China, People’s Republic

This paper investigates the temperature control problem in hydrogen fuel cells based on the improved sliding mode control method specifically within the context of multirotor drone applications. The study focuses on constructing a control-oriented nonlinear thermal model which serves as a foundation for the subsequent development of a practical temperature regulation approach. Initially a novel sliding mode control strategy is proposed which significantly enhances the precision and stability of temperature control by reducing the impact of sensor errors and environmental disturbances. Subsequently the effectiveness and robustness of this control method under various dynamic loads and environmental conditions are demonstrated. The simulation results demonstrate that the improved sliding mode controller is effective in managing and regulating the fuel cell temperature ensuring optimal performance and stability.

To achieve deep decarbonization in the transportation sector this study employs life cycle assessment (LCA) and the GREET model to construct baseline and low-carbon scenarios. It simulates the evolution of emissions and energy consumption within Inner Mongolia’s public transportation energy system (including diesel buses (DBs) electric buses (EBs) and hydrogen fuel cell buses (HFCBs)) from 2022 to 2035 while exploring synergistic pathways for its low-carbon transition. Results reveal that under the baseline scenario reliance on industrial by-product hydrogen causes fuel cell bus emissions to increase by 3.64% in 2025 compared to 2022 with system energy savings below 10% and decarbonization potential will be constrained by scale limitations and storage/transportation losses in cold regions. Under the low-carbon scenario deep grid decarbonization vehicle structure optimization and green hydrogen integration reduced system emissions and energy consumption by 66.86% and 40.44% respectively compared to 2022. The study identifies a 15% green hydrogen penetration rate as the critical threshold for resource misallocation and confirms grid decarbonization as the top-priority policy tool yielding marginal benefits 1.43 times greater than standalone hydrogen policies. This study underscores the importance of multipolicy coordination and ‘technology-supply chain’ synergy particularly highlighting the critical threshold of green hydrogen penetration and the primacy of grid decarbonization offering insights for similar coal-dominated cold-region transportation energy transitions.

In rotating machinery unbalanced mass is one of the most common causes of system vibration. This paper presents an experimental investigation of the unbalance response of a gas foil bearing-rotor system based on a 30 kW-rated commercial hydrogen fuel cell vehicle air compressor. The study examines the response of the system to varying unbalanced masses at different rotational speeds. Experimental results show that after adding unbalanced mass subsynchronous vibration of the rotor is relatively slight while synchronous vibration is the main source of vibration; when unbalanced mass is added to one side of the rotor the synchronous vibration on that side initially decreases and then increases with speed while synchronous vibration on the opposite side continuously increases with speed; when unbalanced mass is added to both sides the synchronous vibration on each side increases with the phase difference of the unbalanced mass at low speed while the opposite trend occurs at high speed. The analysis of the gas foil bearingrotor system dynamics model established based on the dynamic coefficient of the bearing shows that the bending of the rotor offsets the displacement caused by the unbalanced mass which is the primary reason for the nonlinear behavior of the synchronous vibration of the rotor. These findings contribute to an improved understanding of GFB-rotor interactions under unbalanced conditions and provide practical guidance for optimizing dynamic balancing strategies in hydrogen fuel cell vehicle compressors.

As an efficient and low-carbon renewable energy source hydrogen plays a strategic role in the global energy transition particularly in the transportation sector. However the flammable and explosive nature of hydrogen makes leakage risks in enclosed environments a core challenge for the safe promotion of hydrogen fuel cell vehicles. Catalytic combustion sensors are ideal choices due to their high sensitivity and long lifespan. Nevertheless they face technical bottlenecks under vehicle operational conditions such as high-power consumption caused by elevated working temperatures slow response rates weak anti-interference capabilities and catalyst poisoning. This paper systematically reviews the research status of catalytic combustion hydrogen sensors for vehicle applications summarizes technical difficulties and development strategies from the perspectives of hydrogen-sensitive material design and integration processes and provides theoretical references and technical guidance for the development of catalytic combustion hydrogen sensors suitable for vehicle use.

Hydrogen production by seawater electrolysis is significantly hindered by high energy costs and undesirable detrimental chlorine chemistry in seawater. In this work energy-saving hydrogen production is reported by chlorine-free seawater splitting coupling tip-enhanced electric field promoted electrocatalytic sulfion oxidation reaction. We present a bifunctional needle-like Co3S4 catalyst grown on nickel foam with a unique tip structure that enhances the kinetic rate by improving the current density in the tip region. The assembled hybrid seawater electrolyzer combines thermodynamically favorable sulfion oxidation and cathodic seawater reduction can enable sustainable hydrogen production at a current density of 100 mA cm−2 for up to 504 h. The hybrid seawater electrolyzer has the potential for scale-up industrial implementation of hydrogen production by seawater electrolysis which is promising to achieve high economic efficiency and environmental remediation.

To improve the energy utilization rate and realize the low-carbon emission of a park integrated energy system (PIES) this paper proposes an optimal operation strategy for multiple PIESs. Firstly the electrical power cooperative trading framework of multiple PIESs is constructed. Secondly the hydrogen blending mechanism and carbon capture system and power-to-gas system joint operation model are introduced to establish the model of each PIES. Then based on the Nash bargaining game theory a multi-PIES cooperative trading and operation model with electrical power cooperative trading is constructed. Then the alternating direction method of multipliers algorithm is used to solve the two subproblems. Finally case studies analysis based on scene analysis is performed. The results show that the cooperative operation model reduces the total cost of a PIES more effectively compared with independent operation. Meanwhile the efficient utilization and production of hydrogen are the keys to achieve carbon reduction and an efficiency increase in a PIES.

In order to improve energy utilization efficiency and the flexibility of resource transfer in oceanic-island-group microgrids a water–electricity–hydrogen flexible scheduling strategy based on a multi-rate hydrogen-powered ship is proposed. First the characteristics of the seawater desalination unit (SDU) proton exchange membrane electrolyzer (PEMEL) and battery system (BS) in consuming surplus renewable energy on resource islands are analyzed. The variable-efficiency operation characteristics of the SDU and PEMEL are established and the effect of battery life loss is also taken into account. Second a spatiotemporal model for the multi-rate hydrogen-powered ship is proposed to incorporate speed adjustment into the system optimization framework for flexible resource transfer among islands. Finally with the goal of minimizing the total cost of the system a flexible water–electricity–hydrogen hybrid resource transfer model is constructed and a certain island group in the South China Sea is used as an example for simulation and analysis. The results show that the proposed scheduling strategy can effectively reduce energy loss promote renewable energy absorption and improve the flexibility of resource transfer.

The electric–hydrogen coupled integrated energy system (EHCS) is a critical pathway for the low-carbon transition of energy systems. However the inherent uncertainties of renewable energy sources present significant challenges to optimal energy management in the EHCS. To address these challenges this paper proposes an energy management method for the EHCS based on an improved proximal policy optimization (IPPO) algorithm. This method aims to overcome the limitations of traditional heuristic algorithms such as low solution accuracy and the inefficiencies of mathematical programming methods. First a mathematical model for the EHCS is established. Then by introducing the Markov decision process (MDP) this mathematical model is transformed into a deep reinforcement learning framework. On this basis the state space and action space of the system are defined and a reward function is designed to guide the agent to learn to the optimal strategy which takes into account the constraints of the system. Finally the efficacy and economic viability of the proposed method are validated through numerical simulation.

With the advancement of Fuel Cell Vehicles (FCVs) detecting hydrogen leaks is critically important in facilities such as hydrogen refilling stations. Despite its significance the dynamic response performance of hydrogen sensors in confined spaces particularly under ceilings has not been comprehensively assessed. This study utilizes a catalytic combustion hydrogen sensor to monitor hydrogen leaks in a confined area. It examines the effects of leak size and placement height on the distribution of hydrogen concentrations beneath the ceiling. Results indicate that hydrogen concentration rapidly decreases within a 0.5–1.0 m range below the ceiling and declines more gradually from 1.0 to 2.0 m. The study further explores the attenuation pattern of hydrogen concentration radially from the hydrogen jet under the ceiling. By normalizing the radius and concentration it was determined that the distribution conforms to a Gaussian model akin to that observed in open space jet flows. Utilizing this Gaussian assumption the model is refined by incorporating an impact reflux term thereby enhancing the accuracy of the predictive formula.

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances technical challenges research hotspots and future development directions of ejector applications in rail transit aiming to address gaps in existing reviews. (1) In waste heat recovery exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems the throttle valve is replaced with an ejector leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions scarcity of application data for global warming potential refrigerants insufficient stability of hydrogen recycling under wide power output ranges and thermodynamic irreversibility causing turbulence loss. To address these issues future efforts should focus on developing dynamic intelligent control technology based on machine learning designing adjustable nozzles and other structural innovations optimizing multi-system efficiency through hybrid architectures and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency thereby supporting the green transformation and energy conservation objectives of rail transit.