16613 results about "Fuel cells" patented technology

A fuel cell fault diagnosis method based on a neural network. The method comprises: for a PEMFC system, acquiring operating state data, wherein the PEMFC system comprises a humidifier and a fuel cell stack; inputting the operating state data into a trained fault pre-diagnosis model, so as to predict a fault diagnosis result of the fuel cell stack at a subsequent moment. The fault pre-diagnosis model is constructed on the basis of a Transformer neural network, and comprises an encoder and a decoder, wherein the encoder comprises a plurality of small encoders, and each small encoder is provided with a self-attention layer and a feedforward neural network layer; and the decoder comprises a plurality of small decoders, and each small decoder comprises a self-attention layer, an attention layer and a feedforward neural network layer. An early warning can be provided for a water management fault of a PEMFC in an operating state, and the accuracy of pre-diagnosis is effectively improved.

Improved performance ion exchange membranes for use in REM, AEM and DMFC fuel cells, buffered fuel cells, hydrolysis, other applications comprise a molecular matrix of homopolymers, di-monomer, heteropolymers, copolymers, or block-polymers of fluorocarbon and hydrocarbon compounds combined with (i) skeletal support grid to improve durability, handling, reduce membrane swelling, and sequester dopants and nanoparticles from leakage; (ii) microporous membrane formed using a sacrificial filler process enhancing conductivity and limiting fuel crossover; (iii) hetero-ionomeric matrix of two-or-more membrane-bound acids e.g. sulphonic and phosphonic acid expanding usable range; (iv) permanent fillers enhancing conductivity and porosity including nanoparticles, metal-oxides, zeolites, silicates, GOs, CNTs, MOFs, POSS, and others; (v) ionic liquid doping to enhance membrane conductivity; (vi) membrane nanocoating preventing H2O2 diffusion; and / or (vii) catalytic nanocoating with metals, metal-oxides, and MOFs preventing atmospheric toxin catalyst poisoning. Combined with a heterogenous GDI, the IEM is integrated into iBFC power blade and energy bank applications.

The invention discloses a pipe network health real-time monitoring system and an evaluation method. According to the invention, through real-time health monitoring and dynamic deduction capability, the flexibility and safety of energy supply are significantly improved. The healthy twin module constructs a digital mirror image of the full life cycle of energy equipment, solar hydrogen production efficiency fluctuation, hydrogen storage tank pressure change and fuel cell attenuation trend can be accurately tracked, and risk points such as electrolytic cell abnormal hydrogen evolution and proton exchange membrane aging can be recognized in advance. The all-weather transparent monitoring enables the system to dynamically adjust the ratio of hydrogen production to power generation, the fuel cell is automatically switched to supply power in cloudy and rainy days, continuous energy supply is guaranteed, and the system can generate a coping plan in advance by simulating extreme scenes such as sudden drop of photovoltaic output and hydrogen leakage, so that the system is convenient to use. The energy interruption risk caused by sudden equipment failure is greatly reduced, meanwhile, the service life of key components is prolonged, the maintenance cost of a distributed energy network is reduced, and meanwhile the overall energy efficiency utilization rate is also improved.

The invention discloses a DC bus voltage fluctuation suppression method of a renewable energy hydrogen production system, and relates to the technical field of renewable energy electrolysis hydrogen production. The method comprises the following steps: collecting system operation parameters in real time; bus voltage disturbance power is estimated based on a disturbance observer, and frequency decomposition is carried out; fusing the ARIMA model and the LSTM model to predict the load power, and calculating a prediction deviation; dynamically setting upper and lower limits of a bus voltage control interval according to the predicted deviation and the operation state; a multi-objective optimization function is constructed, bus voltage disturbance power, prediction deviation and a control limit value are comprehensively considered, and power regulation instructions of battery energy storage, a fuel cell and an electrolytic cell are solved; and executing power regulation control to realize bus voltage stabilization. The method can improve the grading response capability of voltage disturbance, the prediction accuracy of load power change, the adaptability of the control boundary and the overall operation stability of the system, and is suitable for the electric energy quality control of the hydrogen production system in a multi-source fluctuation scene.

The present invention describes an electric-thermal-hydrogen multi-energy device planning method for zero energy buildings, including the following specific steps: firstly, constructing operation constraints of electric and thermal devices in the zero energy buildings; secondly, constructing operation constraints of hydrogen devices including the electrolyzer, the fuel cell and the hydrogen storage device; then, in view of constraints on annual zero energy of the buildings, establishing the robust electric-thermal-hydrogen multi-energy device planning model considering source-load uncertainties; and finally, solving the robust electric-thermal-hydrogen multi-energy device planning model of the zero energy buildings by adopting an alternating optimization procedure based column-and-constraint generation algorithm. By using the zero energy buildings, the planning method disclosed by the present disclosure plays important roles in aspects of promoting the development and utilization of renewable energy on the demand side, reducing energy consumption in the field of buildings, and reducing the emission of greenhouse gases.

The invention discloses a fuel cell hydrogen circulation cooling integrated system, and relates to the technical field of fuel cells, the fuel cell hydrogen circulation cooling integrated system comprises a hydrogen circulation cooling management center, the hydrogen circulation cooling management center is in communication connection with the following modules: a multi-source state sensing module, which is used for collecting multi-dimensional state data of a hydrogen circulation-cooling system in real time, extracting state characteristics, and sending the state characteristics to a control module; and forming a state feature sequence table. The multi-dimensional state data of the hydrogen circulation-cooling system is collected, the dynamic cooperative control strategy of the reinforcement learning decision module is combined, the precision and stability of temperature control are remarkably improved, the Markov decision process model is used for predicting the instantaneous heat production change caused by load sudden change, and the stability of the system is improved. And through combined adjustment of hydrogen circulation and a cooling system, temperature fluctuation is rapidly restrained, compared with traditional PID control, the temperature overshoot is reduced under the dynamic working condition, it is ensured that the galvanic pile works within the optimal temperature range all the time, the service life of the galvanic pile is prolonged, and the energy conversion efficiency is improved.

A blower (1) for a fuel cell assembly for recirculating a gas mixture used for operating the fuel cell assembly is equipped with a drive motor (7, 8, 9) comprising a rotor (9) coupled to a motor shaft (7) and a stator (8) arranged radially outside the rotor (9). An annular channel (10) is provided radially between the rotor (9) and the stator (8) for conveying the gas mixture from an inlet side to an outlet side of the annular channel (10). A blower impeller (5) coupled to the motor shaft (7) is provided in the region of the outlet side of the annular channel (10) to convey the gas mixture from the inlet side to the outlet side of the annular channel (10) when rotating. Furthermore, a flow guide device (14) is provided to impart a circumferential swirl to the gas mixture entering the annular channel (10).The annular channel (10) is bounded by an assembly consisting of an outer wall (16; 21) and an inner wall (17), wherein the flow guide device (14) is provided on the inlet side between the outer wall (16; 21) and the inner wall (17).

The invention relates to the technical field of new energy vehicles, in particular to a multi-working-condition energy management method and system for a hybrid chariot, and the method comprises the steps: determining a corresponding working condition weight coefficient through obtaining the altitude, environment temperature and road condition data in real time, and the real-time working parameters of three power sources, namely an engine, a fuel cell and a lithium battery, so as to achieve the multi-working-condition energy management of the hybrid chariot; the system constructs a multi-objective optimization model based on the data to realize comprehensive fuel consumption minimization, lithium battery SOC balance and lithium battery life protection, and the model comprises establishment of a power source efficiency parameter mapping relation, determination of a corresponding relation between lithium battery power and cycle life, and construction of a membership function of an optimization objective. By adopting a method of combining Pareto local optimization and fuzzy evaluation, the optimal power distribution proportion among the engine, the fuel cell and the lithium battery is calculated, the overall efficiency of the hybrid chariot is effectively improved, and the service life of the hybrid chariot is effectively prolonged.

A propulsion system for an aircraft as disclosed herein may include a nacelle, a shaft positioned centrally within a cylindrical passageway of the nacelle, a fan coupled to one end of the shaft, a turbine coupled to an opposite end of the shaft, an electric motor coupled to the shaft, a compressor positioned within the cylindrical passageway, and a solid oxide fuel cell positioned with a hollow ring-shaped interior of the nacelle. The hollow ring-shaped interior may surround and be isolated from the cylindrical passageway. The turbine may be configured to provide primary torque to the shaft while the electric motor may be configured to provide additional torque to the shaft. The electric motor may be powered an electric output of the solid oxide fuel cell while the turbine may be powered at least in part by output gases from the solid oxide fuel cell.

Provided is a fuel cell aging prediction method, a system thereof and a medium. The method includes the following steps: acquiring operation parameters and calculation parameters of a fuel cell corresponding to each historical moment in a historical time period, where the calculation parameters include a stack voltage, active area and a hydrogen permeation current; carrying out calculation based on the calculation parameters corresponding to the historical moment to obtain a mixed aging index corresponding to the historical moment; taking the operation parameters and the mixed aging index corresponding to each historical moment in the historical time period as inputs, and predicting the mixed aging index corresponding to the prediction moment by a mixed aging index prediction model.

The invention relates to a mobile hydrogen refueling station comprising at least a first, second and third hydrogen gas source configured for storing gas at different pressures. Said mobile hydrogen refueling station further comprises at least two filling hoses, connectable to said first, second and third hydrogen source a via conduit system and to a receiving vessel. Said mobile hydrogen refueling station further comprises a controller configured for simultaneously controlling refueling of at least a first and a second receiving vessel by: controlling flow of hydrogen gas from said first, second or third hydrogen gas source via a first of said at least two filling hoses to said first receiving vessel, and controlling flow of hydrogen gas from said first, second or third hydrogen gas source via a second of said at least two filling hoses to said second receiving vessel.

The invention discloses a fuel cell system modeling and control-oriented joint simulation design method, which comprises the following steps of: based on an electrochemical and heat transfer mechanism, dividing an electric pile into a plurality of nodes along a reaction gas flowing direction by adopting a distributed parameter method, and establishing a one-dimensional solid oxide fuel cell dynamic model by applying a multi-field unified modeling language Modelica; establishing a dynamic model of each auxiliary machine part of the solid oxide fuel cell system; all the components are connected according to a unified interface to form a system overall dynamic model, and dynamic simulation is carried out; carrying out multi-output multi-input state space model identification in SIMULINK by applying dynamic simulation data of the solid oxide fuel cell system; a model prediction controller KF-MPC based on Kalman filtering is developed; and establishing a joint simulation platform. According to the invention, rapid and accurate load tracking and temperature control are realized, and the operation safety of the system is maintained at the same time.

The invention discloses a gas-heat-electricity balance management and control method and system for a kilowatt-level SOFC (solid oxide fuel cell) cogeneration system, and belongs to the field of solid oxide fuel cells. The method comprises the following steps: setting initial operation parameters according to structure parameters and design working conditions of an SOFC electric pile, a heat exchanger, a reformer and a catalytic burner; a module start-stop coordination instruction is generated through the integrated controller, and temperature and pressure changes of all the modules in the start-stop process are controlled; system operation data are monitored in real time through a sensor, real-time diagnosis is conducted through a multi-dimensional data fusion algorithm, and abnormal states such as over-burning, over-air and temperature runaway are recognized; and according to the diagnosis result, the fuel flow, the air flow, the heat exchange power and the like are adjusted through a multivariable dynamic regulation and control strategy, so that reactor temperature fluctuation is controlled, and a temperature runaway early warning signal is generated. According to the method, the overall stability and efficiency of the SOFC combined heat and power system are improved by optimizing gas-heat-power balance management and control.

The invention provides an efficient and stable ship hybrid power generation system which comprises a hydrogen production unit and an ammonia supply system, and the hydrogen production unit comprises an ammonia decomposer, a hydrogen separator, a high-pressure hydrogen storage tank, a fuel cell and an ammonia-hydrogen internal combustion engine. The ammonia decomposer enables the ammonia flow to enter the ammonia decomposer in a segmented constant mode for catalytic decomposition through four set working conditions; the hydrogen separator is used for separating and purifying the generated mixed gas, and the separated and purified hydrogen is respectively fed into the fuel cell and the ammonia-hydrogen internal combustion engine through valves for power generation; the molten salt system recycles high-temperature tail gas of the ammonia-hydrogen internal combustion engine through the heat exchanger for heat energy storage and power generation through the steam Rankine cycle system. The regulation and control method is used for stabilizing the system and prolonging the service life of equipment by limiting the dynamic loading rate and start-stop times of the fuel cell and the ammonia-hydrogen internal combustion engine, and is used for waste heat recovery power generation through the molten salt and the steam expansion machine, so that the efficiency of the system is improved.

The invention relates to the technical field of comprehensive application of renewable energy sources and hydrogen energy, in particular to a wind-solar-hydrogen multi-energy complementary intelligent scheduling platform. According to the technical scheme, the wind-light-hydrogen multi-energy complementary intelligent scheduling platform comprises a wind-light power generation unit which monitors wind power and photovoltaic power fluctuation in real time; the hybrid energy storage unit comprises a super capacitor and a flywheel for energy storage and respectively responds to millisecond-level and second-level power fluctuations; the hydrogen energy subsystem comprises an electrolytic hydrogen production device, a hydrogen storage tank and a fuel cell and responds to minute-level power scheduling; and the multi-time scale controller is configured to execute millisecond-level, second-level and minute-level cooperative control and dynamically match the wind-light fluctuation and the hydrogen energy response speed. According to the method, through multi-time scale dynamic cooperative control, the matching problem between the wind-solar power generation volatility and the hydrogen energy response lag is effectively solved, and seamless connection between second-level high-frequency fluctuation suppression and minute-level energy scheduling is achieved.

The invention relates to the technical field of hydrogen preparation, and provides a hydrogen storage device based on a solid hydrogen storage material and a hydrogen production method thereof.The device comprises a fuel tank internally provided with a reaction cavity used for containing an aluminum hydride material and mixed powder; the heater is arranged on the outer side of the fuel tank; the first end of the water recycling assembly is communicated with the reaction cavity, and the second end of the water recycling assembly is communicated with the fuel cell system so as to recycle water generated by the fuel cell system to the reaction cavity; the first end of the hydrogen discharging assembly is communicated with the reaction cavity, and the second end is communicated with a fuel cell system. According to the hydrogen storage device provided by the invention, through the application of the high-specific-energy solid hydrogen storage material aluminum hydride which can be stored at normal pressure and release hydrogen at a relatively low temperature, the thermal decomposition process of the metal hydride in the fuel tank and the coupling reaction process of the metal hydride and water are optimized, and the hydrogen is produced by utilizing the hydrolysis reaction of the aluminum hydride thermal decomposition reactant simple substance aluminum and the water; meanwhile, thermal decomposition of aluminum hydride is promoted through heat released by hydrolysis reaction, hydrogen release is coupled, and effective utilization of heat is achieved.

An aircraft propulsion assembly that has a nacelle with a front opening and a rear opening, a propeller driven by an electric motor, a fuel cell supplying the electric motor with electric current, an inner channel arranged in the nacelle between the front opening and the rear opening. The electric motor and the fuel cell are disposed in the inner channel. A motorized fan is arranged at the rear part so as to draw in the air present in the inner channel and expel it to the outside through the rear opening. A control unit controls the motorized fan. With such an arrangement, the outside air cools the inside of the nacelle and the dihydrogen is evacuated.

The invention discloses a fuel cell output voltage control method and system based on fuzzy neural network PID, and the method comprises the steps: building an air-cooled fuel cell voltage model based on an MATLAB / Simulink simulation platform, and obtaining the temperature changes of an air-cooled fuel cell under different working conditions; establishing an air-cooled fuel cell test bench, and obtaining a polarization curve of output voltage changing along with current; according to experimental data, calibrating the semi-empirical equation by adopting a nonlinear least square method, and comparing experimental results to verify the accuracy of the model; the input hydrogen flow is changed through the PID controller, so that stable control of the output voltage of the galvanic pile is realized, and the power generation performance of the battery is improved; a fuzzy neural network is adopted to optimize a PID controller, control parameters of PID are adjusted in a self-adaptive mode according to the error between expected voltage and actual voltage and the error change rate, and therefore a better temperature control effect is achieved. The method has the advantages of high robustness, high response speed and the like, and ensures that the voltage output of the fuel cell stack is maintained at a fixed preset value.

The invention discloses a fuel cell coupled flow battery energy supply system and an operation control method thereof. The energy supply system comprises a basic energy supply unit, an energy storage peak regulation unit, a renewable energy power generation unit, an electrolytic hydrogen production unit, a hydrogen storage unit, a first-stage waste heat recycling unit, a second-stage waste heat recycling unit and a heat storage unit. The basic energy supply unit is used for providing a basic power load of the target building group; the energy storage peak regulation unit is used for providing fluctuation power load of the target building group; the first-stage waste heat recycling unit receives first-stage waste heat generated by power generation of the fuel cell and is used for indoor heating or indoor refrigeration. And the second-stage waste heat recycling unit directly receives the first-stage waste heat or second-stage waste heat from the first-stage waste heat recycling unit and is used for preheating the electrolyzed water and / or the hydrogen storage unit. By arranging the first-stage waste heat recycling unit and the second-stage waste heat recycling unit, waste heat is utilized in a multi-stage mode according to requirements, and the waste heat utilization rate is high.

The invention discloses a layered energy management method of a fuel cell hybrid tramcar with self-adaptive working condition perception. In the recognition layer, a sliding window mechanism is adopted to extract time domain and frequency domain features of load conditions, feature data are clustered based on a spectral clustering algorithm driven by a deep auto-encoder, a data set with category labels is obtained, and a deep dynamic learning vector quantization neural network classifier is trained; in the strategy layer, a double-delay depth deterministic strategy gradient reinforcement learning algorithm is adopted, a reward function is constructed, and lithium battery SOC fluctuation penalty term limit parameters in the reward function are adaptively adjusted according to the real-time load working condition category output by the recognition layer; training the reinforcement learning agent to obtain an optimal power distribution scheme between the multi-stack fuel cell power generation system and the lithium battery; and according to the performance degradation degrees of different fuel cell stacks, a distributed cooperative control strategy considering performance difference is adopted to distribute the output power of each stack, so that the coordinated control of the running state of the multi-stack fuel cell power generation system is realized.

The invention relates to a fuel cell vehicle energy management strategy optimization method facing working condition demands. The method comprises an equivalent factor iteration updating module, a current moment working condition identification module, a future time domain working condition demand prediction module and a power system execution module. Based on current working condition identification classification and demand working condition prediction in a future time domain, equivalent factors are updated from historical and future dimensions, optimal control sequence distribution of the hybrid power system power is obtained by using an F-AECMS algorithm based on the instantaneous local optimization advantage of a Pontryagin minimum principle, and the optimal control sequence distribution of the hybrid power system power is obtained. Energy management of the fuel cell automobile is achieved, and the optimality and working condition adaptability of an energy management strategy are effectively improved.

Side channel compressor (1) for a fuel cell system (2) for compressing a gaseous medium, comprising a housing with a first housing part (3) and a second housing part (4). According to the invention, a compressor wheel assembly (10) and / or a respective bearing (19, 20) has, on its end face facing the second housing part (4), in particular a first end face (30), a cover-shaped sealing element (13) which at least almost completely covers the bearings (19, 20) and / or a bearing device (9) orthogonal to the axis of rotation (R), wherein the cover-shaped sealing element (13) is at least indirectly connected to a hub (16) in such a way that fluidic encapsulation of an interior space (27) of the hub (16) with respect to an environment (29) of the compressor wheel assembly (10) can be achieved. The invention further relates to a fuel cell system (2) with a side channel compressor (1) according to the invention.

The invention provides a low-cost metal modified electrode material, a preparation method and application, solves the problems that a carbon nitride material is difficult to recover and poor in sustainability, and improves the photoelectrocatalysis capability of an active carbon material. Further constructing a packed bed cathode coupled microbial fuel cell system; the treated industrial wastewater is high-salt coking wastewater from Anshan steel, a PEC-MFC system filled with electrogenesis microorganisms is used for realizing wastewater recycling and harmlessness, and energy-saving, high-efficiency and one-step treatment of the industrial wastewater is completed.

The invention relates to a membrane stack (9) for an air humidifier (1) of a fuel cell for humidifying a dry supply air stream (2) of the fuel cell by means of a moist exhaust air stream (3) of the fuel cell, - wherein the membrane stack (9) is configured in a cuboid shape, has a stacking direction (S) and four stacking sides (10) perpendicular to the stacking direction (S), - wherein the membrane stack (9) has a vertical direction (Z) parallel to the stacking direction (S), a longitudinal direction (X) perpendicular to the vertical direction (Z) and a transverse direction (Y) perpendicular to the vertical direction (Z) and perpendicular to the longitudinal direction (X), - wherein the four stack sides (10) form an air supply inlet (ZE) and an air supply outlet (ZA) facing away from each other in the longitudinal direction (X), and an exhaust air inlet (AE) and an exhaust air outlet (AA) facing away from each other in the transverse direction (Y), - wherein the membrane stack (9) comprises several membranes (11) which are permeable to moisture and impermeable to air and which follow one another in the stacking direction (S) such that the membranes (11) within the membrane stack (9) each separate a supply air path (ZP) connecting the supply air inlet (ZE) to the supply air outlet (ZA) from an exhaust air path (AP) connecting the exhaust air inlet (AE) to the exhaust air outlet (AA). Improved functional reliability can be achieved by having the membrane stack (9) have several spacers (12) which are arranged in the stacking direction (S) between two immediately successive membranes (11) in one of the exhaust air paths (AP).

The invention discloses a ship fuel cell cooling system energy efficiency management method based on deep reinforcement learning, and relates to the technical field of ship energy management, and the method comprises the steps: constructing a digital simulation model of a ship fuel cell cooling system, which is used for representing the dynamic characteristics of the cooling system under different working conditions; constructing a multi-time scale prediction and thermal load prediction model, and respectively outputting cooling system state and working condition prediction parameters and thermal load prediction parameters under different time scales; a reinforcement learning framework based on the dual deep Q network is built, a state space, an action space and a reward function are defined, and the state space comprises current state parameters of the cooling system and output parameters of all prediction models; the action space comprises seawater pump rotating speed, fresh water pump rotating speed and regulating valve opening; and an optimal control strategy is generated based on a training result of deep reinforcement learning, and global collaborative optimization operation of execution equipment of the cooling system is realized, so that the system energy efficiency and environmental adaptability are improved.

The invention relates to the technical field of fuel cell system anomaly detection, in particular to a fuel cell system time series data anomaly detection method based on residual analysis, and the method comprises the specific implementation steps: obtaining multi-source design simulation data of a system, and constructing a multi-source design simulation data tensor; constructing a computer aided design model, performing behavior simulation on the simulation data tensor, and outputting a simulation design behavior value; the simulation data is used as a simulation observation value to be compared with a simulation design behavior value, a multi-dimensional residual sequence is obtained through calculation, and online self-adaptive updating is conducted on the design model; establishing a physical reachability matrix, and adjusting a dynamic threshold value based on the matrix and a real-time simulation working condition; performing weighted fusion on the multi-dimensional residual sequence to generate a collaborative design constraint index, and comparing the collaborative design constraint index with the dynamic threshold to generate a computer aided design verification result; and inputting the design verification result into a preset residual-control mapping rule, and outputting a design parameter optimization instruction to optimize the design parameters.

The invention belongs to the technical field of fuel cell electrode material preparation, and particularly relates to a carbon electrode material for a polypyrrole modified bio-based fuel cell and a preparation method of the carbon electrode material. Comprising the following steps: modifying rice hull low-temperature carbonized powder by sequentially adopting POSS (Polyhedral Oligomeric Silsesquioxane) containing unipolar functional groups and POSS containing polypolar functional groups to obtain modified low-temperature carbonized powder; and carrying out in-situ polymerization on a pyrrole monomer on the surface of the modified low-temperature carbonized powder, and carrying out high-temperature carbonization and hydrofluoric acid corrosion to obtain the polypyrrole modified bio-based fuel cell carbon electrode material. The polypolar functional group POSS not only is beneficial to the in-situ polymerization reaction of pyrrole, but also can form a continuous macromolecular chain, and a net structure is formed on the surface of the whole material. The effect of the unipolar functional group POSS is to improve the stability of the low-temperature carbonized powder in the high-temperature carbonization process, and more importantly, the unipolar functional group POSS is to provide a channel for subsequent hydrofluoric acid corrosion, etch away non-conductive substances and improve the conductivity and specific surface area of the carbon electrode material.

The invention relates to the technical field of energy power, in particular to a vehicle power system based on a solid hydrogen pool, a passenger vehicle and a control method. The vehicle power system comprises a power driving module, a fuel cell module, a solid hydrogen pool module, a heat dissipation module and a whole vehicle control module. The fuel cell module comprises a cell stack unit, a hydrogen feeding and discharging unit, an air feeding and discharging unit and a tail discharging unit, and the cell stack unit is electrically connected with the power driving module. The solid hydrogen pool module comprises a solid hydrogen storage unit, a water supply unit and a hydrogen release buffer unit. The heat dissipation module is in butt joint with the cell stack unit and the solid hydrogen storage unit, and the whole vehicle control module is in communication connection with the power driving module, the fuel cell module and the solid hydrogen pool module. The passenger vehicle comprises a vehicle power system. The fuel cell module based on the solid hydrogen pool module is used for stably supplying power to the power driving module, so that power is provided for the passenger car, and the endurance requirement of the passenger car is met.

The invention belongs to the technical field of fuel cells, and particularly relates to a high-dimensional multi-target multi-working-condition optimization method and system for a fuel cell centrifugal air compressor, and the method comprises the steps: constructing a fuel cell air compressor performance analysis and optimization system, a comprehensive performance test platform is built, a multi-physics field coupling CFD simulation model is built, and the simulation and optimization efficiency is improved in combination with a machine learning algorithm; the pressure ratio and isentropic efficiency are defined as optimization targets based on fuel cell system requirements, and the performance of the air compressor is evaluated through experiment and simulation data; a multi-objective multi-population optimization method, an archive sharing technology, a genetic algorithm and the like are fused to establish an MMPS algorithm, and high-dimensional multi-objective optimization is carried out on related structure parameters of an impeller, a volute and a diffuser. The technical problems that the multi-target collaborative optimization requirement of an existing fuel cell centrifugal air compressor is difficult to meet, the high-dimensional variable optimization difficulty is large, and complex flow characteristic control is difficult are solved.