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Fuel cell electric buses (FCBs) have proven to be a technically viable solution for transportation, owing to various advantages, such as reliability, simplicity, better energy efficiency, and quietness of operation. However, large-scale adoption of FCBs is hindered by the lack of extensive and structured infrastructure and the high cost of clean hydrogen. Many studies agree that one of the significant contributors to the lack of competitiveness of green hydrogen is the cost of electricity for its production, followed by transportation costs. On the one hand, to reduce the investment cost of the electrolyzer, high operating hours should be achieved; on the other, as the number of operating hours decreases, the impact of the electricity costs declines. This paper presents an innovative algorithm for a scalable hydrogen refuelling station (HRS) capable of successfully matching and identifying the most cost-efficient levelized cost of hydrogen (LCOH) produced via electrolysis and connected to the grid, based on the HRS components' cost curves and the hourly average electricity price profile. The objective is to identify the least-cost range of LCOH by considering both the electric energy and the investment costs associated with a hydrogen demand given by different FCB sizes and electrolyzer rated powers. In addition, sensitivity analyses have been conducted to quantify the technology cost margins, and a cost comparison between the refuelling of an FCB fleet and the recharging infrastructure required for an equivalent fleet of Battery Electric Buse (BEB) has been performed. An LCOH of around 10.5 €/kg varying from 12 €/kg (2 FCB) to 10.2 €/kg (30 FCB) has been found for the best-optimized configurations. The final major conclusion of this paper is that FCB technology is currently not economically competitive. Still, a cost contraction of the electric energy price and the electrolyzer capital investment would lead to a 50% decrease in the LCOH. Furthermore, increasing renewable energies into the grid may shift the electricity cost curve, resulting in higher prices when the BEB recharging demand is more significant. This impact, in addition to the peak power load and longer recharging times, might contribute to bridging the gap with FCBs. • Techno-economic model for the sizing of an HRS with grid-connected electrolyzer. • The widespread diffusion of H2 technology in mobility needs both reliability and cost-effectiveness. • Investigation of various electrolysers rated powers and fuel cell buses fleet size. • An action on both CAPEX and OPEX would lead to potential cost margins improvement. • It is found that the best configuration that balances the CAPEX and OPEX coincides with an LCOH ranging from 12 to 10 €/kg. [ABSTRACT FROM AUTHOR]

Due to the widespread use of multi-generation systems utilizing renewable energy sources and the growing global demand for such systems from both economic and environmental considerations, numerous researchers have focused on the design and evaluation of their performance. To this end, this research presents a biomass-based multi-generation system with an innovative and practical design that can generate electricity, heat, and hydrogen. This system includes a modified gas turbine cycle, a supercritical CO 2 (SCO 2) cycle, a transcritical CO 2 (TCO 2) cycle, a proton exchange membrane (PEM) electrolyzer, and a PEM fuel cell unit. This study aims to evaluate the impact of various biomass sources (paper, wood, paddy husk, and municipal solid waste) on the system performance. The proposed system has been analyzed using the first and second laws of thermodynamics. This system uses the maximum capacity to produce power, heat and hydrogen. A fuel cell unit has been used to consume hydrogen and generate more electricity. In the basic mode, the system has energy and exergy efficiencies of 47.89% and 32.26%, respectively, and can produce 2.74 kg/h of hydrogen. The biomass fuel consumption rate within the system is 0.055 kg/s. The overall exergy destruction of the system amounts to 1240 kW, with the biomass boiler and the condenser being the components that experience the greatest exergy destruction, registering values of 535.5 kW and 432.3 kW, respectively. Notably, employing municipal waste as biomass increases the system's exergy efficiency to 33.16%. • To investigate a biomass-driven system for producing power, hydrogen, and heating. • To evaluate the impact of various biomass sources on the system performance. • To use PEME for hydrogen and PEMFC for power and heat production. [ABSTRACT FROM AUTHOR]

The single-stack fuel cell system is utilized extensively in several industries. Unfortunately, the main problems are its low efficiency and durability, and unsatisfied reliability, especially in the high-power situation. Due to its significant performance, which includes high output power, durability, and reliability, multi-stack fuel cell systems (MFCS) are becoming more and more attractive. In this study, it is aimed to develope a control algorithm in parallel structure in the Matlab/Simulink software for the efficient use of hydrogen fuel consumption of PEM fuel cells – based boost converter using PI controller with PSO method. Models of both single and parallel connected PEM fuel cells were created in Matlab using mathematical equations in this paper. The analysis made in the study were applied for both models. PEMFCs were connected in parallel and only one DC-DC converter was used for the entire system. According to the load change, the required number of cells are activated due to control algorithm to provide the required power. As a result, the proposed method reduces hydrogen consumption by approximately 5 times under the same load, while optimized parameters reduce output voltage oscillation. • A new control algorithm for parallel connected PEM fuel cell has been successfully implemented. • The suggested method reduces hydrogen consumption by approximately 5 times under the same load. • Using small-capacity fuel cells instead of huge ones minimizes hydrogen consumption. • Optimized parameters decrease the voltage oscillation. [ABSTRACT FROM AUTHOR]

This paper presents a cryogenic turbo-electric hybrid propulsion system (TEHPS) for a 70–80 seat class turboprop regional aircraft, integrating superconducting technology with liquid hydrogen (LH 2) cooling. LH 2 is selected as the cooling medium for the designed cryogenic cooling circuit, and the evaporated hydrogen gas is channeled to a hydrogen fuel cell for electricity generation, making full use of the energy content of the hydrogen. Parametric modeling of critical components is conducted to determine mass, power and heat loss parameters under feasible operating temperature conditions. Four propulsion schemes are conceptualized based on power matching combinations of turbo-engines, hydrogen fuel cell and battery during cruise, descent and landing phases. Performance comparison and analysis of the cryogenic TEHPS for a typical mission profile in 2035 is conducted, considering three projected scenarios – conservative, baseline, and optimistic – derived from existing data. The results show that propulsion Scheme 1, combining turbo-engines, fuel cell and battery for cruise, significantly reduces aviation fuel mass and pollutants emissions, cutting fuel consumption by 34.2%–38.6% at specific power parameters and potentially doubling the cruising range. Propulsion Scheme 3, employing turbo-engines for cruise and a combination of fuel cell and battery for descent and landing, achieves the lowest total mass and highest power-to-weight (PTW). In optimistic scenarios, the PTW ratio reaches 2.40 kW/kg, with baseline and conservative scenarios at 1.81 kW/kg and 1.16 kW/kg respectively, demonstrating significant advancements in propulsion efficiency and sustainability. • Innovative design for a cryogenic turbo-electric hybrid propulsion system. • Developed a cryogenic cooling circuit for efficient hydrogen energy recovery. • Detailed dimensional modeling of critical system components. • Evaluation of performance parameters in different scenarios and propulsion schemes. [ABSTRACT FROM AUTHOR]

Solid oxide fuel cell (SOFC) is regarded as a promising energy conversion device because of its advantages such as high efficiency and fuel flexibility. With the advent of aviation electrification era, SOFC has been gradually studied as aviation power system. However, the high temperature operation and temperature gradient of SOFC bring challenges to practical application. Nowadays SOFC systems often use excessive air as coolant to reduce the temperature gradient of SOFC, which leads to the increases of the fuel consumption and reduction of the power generation efficiency. In order to maintain a lower temperature gradient with less air, a supercritical fuel cooled SOFC scheme is proposed in this paper. By establishing a one-dimensional model of conventional air-cooled fuel cell and fuel cell with fuel cooling channel. Through calculating the fuel cell temperature gradient under different working conditions, the results show that when the excess air coefficient (EAC) is 3, the temperature gradient of air-cooled SOFC reaches 22.7K/cm, while the temperature gradient of SOFC with fuel channel decreases to 8.35K/cm. Therefore, the SOFC with fuel channel can effectively reduce the use of air, reduce parasitic power consumption and improve the efficiency of the system while maintaining a lower temperature gradient. • A supercritical fuel cooled SOFC scheme is proposed in this paper. • When the excess air coefficient is 3, the temperature gradient of fuel cell with fuel channel decreases to 8.35K/cm. • The fuel cell system with fuel channel can effectively reduce the use of air. • The SOFC scheme of fuel cooling can improve the electrochemical performance of SOFC. [ABSTRACT FROM AUTHOR]

Improving the commercial fuel cell system efficiency is critical to reducing hydrogen consumption and improving the operational economy. This paper studies the power consumption pattern of the air supply subsystem, the most power-consuming auxiliary components, aiming to improve the system's efficiency. A method was proposed to get the extremum of the system net power by optimizing the oxygen excess ratio and cathode pressure. Mathematical models describing the fuel cell stack and air supply subsystem power characteristics were developed based on the mechanism analysis and estimation of unknown parameters. Then, a system net power model for energy efficiency optimization was developed. The operating conditions for optimal efficiency at a specific current density can be obtained by numerical calculation. To verify the method's effectiveness, a series of experiments were conducted, and the results show that the proposed method can maximize system net power output at various current density conditions. Compared with the conventional oxygen excess rate based one-dimensional optimization, the two-dimensional method can improve system efficiency by 2.06%, offering a good application prospect. • A mathematical model describing the fuel cell stack and air supply subsystem power characteristics was developed. • An energy efficiency optimization method based on the oxygen excess ratio and cathode pressure is proposed. • The operating conditions for optimal efficiency can be obtained by numerical calculation. • Maximum efficiency improvement of 2.06% can be achieved compared with One-dimensional optimization. [ABSTRACT FROM AUTHOR]

Neural Networks (NNs) can be used for energy management of hybrid vehicles, but they are hard to tune in inference to adapt to different driving conditions. To make the NN-based energy management strategy more flexible, this paper proposes a controllable NN for optimal energy management of fuel cell hybrid electric vehicles. Inspired by the equivalent factor in the Equivalent Consumption Minimization Strategy (ECMS), we introduce an adjustable target variable for the final state as an input to the NN-based strategy. During training, classification and regression networks with single-step and multi-step inputs are considered. An efficient shooting method and an adaptive method are then introduced to realize the precise control of the final state and online parameter adaptation. Simulations of the proposed method and the benchmarking method are carried out in different battery discharge modes. Results demonstrate that the proposed shooting neural classifier can achieve 99.7% fuel optimality of dynamic programming in a similar computational time to the shooting ECMS, and the proposed adaptive neural classifier can adapt to different driving conditions and has better fuel economy than the adaptive ECMS. • A controllable neural model for energy management of fuel cell vehicles is proposed. • Neural regressors and classifiers are trained under single-step and multi-step inputs. • A shooting method and an adaptive method for neural models are proposed. • The proposed method is comprehensively analyzed and compared with benchmarks. [ABSTRACT FROM AUTHOR]

The hybrid combination of hydrogen fuel cells (FCs) and batteries has emerged as a promising solution for efficient and eco-friendly power supply in maritime applications. Yet, ensuring high-quality and cost-effective energy supply presents challenges. Addressing these goals requires effective coordination among multiple FC stacks, batteries, and cold-ironing. Although there has been previous work focusing it, the unique maritime load characteristics, variable cruise plans, and diverse fuel cell system architectures introduce additional complexities and therefore worth to be further studied. Motivated by it, a two-layer energy management system (EMS) is presented in this paper to enhance shipping fuel efficiency. The first layer of the EMS, executed offline, optimizes day-ahead power generation plans based on the vessel's next-day cruises. To further enhance the EMS's effectiveness in dynamic real-time situations, the second layer, conducted online, dynamically adjusts power splitting decisions based on the output from the first layer and instantaneous load information. This dual-layer approach optimally exploits the maritime environment and the fuel cell features. The presented method provides valuable utility in the development of control strategies for hybrid powertrains, thereby enabling the optimization of power generation plans and dynamic adjustment of power splitting decisions in response to load variations. Through comprehensive case studies, the effectiveness of the proposed EMS is evaluated, thereby showcasing its ability to improve system performance, enhance fuel efficiency (potential fuel savings of up to 28%), and support sustainable maritime operations. [Display omitted] • Hybrid PEM fuel cell/battery system enables zero-emission shipping. • Two-layer EMS enhances fuel efficiency while satisfying real-time load requirements. • Rotational sequential distribution prevents uneven degradation. • Rotational sequential distribution enhances computational efficiency. [ABSTRACT FROM AUTHOR]

The All-electric ship (AES) concept has revolutionized the maritime sector. Indeed, AES is a promising solution for modern vessels where decreasing emission pollution, suppressing fossil fuel consumption, and making economical operation are its brilliant merits. Fuel cell (FC) technology based on clean hydrogen energy sources can play a significant role in meeting these requirements in the AES platform. Because of the slow transient response of the FC, an energy storage system (ESS) is required to improve AES performance in different operation scenarios. Therefore, optimal sizing of the FC and the ESS and proper design of energy management strategy is a challenging problem. This paper proposes a systematic approach for the optimal design of hybrid FC-ESS of AES power systems. The proposed method is based on an optimization technique to determine the optimal sizing of the FCs and the ESS. Capital investment, fuel consumption, personnel electrical safety, and occupied volume of the AES power system are the main objectives. The FC size, the battery size, the scheduled output power of the FC, and the battery are the decision variables. Genetic Algorithm (GA) is used to solve the optimization problem. To validate the numerical results, the optimization problem is also solved by Mayfly Algorithm (MA) separately. To assess the feasibility of the proposed strategy, the optimal design of hybrid FC-ESS for a vessel is implemented based on the proposed method. The simulation results validate the proposed approach's sufficiency to investigate and optimize the economic, safety, and dimensional aspects of designing the FC ship's IPS. Numerical results are reported for each design aspect. Considering the minor differences of the numerical results obtained by GA and MA, the optimum points are validated by the two techniques. Using the obtained results, various perceptions can be derived from the FC ship's IPS design. For example, the IPS cost in the cases with optimum volume, weight, and safety, has 2.3%, 2.6%, and 7.3% penalties, respectively compared to the case with the minimum cost. • Fuel cell-based electrification of a fishing ship based on practical information. • Systematic approach for optimal power system design of hydrogen-powered ship. • Proposing safety objective function for integrated power system of fuel cell ship. • Fuel cell hybrid IPS optimization based on volume, mass, cost and safety. • Estimation of propulsion power demand based on ship's resistance and speed profile. [ABSTRACT FROM AUTHOR]