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This paper investigates the control of the air supply system for marine proton exchange membrane fuel cells. A mathematical model of the air supply system is established, and a sliding mode diagonal decoupling controller based on a state observer is proposed. The control effectiveness is validated through experiments and simulations. A decoupling control strategy for the air supply system of marine fuel cells is presented. First, the load input current of the fuel cell system is selected according to the load characteristics of the target vessel, ensuring that the load current meets the power level of the fuel cell system model. Second, the impact of the cathode pressure on the fuel cell system is analyzed. An observer-based measurement method is proposed to address the measurement issue of cathode pressure. On this basis, a decoupling control strategy combining a diagonal decoupling matrix and sliding mode variable structure control theory is proposed. Finally, the effectiveness of the decoupling controller is validated through Matlab/Simulink. The results show the proposed decoupling controller exhibits superior performance to existing controllers with environmental disturbances, continuous time-varying loads, and step loads. The maximum relative error is 2.95%, the average relative error is 0.022%, and the longest adjustment time is 0.5 s. These results indicate that the control performance of the proposed decoupling controller is superior to that of diagonal PI controllers and sliding mode controllers, thereby validating the superiority of the sliding mode decoupling controller. This article provides a useful method for the development and application of control technology for the air supply system of marine fuel cells. • Semi-empirical and semi-mechanistic modelling of PEMFC air supply system. • Optimizing the model through polynomial fitting, parameter identification. • Using ESO to monitor internal changes and external disturbances. • Air supply system decoupled by decoupling controller. • Using SMC for error compensation of decoupling matrices. [ABSTRACT FROM AUTHOR]

Efficient real-time power optimization of direct methanol fuel cell (DMFC) system is crucial for enhancing its performance and reliability. The power of DMFC system is mainly affected by stack temperature and circulating methanol concentration. However, the methanol concentration cannot be directly measured using reliable sensors, which poses a challenge for the real-time power optimization. To address this issue, this paper investigates the operating mechanism of DMFC system and establishes a system power model. Based on the established model, reinforcement learning using Q-learning algorithm is proposed to control methanol supply to optimize DMFC system power under varying operating conditions. This algorithm is simple, easy to implement, and does not rely on methanol concentration measurements. To validate the effectiveness of the proposed algorithm, simulation comparisons between the proposed method and the traditional perturbation and observation (P&O) algorithm are implemented under different operating conditions. The results show that proposed power optimization based on Q-learning algorithm improves net power by 1% and eliminates the fluctuation of methanol supply caused by P&O. For practical implementation considerations and real-time requirements of the algorithm, hardware-in-the-loop (HIL) experiments are conducted. The experiment results demonstrate that the proposed methods optimize net power under different operating conditions. Additionally, in terms of model accuracy, the experimental results are well matched with the simulation. Moreover, under varying load condition, compared with P&O, proposed power optimization based on Q-learning algorithm reduces root mean square error (RMSE) from 7.271% to 2.996% and mean absolute error (MAE) from 5.036% to 0.331%. • Proposed power optimization method considers the overall power of the DMFC system. • Methanol supply control can be achieved without requiring concentration information. • Application of Q-learning algorithm is simple, real-time, and greatly reduce the complexity. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell (PEMFC) has become a hotspot due to its high efficiency, compact structure, and good dynamic operation efficiency. However, problems such as poor reliability and short lifespan create bottlenecks in its large‐scale applications. There has been a large amount of research on fault diagnosis and health management techniques dedicated to addressing the lifespan issues of PEMFC systems. This article provides an in‐depth analysis on the fault mechanism of PEMFC and systematically sorts out the types, causes, and impacts of faults. On this basis, the research progress of PEMFC fault diagnosis technology is summarized, and the measurement characterization methods for fuel cell status monitoring and fault detection are summarized. The literatures of model‐based and data‐driven fault identification methods are summarized and compared. The relevant mitigation measures for PEMFC faults are discussed. Finally, based on the challenges in the current research of fault diagnosis, people mainly conduct research on fault model, online diagnostic technology, and improving diagnostic mechanisms. Overall, this article can provide useful summary and guidance for future research. [ABSTRACT FROM AUTHOR]

The fuel cell market, which utilizes hydrogen as a fuel for zero-carbon power generation to address global warming, continues to grow steadily. In the building sector, where small-scale fuel cells of 10 kW or less have been predominant, there is increasing interest in scaling up fuel cells to increase deployment and reduce system costs. The multi-stack fuel cell system (MFCS), which consists of connecting multiple modules, is one method of configuring large-scale fuel cell systems, offering advantages in system efficiency, durability, and cost. The objective of this paper is to compare and analyze the behavior of the MFCS according to different operation strategies. In particular, it compares the Equivalent operation method, which behaves similarly to the single-stack fuel cell system (SFCS), with others (Daisy-Chain, Electrical Optimization). Unlike previous studies that only focused on the electrical efficiency of MFCS, this study analyzed thermal energy, which is indispensable in building applications, to maximize the effects of MFCS. Simulation of operation strategies based on the electricity and heat demand of a specific residence showed that MFCS outperformed the SFCS in terms of electrical and heat efficiency, hydrogen consumption, degradation, and operating costs. • The Multi-Stack Fuel Cell System (MFCS) considers both electrical and heat efficiency. • Application of MFCS in residential environments with demand for both power and heat. • MFCS offers advantages in terms of efficiency, durability, and operating costs. [ABSTRACT FROM AUTHOR]

Hydrogen fuel cells are one of the main solutions for power generation, combining the decarbonization urgency with a high energy conversion efficiency. In this context, the efficiency of a fuel cell system (FCS) is a key factor to maximize, as conversion efficiency improvements are beneficial to both reduce the hydrogen consumption and increase the power density. In this context, the design of the air supply system allows to operate the cathode at various pressures and flow rates, potentially increasing the cell efficiency although critically raising the power demand on the same system. Hence, its optimization is far from trivial and requires a solid model-based analysis. In this study an analytical methodology is presented to quantify the efficiency variation in FCS operating at various pressure and/or flow rates using supercharging devices. The accompanying MATLAB script is distributed under the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines upon request, and it allows an a priori evaluation of the conditions for maximum FCS efficiency. The methodology is of general use, and it is demonstrated on a wide range of air flow rates (λ c = 1.2 − 10.0) and pressure (p c = 1.0 − 5.0 b a r) using data from two literature cells, and with high and low efficiency turbomachinery. Results indicate that the maximum FCS efficiency is generally obtained for high stoichiometric factors (λ c = 5.0 − 6.8) and low-to-moderate cell backpressure (p c = 1.0 − 1.3 b a r) when no pressure losses are included in the air admission line. When these are accounted for, the same methodology indicates a lower stoichiometric factor (λ c = 2.2 − 3.0) and a slightly higher cell backpressure (p c = 1.2 − 2.0 b a r). Despite numbers vary with specific systems, the methodology is both analytically based and highly general, hence scalable to any FCS. The presented model relevantly offers a model-based guidance to design the air supply line for maximum system efficiency, thus reinforcing the engineering of fuel cell systems. [Display omitted] • Analytical methodology for supercharged fuel cell system maximization. • Pressure and flow rate coupling between fuel cell and supercharger. • Scalable methodology demonstrated on two JRC cells and two supercharger models. • Without pressure losses, λ c = 5.0 − 6.8 and p c = 1.0 − 1.3 b a r maximize the efficiency. • With losses in the air line, λ c = 2.2 − 3.0 and p c = 1.2 − 2.0 b a r maximize the efficiency. [ABSTRACT FROM AUTHOR]

The measurement of hydrogen concentration in fuel cell systems is an important prerequisite for the development of a control strategy to enhance system performance, reduce purge losses and minimize fuel cell aging effects. In this perspective paper, the working principles of hydrogen sensors are analyzed and their requirements for hydrogen control in fuel cell systems are critically discussed. The wide measurement range, absence of oxygen, high humidity and limited space turn out to be most limiting. A perspective on the development of hydrogen sensors based on palladium as a gas-sensitive metal and based on the organic magnetic field effect in organic light-emitting devices is presented. The design of a test chamber, where the sensor response can easily be analyzed under fuel cell-like conditions is proposed. This allows the generation of practical knowledge for further sensor development. The presented sensors could be integrated into the end plate to measure the hydrogen concentration at the anode in- and outlet. Further miniaturization is necessary to integrate them into the flow field of the fuel cell to avoid fuel starvation in each single cell. Compressed sensing methods are used for more efficient data analysis. By using a dynamical sensor model, control algorithms are applied with high frequency to control the hydrogen concentration, the purge process, and the recirculation pump. [ABSTRACT FROM AUTHOR]

Developing anion exchange membranes (AEMs) is an effective way to reduce the cost of water electrolyser systems and fuel cell systems because of the no requirement of platinum-group-metal (PGM) catalysts. However, low conductivity and poor stability are the bottlenecks that constrain its development. In this work, we propose a series of performance enhanced poly (terphenyl-co-fluorene quinuclidinium) (TPFQ) AEMs. The hydroxide conductivity of TPFQ-10 reached 178.5 mS cm−1 at 80 °C. The rigid fluorene group gives the membrane better dimensional stability (swelling ratio: 7.7% in pure water and 1.2% in 10 M NaOH at 80 °C for TPFQ-10). In particular, the membranes exhibit extremely high alkaline stability, with almost no conductivity loss over more than 2000 h in a 10 M NaOH solution. The AEM water electrolysers (AEMWEs) with nickel-alloy foam electrodes shows an excellent current density of 2.32 A cm−2 at 2.0 V. The AEMWEs can work steadily at a current density of 0.5 A cm−2 in 5 M NaOH at 80 °C for more than 500 h, with a low voltage rising rate of 56 μV h−1. • Synthesized a series of performance enhanced poly(terphenyl-co-fluorene quinuclidinium) (TPFQ) AEMs. • The AEMs have a high OH− conductivity (178.5 mS cm−1 at 80 °C), high mechanical properties (60.3 MPa TS) and excellent dimensional stability(swelling ratio: 7.7% in pure water and 1.2% in 10 M NaOH at 80 °C). • The AEMs exhibit extremely high alkaline stability, with almost no conductivity loss over more than 2000 h in a 10 M NaOH solution. • The AEMWE with nickel-alloy foam electrodes shows excellent current density (2.32 A cm−2 at 2.0 V) and high durability. [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]

Fuel cell systems often utilize a hydrogen recirculation system to redirect and transport surplus hydrogen back to the anode, which enhances fuel consumption and boosts the efficiency of the fuel cell. Hydrogen recirculation pumps and ejectors are the most investigated systems. Ejectors are gaining recognition as an essential device in fuel cell systems. However, their application in hydrogen recirculation systems is often limited by a narrow operational range. Therefore, it is advantageous to compile the present condition of the study on various ejector shapes as well as configurations that can accommodate a broader operational range, along with the numerical simulations employed in these studies. This paper begins by examining the structure and operation of ejectors. It then compares and analyzes the latest advancements in research on ejector-based hydrogen recirculation systems with extended operating ranges and reviews the details of numerical simulations of ejectors, which are crucial for the development of innovative and efficient ejectors. This study provides key insights and recommendations for integrating hydrogen ejectors into the hydrogen cycle system of fuel cell engines. [ABSTRACT FROM AUTHOR]

To investigate the functionality and performance of a prototype microjet engine, we constructed a versatile test stand tailored to the specifications of a 400 N prototype. This test stand facilitated a comprehensive study by enabling real-time recording of 45 essential parameters for analysis, encompassing temperatures, pressures, speed, fuel flow, thrust, vibration, and various other monitored metrics. All parameters and control elements were seamlessly integrated via a data acquisition and control system, utilizing a compactDAQ (Data Acquisition) system from National Instruments and a custom Virtual Instrument programmed with graphical language. The test stand offers both manual and automated operation modes, with the flexibility for hybrid operation. For instance, following the idle regime, manual control using a potentiometer can seamlessly transition from automated control via a proportional control (P control) mechanism. Before the experimental campaign, rigorous verification and validation tests were conducted to ensure the reliability and accuracy of the setup. The experimental campaign comprised a series of manual tests focusing on the fuel system and automated tests covering starting, idle, working, and stopping regimes. This structured approach allowed for a comprehensive evaluation across different operational scenarios, providing insights into the engine's behavior and performance under varying conditions. [ABSTRACT FROM AUTHOR]

To enhance the removal of COD (Chemical Oxygen Demand) by microalgae, this study constructed a novel microalgae–microalgae microbial fuel cell system (AA-MFC). It investigated the coupling relationship between the COD treatment efficiency at the anode and the production of high-value microalgal products at the cathode, as well as explored the effects of different initial inoculum densities and light–dark cycles. The experiment first measured the operational performance of the newly constructed AA-MFC in open-circuit and closed-circuit modes, demonstrating that this novel AA-MFC could start up rapidly within 32 h and operate stably. The results showed that the AA-MFC enhanced the removal of COD and the growth of microalgae biomass at the anode while maintaining stable power generation. When the initial inoculation density of the anode was 1.2 × 108 cell/cm2 and the light–dark cycle time was 18:6 h, the AA-MFC had the most obvious promoting effect on the COD removal of the anode. Compared with normal culture conditions, the COD removal rate increased by 26.0% to 96.1%. These results indicate that the AA-MFC can not only effectively remove pollutants, but also promote the accumulation of high-value microalgae biomass. [ABSTRACT FROM AUTHOR]

In the fuel system of an aircraft engine, aero-fuel centrifugal pumps are widely utilized as boost pumps. In this research, we propose the integration of an inlet injector with an aero-fuel centrifugal pump to optimize its flow characteristics and enhance performance. The key geometric parameters of the impeller, volute, and injector are meticulously designed. The effectiveness of our approach is validated through a combination of experimental and numerical analysis, which involves comparing simulation results with experimental data. The findings demonstrate that the presence of the injector significantly impacts the flow characteristics and hydraulic performance of the pump. Specifically, it effectively reduces flow losses in the specific channels of the impeller and volute. Furthermore, the injector enhances the regulation of the inlet flow fields by adjusting the inlet pressure and controlling the suction flow direction. Consequently, the pump's efficiency is enhanced when equipped with the injector compared to its performance without it. Therefore, incorporating an injector in an aero-fuel centrifugal pump has a positive effect on regulating flow characteristics and improving hydraulic efficiency. [ABSTRACT FROM AUTHOR]

As an economic evaluation indicator for fuel cell vehicles (FCVs), real-time hydrogen consumption's accuracy and immediateness are important. Real-time hydrogen consumption obtained through the fuel cell system (FC Power method) has strong immediateness but poor accuracy, while through the hydrogen mass (Mass method) has good accuracy but poor immediateness. Given the difficulty in obtaining sufficient training data on actual vehicles, this paper establishes a hydrogen storage system model whose input and output can be used to obtain data. Then, a new estimation method based on the prediction of the mass's difference (PMD method) has been constructed based on the Neural basis expansion analysis with exogenous variables (NBEATSx) algorithm. After the NBEATSx algorithm is trained, the prediction accuracy of the PMD method is verified under urban and high-speed conditions. The result shows that the new method proposed in this article improves Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) by nearly 45% compared to the FC Power method, and the hydrogen consumption's sampling point is advanced compared to the Mass method. The trained model can be input into Hydrogen Management System (HMS) which is installed on the hydrogen storage system and output data in real-time. [ABSTRACT FROM AUTHOR]

Hydrogen is crucial for achieving SDGs by driving energy transition and combating climate change. Proton exchange membrane fuel cell technology, leveraging hydrogen, faces challenges in meeting high‐power demands. The multistack fuel cell system (MFCS) tackles this by integrating multiple substacks, yet its air supply needs meticulous control. Proportional integral derivative (PID) decoupling from single‐stack falls short of MFCS. This article proposes nonlinear model predictive control (NMPC) for optimized air flow and pressure decoupling. Modeling MFCS's air system and designing a predictive model, it is aimed to ensuring precise control of air flow and pressure in each substack. The decoupling experiments show that NMPC outperforms PID, accurately managing air flow and pressure and reducing load fluctuations. For air mass flow, NMPC cuts mean‐absolute error (MAE) by 64.56% and root‐mean‐square error (RMSE) by 81.36%. For pressure, MAE drops 81.23% and RMSE 83.59%. Comprehensive step load tests confirm NMPC's precise, dynamic regulation too, compared to PID, NMPC lowers average MAE for air mass by 20.67%, pressure by 32.22%. RMSE improvements of 31.08% and 33.23% highlight NMPC's strength. NMPC's quick response mitigates coupling issues, enhancing vehicle load adaptability. [ABSTRACT FROM AUTHOR]

The hydrogen circulation pump (HCP), a device for recovering unconsumed hydrogen gas in fuel cell systems to improve efficiency, is an important equipment in fuel cell systems. Efficient calculation of the output flow rate of the HCP is crucial for accelerating the product development process, but there is a lack of an effective calculation formula for the working clearance leakage. In this paper, a series of HCP models with different working clearances are established and calculated using an overlapping grid simulation method, verifying that the traditional Roots blower leakage flow formula is feasible for HCP, although the maximum calculation error reaches 10.71%. Further study the pressure distribution law inside the HCP chamber, and revise the traditional calculation formula accordingly, so that the average calculation error of the series models is reduced from 5.75% to 3.82%, and the maximum error is also reduced to 7.73%. Compared with the prototype test data, though the flow values obtained from the two calculation formulas are slightly higher, the calculation error of the correction formula is relatively smaller. The research results indicate that the correction formula can more accurately predict the flow rate of HCP and has important application value. [ABSTRACT FROM AUTHOR]

In the conclusion to her book The Birth of Energy: Fossil Fuels, Thermodynamics, and the Politics of Work, political scientist Cara Daggett considers "A Post-Work Energy Politics" in which she examines the historical coupling of energy and work—meaning human, waged work—in an invitation to disassociate their values and futures. The exponential power of fossil fuels animated the pipedream that powerful, inorganic slaves could substitute unfree human labor, ideas that have driven European imperialism. Fossil fuel systems did not lead, however, to a world beyond work. Rather, today's "patriarchal slave states" continue to manage the project of putting the world to work through the maximization of productivity, and the subordination of racialized, immigrant, and gendered bodies—who would work for lower, or for no, wages. "The project of work," Daggett argues, "is in tension with the project of life." 1 And the rise of "work–life balance" is a mere tactic of governance in which the enemy is fatigue, exhaustion, and burn-out. She suggests, in turn, an alliance between post-carbon and feminist post-work politics and asks: what might it mean for energy politics to refer to the politics of ensuring public vitality? In order to advance a feminist revaluation of work, Daggett draws on Kathi Weeks's The Problem with Work to outline a project that makes two utopian demands. One demand articulates a paradoxical relationship between the pragmatism of (present) demands and the speculative seeds of possibility; a second demand outlines a utopian form for such politics: partial, fragmented kin to the genre of the manifesto. Daggett concludes with an invitation that "a radical planet politics, if it seeks to contest ecomodernist claims, needs its own politics of pleasure." 2 In an echo to Daggett's invitation, the authors of this Educators' Roundtable were invited to contribute a short text that picks up on the possibilities of a post-carbon, post-work politics. [ABSTRACT FROM AUTHOR]

The air–fuel ratio is a crucial parameter in internal combustion engines that affects optimal engine performance, emissions, fuel efficiency, engine durability, power, and efficiency. Positive pressure ventilators (PPVs) create specific operating conditions for drive units, characterized by a reduced ambient pressure compared to standard atmospheric pressure, which is used to control carburetor-based fuel supply systems. The impact of these conditions was investigated for four commonly used PPVs (with internal combustion engines) in fire services across the European Union (EU), using a lambda (λ), carbon dioxide (CO2), carbon monoxide (CO), and hydrogen carbon (HC) analyser for exhaust gases. All four ventilators were found to operate with lean and very lean mixtures, with their lambda coefficients ranging from 1.6 to 2.2. The conducted tests of the CO2, CO, and HC concentrations in the exhaust gases of all four fans show dependencies consistent with theoretical analyses of the impact of the fuel–air mixture on emissions. It can be observed that as the amount of burned air decreases, the values of CO and HC decrease, while the concentration of CO2 increases with the increase in engine load. Such an operation can accelerate engine wear, increase the emission of harmful exhaust gases, and reduce the effective performance of the device. This condition is attributed to an inadequate design process, where drive units are typically designed to operate within atmospheric pressure conditions, as is common for these engines. However, when operating with a PPV, the fan's rotor induces significant air movement, leading to a reduction in ambient pressure on the intake side where the engine is located, thereby disrupting its proper operation. [ABSTRACT FROM AUTHOR]

Using modern high-performance microcontrollers with wireless interfaces, built-in ADCs and low overall consumption, we develop a portable, real-time parametric diagnostic system for marine engines. The system is based on the use of modern Android/iOS gadgets that receive information from sensors via Bluetooth and then carry out the necessary calculations and display charts and data in real time. The system developed here uses a combination of a gas pressure sensor in the working cylinder and a vibroacoustic sensor, which expands the diagnostic capabilities of marine diesel engines under operating conditions. This solution allows for diagnosis of the fuel injection system, the valve train mechanism, and several other engine systems. In order to develop a portable diagnostic system for marine diesel engines, it is first necessary to solve the problem of analytically determining top dead centre (TDC), since such a system does not use special sensors for this. An algorithm for determining TDC is proposed here, based on an analysis of the measured pressure diagram rather than its derivative, which minimises the influence of digital and analogue noise. Our algorithm for determining TDC and subsequent data synchronisation is applicable in the absence of information about the actual compression ratio in the cylinder, which is a typical scenario for modern engines with variable valve timing. The algorithm also works under conditions of only approximate data on the charge air pressure, which are refined during the iteration process. A formula is proposed for determining the initial TDC position. Parameters for irregular operation of the engine are considered, and can be calculated in real time using time diagrams of pressure and vibration. Methods for expressly assessing the stability of the functioning of the main engine systems by monitoring and analysing a number of successive operating cycles are considered. To assess the unevenness of operation of the engine, a dispersion estimate of the deviations in the main parameters is used. To enable a comprehensive assessment of the engine stability in real time, the CII (cycle irregularity index) criterion is developed. The data processing methods described in this article provide an accurate estimate of the indicated power, due to the precise determination of TDC, thereby enabling an analysis of the stability of the operating cycles, optimal tuning of the engine systems, and monitoring of the results during operation. [ABSTRACT FROM AUTHOR]

Featured Application: The sliding mode integral separation PID control strategy is utilized to reduce the overshooting amount of the fuel cell system, to reduce the regulation time, to improve the stability of the hydrogen fuel cell system power generation, and to make the system output meet the desired target value faster and more stably. The stability of hydrogen fuel cell system power generation is affected by key variables such as oxygen excess ratio (OER), electric stack temperature, and cathode–anode differential pressure. To increase the fuel cell's stability, a sliding mode integral separation proportional–integral–derivative (SMC−IS−PID) control strategy was proposed by combining the four−segment integral separation PID (IS−PID) control with the switching control in the sliding mode control (SMC). The control mode is selected through the system variable error and the current variable value; if there are significant systematic variable errors, the switching control in the SMC adopts the four−segment integral separation PID control, which determines the values of the segmentation thresholds and controls the integral weights to reduce the amount of overshoot. When the error of the system variables is small, the switching control in the SMC adopts the improved convergence law control, which introduces the hyperbolic tangent exponential power term, the nonlinear function term, and the saturation function term to improve the convergence law and decrease the control's convergence time. Experimentally verifying the effectiveness of the control strategy above, the results show that for the OER, the SMC−IS−PID overshoots 0 and realizes no overshooting with a regulation time of 5.019 s. For the temperature of the stack, the SMC−IS−PID overshoots only 0.134% with a regulation time of 40.521 s. For the pressure of the stack, the SMC−IS−PID realizes the system is basically free of oscillation. [ABSTRACT FROM AUTHOR]

In order to maintain the battery SOC, the fuel cell power will fluctuate dramatically, as well as frequent start-stop, which will greatly increase the life attenuation of the fuel cell and reduce the durability. An optimization-based energy management strategy with a real-time model predictive control and pontryagin's maximum principle for FCHEV is proposed in this paper, both the fuel economy and the fuel cell durability are considered in the optimization. A novel model predictive control is studied to achieve energy distribution. After the calculation of predicted speed sequence through back propagation neural network, pontryagin's maximum principle is introduced to solve the optimal control problem in each prediction horizon and obtain the ideal control strategy. In addition, the fuel cell degradation model is introduced in the modeling process, the minimum power point of the fuel cell system is designed to improve the fuel economy and durability of the fuel cell. Compared with the rule-based strategy, the proposed MPC strategy has better performance to reduce the total equivalent hydrogen consumption, which can save up to 8.44% in the test case of the mid-size fuel cell passenger car while maintaining the stability of the battery's state of charge. [ABSTRACT FROM AUTHOR]

A two-layer coordinated control strategy is proposed to solve the power allocation problem faced by electric–hydrogen hybrid energy storage systems (HESSs) when compensating for the fluctuating power of the DC microgrid. The upper-layer control strategy is the system-level control. Considering the energy storage margin of each energy storage system, fuzzy logic control (FLC) is used to make the initial power allocation between the battery energy storage system (BESS) and the multistack fuel cell system (MFCS). The lower-layer control strategy is the device-level control. Considering the individual differences and energy-storage margin differences of the single-stack fuel cell (FC) in an MFCS, FLC is used to make the initial power allocation of the FC. To improve the hydrogen-to-electricity conversion efficiency of the MFCS, a strategy for optimization by perturbation (OP) is used to adjust the power allocation of the FC. The output difference of the MFCS before and after the adjustment is compensated for by the BESS. The simulation and experiment results show that the mentioned coordinated control strategy can enable the HESS to achieve adaptive power allocation based on the energy storage margin and obtain an improvement in the hydrogen-to-electricity conversion efficiency of the MFCS. [ABSTRACT FROM AUTHOR]

The vehicle fuel economy rating system in South Korea has adopted the US 5-cycle fuel economy system since 2012 to provide consumers with comprehensive information. However, due to resource constraints, derived 5-cycle equations have been utilized to approximate 5-cycle test results using the 2-cycle test. This study examines the accuracy of derived 5-cycle fuel economy equations for 20 recent vehicle models in Korea and updates them based on the correlation between 5-cycle and 2-cycle fuel consumption. The updated equations are expected to refine fuel economy ratings for up to three models, ensuring the label's reliability. [ABSTRACT FROM AUTHOR]

Fast detection and correct diagnosis of any engine condition changes are essential elements of safety and environmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions. Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry. To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to the fault detection of the fuel delivery system of a two-stroke marine engine. The selected diagnostic data is the exhaust gas composition, with four components considered: oxygen, carbon oxide, nitric oxide, and carbon dioxide. With these diagnostics, the method distinguishes eight different engine faults from the efficient state. The manuscript presents in detail the methodology for applying the SVDD method in a marine engine. The method of obtaining diagnostic data and its scaling is described. The method of training and validating the algorithm is also presented, along with ready-made algorithms for use. The 100% accuracy of the proposed fault detection method. Based on the obtained results, the proposed fault detection method is promising for a simple application. Moreover, generalised algorithms that may be adapted to different technical solutions are also presented. Highlights SVDD was used for marine engine fault detection from exhaust gas composition Laboratory measurements were carried out on the two-stroke diesel engine The proposed algorithm detected the considered faults with 100% accuracy A generalised algorithm for adapting other complex technical objects was proposed [ABSTRACT FROM AUTHOR]

The start/stop (S/S) system implemented in motorcycles aims primarily at fuel savings. This study was conducted to assess the effectiveness of this system in conditions of heavy traffic and traffic lights in Lima, using a virtual channel identifier (VCI) and a technical schedule. The detailed analysis covered critical aspects of the S/S system, the description of the route taken, and its segmentation to understand the number of stops and mileage. Speed limits, schedules, and measurement equipment were established, including the MICODUS-ORBD2 device and the VCI-Hero. The study included tests conducted with and without the MICODUSORBD2 device, recording times, distances, and fuel consumption. Data were collected with the S/S activated and deactivated, concluding the system achieves a 10.1% fuel saving. This finding provides valuable insights into understanding the system's effectiveness in actual traffic conditions and emphasizes the importance of maintaining key vehicle components to optimize S/S performance. [ABSTRACT FROM AUTHOR]

Fuels should behave appropriately in all sections of the engine system: the engine, fuel delivery system, and tank. Fuel quality can be linked to the following three crucial areas: performance, fitness for current use, and stability. Classical methods of diesel fuel examination mostly rely on the absolute value measurement of one specific parameter while stabilizing outside conditions. In contrast, multiparametric methods depend on simultaneously measuring a set of parameters. Therefore, multiparametric methods open the possibility of intriguing new examinations and classifications of diesel fuel quality while raising specific issues relating to the instrumentation and construction of sensing devices. This paper presents a review, based on the published literature and the authors' research, of the current state-of-the-art multiparametric methods for rapid diesel fuel quality classification and related instrumentation, systematizing the various types of methods from the point of view of the principles of their operation. The main conclusion is that different measuring procedures use similar methods of data processing. Moreover, the heavy, costly, and complex devices that enable standard examinations can be converted to simpler devices in the future, whose cost of use is significantly lower. However, to achieve this, progress in electronic devices is required. [ABSTRACT FROM AUTHOR]

Solid oxide fuel cells (SOFCs) are an efficient, reliable and clean source of energy. Predictive modeling and analysis of their performance is becoming increasingly important, especially with the growing emphasis on sustainable development's requirements. However, mathematical modeling is difficult due to the complexity of its internal structure. In this study, the system's electricity generating performance and operational characteristics were analyzed using recent on-site monitoring data first. Then, based on Pearson's correlation coefficient, some of the variables were selected to build two prediction models: an artificial neural network (ANN) model and a multiple linear regression (MLR) model. The models were evaluated on the basis of the normalized mean square error (NRMSE), which was 1.89% for the MLR model and 0.66% for the ANN model, with no overall bias. They were also compared with other existing models, and it was found that the two models used in this study have the advantage of high accuracy and low difficulty. Therefore, the models developed in this study can more accurately and effectively assess the SOFC system's state and can better support work to improve the thermoelectric performance of SOFC systems. [ABSTRACT FROM AUTHOR]

Carbon is one of the most abundant minerals in the universe. The world’s energy needs are being unmet due to the exponential rise in population. Since its inception 20 years ago, carbon and its allotropes, including fullerenes, carbon nanotubes, and graphene, have been marketed as potential energy storage and generation materials. By solving important issues like accumulation and inadequate thermodynamic compatibility, carbon fiber, expanded graphite, and carbon nanotubes are promising functional materials that can be used to improve the performance of bipolar plates further. There are several potential uses for carbon-based nanomaterials (CBNMs) in the energy area. This mini-review provides an overview of the synthetic routes employed for producing CBNMs, categorizing them based on their types, elucidating their diverse applications in fuel energy systems, and emphasising the uses of CBNMs in energy. The advantages and disadvantages of several synthetic processes have been examined and compared. The types of CBNMs, like carbon nanotubes, graphene, carbon dots, and fullerenes, are explored in terms of their unique structural properties and fabrication methods. Furthermore, the utilization of CBNMs in fuel energy systems, such as fuel cells, energy storage devices, and catalysis, is comprehensively reviewed. [ABSTRACT FROM AUTHOR]

Regenerative pumps are considered a promising option for hydrogen recirculation in proton exchange membrane fuel cell (PEMFC) systems. The geometry of the impeller exerts a direct influence on the pressurization process within the regenerative pumps. However, the influence has not been explored systematically in any available publications. This study investigates the effects of geometric parameters on pump performance and provides design guidelines for hydrogen regenerative pumps. A three-dimensional (3D) numerical model is developed and validated. The effects of critical geometric parameters, including the number of blades, impeller radius, and impeller radius ratio, on the performance of the regenerative pumps are then analyzed. Based on the analysis, this work recommends 35 blades and an impeller radius ratio of 0.65. To establish a correlation between operational performance and micro-flow mechanisms, the fluid velocity distribution at the interface of the rotating and stationary domains is quantitatively analyzed. Results indicate that a reduction in the flow rate results in increased axial velocity and decreased tangential velocity. The increased axial velocity enhances mass transfer, thus increasing the pressure and diminishing the efficiency, whereas the decreased tangential velocity intensifies the impact of the fluid on the blades, leading to increased shock losses and reduced efficiency. • The effects of the number of blades, impeller radius, and impeller radius ratio on the performance of hydrogen regenerative pumps are revealed. • The optimal values of the number of blades and impeller radius ratio are proposed. • The fluid flow velocities at the interface of rotating and stationary domains are quantitatively analyzed. • The flow mechanism of regenerative machines is elucidated through numerical methods. [ABSTRACT FROM AUTHOR]

This study focuses on overview and general economic viability evaluation of four types of portable electric generators: diesel and petrol internal combustion engines, batteries/accumulators and inverter systems (especially lithium polymer and lithium-ion battery systems), hydrogen fuel cell systems and combination (hybrid) of the latter. It does not include the rarely used, inefficient forms of energy conversion, such as steam turbines, as well as energy generators that are difficult to adjust with consumption and supply variations (variable forms of RES like wind and solar energy). The main targets of the study are battery/inverter systems, hydrogen fuel cell systems, and hybrid battery/inverter and hydrogen fuel cell systems, with hydrogen fuel cell systems being the thematic core. [ABSTRACT FROM AUTHOR]

Recent research has focused on applying PEM fuel cell systems to heavy-duty unmanned aerial vehicles (UAVs) as eco-friendly power sources to enhance their mission capabilities. High-altitude operation poses challenges owing to low temperatures, poor oxygen concentrations, and humidity, which affect fuel cell performance. In this study, the thermal stability of a PEM fuel cell system for UAVs was analyzed using an integrated system model in MATLAB/Simulink. Parametric studies were conducted to analyze the thermal parameters of the stack and observe the changes in the cooling load of the system according to the cruising altitude, as well as variations in the optimal operating conditions to ensure the durability of the fuel cell stack. The results of this study are expected to contribute to the selection of optimal operating conditions and the development of thermal management strategies for PEM fuel cell-based UAVs operating at different cruising altitudes. [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]

The proton exchange membrane fuel cell (PEMFC) in a fuel cell electric bus (FCEB) converts hydrogen's chemical energy into electrical energy. The fuel cell system comprises a fuel cell stack and a balance of plant (BOP) system, which efficiently controls the stack. Fuel cell and battery are sensitive to operational temperature, which directly impacts performance, lifespan, and safety. Therefore, a thermal management system (TMS) is necessary to maintain an appropriate temperature by dissipating the heat generated by the fuel cell and battery. In this study, the exponential or quadratic relationships between the power consumption of the major components of an FCEB and various factors, such as temperature and flow rate influencing the operational behavior and control of the components, were analyzed based on the results of a dynamometer vehicle test. Additionally, the vehicle's energy flow was calculated under different fuel cell load conditions. When the fuel cell operated at 56.3 kW, TMS power was 6.6 times higher than at 20 kW. At full load, under 90 kW, it increased to 17.4 times higher. The rise in fuel cell load correlated with higher heat generation, resulting in a significant increase in power consumption for both the radiator fan and coolant pump. [ABSTRACT FROM AUTHOR]

The energy management system of a fuel cell electric robot should be highly responsive to provide the required power for various tactical operations, navigation of different routes, and acceleration. This paper presents a new multi-level online energy management strategy for a fuel cell electric robot based on the proposed functions of equivalent hydrogen fuel value evaluation, classification of the battery state of charge via the squared combined efficiency function, identification of the robot maneuver condition based on the proposed operation state of robot function, improvement of the overall energy efficiency based on the proposed function of the battery overcharge control, and separation of the functional points of the fuel cell based on the operational mode control strategy. The simulation study of the proposed online multi-level energy management strategy was carried out with MATLAB R2018b software to verify its superiority by comparing with other strategies. The results indicate a reduction in hydrogen consumption, reduction in fuel cell power fluctuations, prevention of battery overcharging, and incrementation in the total energy efficiency of energy storage systems compared to other energy management strategies. [ABSTRACT FROM AUTHOR]

Mimicking the dissipative assemblies found in living systems fueled by bioenergy, we present a novel chemical fuel-driven transient 2D SOF, formed via the redox reaction-driven transient self-assembly of tetraphenylene-based structural units and cucurbit[8]uril (CB[8]). The system was initiated by adding sodium dithionite (SDT) as the fuel, leading to the formation of 2D SOFs through 2 : 1 host–guest complexation between the viologen cation radical and CB[8]. These 2D SOFs then spontaneously disassemble over time as the radicals are oxidized by air. The temporal assembly and lifetimes of these transient SOFs can be controlled by adjusting the concentrations of the fuel. Moreover, the resulting transient 2D SOFs exhibited remarkable potential as catalysts for the green synthesis of benzyl sulfones in water. [ABSTRACT FROM AUTHOR]

This study proposes a machine learning-based maximum power point tracking method for fuel cell systems. Initially, a Matlab model was developed to accurately represent the behaviour of a proton exchange membrane fuel cell. A dataset for training of machine learning methods was collected from fuel cells operating under different conditions. To demonstrate the effectiveness of the proposed method, comparison studies were conducted using classical methods, namely "perturb and observe" and "incremental conductance" under varying temperature and pressure conditions. Notably, under the condition of temperature and pressure variation, the output powers obtained from the system were 2005.2 W for support vector machine and 2018.5 W for linear regression at 4.5 s, while the output powers of 'incremental conductance' and 'perturb and observe' were 1989.6 W and 1986.3 W, respectively. The results demonstrate that the proposed method contributes to a more efficient operating condition and faster dynamic responses to changes. • An MPPT method based on machine learning is proposed. • The utilization of a machine learning-based MPPT technique enhances the efficiency of PEMFC. • By utilizing the machine learning, the PEMFC system adapts to varying operating conditions. • The proposed method provides an efficient solution for maximizing power extraction from PEMFC. [ABSTRACT FROM AUTHOR]

The Sine–Cosine algorithm (SCA) is efficient but faces challenges in exploitative abilities, slow convergence, and exploration–exploitation balance. This study proposes a novel optimization method, the learning-based sine–cosine algorithm (L-SCA), to solve the optimal power flow (OPF) problem. The basic SCA has been modified with a learning phase operator inspired by TLBO. The SCA handles global exploration, while the learner phase of teaching–learning based optimization (TLBO) offers strong local search capabilities, which can be utilized to enhance the solution neighborhood space provided by the SCA technique. The L-SCA and original SCA algorithms address OPF in IEEE 57-bus, Algerian 59-bus, and IEEE 118-bus power systems, considering twelve cases with a focus on cost savings, voltage stability, voltage profile, emissions, and power losses. The comparative study shows that the proposed L-SCA consistently outperforms standard SCA and other reported methods in all cases for varied-scale standard test systems as well as for a practical power system, within reasonable execution times. For instance, L-SCA in the Algerian 59-bus system cut fuel costs by around 13.13% compared to initial case, equating to annual savings of $2.2 million, while in the IEEE-118 bus system, power loss is significantly reduced to 17.881 MW, marking an 86.5% reduction compared to the base case. [ABSTRACT FROM AUTHOR]

This paper propose a wide gain single-bridge interleaved three-level LLC resonant converter with current sharing capability. This novel converter offers numerous advantages, including low cost, low current ripple, reduced voltage and current stress, widely gain range, high efficiency, good current sharing capability and versatile application scalability. Utilizing the three-level inverter + full-wave rectifier LLC converter as a representative case, the paper conducts an in-depth analysis and research on the proposed method. Finality, a 600 W experimental prototype was constructed and tested. Experimental results reveal that the proposed converter exhibits lower current ripple and a broader gain range. Moreover, the converter shows good current sharing capability (with a resonant element tolerance of 10%, the current error between the two phases does not exceed 12%) and high efficiency (peaking at 95.8%). [ABSTRACT FROM AUTHOR]

Microbial contamination in aircraft fuel-containing systems poses significant threats to flight safety and operational integrity as a result of microbiologically influenced corrosion (MIC). Regular monitoring for microbial contamination in these fuel systems is essential for mitigating MIC risks. However, the frequency of monitoring remains a challenge due to the complex environmental conditions encountered in fuel systems. To investigate the impact of environmental variables such as water content, oxygen levels, and temperature on the MIC of aluminum alloy in aircraft fuel systems, orthogonal experiments with various combinations of these variables were conducted in the presence of sulfate-reducing bacteria. Among these variables, water content in the fuel oil demonstrated the most substantial influence on the corrosion rate of aluminum alloys, surpassing the effects of oxygen and temperature. Notably, the corrosion rate of aluminum alloys was the highest in an environment characterized by a 1:1 water/oil ratio, 0% oxygen, and a temperature of 35 °C. Within this challenging environment, conducive to accelerated corrosion, changes in the corrosion behavior of aluminum alloys over time were analyzed to identify the time point at which MIC intensified. Observations revealed a marked increase in the depth and width of corrosion pits, as well as in the corrosion weight-loss rate, starting from the 7th day. These findings offer valuable insights for determining the optimal frequency of microbial contamination detection in aircraft fuel systems. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the performance of a Proton Exchange Membrane (PEM) fuel cell, which is equipped with a flow field design featuring dual inlets and outlets, while operating under conditions of excess stoichiometry. These experiments were conducted using a fuel cell system connected to a station that allowed for the precise adjustment of gas flow rates. During the initial phase of experimentation, various proportions of excess oxygen were systematically applied, while maintaining constant hydrogen flow rates of 80 mL/min and 100 mL/min. Particularly noteworthy, for the case of a 100 mL/min hydrogen gas flow rate and the optimized excess oxygen proportion of 150%, further experiments were undertaken to ascertain the ideal humidification conditions. The outcomes of these experiments revealed that a hydrogen gas flow rate of 100 mL/min consistently outperformed the 80 mL/min flow rate in terms of fuel cell performance. Moreover, it was observed that the introduction of excess oxygen significantly improved performance, up to a 50% oxygen proportion for the 80 mL/min hydrogen flow rate and up to a 150% proportion for the 100 mL/min hydrogen flow rate. One intriguing observation pertained to the influence of humidification. Specifically, it was found that the utilization of a humidification temperature of 100°C, or the absence of humidification altogether, resulted in notably diminished power output. In contrast, intermediate humidification temperatures of 60°C, 70°C, 80°C, and 90°C consistently yielded identical maximum power points (MPP) when combined with a 150% excess oxygen supply and a hydrogen flow rate of 100 mL/min. The twin inlet-twin outlet flow field provides a slight advantage over the conventional serpentine flow field in the overall analysis. [ABSTRACT FROM AUTHOR]

The control strategy of the gas supply subsystem is very important to ensure the performance and stability of the fuel cell system. However, due to the inherent nonlinear characteristics of the fuel cell gas supply subsystem, the traditional control strategy is mainly based on proportional integral (PI) control, which has the disadvantages of large limitation, large error, limited immunity, and inconsistent control performance, which seriously affects its effectiveness. In order to overcome these challenges, this paper proposes an optimal control method for air supply subsystems based on nonlinear active disturbance rejection control (ADRC). Firstly, a seven-order fuel cell system model is established, and then, the nonlinear ADRC and traditional PI control strategies are compared and analyzed. Finally, the two strategies are simulated and compared. The validation results indicate that the integral absolute error (IAE) measure of PI control is 0.502, the integral square error (ISE) measure is 0.1382, and the total variation (TV) measure is 399.1248. Compared with the PI control, the IAE and ISE indexes of ADRC were reduced by 61.31% and 58.03%, respectively. ADRC is superior to PI control strategy in all aspects and realizes the efficient adjustment of the system under different working conditions. ADRC is more suitable for the nonlinear characteristics of the gas supply system and is more suitable for the oxygen excess ratio (OER). [ABSTRACT FROM AUTHOR]

The maritime industry is undergoing a major transformation to achieve reduction of greenhouse gas emissions. Many new options, such as alternative propulsion systems and fuels, optimized routes, or auxiliary propulsion systems, including wind‐assistance devices, need to be integrated and aligned within a wide network of different stakeholders. New ways are necessary to work with and manage the increasing complexity in the maritime industry. Model‐based systems engineering approaches are a promising strategy to gain a better understanding of the as‐is situation and to develop advanced solutions. This paper shows the application of the ARCADIA method for the maritime industry, with the target of integrating wind‐assistance devices to vessels, using the ARCADIA modeling language and the Capella tool. [ABSTRACT FROM AUTHOR]

The economy and stability of the hydrogen recirculation system in high-power fuel cells significantly impact the performance of the stack system. However, there is no consensus on the optimal hydrogen recirculation mode to be employed. To determine the most effective solution across the entire power range of the stack, this study compares the performance of various coupling modes. The dynamic performance variations of the system were investigated under different modes by the Computational Fluid Dynamics (CFD) method. The simulation results demonstrated that within the low and medium power range of the stack, the PUE (Pump Upstream of Ejector) mode had the lowest power consumption of all modes, at 112 W. The power of the PUE mode had a reduction of 56.3% compared to the full-power single hydrogen pump mode, and a reduction of 22.8% compared to the PDE (Pump Downstream of Ejector) mode. [Display omitted] • Various coupling models of hydrogen pumps and ejectors are studied. • The pressure rise distribution of coupling modes are compared and analyzed. • Coupling mode reduces power consumption by more than 50%. • The optimal solution for the full power range of the stack is derived. [ABSTRACT FROM AUTHOR]

This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. Through meticulous simulations and analyses, the study explores the collaborative integration of these techniques with boost converters to enhance reliability and productivity. It was found that FSSO consistently works better than CS, achieving an average increase of 12.5% in power extraction from PEM fuel cells in a variety of operational situations. Additionally, FSSO exhibits superior adaptability and convergence speed, achieving the maximum power point (MPP) 25% faster than CS. These findings underscore the substantial potential of FSSO as a robust and efficient MPPT method for optimizing PEM fuel cell systems. The study contributes quantitative insights into advancing green energy solutions and suggests avenues for future exploration of hybrid optimization methods. [ABSTRACT FROM AUTHOR]

Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system. • HMS methods for FC diagnosis are introduced and classified into three main categories. • New scheme is introduced categorising HMS methods by approach and characteristics. • Matrix evaluation is introduced rating HMS methods for individual FC application. • Method properties affect classification results requiring evaluation for each use case. • For FCs, feature extraction, reduction and fault classification methods are chosen. [ABSTRACT FROM AUTHOR]

Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system's operation and the system's durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore, diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modeled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far, it turns out that the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis. [ABSTRACT FROM AUTHOR]

Solid oxide fuel cell power generation systems are devices that utilize solid electrolytes to transfer ions for electrochemical energy conversion. A wide range of gases can be used as fuel gas, including hydrogen, natural gas, and carbon monoxide. Considering the high cost of pure hydrogen, hydrogen production from natural gas reforming has become a hot research area. In this study, the 4F-LCA method was employed to construct an evaluation framework, with a particular emphasis on the cost analysis of solid oxide fuel cell power generation systems, and uses a bottom-up approach to build a system economic analysis model to visualize the major costs involved in the system. An economic benefit analysis and sensitivity analysis were carried out for the 2 kW natural gas solid oxide fuel cell as a case by taking the financial net present value (NPV), internal rate of return (IRR) and payback period into account. In this study, the investment cost and payback period of a 2 kW solid oxide fuel cell system are obtained, which can provide a reference for the project construction and operation of solid oxide fuel cell systems. [ABSTRACT FROM AUTHOR]

Ejector-based proton exchange membrane fuel cells (PEMFCs) are of great interest due to their simplicity and feasibility. Thus, proton exchange membrane fuel cells are considered the most suitable technology for in-vehicle systems, industrial applications, etc. Despite the passive characteristics of the ejector, active control of the hydrogen supply system is needed to ensure sufficient hydrogen, maintain the stack pressure, and ensure effective entrainment. In this research, a novel semi-empirical model is proposed to accurately predict the entrainment performance of the ejector with an 80 kW fuel cell system. According to the precise semi-empirical model, the hydrogen supply system and the anode channel are modeled. Then, a fuzzy logic controller (FLC) is developed to supply sufficient and adequate gas flow and maintain the rapid dynamic response. Compared to the conventional proportional–integral–derivative controller, the fuzzy logic controller could reduce the anode pressure variability by 5% during a stepped case and 2% during a dynamic case. [ABSTRACT FROM AUTHOR]