves the ability of the new magnetic field analyzer to provide a significant (highly sensitive) information to detect local faults inside fuel cell during operation, and therefore to allow accurate discrimination between different fuel cell normal and faulty operating conditions. • Diagnose stack behavior at the end of the production line via a new magnetic measurement concept. • Validate the ability of the magnetic analyzer to detect different FC stack operating conditions. • Correlation between FC stack external magnetic field and the internal faults is clarified. • A data-driven approach is applied to detect different FC stack operating conditions. • The obtained results describe a highly feasible online application using a real-time dataset. [ABSTRACT FROM AUTHOR]

Resilience is becoming increasingly important in power systems, microgrids (MG) and buildings. It evaluates their performance against disruptive events. The approaches mainly correspond to high-impact, low-probability events such as natural disasters and intentional attacks affecting the electrical systems infrastructure. However, resilience can encompass medium and low-impact events such as minor civil structural accidents, light faults and supply disturbances. Some resilience assessment advances are in buildings at the low-voltage (LV) level. They include vulnerability to natural disasters, reliability of supply, and service quality. These works usually use approaches independent of each other, leaving a gap between their relationship and interpretation. Therefore, there is a need to consolidate a resilience assessment strategy to guide the analysis of vulnerabilities and strengths in the same direction. This paper proposes a comprehensive approach to evaluate electrical resilience for buildings. It compiles quantitative strategies for studying electrical resilience, focusing on LV systems. It proposes a methodology for integrating the electrical system infrastructure's vulnerability, the supply's continuity and the voltage service's quality. Implementing this approach in a university building equipped with smart metering demonstrates the effectiveness of the proposed methodology for assessing electrical resilience. The results show a comprehensive resilience analysis and the possibility of extending the methodology to MG and LV distribution networks. • A categorisation of building electrical system disturbances by impact level and frequency. • A methodology to assess electrical resilience for each category of disturbance. • A Comprehensive assessment of electrical resilience, covering structural robustness, service continuity, and supply quality. • A case study application integrating critical loads, a backup system, and smart metering. [ABSTRACT FROM AUTHOR]