Search Results (268)

Driven by carbon neutrality and peak carbon policies, hydrogen energy, due to its zero-emission and renewable properties, is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However, the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited, particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First, a quantitative model evaluates TCO from vehicle purchase to disposal. Second, a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally, a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW, H-FCV can achieve optimal fuel economy and hydrogen consumption. However, even with advanced technology, their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system, assuming negligible fuel cell degradation. In the short term, H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship. Full article

Fuel cells (FCs) are widely used in various applications such as transportation, vehicles, and energy storage, as well as in commercial and residential buildings. The FC is connected to the grid via an inverter, which converts DC power to AC power for integration with the AC grid. Thus, it is essential to adjust the gain of the inverter’s controllers to improve FC performance and the quality of the power generated by the FCs. In this work, a fractional-order PID (FOPID) controller is used to control an inverter where the FOPID’s gain settings are determined optimally to improve the performance of the current controller of the solid-oxide fuel cell (SOFC). The optimal parameters of the FOPID are obtained using a newly developed and efficient algorithm called beluga whale optimization (BWO). To highlight the efficiency of the proposed optimization approach, the obtained results are compared with particle swarm optimization (PSO) and the conventional active power controller (APC). The findings of this paper demonstrate that the SOFC achieves significantly superior performance when the FOPID controller is optimally tuned using BWO across all performance metrics related to the FC inverter. PSO also yields good results, ensuring smooth system operation and good performance. Based on the results, the output current from the SOFC using the BWO and PSO algorithms aligns well with the reference current, whereas the APC exhibits poor performance in tracking reference current changes in two cases. Specifically, the APC introduces a delay of approximately one second (0.5 to 0.6 s), resulting in poor control performance. This delay causes the system to deviate from the reference current control (RCC) by 10%, leading to poor performance. However, the proposed optimization algorithms effectively resolve this issue, offering a robust solution for enhanced current control. Full article

This study investigates the structure of a metal hydride (MH) cartridge as a hydrogen storage tank for small-scale fuel cells (FCs). This cartridge is designed to be stacked and used in layers, allowing flexible capacity adjustment according to demand. MH enables compact and safe hydrogen storage for small-scale fuel cell (FC) applications due to its high energy density and low-pressure operation. However, because hydrogen desorption from MH is an endothermic reaction, an external heat supply is required for stable performance. To enhance both the heat transfer efficiency and cartridge usability, we propose a heat supply method that utilizes waste heat from an air-cooled proton-exchange membrane fuel cell (PEMFC). The proposed cartridge incorporates four cylindrical MH tanks that require uniform heat transfer. Therefore, we proposed the tank arrangements within the cartridge to minimize the non-uniformity of heat transfer distribution on the surface. The flow of exhaust air from the PEMFC into the cartridge was analyzed using computational fluid dynamics (CFD) simulations. In addition, an empirical correlation for the Nusselt number was developed to estimate the heat transfer coefficient. As a result, it was concluded that the heat utilization rate of the exhaust heat flowing into the cartridge was 13.2%. Full article

Due to climate change, the electric vehicle (EV) industry is rapidly growing and drawing researchers interest. Driving conditions like mountainous roads, slick surfaces, and rough terrains illuminate the vehicles inherent nonlinearities. Under such scenarios, the behavior of power sources (fuel cell, battery, and super-capacitor), power processing units (converters), and power consuming units (traction motors) deviates from nominal operation. The increasing demand for FCHEVs necessitates control systems capable of handling nonlinear dynamics, while ensuring robust, precise energy distribution among fuel cells, batteries, and super-capacitors. This paper presents a DSMC strategy enhanced with Robust Uniform Exact Differentiators for FCHEV energy management. To optimally tune DSMC parameters, reduce chattering, and address the limitations of conventional methods, a hybrid metaheuristic framework is proposed. This framework integrates moth flame optimization (MFO) with the gravitational search algorithm (GSA) and Fractal Heritage Evolution, implemented through three spiral-based variants: MFOGSAPSO-A (Archimedean), MFOGSAPSO-H (Hyperbolic), and MFOGSAPSO-L (Logarithmic). Control laws are optimized using the Integral of Time-weighted Absolute Error (ITAE) criterion. Among the variants, MFOGSAPSO-L shows the best overall performance with the lowest ITAE for the fuel cell (56.38), battery (57.48), super-capacitor (62.83), and DC bus voltage (4741.60). MFOGSAPSO-A offers the most accurate transient response with minimum RMSE and MAE FC (0.005712, 0.000602), battery (0.004879, 0.000488), SC (0.002145, 0.000623), DC voltage (0.232815, 0.058991), and speed (0.030990, 0.010998)—outperforming MFOGSAPSO, GSA, and PSO. MFOGSAPSO-L further reduces the ITAE for fuel cell tracking by up to 29% over GSA and improves control smoothness. PSO performs moderately but lags under transient conditions. Simulation results conducted under EUDC validate the effectiveness of the MFOGSAPSO-based DSMC framework, confirming its superior tracking, faster convergence, and stable voltage control under transients making it a robust and high-performance solution for FCHEV. Full article

Proton-Exchange-Membrane Fuel Cell (PEMFC) systems are proving to be a promising solution for decarbonizing various means of transport, especially heavy ones. However, their reliability, availability, performance, durability, safety and operating costs are not yet fully competitive with industrial and commercial systems (actual systems). Predictive maintenance (PrM) is proving to be one of the most promising solutions for improving these critical points. In this paper, several PrM approaches will be developed considering the constraints of actual systems. The first approach involves estimating the overall State of Health (SOH) of a PEMFC operating under a dynamic load according to an FC-DLC (Fuel Cell Dynamic Load Cycle) profile, using a Health Indicator (HI). This section will also discuss the relevance of current End-of-Life (EoL) indicators by putting the performance, safety and economic profitability of PEMFC systems into perspective. The second approach involves predicting the voltage of the PEMFC while operating under this same profile in order to estimate its overall Remaining Useful Life (RUL). Finally, the last approach proposed will make it possible to estimate the time when it will be worthwhile, or even economically necessary, to replace a degraded PEMFC with a new one. Full article

The biology literature addresses two puzzles: (i) the increase in specific metabolic rate of organs (SOrMR, W/kg of organ) with a decrease in body mass (M_B) of biological species (BS), and (ii) how the organs recognize they are in a smaller or larger body and adjust metabolic rates of the body (${\dot{q}}_B$) accordingly. These puzzles were answered in the author’s earlier work by linking the field of oxygen-deficient combustion (ODC) of fuel particle clouds (FC) in engineering to the field of oxygen-deficient metabolism (ODM) of cell clouds (CC) in biology. The current work extends the ODM hypothesis to predict the whole-body metabolic rates of 114 BS and demonstrates Kleiber’s power law {${\dot{q}}_B = a {M_B}^b$}. The methodology is based on the postulate of Lindstedt and Schaeffer that “150 ton blue whale. and the 2 g Etruscan shrew.. share the same.. biochemical pathways” and involve the following steps: (i) extension of the effectiveness factor relation, expressed in terms of the dimensionless group number G (=Thiele Modulus²), from engineering to the organs of BS, (ii) modification of G as G_OD for the biology literature as a measure of oxygen deficiency (OD), (iii) collection of data on organ and body masses of 116 species and prediction of SOrMR_k of organ k of 114 BS (from 0.0076 kg Shrew to 6650 kg elephant) using only the SOrMR_k and organ masses of two reference species (Shrew, 0.0076 kg: RS-1; Rat Wistar, 0.390 kg: RS-2), (iv) estimation of ${\dot{q}}_B$ for 114 species versus M_B and demonstration of Kleiber’s law with a = 2.962, b = 0.747, and (v) extension of ODM to predict the allometric law for maximal metabolic rate (under exercise, {${\dot{q}}_{B,MMR} = a_{MMR} {M_B}^{b_{MMR}}$}) and validate the approach for MMR by comparing b_MMR with the literature data. A method of detecting hypoxic condition of an organ as a precursor to cancer is suggested for use by medical personnel Full article

This paper provides a comprehensive review of hybrid energy systems (HESs), focusing on their challenges, optimization techniques, and control strategies to enhance performance, reliability, and sustainability across various applications, such as microgrids (MGs), commercial buildings, healthcare facilities, and cruise ships. The integration of renewable energy sources (RESs), including solar photovoltaics (PVs), with enabling technologies such as fuel cells (FCs), batteries (BTs), and energy storage systems (ESSs) plays a critical role in improving energy management, reducing emissions, and increasing economic viability. This review highlights advancements in multi-objective optimization techniques, real-time energy management, and sophisticated control strategies that have significantly contributed to reducing fuel consumption, operational costs, and environmental impact. However, key challenges remain, including the scalability of optimization techniques, sensitivity to system parameter variations, and limited incorporation of user behavior, grid dynamics, and life cycle carbon emissions. The review underlines the need for robust, adaptable control strategies capable of accommodating rapidly changing energy environments, as well as the importance of life cycle assessments to ensure the long-term sustainability of RES technologies. Future research directions emphasize the integration of variable RESs, advanced scheduling, and the application of emerging technologies such as artificial intelligence and blockchain to improve system resilience and efficiency. This paper introduces a novel classification framework, distinct from existing taxonomies, addressing gaps in prior reviews by incorporating emerging technologies and focusing on the dynamic nature of energy management in hybrid systems. It also advocates for bridging the gap between theoretical advancements and real-world implementation to promote the development of more sustainable and reliable HESs. Full article

The increasing integration of renewable energy into modern power systems has prompted the need for efficient hybrid energy solutions to ensure reliability, sustainability, and economic viability. However, optimizing the design of hybrid renewable energy systems, particularly those incorporating both hydrogen and battery storage, remains challenging due to system complexity and fluctuating energy trading conditions. This study addresses these gaps by proposing a novel framework that combines the Chimp Optimization Algorithm (ChOA) with a rule-based energy management strategy (REMS) to optimize component sizing and operational efficiency in a grid-connected microgrid. The proposed system integrates photovoltaic (PV) panels, wind turbines (WT), electrolyzers (ELZ), hydrogen storage, fuel cells (FC), and battery storage (BAT), while accounting for seasonal variations and dynamic energy trading. Each contribution in the Research Contributions section directly addresses critical limitations in previous studies, including the lack of advanced metaheuristic optimization, underutilization of hydrogen-battery synergy, and the absence of practical control strategies for energy management. Simulation results show that the proposed ChOA-based model achieves the most cost-effective and efficient configuration, with a PV capacity of 1360 kW, WT capacity of 462 kW, 164 kWh of BAT storage, 138 $H_2$ tanks, a 571 kW ELZ, and a 381 kW FC. This configuration yields the lowest cost of energy (COE) at $0.272/kWh and an annualized system cost (ASC) of $544,422. Comparatively, the Genetic Algorithm (GA), Salp Swarm Algorithm (SSA), and Grey Wolf Optimizer (GWO) produce slightly higher COE values of $0.274, $0.275, and $0.276 per kWh, respectively. These findings highlight the superior performance of ChOA in optimizing hybrid energy systems and offer a scalable, adaptable framework to support future renewable energy deployment and smart grid development. Full article

Due to the complementary operational features, photovoltaic (PV) and fuel cell (FC) systems are increasingly being integrated into hybrid microgrids. PV systems provide clean energy during the day, while FCs provide continuous power supply throughout the day and night; thus, FCs can address PV’s incapacity during the night. However, voltage instability, frequency deviation, and enhanced harmonic distortion can result from the intrinsic intermittency of solar energy, switching errors in power electronic equipment, and varying load demands. Thus, a fuzzy logic-based current-controlled voltage source inverter (CC-VSI) is proposed in this paper to overcome these issues and enhance power quality in PV-FC hybrid microgrids. As per IEEE 1547 regulations, the fuzzy controller dynamically modifies the inverter current to maintain steady voltage and frequency profiles. MATLAB/Simulink (R2022a) is used to model and simulate the system, and its performance is evaluated under various reactive load scenarios. To test the efficacy of the proposed control technique, various power quality metrics, viz., voltage profiles (sag and swell), frequency profile, and total harmonic distortions, are plotted when subjected to large reactive load variations. The simulation results that are obtained with the proposed fuzzy-based current control technique are compared with the conventional artificial neural networks-based controller to verify the effectiveness. From the comparison study, it is found that the proposed technique shows superior power quality performance over the conventional technique. This encourages the development of renewable energy-based sustainable hybrid microgrids worldwide. Full article

This study deals with a fuel-cell-based power supply system created from a fuel cell stack with a proton exchange membrane fuel cell (PEMFC) and controller monitoring system (Horizon Fuell Cell Technologies (HFCT)). In the fuel cell (FC) stack H60, the reactants are air and hydrogen. Reactants are used for the generation of electricity. The reactants supply fuel cell stacks with hydrogen through the hydrogen supply valve, and redundant reactants are extruded from the region of the 20 fuel cells of the H60 stack through the purge valve, both controlled by an FC controller. The main contribution of this study is the proposal, practical design and integration of an embedded monitoring system into the function of a fuel-cell-based power supply system for monitoring its operation parameters in mobile applications (such as in UGVs—Unmanned Ground Vehicles). The next contribution is the usage of INA226 power monitors for the measurement of input/output parameters in selected parts of the fuel-cell-based power supply system for the evaluation of electrical efficiency or power loss in the system. The third contribution is the integration of Bluetooth technology for the transfer of data from a fuel-cell-based power supply system in a mobile platform to a smartphone or PC for monitoring and data processing. At the end of this study, the computed efficiency values of the fuel cell stack, controller and switching power supply outputs are analysed, and the advantages, disadvantages and practical experience are summarized. Full article

Transitioning to clean energy in off-grid remote locations is essential to reducing fossil-fuel-generated greenhouse gas emissions and supporting renewable energy growth. While hybrid renewable energy systems (HRES), including multiple renewable energy (RE) sources and energy storage systems are instrumental, it requires technical reliability with economic efficiency. This study examines the feasibility of an HRES incorporating solar, wind, hydrogen, and biofuel energy at a remote location in Australia. An electric vehicle charging load alongside a residential load is considered to lower transportation-based emissions. Additionally, the input data (load profile and solar data) is validated through statistical analysis, ensuring data reliability. HOMER Pro software is used to assess the techno-economic and environmental performance of the hybrid systems. Results indicate that the optimal HRES comprising of photovoltaic, wind turbines, fuel cell, battery, and biodiesel generators provides a net present cost of AUD 9.46 million and a cost of energy of AUD 0.183, outperforming diesel generator-inclusive systems. Hydrogen energy-based FC offered the major backup supply, indicating the potential role of hydrogen energy in maintaining reliability in off-grid hybrid systems. Sensitivity analysis observes the effect of variations in biodiesel price and electric load on the system performance. Environmentally, the proposed system is highly beneficial, offering zero carbon dioxide and sulfur dioxide emissions, contributing to the global net-zero target. The implications of this research highlight the necessity of a regional clean energy policy facilitating energy planning and implementation, skill development to nurture technology-intensive energy projects, and active community engagement for a smooth energy transition. Potentially, the research outcome advances the understanding of HRES feasibility for remote locations and offers a practical roadmap for sustainable energy solutions. Full article

The development of innovative proton-conducting materials for low-temperature fuel cells (FCs) is, today, a central topic among the scientific community. Polyantimonic acid (PAA) is characterized by high conductivity and sufficient thermal stability; however, PAA-based solid membrane fabrication with high proton conductivity remains challenging. Additionally, PAA cannot be compacted into solid shaped electrolytes without a binder. In a previous work, using a fluoroplastic binder, the authors fabricated and investigated proton conductivity of bulk PAA-based membranes in the temperature range 25–250 °C. In the present research, the authors opted to use another binder, poly(vinyl alcohol), PVA (which already allowed to obtain PAA sensors with higher sensitivity to moisture, low hysteresis, and similar aging than the produced previously with the fluoroplastic binder), for fabricating new solid membranes. The sample’s structure and morphology were studied using diverse experimental techniques (Thermogravimetric analysis, X-ray diffraction analysis, etc.). Electrical Impedance spectroscopy, EIS, was used to assess the electrical response and respective time stability of the membranes; it also allowed the development of an equivalent model circuit to better interpret the samples’ electrical behavior and respective contributions. The samples with 20 wt% PVA content showed improved protonic conductivity and chemical stability up to 100 °C, when compared to previous prepared and reported ones using the fluoroplastic binder. Full article

The turbocharging of hydrogen fuel cell systems (FCSs) has recently become a prominent research area, aiming to improve FCS efficiency to help decarbonise the energy and transport sectors. This work compares the performance of an electrically assisted variable-geometry turbocharger (VGT) with a fixed-geometry turbocharger (FGT) by optimising both the sizing of the components and their operating points, ensuring both designs are compared at their respective peak performance. A MATLAB-Simulink reduced-order model is used first to identify the most efficient components that match the fuel cell air path requirements. Maps representing the compressor and turbines are then evaluated in a 1D flow model to optimise cathode pressure and stoichiometry operating targets for net system efficiency, using an accelerated genetic algorithm (A-GA). Good agreement was observed between the two models’ trends with a less than 10.5% difference between their normalised e-motor power across all operating points. Under optimised conditions, the VGT showed a less than 0.25% increase in fuel cell system efficiency compared to the use of an FGT. However, a sensitivity study demonstrates significantly lower sensitivity when operating at non-ideal flows and pressures for the VGT when compared to the FGT, suggesting that VGTs may provide a higher level of tolerance under variable environmental conditions such as ambient temperature, humidity, and transient loading. Overall, it is concluded that the efficiency benefits of VGT are marginal, and therefore not necessarily significant enough to justify the additional cost and complexity that they introduce. Full article

This review is focused on FC-BENTEN, an advanced synchrotron X-ray experimental database developed at SPring-8 with support from Japan’s New Energy and Industrial Technology Development Organization (NEDO). Designed to advance polymer electrolyte fuel cells (PEFCs) research, FC-BENTEN addresses challenges in improving efficiency, durability, and cost-effectiveness through data-driven approaches informed by materials informatics (MI). Through standardization of protocols for sample preparation, data acquisition, analysis, and formatting, the database ensures high-quality, reproducible data essential for reliable scientific outcomes. FC-BENTEN streamlines metadata creation using automated processes and template-based tools, enhancing data management, accessibility, and interoperability. Security measures include two-factor authentication, safeguarding sensitive information and maintaining controlled user access. Planned integration with MI platforms will broaden data cross-referencing capabilities, facilitate PEFC applications expansion, and guide future research. This review discusses FC-BENTEN’s architectural framework, metadata standardization efforts, and role in advancing PEFC research through a high-throughput experimental workflow. It illustrates how data-driven methods and standardized practices contribute to innovation, underscoring databases’ potential to accelerate next-generation PEFC technologies development. Full article

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is insidious, with only 15–20% of those diagnosed suitable for surgical resection as it is either too advanced and has invaded local structures or has already spread to distant sites. The associated tumor microenvironment provides a protective shield which limits the efficacy of chemotherapeutic agents, but also impairs the delivery of nutrients required for the PDAC cells. To compensate for this, metabolic adaptions occur to provide alternative sources of fuel. The aim of this study is to explore metabolomic differences between participants with resectable PDAC compared to healthy volunteers (HV). The objectives were to use nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to determine if resectable PDAC induces sufficient metabolic adaptations and variations which could be used to discriminate between the two groups. Methods: Plasma samples were collected from fasted individuals with resectable PDAC (n = 23, median age 68 [IQR 56–75], 69.6% male) and HV (n = 24, median age 63 [IQR 58–71], 54.2% male). Samples were analyzed using NMR and the Biocrates MxP Quant 500 kit at University Hospital Southampton. Results: NMR spectroscopy identified six independent metabolites that significantly discriminated between the PDAC and HV groups, including elevated plasma concentrations of 3-hydroxybutyrate and citrate, with decreased amounts of glutamine and histidine. MS analysis identified 84 metabolites with a significant difference between the PDAC and HV cohorts. The metabolites with a fold change (FC) > 1.5 in the PDAC population were conjugated bile acids (taurocholic acid, glycocholic acid, and glycochenodexoycholic acid). Discussion: In conclusion, using metabolomics, biochemical differences between resectable PDAC and HV were detected. These differences indicate metabolic plasticity and utilization of alternative fuel sources. Full article