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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]

This brief aims at providing a proof of concept of a systematically designed linear parameter varying (LPV)/H∞-based energy management system (EMS) for coordinated multi-variable control of multi-source electrical systems. A three-source electrical system representing the power supply system on board of an electric vehicle has been chosen as a representative example of irregular and generally not a priori known load variation. The power supply system is composed of the fuel cell, battery, and supercapacitor. Each power source is coupled to a dc–dc converter, all converters being connected in parallel to a common dc-bus in order to feed the load represented by the vehicle’s electrical motor. The system is modeled as an LPV system—as its operating point depends on the load—and the control objectives are cast into the H∞ formalism as a disturbance-rejection problem. A dedicated hardware-in-the-loop system was built for the proof-of-concept purpose, with real-world battery and supercapacitor being used, while the fuel cell system is entirely emulated. A dSPACE MicroAutoBox II device embeds the designed EMS, due to its flexibility and ease of programming with MATLAB. A driving cycle from [Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux (IFSTTAR)] is chosen as a pertinent scenario of load variation due to its rich frequency content able to challenge all the three sources. Effectiveness of the EMS is assessed in relation to the imposed control objectives—dc-bus voltage regulation, dynamical separation of power sources’ current variations depending on the specialization range of each source, and imposing desired steady-state behavior for each of the three power sources—with very promising results. [ABSTRACT FROM AUTHOR]

This paper presents the modeling and control of an ultrahigh-speed centrifugal compressor for the air management of proton exchange membrane fuel-cell (PEMFC) systems. Centrifugal compressors have the advantages of compactness, high efficiency, and low noise, compared with other kinds of displacement compressors. Moreover, ultrahigh-speed technology can also reduce the size and weight of the compressor, which makes it more feasible for automotive applications. However, the adoption of a centrifugal compressor results in control being difficult because of coupling between mass flow and pressure. In this paper, a neural network model of the compressor is developed, and a decentralized sliding-mode controller based on twisting and super twisting algorithms is proposed and tested to control the compressor pressure and mass flow. The experimental results show good dynamic characteristics and faster response compared with conventional proportional–integral (PI) control. [ABSTRACT FROM PUBLISHER]

Power electronic converters are essential part of hybrid fuel cell automotive application systems. The converter needs to provide high-voltage ratio for a wide range of input voltage. In addition, the converter should have high efficiency for a wide range of duty cycle control range. A four-phase floating interleaved boost converter (FIBC) is analysed and a small-signal AC model using an averaged pulse-width modulation (PWM) switch technique is used for supporting the feedback controller and aiding a frequency response design. The small-signal AC model as well as the current controller are validated by simulation and evaluated by experimental results. The proposed converter has competitive device ratings, the total inductance volume and weight is decreased, current ripple is minimised and converter efficiency and reliability are improved. Proof of concept of the proposed topology is demonstrated through an experimental prototype. [ABSTRACT FROM AUTHOR]

Electric vehicle technology has been adopting fuel cells (FCs) for hybrid applications over the past few years. Therefore, the development of advanced power electronic systems for the integration of fuel cells with on-board energy management is fundamental for achieving high-performance systems. An FC for vehicular applications is usually a low-voltage current-source like device that produces electricity and heat directly from input hydrogen and oxygen. Most often, it is required that the FCs be stacked for high-voltage dc-link in order to supply the input power for the drivetrain and electric motor drive system. The FC has a nonlinear nature, and it must be controlled to operate in the high-efficiency operating range. Hybrid electric vehicles have physical constraints such as volume and weight under limited cost and expected lifetime. There is a need for high-voltage input/output ratio of dc-dc boost converters to be connected between the FC to the motor drive dc-link. In addition, it is necessary to have low input ripple at the dc-dc boost converter in order to maximize the FC lifetime, and the traditional dc-dc boost converter topologies have poor performance on these specifications. This paper proposes a new dc-dc converter family of topologies aimed at improving the application to electric vehicle power control. This family is defined as floating-interleaving boost converters (FIBCs). The paper will thoroughly show analysis and experimental verification of FIBC's, and they will be compared with conventional boost converter characteristics. The paper supports how performance figures related to the passive components, i.e., the inductor and capacitor, will have better volume and weight, extremely low input current ripple, and improved efficiency and transfer ratio. The analysis presented in this paper shows how to choose the most suitable topology in order to achieve the desired specifications. The selected topology is fully validated experimentally using advanced nonlinear sliding mode control, which has the additional feature of operating even in faulty conditions. [ABSTRACT FROM PUBLISHER]

This paper presents a multiphysical proton exchange membrane fuel cell (PEMFC) stack model. The stack model is divided into three submodels describing the different physical domains, namely, electrical, fluidic, and thermal. The stacking method has been used to model the fuel cell stack from a single-cell model. The proposed model has been validated against a 1.2-kW commercial PEMFC stack with excellent agreement between simulation and experimentation. Based on the simulation results, a novel model reduction method is proposed. The reduced model is suitable for real-time simulation purpose. Moreover, a real-time-model-based fuel cell emulator is introduced. The emulator has three real-time computation cores with different rates. The three computation cores are interconnected with a digital communication bus. A dc/dc buck converter is designed in order to receive the model-predicted stack power conditions and emulate the real fuel cell stack power output. The experimental test results show that such an emulator is suitable for fuel cell system hardware-in-the-loop applications. [ABSTRACT FROM AUTHOR]

This paper describes a new methodology based on the statistical description of driving cycles to size the energy source of a hybrid vehicle. This methodology is applied to a fuel-cell-based collection truck for very specific driving patterns. Based on experimental data, random driving cycles are then generated, allowing the distribution of the average powers and energies to be computed. The analysis proves that a 20-kW fuel cell stack is sufficient for a 13 000-kg truck. The results show that the fuel cell system could be downsized, compared with classical solutions, where much larger fuel cells are required. [ABSTRACT FROM PUBLISHER]

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]

Abstract: This paper presents a control solution based on dynamic disturbance decoupling control (DDC) for a centrifugal compression system, which is used to supply the compressed air to the fuel cell, thereby reacting with the hydrogen to produce electricity. As a result of its ultra-high speed, this compressor has a great advantage of ultra-compactness, which makes it more suitable for transportation applications. However, unlike positive displacement compressors, the centrifugal compressor has strong coupling between mass flow and pressure, which gives rise to the difficulty of control and also limits its operating region. In this paper, a unique dynamic DDC strategy, based on the active disturbance rejection control (ADRC) framework, is developed to control the mass flow and pressure simultaneously. The experimental results show that, compared with a traditional PI controller this controller performs better in both the transient and steady states. This control system has been validated on a 10 kW fuel cell model under load variations. [Copyright &y& Elsevier]

Abstract: The use of hydrocarbon fed fuel cell systems including a fuel processor can be an entry market for this emerging technology avoiding the problem of hydrogen infrastructure. This article presents a 1 kW low temperature PEM fuel cell system with fuel processor, the system is fueled by a mixture of methanol and water that is converted into hydrogen rich gas using a steam reformer. A complete system model including a fluidic fuel processor model containing evaporation, steam reformer, hydrogen filter, combustion, as well as a multi-domain fuel cell model is introduced. Experiments are performed with an IDATECH FCS1200™ fuel cell system. The results of modeling and experimentation show good results, namely with regard to fuel cell current and voltage as well as hydrogen production and pressure. The system is auto sufficient and shows an efficiency of 25.12%. The presented work is a step towards a complete system model, needed to develop a well adapted system control assuring optimized system efficiency. [Copyright &y& Elsevier]