Hydrogen Fuel Cell Process Optimization Method and System

Abstract

The present invention relates to the technical field of hydrogen fuel cells, and discloses a method and system for optimizing the process of hydrogen fuel cells, including obtaining a set of structural parameters of the hydrogen fuel cell; inputting the set of structural parameters into a pre-constructed humidity parameter matching model to obtain an internal humidity control parameter and an external humidity control parameter; during the production of the hydrogen fuel cell, controlling an internal humidity control system and an external humidity control system to perform humidity control on the production of the hydrogen fuel cell according to the internal humidity control parameter and the external humidity control parameter respectively; adjusting the internal humidity control parameter and the external humidity control parameter according to the monitored battery internal resistance of the hydrogen fuel cell. For the method and system for optimizing the process of hydrogen fuel cells of the present invention, the internal and external humidity controls are linked, and the internal humidity control parameter and the external humidity control parameter are dynamically adjusted in combination with the feedback of the battery internal resistance, enhancing the consistency and reliability of the battery internal resistance in the production of hydrogen fuel cells and improving the battery performance.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen fuel cells, and in particular to a method and system for optimizing the process of hydrogen fuel cells. Background Art

[0002] As a clean and efficient energy conversion device, hydrogen fuel cells are of great significance in promoting the application of renewable energy and achieving sustainable development; its core principle is to release energy through the electrochemical reaction of hydrogen and oxygen, generating electricity and water; in order to achieve the efficient operation of hydrogen fuel cells, the performance of the battery must be optimized under specific environmental conditions, and humidity control is a crucial factor among them.

[0003] Research shows that humidity has a significant impact on multiple performance indicators of hydrogen fuel cells. For example, appropriate humidity can improve the ionic conductivity of hydrogen fuel cells, reduce the internal resistance of the battery, thereby enhancing the power density and operating efficiency of the battery. On the contrary, too low humidity will cause the membrane to dry out and the conductance to decrease; too high humidity may cause water management problems, resulting in a decrease in the efficiency and lifespan of the fuel cell. Therefore, accurately controlling the humidity level of hydrogen fuel cells during the production process is the key to ensuring their performance and stability.

[0004] The humidity regulation of hydrogen fuel cells includes internal humidity control and external humidity control. Internal humidity control means not introducing an additional humidification system, and controlling humidity by storing moisture through the battery's own structure or by changing the intake air flow and pressure to balance the generation and consumption of moisture; external humidity control is to use an additional humidifier in the anode and cathode intake air systems to humidify the gas introduced into the electrodes.

[0005] The existing technology lacks a systematic analysis of the impact of different humidity controls on battery performance, especially the impact analysis of the dynamic regulation combining internal and external humidity controls on the internal resistance performance of the battery, and cannot make a quick response based on the change of the battery internal resistance, affecting the consistency and reliability of hydrogen fuel cells. Summary of the Invention

[0006] Therefore, the technical problem to be solved by the present invention is to overcome the lack of a systematic analysis of the impact of different humidity controls on the battery internal resistance in the existing technology, and provide a method and system for optimizing the process of hydrogen fuel cells, with internal and external humidity control linkage, and dynamically adjusting the internal humidity control parameters and external humidity control parameters in combination with the feedback of the battery internal resistance, enhancing the consistency and reliability of the battery internal resistance in the production of hydrogen fuel cells, and improving the battery performance.

[0007] In the first aspect, to solve the above technical problem, the present invention provides a method for optimizing the process of hydrogen fuel cells, including,

[0008] Obtaining a set of structural parameters of a hydrogen fuel cell;

[0009] Input the set of structure parameters into a pre - constructed humidity parameter matching model to obtain internal humidity control parameters and external humidity control parameters;

[0010] During the production of the hydrogen fuel cell, control the internal humidity control system and the external humidity control system to conduct humidity control on the production of the hydrogen fuel cell according to the internal humidity control parameters and the external humidity control parameters respectively;

[0011] Adjust the internal humidity control parameters and the external humidity control parameters according to the monitored battery internal resistance of the hydrogen fuel cell.

[0012] In an embodiment of the present invention, adjusting the internal humidity control parameters and the external humidity control parameters according to the monitored battery internal resistance of the hydrogen fuel cell includes,

[0013] Conduct stage division according to the process of the hydrogen fuel cell, and test the local internal resistance of the stage product in each process stage;

[0014] Analyze the local internal resistance to obtain an internal resistance identification stage; wherein, the internal resistance identification stage is the process stage where the local internal resistance is greater than or equal to the local internal resistance threshold;

[0015] Determine the local internal resistance index of the internal resistance identification stage;

[0016] Adjust the internal humidity control parameters and the external humidity control parameters according to the local internal resistance index.

[0017] In an embodiment of the present invention, determining the local internal resistance index of the internal resistance identification stage includes,

[0018] Conduct area division according to the structure of the stage product to obtain multiple divided areas;

[0019] Test the local area internal resistance of the multiple divided areas and calculate the local area internal resistance gradient between adjacent divided areas; wherein, the calculation method of the local area internal resistance gradient is:

[0020] ;

[0021] Wherein, , are the numbers of adjacent divided areas, is the local area internal resistance gradient between adjacent divided areas; is the local area internal resistance of the th divided area; is the local area internal resistance of the th divided area; is the distance between the th divided area and the th divided area;

[0022] Determine the local internal resistance index of the identified internal resistance stage according to the internal resistance gradient of the local area.

[0023] In an embodiment of the present invention, it further includes

[0024] Conduct a stability analysis on the monitored internal resistance of the battery to obtain the battery internal resistance stability coefficient of the batch of hydrogen fuel cells;

[0025] Taking the minimization of the difference between the battery internal resistance stability coefficient and the preset stability coefficient as the feedback target, optimize the internal humidity control parameter and the external humidity control parameter to obtain the optimized humidity control parameter;

[0026] Conduct humidification control on the internal humidity control system and the external humidity control system according to the optimized humidity control parameter.

[0027] In an embodiment of the present invention, the structural parameter set includes the catalyst layer thickness, the electrode structure, the electrolyte membrane thickness, and the gas diffusion layer thickness.

[0028] In an embodiment of the present invention, it further includes

[0029] Divide the structural parameter set according to the manufacturing process to obtain a multi-process structural parameter set;

[0030] Input the multi-process structural parameter set into the humidity parameter matching model to obtain the multi-process internal humidity control parameter and the multi-process external humidity control parameter;

[0031] During the production of the hydrogen fuel cell, stage-start the multi-process internal humidity control parameter to control the internal humidity control system, and stage-start the multi-process external humidity control parameter to control the external humidity control system to conduct humidity control on the production of the hydrogen fuel cell.

[0032] In an embodiment of the present invention, it further includes pre-configuring a synchronous starter, and through the synchronous starter, during the production of the hydrogen fuel cell, synchronously start the internal humidity control system and the external humidity control system to conduct synchronous humidity control on the production of the hydrogen fuel cell.

[0033] In an embodiment of the present invention, constructing the humidity parameter matching model includes

[0034] Extract a sample catalyst layer thickness set, a sample electrode structure set, a sample gas diffusion layer thickness set, a sample electrolyte membrane thickness set, a sample internal humidity control parameter set, and a sample external humidity control parameter set from the historical data of the production of the hydrogen fuel cell;

[0035] Taking the sample catalyst layer thickness set, sample electrode structure set, sample gas diffusion layer thickness set, and sample electrolyte membrane thickness set as input data, and taking the in-sample humidity control parameter set and out-of-sample humidity control parameter set as output data to train a convolutional neural network model, a humidity parameter matching model is obtained.

[0036] In one embodiment of the present invention, the humidity parameter matching model includes a plurality of humidity parameter matching branches, and the number of the humidity parameter matching branches is the same as the number of divisions of the process stages;

[0037] Inputting the in-multi-process humidity control parameters and out-of-multi-process humidity control parameters into the plurality of humidity parameter matching branches respectively, in-multi-process humidity control parameters and out-of-multi-process humidity control parameters are obtained.

[0038] In a second aspect, based on the same inventive concept, the present invention provides a hydrogen fuel cell process optimization system, including,

[0039] A structure parameter acquisition module, which is used to acquire the structure parameter set of the hydrogen fuel cell;

[0040] A humidity parameter matching module, which is used to obtain in-humidity control parameters and out-humidity control parameters according to the structure parameter set;

[0041] A humidity control module, which is used to control the in-humidity control system and out-humidity control system to perform humidity control on the production of the hydrogen fuel cell respectively according to the in-humidity control parameters and out-humidity control parameters during the production of the hydrogen fuel cell;

[0042] A humidity control optimization module, which is used to adjust the in-humidity control parameters and the out-humidity control parameters according to the monitored battery internal resistance of the hydrogen fuel cell.

[0043] The above technical solutions of the present invention have the following beneficial effects compared with the prior art:

[0044] For the hydrogen fuel cell process optimization method and system of the present invention, the internal and external humidity control are linked to ensure that the electrolyte membrane operates in the best hydrated state, thereby significantly reducing the battery internal resistance and directly improving the power density and overall energy conversion efficiency of the hydrogen fuel cell; according to the monitored battery internal resistance situation, the in-humidity control parameters and out-humidity control parameters are dynamically adjusted to ensure that in different production environments and conditions, the humidity fluctuations during the production process are effectively reduced, thereby enhancing the product consistency and quality reliability and improving the battery performance. Description of the Drawings

[0045] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to the specific embodiments of the present invention in conjunction with the drawings, wherein,

[0046] Figure 1 It is a flowchart of the hydrogen fuel cell process optimization method in the preferred embodiment of the present invention;

[0047] Figure 2 It is a flowchart of adjusting the humidity control parameters according to the battery internal resistance in the preferred embodiment of the present invention;

[0048] Figure 3 It is a structural block diagram of the hydrogen fuel cell process optimization system in the preferred embodiment of the present invention. Detailed implementation manners

[0049] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the specific embodiments cited are not intended to limit the present invention. Embodiment 1

[0050] Refer to Figure 1 As shown, the embodiment of the present invention discloses a hydrogen fuel cell process optimization method, aiming to optimize the performance and production efficiency of the fuel cell by precisely adjusting the humidity control parameters. The following is a further refinement of the method, including,

[0051] S100. Obtain the structural parameter set of the hydrogen fuel cell;

[0052] In a specific application scenario, at each stage of the hydrogen fuel cell production line, such as the electrode manufacturing stage, the electrolyte membrane manufacturing stage, and the membrane electrode assembly stage, etc., high-precision measurement tools (such as laser scanners, X-ray CT scanners, scanning electron microscopes SEM, etc.) are used to detect each component constituting the hydrogen fuel cell, and accurate data such as the catalyst layer thickness, electrode structure, electrolyte membrane thickness, gas diffusion layer thickness, etc. are obtained, constituting the structural parameter set of the hydrogen fuel cell. These structural parameters will directly affect the humidity control requirements of the battery and have an impact on the final battery internal resistance. The structural parameter set provides an accurate basis for humidity control, enabling subsequent humidity adjustment to precisely match the battery structure characteristics and improving the battery performance.

[0053] S200. Input the structural parameter set into a pre-constructed humidity parameter matching model to obtain the internal humidity control parameter and the external humidity control parameter;

[0054] In a specific application scenario, based on a large amount of experimental data and the humidity control effects under different structural parameters in the actual production process, a humidity matching model is constructed through deep learning. Specifically, constructing the humidity parameter matching model includes extracting a set of sample catalyst layer thicknesses, a set of sample electrode structures, a set of sample gas diffusion layer thicknesses, a set of sample electrolyte membrane thicknesses, a set of sample internal humidity control parameters, and a set of sample external humidity control parameters from the historical data of hydrogen fuel cell production; using the set of sample catalyst layer thicknesses, the set of sample electrode structures, the set of sample gas diffusion layer thicknesses, and the set of sample electrolyte membrane thicknesses as input data, and using the set of sample internal humidity control parameters and the set of sample external humidity control parameters as output data to train a convolutional neural network model to obtain a humidity parameter matching model. The humidity matching model should be understood as constructing a convolutional neural network model using a convolutional neural network architecture. The convolutional neural network model is trained with the historical data of hydrogen fuel cell production. During training, the set of sample catalyst layer thicknesses, the set of sample electrode structures, the set of sample gas diffusion layer thicknesses, and the set of sample electrolyte membrane thicknesses are used as input data, and the set of sample internal humidity control parameters and the set of sample external humidity control parameters are used as output data. During the training process, the model parameters are continuously optimized until the convergence requirements are met. The neural network basic model that has completed training and passed verification is the humidity matching model. After obtaining the humidity matching model, when the set of structural parameters is input into the humidity matching model, the internal humidity control parameters and the external humidity control parameters can be obtained. By predicting the internal humidity control parameters and the external humidity control parameters based on different structural parameters through the humidity parameter matching model, the accuracy of humidity control is significantly improved. Precise humidity control will reduce unnecessary production defects and product inconsistency problems caused by improper humidity control.

[0055] S300. When the hydrogen fuel cell is produced, the internal humidity control system and the external humidity control system are respectively controlled according to the internal humidity control parameters and the external humidity control parameters to control the humidity of the hydrogen fuel cell production.

[0056] In a specific application scenario, the internal humidity control system and the external humidity control system are systems pre-configured for the hydrogen fuel cell production line. Among them, the internal humidity control system is a system that stores moisture through the battery's own structure or balances the generation and consumption of moisture by changing the intake air flow rate and pressure, and is the humidity control system of the hydrogen fuel cell production line itself; the external humidity control system is an additional humidifier that humidifies the gas introduced into the electrodes in the anode and cathode intake air systems. The internal humidity control system regulates the humidity according to the internal humidity control parameters; the external humidity control system regulates the humidity according to the external humidity control parameters.

[0057] S400. Adjust the internal humidity control parameters and the external humidity control parameters according to the monitored battery internal resistance of the hydrogen fuel cell.

[0058] In a specific application scenario, the internal resistance changes of each hydrogen fuel cell in a continuous monitoring batch are continuously monitored. Through the internal resistance test module, the battery internal resistance data is collected and analyzed in real time. When the internal resistance value of the battery is abnormal, a feedback adjustment mechanism is activated. If the battery internal resistance is large, it indicates that the humidity in some areas is insufficient; conversely, if the battery internal resistance is too low, it indicates that the humidity in some areas is too high. By combining with the real-time feedback mechanism of the battery internal resistance, the humidity can be accurately adjusted to avoid performance instability caused by uneven humidity and improve the consistency and reliability of the battery internal resistance.

[0059] In the hydrogen fuel cell process optimization method of the present invention, the internal and external humidity control are linked to ensure that the electrolyte membrane operates in the best hydrated state, thereby significantly reducing the battery internal resistance and directly improving the power density and overall energy conversion efficiency of the hydrogen fuel cell. According to the monitored battery internal resistance situation, the internal humidity control parameters and the external humidity control parameters are dynamically adjusted to ensure that under different production environments and conditions, the humidity fluctuations during the production process are effectively reduced, thereby enhancing the product consistency and quality reliability and improving the battery performance.

[0060] Specifically, referring to Figure 2 As shown, the internal humidity control parameters and the external humidity control parameters are adjusted according to the monitored battery internal resistance of the hydrogen fuel cell, including dividing the process of the hydrogen fuel cell into stages according to the process, and testing the local internal resistance of the stage product in each process stage; analyzing the local internal resistance to obtain an internal resistance stage identifier; wherein, the internal resistance stage identifier is a process stage where the local internal resistance is greater than or equal to the local internal resistance threshold; determining the local internal resistance index of the internal resistance stage identifier; and adjusting the internal humidity control parameters and the external humidity control parameters according to the local internal resistance index.

[0061] In a specific application scenario, according to the production process flow of the hydrogen fuel cell, the production process is divided into multiple stages, such as the electrode manufacturing stage, the electrolyte membrane manufacturing stage, and the membrane electrode assembly stage, etc. Process requirements and corresponding test nodes are set for each process stage. The alternating current impedance spectroscopy (EIS) or the constant current test method is used to test the local internal resistance of the stage product. The test results include the ohmic internal resistance and the diffusion internal resistance. The ohmic resistance is determined by the membrane resistance and the contact resistance, and the diffusion internal resistance is related to humidity management. The humidity control in multiple processes involved in the entire production process of the hydrogen fuel cell affects the battery internal resistance. By measuring the local internal resistance of the stage product in each process stage and analyzing the measured local internal resistance, it is possible to clearly locate whether there are humidity control problems in each process stage, avoiding the problems of difficult positioning and difficult optimization when humidity control problems occur.

[0062] Analyze the measured local internal resistance to determine whether it exceeds the set local internal resistance threshold. The local internal resistance threshold is determined based on experimental data. For example, the ohmic internal resistance is generally higher under relatively dry conditions and is usually controlled within the range of dozens of milliohms; the diffusion internal resistance generally increases significantly when the humidity is insufficient or gas transmission is restricted; the local internal resistance threshold is dynamically adjusted according to specific process conditions and production requirements. Record the process stages with local internal resistance values greater than or equal to the threshold as the marked internal resistance stages. For example: If the local internal resistance is high after membrane electrode pressing, it may be due to insufficient humidity resulting in poor bonding between the membrane and the catalyst layer; if the local internal resistance increases after the battery stack is assembled, it may be due to insufficient wetting of the diffusion layer or uneven pressure drop within the stack. Optimize the internal and external humidity control parameters according to the local internal resistance index of the marked internal resistance stage. Among them, increase the humidity of the internal humidity control system by increasing the gas flow rate within the stack, raising the intake pressure, or optimizing the lifting cycle path; increase the environmental humidity compensation by adjusting the humidifier parameters to increase the humidity of the external humidity control system.

[0063] An overall closed-loop control is formed. Through the real-time monitored local internal resistance and humidity data, continuously optimize the internal and external humidity control parameters, focus on regulation during the marked internal resistance stage, and gradually optimize the humidity distribution in other process stages. In addition, through staged humidity control and the coordinated optimization of internal and external parameters, reduce unnecessary external humidification operations and lower the energy consumption of the humidifier; precisely control the internal humidity and reduce the power consumption of the gas circulation system.

[0064] Furthermore, referring to Figure 3 as shown, determining the local internal resistance index of the marked internal resistance stage includes dividing the area according to the structure of the product in this stage to obtain multiple divided areas; testing the local internal resistance of the multiple divided areas and calculating the local area internal resistance gradient between adjacent divided areas; determining the local internal resistance index of the marked internal resistance stage according to the local area internal resistance gradient. Among them, the calculation method of the local area internal resistance gradient is:

[0065] ;

[0066] Among them, 、 are the numbers of adjacent divided areas, is the local area internal resistance gradient between adjacent divided areas; is the local area internal resistance of the th divided area; is the local area internal resistance of the th divided area; is the distance between the rd divided area and the th divided area.

[0067] In specific application scenarios, the area is divided according to the structure of the product in the described stage. For example, for a membrane electrode assembly, it is divided into a central area, an edge area, etc. according to the geometric distribution of the electrodes. Further, the central area and the edge area are further subdivided to obtain multiple divided areas. By calculating the local area internal resistance gradient between adjacent divided areas, the change trend of the local area internal resistance of adjacent areas is calculated. If the gradient is large, it means that the internal resistance difference between adjacent areas is large, which is usually caused by uneven humidity and temperature distribution or uneven electrolyte membrane hydration, and uneven catalyst activity and blocked gas diffusion layer may also be the reasons for the increase in the local internal resistance gradient. If the gradient is small, it indicates that the hydration and catalyst activity distribution in this area are relatively uniform, which may indicate that the humidity control is relatively balanced at this time and the working state of the battery is relatively stable. In this case, no humidity adjustment is required, and the existing humidity control strategy can be maintained to ensure that the battery operates in the best state. By introducing the local area internal resistance gradient, the humidity control parameters can be dynamically adjusted to ensure uniform humidity distribution in the battery and appropriate hydration of the electrolyte membrane, thereby improving the overall performance and reliability of the hydrogen fuel cell.

[0068] In another embodiment of the solution of the present invention, after monitoring the battery internal resistance, it further includes performing a stability analysis on the monitored battery internal resistance to obtain the battery internal resistance stability coefficient of a batch of hydrogen fuel cells; taking minimizing the difference between the battery internal resistance stability coefficient and a preset stability coefficient as a feedback target, optimizing the internal humidity control parameters and the external humidity control parameters to obtain optimized humidity control parameters; performing humidification control on the internal humidity control system and the external humidity control system according to the optimized humidity control parameters.

[0069] During specific application implementation, the battery internal resistance is continuously monitored during continuous production, and a stability analysis is performed on the battery internal resistance of a batch of hydrogen fuel cells obtained to evaluate the stability of the humidity control process. The goal of the stability analysis is to determine whether the battery internal resistance can quickly reach the set value and remain stable after humidity adjustment, or whether there will be excessive fluctuations when adjusting the humidity. Analyze the battery internal resistance value, calculate the time required for the battery internal resistance to reach the set value, the fluctuation amplitude, etc., and convert these data into the battery internal resistance stability coefficient. The battery internal resistance stability coefficient is used to quantify the stability parameter of the humidity control process, which reflects the stability degree of the system when reaching the set battery internal resistance. The smaller the battery internal resistance stability coefficient, the smoother the humidity control process; on the contrary, the larger the battery internal resistance stability coefficient, the greater the fluctuation or instability of the humidity control process.

[0070] The preset stability coefficient is a pre-set target stability value, which reflects the stable state that the humidity regulation should reach under ideal working conditions. The difference between the battery internal resistance stability coefficient and the preset stability coefficient is used to measure the deviation between the actual humidity control process and the ideal working condition. The larger the difference, the worse the stability; the smaller the difference, the closer the humidity control is to the ideal state. With the goal of minimizing the difference, by adjusting the humidity control data, the battery internal resistance stability coefficient is made as close as possible to the preset stability coefficient. Through continuous iteration and adjustment, optimized internal and external humidity control parameters are output to ensure that the adjustment process of humidity control is smoother, the fluctuation is reduced, and it is closer to the ideal stable state.

[0071] In another embodiment of the solution of the present invention, it further includes dividing the set of structural parameters according to the manufacturing process to obtain a multi-process set of structural parameters; inputting the multi-process set of structural parameters into the humidity parameter matching model to obtain multi-process internal humidity control parameters and multi-process external humidity control parameters; when producing the hydrogen fuel cell, stage-starting the multi-process internal humidity control parameters to control the internal humidity control system, and stage-starting the multi-process external humidity control parameters to control the external humidity control system to perform humidity control on the production of the hydrogen fuel cell.

[0072] In a specific application scenario, according to the technological process of the hydrogen fuel cell, the humidity control process is divided into different manufacturing process stages, and each manufacturing process stage has different humidity control requirements. According to the requirements of each manufacturing process stage, the set of structural parameters is divided into a multi-process set of structural parameters. Inputting the multi-process set of structural parameters into the humidity parameter matching model, the humidity parameter matching model predicts the internal humidity control parameters and external humidity control parameters of each manufacturing process stage according to the humidity control requirements of each manufacturing process stage. At the beginning of each manufacturing process stage, the internal humidity control system and the external humidity control system are correspondingly started to perform humidity control according to the internal humidity control parameters and the external humidity control parameters respectively. This process is staged, that is, the humidity control parameters of different manufacturing process stages are different, and the humidity control parameters are adaptively set according to different manufacturing process stages to achieve rapid and effective humidity regulation and control, and reduce the battery internal resistance stability coefficient.

[0073] Furthermore, it further includes pre-configuring a synchronous starter. When producing the hydrogen fuel cell, the internal humidity control system and the external humidity control system are synchronously started by the synchronous starter to perform synchronous humidity control on the production of the hydrogen fuel cell. The synchronous starter is responsible for connecting the humidity control system with the internal humidity control system and the external humidity control system, which can be realized through an industrial communication protocol, so that real-time communication can be carried out among the three. When producing the hydrogen fuel cell, the internal humidity control system and the external humidity control system are started and run synchronously, and the internal and external humidity control systems are coordinated with the production pace to ensure that the humidity change matches the change in the battery internal resistance.

[0074] Further, the humidity parameter matching model includes multiple humidity parameter matching branches, and the number of humidity parameter matching branches is the same as the number of divisions of the process stages; the humidity control parameters within multiple processes and the humidity control parameters outside multiple processes are respectively input into the multiple humidity parameter matching branches to obtain the humidity control parameters within multiple processes and the humidity control parameters outside multiple processes.

[0075] In a specific application scenario, the number of humidity parameter matching branches included in the humidity parameter matching model is the same as the number of divisions of the process stages. For example, according to the humidity control requirements, the process flow is divided into three process stages, and the humidity parameter matching model includes three humidity parameter matching branches. Each humidity parameter matching branch corresponds to a process stage one by one, and the internal humidity control parameters and external humidity control parameters are matched for the corresponding process stage. Each humidity parameter matching branch corresponds to a specific process stage one by one, ensuring that the humidity control parameters (internal humidity and external humidity) can be accurately matched according to the requirements of each process stage. For example, in some stages, a higher humidity may be required to ensure the hydration of the membrane electrode, while in other stages, a lower humidity may be required to maintain the performance of the gas diffusion layer; this targeted humidity matching can optimize the humidity control in each stage and avoid performance fluctuations caused by too high or too low humidity. Embodiment II

[0076] Based on the same inventive concept, the embodiment of the present invention discloses a hydrogen fuel cell process optimization system. Refer to Figure 3 as shown, including,

[0077] A structural parameter acquisition module, which is used to acquire the structural parameter set of the hydrogen fuel cell;

[0078] A humidity parameter matching module, which is used to obtain the internal humidity control parameters and external humidity control parameters according to the structural parameter set;

[0079] A humidity control module, which is used to control the internal humidity control system and the external humidity control system to perform humidity control on the production of the hydrogen fuel cell according to the internal humidity control parameters and the external humidity control parameters during the production of the hydrogen fuel cell;

[0080] A humidity control optimization module, which is used to adjust the internal humidity control parameters and the external humidity control parameters according to the monitored battery internal resistance of the hydrogen fuel cell.

[0081] The hydrogen fuel cell process optimization system disclosed in the embodiment of the present invention is used to execute the hydrogen fuel cell process optimization method in the above embodiment. Based on the same inventive concept, it has the same technical effects and will not be elaborated here.

[0082] In summary, for the hydrogen fuel cell process optimization method and system described in the present invention, the internal and external humidity control are linked to ensure that the electrolyte membrane operates in the optimal hydration state, thereby significantly reducing the battery internal resistance and directly enhancing the power density and overall energy conversion efficiency of the hydrogen fuel cell. According to the monitored battery internal resistance situation, the internal humidity control parameters and external humidity control parameters are dynamically adjusted to ensure that under different production environments and conditions, the humidity fluctuations during the production process are effectively reduced, thereby enhancing the product consistency and quality reliability and improving the battery performance.

[0083] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more of the processes Figure 1 or multiple processes and / or blocks

[0085] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more of the processes Figure 1 or multiple processes and / or blocks

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one or more of the processes Figure 1 or multiple processes and / or blocks

[0087] Obviously, the above embodiments are merely examples given for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or alterations can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or alterations derived therefrom still fall within the protection scope of the present invention.

Claims

1. A hydrogen fuel cell process optimization method, characterized in that: include, Obtaining a structural parameter set of a hydrogen fuel cell; Inputting the structural parameter set into a pre-built humidity parameter matching model to obtain internal humidity control parameters and external humidity control parameters; During the production of the hydrogen fuel cell, the internal humidity control system and the external humidity control system are respectively controlled according to the internal humidity control parameters and the external humidity control parameters to control the humidity of the hydrogen fuel cell production; the internal humidity control system is a system that stores water through the battery's own structure or balances the generation and consumption of water by changing the intake flow rate and pressure; the external humidity control system is a system that humidifies the gas introduced into the electrodes in the anode and cathode intake systems through an additionally introduced humidifier; Adjusting the internal humidity control parameter and the external humidity control parameter according to the monitored internal resistance of the hydrogen fuel cell; That The method comprises: performing stability analysis on the monitored battery internal resistance to obtain the battery internal resistance stability coefficient of a batch of hydrogen fuel cells; optimizing the internal humidity control parameters and the external humidity control parameters with minimizing the difference between the battery internal resistance stability coefficient and a preset stability coefficient as a feedback target to obtain optimized humidity control parameters; and performing humidification control on the internal humidity control system and the external humidity control system according to the optimized humidity control parameters.

2. The hydrogen fuel cell process optimization method according to claim 1, characterized in that: The internal humidity control parameter and the external humidity control parameter are adjusted according to the monitored internal resistance of the hydrogen fuel cell, including: Divide the process of the hydrogen fuel cell into stages according to the process, and test the local internal resistance of the stage product at each stage of the process; Analyze the local internal resistance to obtain an identified internal resistance stage; wherein the identified internal resistance stage is a process stage in which the local internal resistance is greater than or equal to a local internal resistance threshold; Determining a local internal resistance index of the internal resistance identification stage; The internal humidity control parameter and the external humidity control parameter are adjusted according to the local internal resistance index.

3. The hydrogen fuel cell process optimization method according to claim 2, characterized in that: Determining the local internal resistance index of the internal resistance identification stage includes: Performing regional division according to the structure of the product at the stage to obtain a plurality of divided regions; The local regional resistance of the plurality of divided regions is tested, and the local regional resistance gradient of the adjacent divided regions is calculated; wherein the local regional resistance gradient is calculated as follows: ； Among them, i and j are the numbers of adjacent divided areas. is the local intra-regional resistance gradient of the adjacent divided regions; is the local area resistance of the i-th partition area; is the local area resistance of the jth partition area; is the distance between the i-th partition area and the j-th partition area; The local internal resistance index of the internal resistance identification stage is determined according to the local regional internal resistance gradient.

4. The hydrogen fuel cell process optimization method according to claim 1, characterized in that: The structural parameter set includes catalyst layer thickness, electrode structure, electrolyte membrane thickness and gas diffusion layer thickness.

5. The hydrogen fuel cell process optimization method according to claim 1, characterized in that: Also includes, Divide the structure parameter set according to process to obtain a multi-process structure parameter set; Inputting the multi-process structure parameter set into the humidity parameter matching model to obtain multi-process internal humidity control parameters and multi-process external humidity control parameters; During the production of the hydrogen fuel cell, the multi-process internal humidity control parameters are started in stages to control the internal humidity control system, and the multi-process external humidity control parameters are started in stages to control the external humidity control system to control the humidity of the hydrogen fuel cell production.

6. The hydrogen fuel cell process optimization method according to claim 5, characterized in that: It also includes a pre-configured synchronous starter, through which the internal humidity control system and the external humidity control system are synchronously started during the production of the hydrogen fuel cell to perform synchronous humidity control on the production of the hydrogen fuel cell.

7. The hydrogen fuel cell process optimization method according to claim 5, characterized in that: Constructing the humidity parameter matching model, including: Extracting a sample catalyst layer thickness set, a sample electrode structure set, a sample gas diffusion layer thickness set, a sample electrolyte membrane thickness set, a sample internal humidity control parameter set, and a sample external humidity control parameter set from the historical data of the hydrogen fuel cell production; A convolutional neural network model is trained with a sample catalyst layer thickness set, a sample electrode structure set, a sample gas diffusion layer thickness set, and a sample electrolyte membrane thickness set as input data, and with the sample in-sample humidity control parameter set and the sample out-of-sample humidity control parameter set as output data to obtain a humidity parameter matching model.

8. The hydrogen fuel cell process optimization method according to claim 7, characterized in that: The humidity parameter matching model includes a plurality of humidity parameter matching branches, and the number of the humidity parameter matching branches is consistent with the number of divisions of the process stages; The multiple in-process humidity control parameters and the multiple out-process humidity control parameters are respectively input into the multiple humidity parameter matching branches to obtain the multiple in-process humidity control parameters and the multiple out-process humidity control parameters.

9. A hydrogen fuel cell process optimization system, characterized in that: include, A structural parameter acquisition module, which is used to obtain a structural parameter set of a hydrogen fuel cell; A humidity parameter matching module, which is used to obtain internal humidity control parameters and external humidity control parameters according to the structural parameter set; A humidity control module, which is used to control the humidity of the hydrogen fuel cell production by controlling the internal humidity control system and the external humidity control system according to the internal humidity control parameters and the external humidity control parameters respectively during the production of the hydrogen fuel cell; the internal humidity control system is a system that stores moisture through the battery structure itself or balances the generation and consumption of moisture by changing the intake flow rate and pressure; the external humidity control system is a system that humidifies the gas introduced into the electrode in the anode and cathode intake systems through an additional humidifier; A humidity control optimization module, which is used to adjust the internal humidity control parameter and the external humidity control parameter according to the monitored battery internal resistance of the hydrogen fuel cell; That The method comprises: performing stability analysis on the monitored battery internal resistance to obtain the battery internal resistance stability coefficient of a batch of hydrogen fuel cells; optimizing the internal humidity control parameters and the external humidity control parameters with minimizing the difference between the battery internal resistance stability coefficient and a preset stability coefficient as a feedback target to obtain optimized humidity control parameters; and performing humidification control on the internal humidity control system and the external humidity control system according to the optimized humidity control parameters.

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