417 results about "Hydrogen consumption" patented technology

The invention discloses a power distribution method and system based on fuel cell multi-stack health state difference, and belongs to the technical field of fuel cell application. The specific method comprises the following steps: monitoring operation parameters of a plurality of fuel cell stacks through a sensor; obtaining the health state of each fuel cell stack and the health state of the lithium battery; establishing a hydrogen consumption model, a fuel cell SOH loss model, a multi-stack SOH difference equivalent loss model, a lithium battery SOH loss model and a lithium battery start and end SOC loss model; the calculation loss is converted into equivalent hydrogen loss, and a target function model is constructed; and optimizing the target function by using a reinforcement learning algorithm, distributing power output of the fuel cell and the lithium battery according to the current required power and the health state through an energy management system, and regularly updating parameters of a parameter identification module and a model to realize dynamic optimization. The method can identify the life difference between multiple piles, balance the life difference to realize multi-pile performance balance and improve the overall life of a multi-pile system.

The invention discloses a hydrogen fuel cell hybrid electric vehicle energy management method based on robust optimization, and the method comprises the following steps: building a vehicle model: building a longitudinal dynamic model of a hydrogen fuel cell hybrid electric vehicle, determining a vehicle demand power model, and building an evaluation function of instantaneous hydrogen consumption, constructing an output power model of the hydrogen fuel cell and the capacitor; performing uncertainty analysis on the hydrogen fuel cell hybrid electric vehicle, determining uncertain parameters in the vehicle model, and constructing an uncertainty set of the uncertain parameters; the method comprises the following steps: constructing an sLSTM vehicle speed prediction model through vehicle historical speed data, predicting a future driving speed, analyzing the uncertainty of the prediction model, and outputting a prediction speed error in a current prediction time domain; and according to the optimization target, constructing a target function for minimizing the hydrogen consumption, solving the target function by applying a robust optimization algorithm, and outputting a first control result of the optimal control sequence.

The invention discloses a hydrogen fuel cell unmanned aerial vehicle energy management and trajectory tracking cooperative control method, and belongs to the field of hydrogen fuel cell long-endurance unmanned aerial vehicle energy management and trajectory tracking control. According to the method, the influence of external disturbance and model uncertainty is studied, fixed time control and active disturbance rejection control principles are introduced, a double-closed-loop unmanned aerial vehicle trajectory tracking method based on fixed time active disturbance rejection control is designed, and effective unmanned aerial vehicle working condition demand information and power control output in a time domain are obtained; based on demand information generated by trajectory tracking control, factors such as hydrogen fuel cell temperature difference, lithium battery SoC maintenance, hydrogen fuel consumption and energy source service life are comprehensively considered, a life attenuation cost function and an energy consumption cost function based on minimum equivalent fuel consumption are established, and an intelligent energy management cooperative control method fusing trajectory tracking control is designed. Hydrogen consumption is reduced, and the cruising ability of the whole machine is improved.

The invention discloses a fuel cell hybrid train energy dispatching method and system. The method comprises the steps that S1, a hydrogen fuel hybrid train power system model is constructed; s2, acquiring required power in a train running process, and decomposing the required power into a low-frequency component and a high-frequency component by using a low-pass filter with adjustable cut-off frequency; constructing a double-layer reinforcement learning agent, and performing real-time dynamic optimization adjustment by taking the cut-off frequency of the low-pass filter as an action variable of the reinforcement learning agent; s3, designing a multi-objective reward function and a system total cost function, and synchronously optimizing fuel cell efficiency, fuel cell power fluctuation, hydrogen consumption and lithium battery SOC to approach initial values; and updating double-layer reinforcement learning agent network parameters through a depth deterministic strategy gradient algorithm, and finally outputting a real-time power distribution instruction of the fuel cell and the lithium battery. The method has the advantages of reducing the fluctuation of the output power of the hydrogen fuel cell, reducing the hydrogen consumption and the like.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

The invention discloses a method for calculating the real-time hydrogen storage amount and the remaining endurance mileage of a fuel cell vehicle, and belongs to the solid hydrogen storage amount measurement technology of a fuel cell. The method comprises the following steps: firstly, carrying out calibration and cycle test analysis on a hydrogen storage material, including establishing relationships between hydrogen storage capacity, temperature and pressure in a full life cycle of a fuel cell stack; the initial hydrogen storage amount is obtained when the vehicle is started, and the obtaining mode comprises the steps that the temperature of the hydrogen storage device and pressure sensor data are read based on the FCU to convert and calculate the initial hydrogen storage amount; when the vehicle runs, the hydrogen consumption amount of the fuel cell stack and the remaining hydrogen storage amount in the hydrogen storage device are calculated in real time, the remaining endurance mileage is calculated in real time on the basis of the remaining hydrogen storage amount, and calculation includes calculation based on the driving mileage within the time t1 to t2 and the hydrogen consumption amount. The method can overcome the defect that in the prior art, the error of estimating the hydrogen storage amount based on thermodynamics in the vehicle running process is too large, the estimation precision of the real-time hydrogen storage amount in the hydrogen storage device is improved, application of hydrogen energy to new energy vehicles, ships and aircrafts can be promoted, and precise prediction of endurance is improved.

The invention provides a fuel cell vehicle energy-heat cooperative control method considering thermal characteristics of a power system, and solves the problem that energy and heat management at low temperature is difficult to collaboratively optimize. According to the method, an energy-heat collaborative global dynamic planning model is established through a long-time-domain average vehicle speed, and the optimal reference trajectory of the SOC and the fuel cell temperature is solved off line by integrating the preheating energy consumption of a power cell and the temperature coupling effect of the fuel cell. And in a short time domain, an LSSVM and BPNN fusion algorithm is adopted to predict the vehicle speed, real-time rolling optimization is performed on the SOC and the fuel cell temperature in combination with a nonlinear MPC strategy, and a global optimal track is tracked. According to the method, on the premise of meeting the temperature requirements of the cabin and the battery, the lowest hydrogen consumption of the whole vehicle and the optimal power system efficiency are achieved, and the energy utilization rate and the cruising ability under the severe cold working condition are improved.

The invention provides an energy management method and device of an unmanned aerial vehicle, which can be used for the unmanned aerial vehicle capable of autonomous flight and can significantly improve the energy utilization efficiency of the unmanned aerial vehicle capable of autonomous flight, and the unmanned aerial vehicle can perform autonomous flight. The unmanned aerial vehicle flight power demand table comprises load powers required by the unmanned aerial vehicle for executing different flight actions at various speeds of the unmanned aerial vehicle; according to the flight task, performing flight path planning; according to the optimal flight path obtained by planning, querying an unmanned aerial vehicle flight power demand table, obtaining load power required by different flight stages in the flight path, and further obtaining global load power change of the unmanned aerial vehicle completing a flight task; a global load power change is derived based on the path planning, and the fuel cells and the power output of the cells are optimized to meet load power consumption and minimize hydrogen consumption of the fuel cells.

The invention discloses a real-time SLMP fuel cell hybrid electric vehicle energy management method. The method comprises the following steps: firstly, collecting vehicle operation data in real time, constructing an operation state vector containing kinetic parameters, and initializing a state transition matrix as agent action input; on the basis, the speed and the acceleration are predicted through a self-learning Markov predictor, and dynamic self-adaptive power distribution of the fuel cell and the power cell is achieved in combination with a multi-objective optimization function and power distribution constraints. The method passes hardware-in-the-loop (HIL) verification, aims at reducing hydrogen consumption and improving efficiency, and exits if two times of circulation are not passed. Compared with a traditional method based on rules or static optimization, the method innovatively embeds a self-learning mechanism, has the advantages of being high in adaptability, high in prediction precision and good in generalization performance, and is suitable for energy management optimization under complex working conditions.

According to the hydrogen fuel heavy truck energy management method provided by the invention, according to the current electric quantity of a power battery, the optimization objectives of reducing or maintaining the temperature of a battery cell group of the power battery and reducing the hydrogen consumption of a fuel battery system are taken; according to the minimum value of the power system boundary power, the power battery boundary power, the fuel cell system boundary power and the management strategy boundary power as the fuel cell system target power in the current state, the output power of the fuel cell system is adjusted within the minimum variable power time allowed by the fuel cell system; and the endurance of the whole vehicle is prolonged while the dynamic property is considered.

The invention relates to the technical field of renewable energy consumption, in particular to a vehicle-hydrogen-steel collaborative green hydrogen fluctuation stabilizing method and system, a physical layer is provided with a wind-solar power generation device, an electrolytic hydrogen production device, a hydrogen storage buffer tank, a steel heat supply device, an electric vehicle and a V2G charging pile which are connected with one another through a hydrogen conveying pipeline and a power cable; the information layer takes the central regulation and control platform as a core, collects wind-solar power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC by using sensors, and transmits the collected power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC to the central regulation and control platform; the central regulation and control platform executes a hierarchical dynamic fluctuation regulation and control mechanism; when the fluctuation range of the hydrogen yield does not exceed a set value, the hydrogen is stabilized by controlling the hydrogen storage buffer tank to charge and discharge hydrogen; and when the fluctuation amplitude exceeds a set value, a V2G system is started, and stabilizing is carried out by controlling charging and discharging of the electric vehicle. On the premise that the special energy storage cost is not greatly increased, stable and low-cost supply of green hydrogen is achieved, and energy conservation and emission reduction of steel and other high-energy-consumption industries are achieved.

The invention provides a bacteriostatic proppant technology based on a palladium oxide-reduced graphene oxide composite material, aiming at the problem of hydrogen loss caused by microbial activity in a hydrogen storage bank of an exhausted gas reservoir. A PdO (at) rGO composite material functionally modified by lead ions (Pb < 2 + >) is loaded on the surface of a porous ceramsite carrier to form an adsorption-inactivation-blocking synergistic antibacterial network; precise laying of the proppant in a crack network is achieved through the end sand removal technology, hydrogen consumption is reduced, and an efficient, economical and environment-compatible innovative solution is provided for biological pollution control of the underground hydrogen storage library.

The invention discloses a fuzzy control-based multi-stack fuel cell energy management method and a fuzzy control-based multi-stack fuel cell energy management system. The method comprises the following steps of constructing an energy system comprising a multi-stack fuel cell and a lithium battery; constructing a fuzzy logic controller by taking the required power of the energy system and the charge state of the lithium battery as input variables and taking the output power of the multi-stack fuel battery as an output variable; establishing a hydrogen consumption function of the energy system according to the relationship between the output power of the multi-stack fuel cells and the lithium batteries and the hydrogen consumption, and establishing an optimization function by taking the value of the minimum hydrogen consumption function as a target; and solving the optimization function to obtain an optimal parameter of the fuzzy logic controller, and controlling the output power of the multi-stack fuel cell according to the optimal parameter. According to the method, the energy consumption of the fuel cell is optimized, the use of hydrogen fuel is reduced, and the energy utilization efficiency of the system is improved.

The invention discloses a power control method of a hybrid power system, the hybrid power system comprises a hydrogen fuel cell and a power cell, and the method comprises the following steps: establishing a hydrogen fuel cell model, a power cell model and a load model; monitoring the SOC of a power battery, the opening degree of an accelerator pedal and the real-time rotating speed of a motor in real time; based on an intelligent control algorithm, with the hydrogen consumption, the hydrogen fuel cell output power variation and the power cell SOC as optimization targets, designing a target function and formulating constraint conditions; performing smooth filtering processing on the optimal control sequence solved based on the intelligent control algorithm; if the current working mode is in a hybrid mode, real-time acquisition and optimization are repeated in each control period, and otherwise, power control is performed according to a pure electric mode; and applying the solved control sequence to the hybrid power system. While power dynamic response is guaranteed, the hydrogen consumption is effectively reduced, and the problem of frequent load changing of a hydrogen fuel system is solved.

The invention discloses a reverse shift catalyst capable of inhibiting methanation side reaction under the process condition of higher pressure and a preparation method of the reverse shift catalyst, the catalyst comprises the following effective component: iron accounting for 40-80% (weight percentage) of the total amount of the catalyst in terms of Fe2O3, an auxiliary agent for inhibiting methanation side reaction is added, and the preparation method of the catalyst is a mixing and kneading method. According to the present invention, the auxiliary agent for inhibiting the methanation side reaction is added under the reverse transformation process condition, such that the methane generation amount of the catalyst under the reverse transformation high pressure process condition is significantly reduced, the selectivity of the CO2 reverse transformation reaction is improved, the hydrogen consumption is reduced, and the new requirement of the national green dual-carbon development is met.

The invention provides a fuel cell vehicle hydrogen consumption life optimization management method and system, relates to the technical field of vehicle control and energy management of fuel cell vehicles, and aims to solve the problem that in the prior art, a fuel cell vehicle is difficult to balance hydrogen consumption economy and life durability at the same time. According to the method, a hydrogen consumption-service life dual-objective optimization model containing a dynamic efficiency coefficient and a catalyst attenuation item is constructed by collecting the whole vehicle working condition, environment and fuel cell stack core state data in real time, an improved NSGA-II algorithm introducing a self-adaptive crossover operator and an elitist retention strategy is adopted for solving, optimization parameters are selected in combination with scene priorities, and the optimal performance of the fuel cell stack is improved. Working condition pre-judgment response is realized through a pre-adjustment unit; the system is composed of a data acquisition module, a model construction module, an algorithm solution module, an optimization decision module and a control execution module, supports model online updating and fault degradation, can consider hydrogen consumption economy, service life durability and dynamic responsiveness, and is suitable for various fuel cell commercial vehicles and passenger vehicles.

The invention discloses a hierarchical energy management method for a multi-stack fuel cell hybrid power system. The method comprises the following steps: acquiring the recession state and real-time maximum efficiency of each fuel cell, each lithium battery and each super capacitor of the system; dividing a fuel cell, a lithium battery and a super capacitor with similar decline degrees and maximum efficiency into a region by using a decoupling feature clustering neural network, so as to divide the whole system into a plurality of regions; a nested deep reinforcement learning controller is constructed according to the instantaneous efficiency of the fuel cell, the equivalent hydrogen consumption of the system, the instantaneous decline rate of each power unit, the SOC of the lithium battery and the super capacitor and the operating temperature of the fuel cell, and optimal energy management of each region is realized; and performing system-level coordination scheduling on energy management results of all regions, and realizing cross-region power balance and boundary condition constraint through a central power coordination module. According to the invention, efficient operation and service life protection of a multi-pile hybrid power system in high-power and high-reliability application scenes such as rail transit vehicles are realized.

The invention discloses a method and a device for adjusting the output power of a fuel cell in a vehicle and the vehicle. The method comprises the following steps: acquiring operation data of a vehicle in an operation process; a self-adaptive parameter set corresponding to the operation condition is determined, and the self-adaptive parameter set comprises a plurality of self-adaptive parameters; based on the self-adaptive parameter set, an objective function is constructed and obtained, the objective function is used for representing the mapping relation between the equivalent hydrogen consumption of the fuel cell and the distribution power, and the distribution power is used for guiding power distribution between the fuel cell and the power cell; according to a target function, mapping the plurality of distribution powers into a plurality of equivalent hydrogen consumptions, and screening out a target distribution power corresponding to the fuel cell from the plurality of distribution powers based on the plurality of equivalent hydrogen consumptions; and determining the output power of the fuel cell according to the target distribution power. The technical problem that the working condition adaptability of the energy management strategy of the battery in the vehicle is poor is solved.

The invention relates to the technical field of catalysts, in particular to a desulfurization catalyst and application thereof in hydrodesulfurization. The desulfurization catalyst adopts a hollow core shell, a weak acid site is constructed on a shell surface, and a boron-containing polymerization network is formed through surface-initiated polymerization; and linear / branched polyethyleneimine complexation is used for synergistically introducing Ni and Mo, in-situ vulcanization is performed after inert atmosphere pretreatment, and a dispersed nickel molybdenum sulfide active phase and shallow and deep double-peak metal distribution are obtained. The structure inhibits excessive hydrogenation while ensuring diffusion and structural stability, promotes a direct desulfurization path, and shows high conversion and high selectivity to 4, 6-dimethyl dibenzothiophene. The catalyst has low hydrogen consumption, high aromatic hydrocarbon retention and cycling stability, and is suitable for deep desulfurization of diesel oil and preparation of ultralow-sulfur fuel.

The invention discloses an NH3-SCR (Selective Catalytic Reduction) catalyst as well as a preparation method and application thereof. The NH3-SCR catalyst is a cerium oxide composite oxide catalyst and contains Ce, M and R elements, and the M element is selected from at least one of Cu, Nb, Fe, Co, Mn, Ni and Zn; the R element is selected from at least one of Ru, Pt, Pd, Rh, Ag and Au; the molar ratio of the Ce element to the M element is (0.5: 1)-(10: 1); based on the total mass of the NH3-SCR catalyst, the loading amount of the R element is 0.1-3 wt%; the NH3-SCR catalyst is in a spherical shape; the cerium oxide exposes a crystal face [111], and the surface active oxygen content accounts for 35-70% of the total surface oxygen content of the NH3-SCR catalyst; the acid content is 7500-9000 [mu] L, the hydrogen consumption is 1500-2500 [mu] L, and the specific surface area is 50-90 m < 2 > / g. The catalyst disclosed by the invention has the advantages that nitrogen oxides are subjected to ammonia selective catalytic reduction at the low temperature of less than or equal to 200 DEG C, the conversion rate of NOx is high, the selectivity of N2 is high, and the generation amount of a byproduct N2O is small.

The invention discloses a multi-objective optimization method for the overall performance of a fuel cell hybrid electric vehicle, and relates to the technical field of overall performance optimization of fuel cell hybrid electric vehicles. According to the method, a support vector regression (SVR) algorithm is utilized under the multi-input multi-output complex nonlinear system condition of the fuel cell hybrid electric vehicle, the correlation between the whole vehicle key parameters and the energy conversion efficiency and the equivalent hydrogen consumption per hundred kilometers of an electric pile system is deeply mined, and an optimal training model is determined to serve as an agent model; and multi-target optimization is carried out by using an NSGA-II algorithm, and each target is accurately weighed, so that the overall performance of the fuel cell hybrid electric vehicle is improved.

A hydrogen supply system includes a detachable hydrogen tank, a hydrogen consumption apparatus that consumes hydrogen in the hydrogen tank, and a control device. The hydrogen consumption apparatus includes a detachment and attachment mechanism that detaches the hydrogen tank from the hydrogen consumption apparatus and attaches the hydrogen tank to the hydrogen consumption apparatus. The detachment and attachment mechanism includes a motor that controls detachment and attachment of the hydrogen tank from and to the hydrogen consumption apparatus. When a torque value of the motor exceeds a threshold during the control of the detachment and attachment of the hydrogen tank from and to the hydrogen consumption apparatus, the control device returns the hydrogen tank to a position where a moving process in which the threshold being exceeded is detected is started.

The invention discloses a data-driven hydrogen-electricity hybrid power energy management method and device, and relates to the technical field of engineering control, and the method comprises the steps: calculating a hydrogen consumption predicted value of a fuel cell at a k + 1 moment by applying a TDL method according to an actual hydrogen consumption value of the fuel cell at the k moment and a historical SOC actual value of a lithium battery, and then calculating an SOC reference value of the lithium battery at the k + 1 moment, constructing an SOC prediction model in the prediction time domain at the moment k by applying a TDL method, and solving a power control increment sequence of the lithium battery in the control time domain at the moment k; and calculating the reference power of the lithium battery at the k moment according to the first item in the power control increment sequence and the reference power of the lithium battery at the k-1 moment, and further calculating the reference power of the fuel battery at the k moment, thereby realizing the control of the actual output power of the lithium battery and the fuel battery at the k moment. According to the invention, the optimal power distribution between the hydrogen fuel cell and the lithium battery can be realized, and the endurance time is prolonged.

The invention provides a fuel cell automobile energy management method fusing a TRANSFORMER algorithm and a TD3 algorithm, and the method comprises the steps: comprehensively considering the energy flow and consumption characteristics in a vehicle system in modeling, and building a multi-objective optimization control frame including battery aging, fuel cell durability constraint, hydrogen consumption and cabin temperature comfort; in addition, future multi-step power demands are predicted by using a TRANSFORMER model and a TD3 algorithm, the consideration of future driving conditions is realized, an optimal action is generated according to the real-time state of the vehicle on the basis, prediction errors can be effectively reduced, the adaptability of an energy management strategy can be improved, and the energy management efficiency is improved. And the method has important practical significance on optimal balance of driving performance, system durability and hydrogen consumption of a real vehicle.

This invention relates to the field of petroleum refining and chemical engineering, and discloses a method for hydrogenating waste tire pyrolysis oil. The method includes the following steps: (1) in the presence of hydrogen, the waste tire pyrolysis oil raw material undergoes a gas-phase desulfurization reaction in a first gas-phase hydrogenation reactor to obtain a gas-phase desulfurization reaction product; (2) the gas-phase desulfurization reaction product is subjected to gas-liquid separation to obtain a gas-phase component and a liquid-phase component; (3) the liquid-phase component is pressurized and mixed with hydrogen, and then subjected to a liquid-phase dearomatics reaction in a second hydrogenation reactor to obtain a liquid-phase dearomatics reaction product; the nitrogen content in the waste tire pyrolysis oil raw material is 3000-10000 μg / g. This method uses waste tire pyrolysis oil from the middle distillate as raw material, achieving deep desulfurization while reducing the removal of nitrogen oxides and monocyclic aromatic hydrocarbon saturation. It also simplifies the overall process flow, reduces the reaction severity, and lowers energy and hydrogen consumption.

The invention provides a fuel cell vehicle energy management method, which comprises the following steps of: analyzing a fuel cell and a power cell to obtain fuel cell efficiency, power cell efficiency, fuel cell recession condition, power cell recession condition and power cell # imgabs0 #, and further calculating equivalent hydrogen consumption; inputting the power battery # imgabs1 # and the required power of the whole vehicle into a fuzzy controller for data processing to obtain the output power of the fuel cell; and carrying out evaluation management on the service life and energy consumption balance of the fuel cell and the power cell by taking the equivalent hydrogen consumption, the decline degree of the fuel cell and the decline degree of the power cell as energy management strategy evaluation indexes. By increasing the power variation limit value of the fuel cell, the actual variable load capacity of the fuel cell system is closer, and the influence of the power fluctuation of the fuel cell on the service life is reduced; and when the SOC of the fuel cell is very small, the fuel cell can operate at the minimum power instead of being directly shut down, so that the start-stop times of the fuel cell system can be reduced, and the service life of the fuel cell is prolonged.

The invention discloses a hydrogen fuel cell optimization algorithm based on particle swarm optimization of an integrated system, and belongs to the technical field of micro-grid energy management. An existing hydrogen fuel cell has the problems of low fuel utilization rate, slow response speed and the like under a dynamic load condition. In order to solve the problem, a hybrid energy system topology consisting of a photovoltaic (PV), a proton exchange membrane fuel cell (PEMFC), a lithium ion battery (BAT) and a super capacitor (SC) is constructed, and mathematical models, including a photovoltaic output power model, a fuel cell voltage model and a cell state-of-charge model, of all energy units are established. A PI controller is designed for a fuel cell, and a proportional gain KP and an integral gain KI of the fuel cell are dynamically adjusted through a particle swarm optimization (PSO) algorithm. Specifically, PI parameters are coded into particle position vectors, a multi-target fitness function is constructed, and hydrogen consumption, system stability and oxygen utilization rate are comprehensively considered; and a dynamically adjusted inertia weight mechanism is adopted to guide particle search, and iterative optimization is realized. After optimization, parameters are written into a PI controller in real time, and the hydrogen and air flow is accurately adjusted. Meanwhile, a continuous monitoring mechanism is introduced, when the photovoltaic power fluctuation exceeds 10%, re-optimization is automatically triggered, and closed-loop control is formed. The method improves the fuel utilization rate and the reaction rate of the fuel cell, is suitable for the dynamic load micro-grid, and improves the overall efficiency and stability of the system.

The application discloses a biomass-based nitrogen-doped carbon-carbide molybdenum composite catalyst and a preparation method and application thereof, and is characterized in that: a widely-sourced biomass, especially agricultural biomass waste, is used as a carbon and nitrogen source, ammonium molybdate is used as a molybdenum source, and a nitrogen-doped carbon-carbide molybdenum composite catalyst is prepared through one-step pyrolysis under an ammonia atmosphere; the catalyst is mesoporous nitrogen-doped carbon loaded with pure beta-phase carbide molybdenum, has the characteristics of a large pore size, high dispersion of beta-phase carbide molybdenum and the like, and has good thermal stability; the catalyst can efficiently denitrogenate quinoline and directively convert the quinoline, and high-selectivity aromatic hydrocarbon products can be obtained; the conversion rate is not less than 99%, the denitrogenation rate is not less than 99%, the selectivity of aromatic compounds is not less than 86%, and the catalyst has the characteristics of low hydrogen consumption due to the avoidance of hydrogen saturation reaction.

The invention provides a hydrogen consumption calculation method and device of a vehicle, the vehicle and a storage medium. The method comprises the steps that the consumed electric quantity of a power battery, the comprehensive thermal efficiency of a fuel cell, the actual load of the current vehicle, parking charging energy consumption and driving condition data are obtained; obtaining first hydrogen consumption according to the consumed electric quantity, the comprehensive thermal efficiency of the fuel cell and a preset hydrogen heat value, inputting the actual load into a preset hydrogen consumption model to obtain second hydrogen consumption, obtaining third hydrogen consumption according to the parking charging energy consumption, and obtaining fourth hydrogen consumption according to the driving condition data; and inputting the first hydrogen consumption, the second hydrogen consumption, the third hydrogen consumption and the fourth hydrogen consumption into a total hydrogen consumption model to determine the hydrogen consumption of the current vehicle. According to the method, the problem that hydrogen consumption obtained in related technologies is inaccurate is solved, multiple factors such as the battery electric quantity and the vehicle load are comprehensively considered, and the accuracy and applicability of a hydrogen consumption prediction result are improved.

A hydrogen distribution system for supplying hydrogen to a hydrogen consumer comprising: a tank storing a liquid hydrogen fuel; a conditioning system configured to provide a gaseous hydrogen stream downstream from the tank towards the hydrogen consumer; a compressor downstream of the conditioning system and configured to receive the gaseous hydrogen stream and provide a high-pressure gaseous hydrogen stream; a heater downstream of the compressor and configured to receive the high-pressure gaseous hydrogen stream and provide a high-temperature, high-pressure gaseous hydrogen stream; and, a valve downstream of the heater and configured to adjust a flow of the high-temperature, high-pressure gaseous hydrogen stream; wherein the hydrogen consumer is downstream of the valve and configured to receive the high-temperature, high-pressure gaseous hydrogen stream and provide energy by consuming hydrogen from the high-temperature, high-pressure gaseous hydrogen stream. Also, an aircraft with such a system.