Fuel cell gas flow field optimization control system and method based on automatic regulation control

Abstract

The invention relates to the technical field of cell regulation and control, in particular to a fuel cell gas flow field optimization control system and method based on automatic regulation and control. The method comprises the following steps: deploying a gas flow sensor, a pressure sensor, a temperature sensor and a humidity sensor in a fuel cell, and monitoring gas flow data, gas pressure data, gas temperature data and gas humidity data in real time; gas flow channel structure parameters are obtained, gas distribution flow field coupling simulation and reaction output load evaluation are carried out, and a gas reaction output power load is obtained; and carrying out battery reaction activity influence analysis and gas reaction abnormity quantification on the corresponding reaction distribution area in the fuel battery to obtain a gas reaction distribution abnormity degree, and carrying out reaction distribution non-uniformity determination and gas flow optimization control so as to execute corresponding reaction distribution non-uniformity gas flow control work. According to the invention, uniform distribution of gas in the fuel cell can be ensured, and the performance and stability of the cell are continuously improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery regulation control, and in particular to a fuel cell gas flow field optimization control system and method based on automatic regulation control. Background Art

[0002] Fuel cells are highly efficient energy conversion devices that convert chemical energy into electrical energy. They are widely used in electric vehicles, portable devices, and backup power supplies. The core components of a fuel cell include an anode, cathode, and electrolyte membrane. The reactant gases (such as hydrogen and oxygen) need to be distributed through an appropriate flow field to ensure reaction efficiency and battery output performance. During the operation of the fuel cell, the optimization of the gas flow field plays a vital role in improving battery performance, extending service life, and ensuring stable output. Traditional fuel cell gas flow field design is usually based on experience and experimental data, and optimization is achieved by manually adjusting parameters such as the flow field geometry and gas flow rate. However, gas flow field optimization is not only closely related to the operating conditions of the battery, but is also affected by multiple factors such as environmental factors, load changes, and reaction activity. Traditional optimization methods often lack flexibility in practical applications, cannot achieve real-time and precise adjustments, and have difficulty coping with dynamic changes under different operating conditions. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a fuel cell gas flow field optimization control system and method based on automatic adjustment control to solve at least one of the above technical problems.

[0004] To achieve the above objectives, a fuel cell gas flow field optimization control method based on automatic regulation control includes the following steps:

[0005] Step S1: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the gas inlet, flow channel, and reaction area corresponding to the fuel cell, and using the gas flow sensors, pressure sensors, temperature sensors, and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell in real time;

[0006] Step S2: Obtaining gas flow channel structural parameters corresponding to the fuel cell, and performing a gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell; obtaining the gas flow, gas pressure, gas temperature, and gas humidity corresponding to each distribution area through the gas reaction distribution flow field corresponding to the fuel cell;

[0007] Step S3: Based on the gas flow rate and gas pressure corresponding to each distribution area, a reaction output load evaluation is performed on the corresponding reaction distribution area in the fuel cell to obtain the gas reaction output power load corresponding to each distribution area; based on the gas temperature and gas humidity corresponding to each distribution area, a cell reaction activity impact analysis is performed on the corresponding reaction distribution area in the fuel cell to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area;

[0008] Step S4: Based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, the corresponding reaction distribution area is quantified to obtain the gas reaction distribution anomaly degree corresponding to each distribution area; based on the gas reaction distribution anomaly degree corresponding to each distribution area, the reaction uneven distribution of the gas reaction distribution flow field is determined to obtain the fuel cell gas reaction uneven distribution area; the gas flow of the corresponding fuel cell gas reaction uneven distribution area in the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

[0009] Furthermore, step S1 includes the following steps:

[0010] Step S11: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the corresponding gas inlets, flow channels, and reaction areas of the fuel cell;

[0011] Step S12: using a gas flow sensor to monitor the flow of the fuel cell in real time to obtain gas flow data corresponding to the fuel cell;

[0012] Step S13: using a pressure sensor to monitor the pressure of the fuel cell in real time to obtain gas pressure data corresponding to the fuel cell;

[0013] Step S14: using a temperature sensor to monitor the temperature of the fuel cell in real time to obtain gas temperature data corresponding to the fuel cell;

[0014] Step S15: using a humidity sensor to monitor the humidity of the fuel cell in real time to obtain gas humidity data corresponding to the fuel cell.

[0015] Furthermore, step S2 includes the following steps:

[0016] Step S21: obtaining gas flow channel structural parameters corresponding to the fuel cell, including shape, size, microscopic surface roughness, micro-protrusions, and micro-depression position parameters corresponding to the gas flow channel;

[0017] Step S22: performing topological simulation design on the gas flow channel corresponding to the fuel cell based on the structural parameters of the gas flow channel corresponding to the fuel cell, so as to generate a topological structure simulation model of the gas flow channel corresponding to the fuel cell;

[0018] Step S23: performing a gas distribution flow field coupling simulation on the gas flow channel topology structure simulation model corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell;

[0019] Step S24: performing reaction distribution division on the gas reaction distribution flow field corresponding to the fuel cell to obtain various gas reaction distribution areas corresponding to the fuel cell;

[0020] Step S25: extracting gas parameters of the corresponding gas reaction distribution flow field based on each gas reaction distribution area to obtain the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area.

[0021] Furthermore, step S23 includes the following steps:

[0022] Step S231: obtaining adsorption, desorption, and collision behaviors of reactant gas molecules in the corresponding gas flow channel of the fuel cell, and performing a gas flow channel characteristic analysis on a topological structure simulation model of the corresponding gas flow channel of the fuel cell based on the adsorption, desorption, and collision behaviors of the reactant gas molecules in the corresponding gas flow channel of the fuel cell, to obtain gas flow channel transmission characteristic parameters corresponding to the fuel cell, including diffusion coefficients and viscosity coefficients corresponding to the reactant gas molecules;

[0023] Step S232: performing a gas transmission constraint analysis on the gas flow channel topology simulation model corresponding to the fuel cell based on the gas flow channel transmission characteristic parameters corresponding to the fuel cell, so as to generate a gas flow channel transmission constraint condition corresponding to the fuel cell;

[0024] Step S233: performing finite element simulation division on the gas flow channel topology structure simulation model corresponding to the fuel cell to obtain simulation unit models of each gas flow channel structure;

[0025] Step S234: performing unit simulation numerical simulation on each gas flow channel structure simulation unit model based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution, and gas humidity distribution within each gas flow channel unit;

[0026] Step S235: Based on the gas flow channel transmission constraints corresponding to the fuel cell, a gas distribution flow field coupling simulation is performed on the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution and gas humidity distribution in each gas flow channel unit to generate a gas reaction distribution flow field corresponding to the fuel cell.

[0027] Furthermore, step S3 includes the following steps:

[0028] Step S31: obtaining the gas participation reaction rate and gas reaction energy loss corresponding to each distribution area through the corresponding reaction distribution area in the fuel cell;

[0029] Step S32: performing distribution gradient analysis on the gas flow and gas pressure corresponding to each distribution area to obtain the gas flow distribution gradient and gas pressure distribution gradient corresponding to each distribution area;

[0030] Step S33: performing reaction rate impact assessment analysis on the gas participating reaction rate corresponding to each distribution area based on the gas flow distribution gradient and the gas pressure distribution gradient corresponding to each distribution area, and obtaining the flow reaction rate impact degree and the pressure reaction rate impact degree corresponding to each distribution area;

[0031] Step S34: Based on the gas reaction energy loss corresponding to each distribution area, the energy conversion efficiency of the corresponding reaction distribution area in the fuel cell is evaluated to obtain the gas reaction energy conversion efficiency corresponding to each distribution area; based on the gas reaction energy conversion efficiency corresponding to each distribution area, the reaction output load is evaluated and calculated using the reaction power load calculation formula for the flow reaction rate influence and the pressure reaction rate influence corresponding to each distribution area to obtain the gas reaction output power load corresponding to each distribution area;

[0032] Step S35: performing a cell reaction activity impact analysis on the corresponding reaction distribution areas in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, and obtaining the cell gas reaction activity impact efficiency corresponding to each distribution area.

[0033] Furthermore, the reactive power load calculation formula is specifically as follows:

[0034]

[0035] Where, ε i is the gas reaction output power load corresponding to the i-th distribution area, n is the total number of distribution areas, T is the time interval range parameter, t is the time variable parameter, η i is the gas reaction energy conversion efficiency corresponding to the i-th distribution area, F i (t) is the gas flow rate in the ith distribution area at time t, Pi (t) is the gas pressure in the ith distribution area at time t, α i is the influence degree of the flow reaction rate corresponding to the i-th distribution area, β i is the influence degree of the pressure reaction rate corresponding to the i-th distribution area, and ξ is the correction coefficient of the gas reaction output power load.

[0036] Furthermore, step S35 includes the following steps:

[0037] Step S351: performing cell reaction activity measurement on corresponding reaction distribution areas within the fuel cell to obtain cell reaction activity distribution corresponding to each distribution area;

[0038] Step S352: performing a statistical analysis on the fluctuation amplitudes of the gas temperature and gas humidity corresponding to each distribution area to obtain the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area;

[0039] Step S353: evaluating the battery reaction activity loss distribution corresponding to each distribution area based on the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area, so as to obtain the temperature fluctuation reaction activity loss and humidity fluctuation reaction activity loss corresponding to each distribution area;

[0040] Step S354: Calculating the ratio of the temperature fluctuation reaction activity loss and the humidity fluctuation reaction activity loss corresponding to each distribution area to obtain the temperature-humidity reaction activity loss ratio corresponding to each distribution area;

[0041] Step S355: performing a battery reaction activity impact analysis on the battery reaction activity distribution corresponding to each distribution area based on the temperature-humidity reaction activity loss ratio corresponding to each distribution area, and obtaining the battery gas reaction activity impact efficiency corresponding to each distribution area.

[0042] Furthermore, step S4 includes the following steps:

[0043] Step S41: quantifying the gas reaction anomaly in the reaction distribution area corresponding to the fuel cell using a gas reaction distribution anomaly calculation formula based on the gas reaction output power load corresponding to each distribution area and the cell gas reaction activity impact efficiency, to obtain the gas reaction distribution anomaly degree corresponding to each distribution area;

[0044] Step S42: comparing and judging the degree of gas reaction distribution abnormality corresponding to the corresponding distribution area according to a preset gas reaction distribution abnormality threshold; if the degree of gas reaction distribution abnormality is less than the preset gas reaction distribution abnormality threshold, iteratively judging the degree of gas reaction distribution abnormality corresponding to the next distribution area; if the degree of gas reaction distribution abnormality is greater than or equal to the preset gas reaction distribution abnormality threshold, determining the corresponding distribution area as a fuel cell gas reaction uneven distribution area;

[0045] Step S43: The gas flow rate of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel, so as to send a control instruction to the central control system according to the gas distribution corresponding to the fuel cell gas reaction uneven distribution area, and accurately control the corresponding opening of the adjustable micro valve according to the control instruction, change the corresponding geometric shape of the gas flow channel, and optimize the distribution of the reaction gas in the gas flow channel, so as to perform the corresponding reaction uneven distribution gas flow control work.

[0046] Furthermore, the calculation formula for the gas reaction distribution anomaly in step S41 is specifically:

[0047]

[0048] Where Δ∈ i is the abnormal degree of gas reaction distribution corresponding to the i-th distribution area, ε i is the gas reaction output power load corresponding to the i-th distribution area, A i is the effective gas reaction area corresponding to the i-th distribution area, f is the gas reaction frequency, is the battery gas reaction activity affecting the efficiency of the ith distribution area at frequency f, is the reaction efficiency corresponding to the i-th distribution area under low frequency state, δ i is the reaction frequency dependence parameter corresponding to the ith distribution area, ρ is the gas reaction activity efficiency attenuation index, θ i is the gas reaction influence weight coefficient corresponding to the i-th distribution area, μ i is the gas reactivity index attenuation factor corresponding to the i-th distribution area, C i is the basic reaction inhibition degree corresponding to the i-th distribution area, γ i is the reaction frequency response constant corresponding to the ith distribution area, and ζ is the correction coefficient of the abnormal degree of gas reaction distribution.

[0049] Furthermore, the present invention also provides a fuel cell gas flow field optimization control system based on automatic regulation control, which is used to execute the fuel cell gas flow field optimization control method based on automatic regulation control as described above. The fuel cell gas flow field optimization control system based on automatic regulation control includes:

[0050] The fuel cell gas parameter monitoring module is used to deploy gas flow sensors, pressure sensors, temperature sensors and humidity sensors at the gas inlet, flow channel and reaction area corresponding to the fuel cell, and use the gas flow sensors, pressure sensors, temperature sensors and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell in real time;

[0051] The gas flow field simulation and partitioning module is used to obtain the gas flow channel structural parameters corresponding to the fuel cell, and perform gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell to generate the gas reaction distribution flow field corresponding to the fuel cell; the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area are obtained through the gas reaction distribution flow field corresponding to the fuel cell;

[0052] A partitioned gas reaction load assessment module is used to assess the reaction output load of the corresponding reaction distribution area in the fuel cell based on the gas flow rate and gas pressure corresponding to each distribution area, so as to obtain the gas reaction output power load corresponding to each distribution area; and to analyze the cell reaction activity impact of the corresponding reaction distribution area in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, so as to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area;

[0053] The gas uneven distribution optimization control module is used to quantify the gas reaction anomaly in the corresponding reaction distribution area based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, and obtain the gas reaction distribution anomaly degree corresponding to each distribution area; determine the reaction uneven distribution of the gas reaction distribution flow field based on the gas reaction distribution anomaly degree corresponding to each distribution area to obtain the fuel cell gas reaction uneven distribution area; optimize the gas flow control of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

[0054] Beneficial effects of the present invention:

[0055] 1. The fuel cell gas flow field optimization control method based on automatic regulation and control proposed in the present invention has the beneficial effect of real-time monitoring of various parameters during fuel cell operation by deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the corresponding gas inlet, flow channel, and reaction area of ​​the fuel cell. The gas flow sensor is used to monitor the gas flow rate in real time to assess whether the gas has fully entered the reaction area and maintained an appropriate reaction rate. The pressure sensor can detect the pressure of the gas in the flow channel to ensure that the gas delivery meets the design requirements and prevent the performance degradation or damage of the fuel cell due to excessively high or low pressure. The temperature sensor is used to monitor the temperature of the gas to ensure that the operating temperature range of the fuel cell is always in the optimal state to prevent efficiency loss caused by overheating or uneven temperature. The humidity sensor is used to control the humidity level in the fuel cell to ensure that the humidity is within the optimal range to avoid the impact of excessively low or high humidity on reaction efficiency or battery life. The real-time data from these sensors can provide basic data support for subsequent reaction analysis, fault diagnosis, and optimization adjustment, helping to ensure the stability and performance of the fuel cell under complex operating conditions. Secondly, the structural parameters of the fuel cell gas flow channel are obtained, and based on the real-time monitored gas flow, gas pressure, gas temperature and gas humidity data, the gas distribution flow field of the fuel cell gas flow channel is coupled to simulate the computational fluid dynamics (CFD) simulation. In this process, by constructing a mathematical model of the gas flow channel and combining it with the actual gas flow, pressure, temperature and humidity data, the flow characteristics of the gas inside the fuel cell can be accurately predicted, especially the distribution in different areas. The simulated gas reaction distribution flow field can reveal whether the gas flow in the reaction area is uniform and which areas have excessive or insufficient gas. Furthermore, the simulation results can provide a basis for subsequent battery performance optimization, helping designers to make necessary adjustments to the structure of the flow channel and optimize the distribution of gas inside the fuel cell, so as to monitor and adjust the dynamic changes of the gas reaction in the fuel cell under different working conditions in real time. Then, based on the gas flow and gas pressure data of each distribution area, the reaction output load of each reaction area in the fuel cell is evaluated. The fuel supply situation in each reaction area can be evaluated, thereby judging the battery output power load of each area. This process helps to identify the problem of uneven power output of the fuel cell in different working areas and ensure that the battery can balance the load in each area. At the same time, the impact analysis of battery reaction activity based on the gas temperature and humidity data of each distribution area can evaluate the impact of temperature and humidity on the reaction rate and help identify the negative effects of abnormal temperature and humidity on reaction efficiency. This step can accurately evaluate the battery reaction activity in each area, ensure that the fuel cells in each area operate under optimal working conditions, and avoid reduced reaction efficiency or battery damage due to unsuitable temperature and humidity.Finally, by further analyzing the degree of abnormality in the gas reaction distribution in each area, this process can identify which areas have uneven gas reaction problems by quantifying the changes in gas flow, pressure, temperature and humidity. For example, in some areas, the reaction load is too high due to poor airflow or improper temperature and humidity control, which in turn affects the overall performance. Based on these abnormal evaluations, the areas with uneven gas reaction distribution are further determined, providing a basis for subsequent optimization. By deploying adjustable microvalves in the gas flow channel and finely adjusting the gas flow, the gas flow distribution can be optimized and the uneven reaction phenomenon can be reduced. This optimized control can greatly improve the working efficiency of the fuel cell, so that the gas is evenly distributed throughout the reaction area, thereby improving the battery's reaction efficiency, reducing energy loss, and extending the battery's service life. Through continuous monitoring and adjustment, it can ensure that the fuel cell always maintains optimal performance under various operating conditions, thereby improving the flexibility of the fuel cell gas distribution control.

[0056] 2. The fuel cell gas flow field optimization control system based on automatic adjustment control proposed in the present invention is composed of a fuel cell gas parameter monitoring module, a gas flow field simulation and partitioning module, a partitioned gas reaction load evaluation module and a gas uneven distribution optimization control module. It can realize any fuel cell gas flow field optimization control method based on automatic adjustment control described in the present invention, and is used to combine the operations between computer programs running on each module to realize the fuel cell gas flow field optimization control method based on automatic adjustment control. The internal structures of the system cooperate with each other, which can greatly reduce repetitive work and manpower investment, and can quickly and effectively provide a more accurate and efficient fuel cell gas flow field optimization control process based on automatic adjustment control, thereby simplifying the operation process of the fuel cell gas flow field optimization control system based on automatic adjustment control. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0058] Figure 1 Schematic diagram of the steps of the fuel cell gas flow field optimization control method based on automatic adjustment control of the present invention;

[0059] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0060] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0061] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. It is obvious that the embodiments described are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts are within the scope of protection of the present invention.

[0062] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0063] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0064] To achieve this, please refer to Figures 1 to 3 The present invention provides a fuel cell gas flow field optimization control method based on automatic regulation control, the method comprising the following steps:

[0065] Step S1: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the gas inlet, flow channel, and reaction area corresponding to the fuel cell, and using the gas flow sensors, pressure sensors, temperature sensors, and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell in real time;

[0066] Step S2: Obtaining gas flow channel structural parameters corresponding to the fuel cell, and performing a gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell; obtaining the gas flow, gas pressure, gas temperature, and gas humidity corresponding to each distribution area through the gas reaction distribution flow field corresponding to the fuel cell;

[0067] Step S3: Based on the gas flow rate and gas pressure corresponding to each distribution area, a reaction output load evaluation is performed on the corresponding reaction distribution area in the fuel cell to obtain the gas reaction output power load corresponding to each distribution area; based on the gas temperature and gas humidity corresponding to each distribution area, a cell reaction activity impact analysis is performed on the corresponding reaction distribution area in the fuel cell to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area;

[0068] Step S4: Based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, the corresponding reaction distribution area is quantified to obtain the gas reaction distribution anomaly degree corresponding to each distribution area; based on the gas reaction distribution anomaly degree corresponding to each distribution area, the reaction uneven distribution of the gas reaction distribution flow field is determined to obtain the fuel cell gas reaction uneven distribution area; the gas flow of the corresponding fuel cell gas reaction uneven distribution area in the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

[0069] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a flow chart showing the steps of a fuel cell gas flow field optimization control method based on automatic regulation control according to the present invention. In this example, the fuel cell gas flow field optimization control method based on automatic regulation control includes the following steps:

[0070] Step S1: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the gas inlet, flow channel, and reaction area corresponding to the fuel cell, and using the gas flow sensors, pressure sensors, temperature sensors, and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell in real time;

[0071] In an embodiment of the present invention, a variety of sensors, including gas flow sensors, pressure sensors, temperature sensors and humidity sensors, are deployed at the gas inlet, flow channel and reaction area of ​​the fuel cell. The gas flow sensor is used to measure the gas flow entering the reaction area of ​​the fuel cell in real time and output data in unit flow (such as standard cubic meters per hour). The pressure sensor is installed at different positions of the gas inlet and flow channel for real-time monitoring of gas pressure changes, and the unit is usually Pascal (Pa). The temperature sensor and humidity sensor monitor the temperature and humidity of the gas respectively to ensure that the temperature and humidity conditions of the fuel cell are suitable during operation, and prevent the battery performance from degrading due to environmental changes. All sensors are connected to the central control unit through a data acquisition system, and finally the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell are obtained.

[0072] Step S2: Obtaining gas flow channel structural parameters corresponding to the fuel cell, and performing a gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell; obtaining the gas flow, gas pressure, gas temperature, and gas humidity corresponding to each distribution area through the gas reaction distribution flow field corresponding to the fuel cell;

[0073] In an embodiment of the present invention, the structural parameters of the gas flow channels corresponding to the fuel cell, including the geometric dimensions of the flow channels, the connection method between the flow channels, and the material properties of the flow channel surfaces, are obtained. A gas flow field simulation is then performed using CFD (computational fluid dynamics) simulation software. The gas flow rate, gas pressure, gas temperature, and humidity data are input into the simulation model to perform coupled calculations of the gas distribution flow field. The numerical simulations are used to determine the airflow, pressure, temperature, and humidity distributions within each gas flow channel region within the fuel cell, thereby generating an accurate gas reaction distribution flow field. This process utilizes the principles of fluid dynamics, taking into account the effects of variations in gas velocity, pressure, temperature, and humidity in different regions. Gas parameters are extracted from the coupled simulation results based on the defined gas reaction distribution regions. For each reaction region, gas parameters such as gas flow rate, pressure, temperature, and humidity are extracted to obtain detailed gas parameters within each region. All extracted parameters serve as the basis for optimized control and regulation to ensure gas stability and reaction efficiency within each reaction region of the fuel cell. Ultimately, the gas flow rate, gas pressure, gas temperature, and gas humidity corresponding to each distribution region are obtained.

[0074] Step S3: Based on the gas flow rate and gas pressure corresponding to each distribution area, a reaction output load evaluation is performed on the corresponding reaction distribution area in the fuel cell to obtain the gas reaction output power load corresponding to each distribution area; based on the gas temperature and gas humidity corresponding to each distribution area, a cell reaction activity impact analysis is performed on the corresponding reaction distribution area in the fuel cell to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area;

[0075] In an embodiment of the present invention, the gas flow rate and gas pressure of each distribution area are further evaluated based on the gas reaction distribution flow field data. The obtained gas flow rate and gas pressure data are used to calculate the output load of the fuel cell reaction area. The load evaluation is primarily based on the impact of the gas flow rate of each distribution area within the fuel cell on the reaction activity. During the evaluation process, a mathematical model is used to combine the reaction rate to calculate the gas reaction output power load of each area. At the same time, the impact of the fuel cell reaction activity is analyzed based on the gas temperature and humidity data. Cell reaction activity is strongly affected by changes in temperature and humidity. Therefore, the impact of gas temperature and humidity on the reaction activity efficiency of different areas is analyzed to evaluate the gas reaction activity impact efficiency of each area. This can determine which areas have more active reactions and which areas have slow or incomplete reactions. Ultimately, the gas reaction activity impact efficiency corresponding to each distribution area is obtained.

[0076] Step S4: Based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, the corresponding reaction distribution area is quantified to obtain the gas reaction distribution anomaly degree corresponding to each distribution area; based on the gas reaction distribution anomaly degree corresponding to each distribution area, the reaction uneven distribution of the gas reaction distribution flow field is determined to obtain the fuel cell gas reaction uneven distribution area; the gas flow of the corresponding fuel cell gas reaction uneven distribution area in the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

[0077] In an embodiment of the present invention, the degree of gas reaction distribution anomaly in each distribution area is calculated by comprehensively analyzing the gas reaction output power load and the impact of the cell gas reaction activity on efficiency. Specifically, if the gas flow rate or gas pressure in a distribution area is abnormal, or the gas temperature and humidity do not meet the expected range, it indicates that the gas reaction in that area is abnormal. By quantifying abnormal data, such as the deviation of the reaction output power load, the mismatch of gas temperature and humidity, etc., the degree of gas reaction anomaly in each area is determined. Furthermore, based on the degree of gas reaction anomaly in each area, the reaction distribution unevenness of the gas flow channel is analyzed to determine which areas have obvious unevenness in gas flow, temperature, humidity, etc. Finally, the adjustable microvalves preset in the fuel cell gas flow channel will come into play. Based on the identified gas reaction uneven distribution area, the microvalves will automatically adjust the gas flow in the corresponding area to optimize the gas distribution flow field. By fine-tuning the gas flow rate, the gas reaction conditions in each area are guaranteed to be optimal, thereby improving the overall operating efficiency and stability of the fuel cell. This process, based on real-time feedback data, ensures the precise execution of gas flow optimization control, guarantees the efficient operation of the fuel cell, and ultimately performs the corresponding reaction uneven distribution gas flow control work.

[0078] Furthermore, step S1 includes the following steps:

[0079] Step S11: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the corresponding gas inlets, flow channels, and reaction areas of the fuel cell;

[0080] Step S12: using a gas flow sensor to monitor the flow of the fuel cell in real time to obtain gas flow data corresponding to the fuel cell;

[0081] Step S13: using a pressure sensor to monitor the pressure of the fuel cell in real time to obtain gas pressure data corresponding to the fuel cell;

[0082] Step S14: using a temperature sensor to monitor the temperature of the fuel cell in real time to obtain gas temperature data corresponding to the fuel cell;

[0083] Step S15: using a humidity sensor to monitor the humidity of the fuel cell in real time to obtain gas humidity data corresponding to the fuel cell.

[0084] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0085] Step S11: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the corresponding gas inlets, flow channels, and reaction areas of the fuel cell;

[0086] In an embodiment of the present invention, a gas flow sensor, a pressure sensor, a temperature sensor, and a humidity sensor are deployed at the gas inlet, flow channel, and reaction area of ​​the fuel cell. When deployed, the gas flow sensor should be installed at the gas inlet of the fuel cell to monitor the gas flow in real time. The sensor adopts the principle of a thermal sensor or a differential pressure sensor, and is connected to the current signal output module through the sensor's sensing element to read the gas flow data in real time; the pressure sensor is deployed in the reaction area or gas flow channel inside the fuel cell, and senses the gas pressure through the principle of a piezoelectric element or a strain gauge, and outputs the measured pressure data through an electrical signal; the temperature sensor and the humidity sensor are installed at key positions in the gas flow path and the reaction area respectively. The temperature sensor uses a thermocouple or RTD (platinum resistance detector) to measure the temperature change of the gas; the humidity sensor uses the principle of a capacitive sensor or a relative humidity sensor to collect the gas humidity data in real time. All sensors are connected to the central control unit through a data acquisition system to form a complete monitoring system to collect the gas flow, pressure, temperature, and humidity data of the fuel cell in real time.

[0087] Step S12: using a gas flow sensor to monitor the flow of the fuel cell in real time to obtain gas flow data corresponding to the fuel cell;

[0088] In an embodiment of the present invention, a gas flow sensor is used to monitor the flow of a fuel cell in real time to obtain gas flow data corresponding to the fuel cell. During implementation, the flow sensor is located at the gas inlet and adopts a thermal flow sensor. The sensor uses the difference between the heat source and the temperature sensor to detect the gas flow rate. In specific operation, the heating element of the sensor will release a certain amount of heat to the gas. The flow of the gas will take away the heat and change the temperature distribution of the thermocouple. The gas flow is calculated by calculating the temperature change. During the real-time monitoring of the flow, the sensor converts the flow data into an electrical signal output and transmits it to the data acquisition system to ensure real-time acquisition and recording of the flow changes of the gas inside the fuel cell, and finally obtain the gas flow data corresponding to the fuel cell.

[0089] Step S13: using a pressure sensor to monitor the pressure of the fuel cell in real time to obtain gas pressure data corresponding to the fuel cell;

[0090] In an embodiment of the present invention, the pressure of the fuel cell is monitored in real time by using a pressure sensor to obtain gas pressure data. In implementation, the pressure sensor should be deployed in the reaction area or flow channel inside the fuel cell. The specific location is determined according to the gas flow path and key control points. The sensor used is usually a piezoelectric or strain gauge pressure sensor. The pressure sensor senses the change in gas pressure, causing the sensing element to produce a slight deformation, and outputs an electrical signal proportional to the gas pressure after circuit conversion. During the real-time monitoring process, the sensor continuously measures the pressure value and transmits it to the control system in real time. The system adjusts the operating state of the fuel cell according to the signal change, and finally obtains the gas pressure data corresponding to the fuel cell.

[0091] Step S14: using a temperature sensor to monitor the temperature of the fuel cell in real time to obtain gas temperature data corresponding to the fuel cell;

[0092] In an embodiment of the present invention, the temperature of the fuel cell is monitored in real time by using a temperature sensor to obtain the temperature data of the gas. During the implementation process, the temperature sensor should be installed at key positions of the gas inlet, reaction zone and outlet of the fuel cell. A thermocouple or RTD (platinum resistance) temperature sensor can be used. When working, the thermocouple sensor will generate a voltage change based on the temperature difference between the materials, and the RTD sensor measures the temperature through the characteristic of resistance changing with temperature. The temperature sensor converts the real-time temperature data into an electrical signal and transmits it to the data acquisition system. The system will adjust the gas flow and operating conditions of the fuel cell according to the temperature change to ensure that the internal temperature of the battery remains within the preset range, avoid affecting the performance and safety of the fuel cell due to excessively high or low temperature, and finally obtain the gas temperature data corresponding to the fuel cell.

[0093] Step S15: using a humidity sensor to monitor the humidity of the fuel cell in real time to obtain gas humidity data corresponding to the fuel cell.

[0094] In an embodiment of the present invention, the humidity of the fuel cell is monitored in real time by using a humidity sensor to obtain gas humidity data. During implementation, the humidity sensor should be installed in the gas flow channel or reaction area inside the fuel cell. A capacitive humidity sensor is usually used. The sensor determines the relative humidity of the gas by measuring the change in capacitance. As the humidity changes, the capacitance value inside the sensor changes. The sensor outputs a corresponding electrical signal based on this change. The humidity data will be transmitted to the data acquisition system in real time. By monitoring and feedback of the humidity data, it can be determined whether the gas humidity meets the working requirements of the fuel cell, and the operating state of the fuel cell can be adjusted according to the humidity change, and finally the gas humidity data corresponding to the fuel cell can be obtained.

[0095] Furthermore, step S2 includes the following steps:

[0096] Step S21: obtaining gas flow channel structural parameters corresponding to the fuel cell, including shape, size, microscopic surface roughness, micro-protrusions, and micro-depression position parameters corresponding to the gas flow channel;

[0097] Step S22: performing topological simulation design on the gas flow channel corresponding to the fuel cell based on the structural parameters of the gas flow channel corresponding to the fuel cell, so as to generate a topological structure simulation model of the gas flow channel corresponding to the fuel cell;

[0098] Step S23: performing a gas distribution flow field coupling simulation on the gas flow channel topology structure simulation model corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell;

[0099] Step S24: performing reaction distribution division on the gas reaction distribution flow field corresponding to the fuel cell to obtain various gas reaction distribution areas corresponding to the fuel cell;

[0100] Step S25: extracting gas parameters of the corresponding gas reaction distribution flow field based on each gas reaction distribution area to obtain the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area.

[0101] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in the embodiment, step S2 includes the following steps:

[0102] Step S21: obtaining gas flow channel structural parameters corresponding to the fuel cell, including shape, size, microscopic surface roughness, micro-protrusions, and micro-depression position parameters corresponding to the gas flow channel;

[0103] In an embodiment of the present invention, the gas flow channel structure of the fuel cell is obtained by scanning or digital modeling technology. CT scanning, laser scanning or three-dimensional modeling tools can be used to accurately obtain the geometric shape and size of the gas flow channel. Then, a fine surface analysis technology is used to obtain the microstructure of the inner surface of the gas flow channel, including surface roughness, tiny protrusions and tiny recesses position parameters. For the micro surface roughness, an atomic force microscope (AFM) or a scanning electron microscope (SEM) is used to measure the details of the surface structure to obtain accurate surface profile data. Through this process, the gas flow channel structure of the fuel cell can be understood in detail, and finally the gas flow channel structural parameters corresponding to the fuel cell are obtained, including the shape, size, micro surface roughness, tiny protrusions and tiny recesses position parameters corresponding to the gas flow channel.

[0104] Step S22: performing topological simulation design on the gas flow channel corresponding to the fuel cell based on the structural parameters of the gas flow channel corresponding to the fuel cell, so as to generate a topological structure simulation model of the gas flow channel corresponding to the fuel cell;

[0105] In an embodiment of the present invention, after obtaining the geometric and microscopic characteristic parameters of the gas flow channel structure, computational fluid dynamics (CFD) software is used to perform gas flow channel topology simulation design. For example, ANSYS Fluent, COMSOL Multiphysics and other software tools are used for modeling, and the geometric parameters, surface roughness and other microscopic structural characteristics of the gas flow channel are input to construct a preliminary topological model of the flow channel. At this time, information such as the size, shape, and surface roughness of the flow channel is processed by a numerical simulation algorithm to optimize the design of the gas flow channel to ensure that the layout of the flow channel can effectively support the reaction process of the gas flow and the fuel cell. Through topological optimization, the goals of improving gas flow uniformity and reducing flow resistance can be achieved, and finally a simulation model of the gas flow channel topological structure corresponding to the fuel cell is generated.

[0106] Step S23: performing a gas distribution flow field coupling simulation on the gas flow channel topology structure simulation model corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell;

[0107] In an embodiment of the present invention, once the topological structure model of the gas flow channel is established, a coupled simulation of the gas distribution flow field is performed. Through simulation software such as Fluent or OpenFOAM, data such as gas flow, pressure, temperature and humidity in a real working environment are input to carry out simulation analysis of multi-physical field coupling. These data are provided by sensors and change dynamically according to the operating state of the fuel cell. During the simulation process, multiple factors such as gas flow, temperature change, and humidity regulation interact with each other, affecting the reaction distribution and flow field morphology of the gas. The coupled simulation can reflect the flow field distribution, turbulence effect and thermal and humidity influence in the gas flow channel, and finally generate the gas reaction distribution flow field corresponding to the fuel cell.

[0108] Step S24: performing reaction distribution division on the gas reaction distribution flow field corresponding to the fuel cell to obtain various gas reaction distribution areas corresponding to the fuel cell;

[0109] In an embodiment of the present invention, the reaction distribution flow field of the gas flow channel in the fuel cell is divided by analyzing the coupling simulation results, and the reaction distribution is regionalized according to factors such as gas flow velocity, gas concentration and reaction rate using an analysis method based on thermodynamics and fluid mechanics. In this process, the flow field analysis results and physical models are used to quantitatively divide the gas reaction area, and parameters such as gas flow, temperature and humidity in different reaction zones are determined. For example, the gas flow and reaction characteristics of different areas can be calibrated through streamline diagrams, velocity field diagrams and temperature distribution diagrams, and the characteristics of each reaction area can be specifically analyzed and optimized to finally obtain the gas reaction distribution areas corresponding to the fuel cell.

[0110] Step S25: extracting gas parameters of the corresponding gas reaction distribution flow field based on each gas reaction distribution area to obtain the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area.

[0111] In an embodiment of the present invention, gas parameters are extracted from the coupled simulation results for each divided gas reaction distribution area. For each reaction area, gas flow, pressure, temperature, humidity and other parameters are extracted, and the gas flow characteristics of each area are obtained by corresponding calculation methods. The extraction method can be automated by post-processing software, and the gas parameter data of a specific area is extracted through flow field analysis. In this process, a numerical integration method can be used to perform segmented calculations on the gas flow in the flow channel to obtain detailed parameters of the gas in each area. All extracted parameters will be used as the basis for optimization control and adjustment to ensure the stability and reaction efficiency of the gas in each reaction area of ​​the fuel cell, and finally the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area are obtained.

[0112] Furthermore, step S23 includes the following steps:

[0113] Step S231: obtaining adsorption, desorption, and collision behaviors of reactant gas molecules in the corresponding gas flow channel of the fuel cell, and performing a gas flow channel characteristic analysis on a topological structure simulation model of the corresponding gas flow channel of the fuel cell based on the adsorption, desorption, and collision behaviors of the reactant gas molecules in the corresponding gas flow channel of the fuel cell, to obtain gas flow channel transmission characteristic parameters corresponding to the fuel cell, including diffusion coefficients and viscosity coefficients corresponding to the reactant gas molecules;

[0114] In an embodiment of the present invention, the adsorption, desorption, and collision behaviors of reactant gas molecules within the fuel cell gas flow channel simulation model must first be considered. Specifically, the particle tracking method (PTM) is used to dynamically track the gas molecules by simulating the interactions between the gas molecules and the flow channel walls and the gas molecules within the flow channel. During this process, the adsorption process of the gas molecules on the flow channel walls, namely, the physical adsorption and chemical adsorption mechanisms of the gas molecules on the solid wall, must be considered. Furthermore, the desorption process should be considered in combination with factors such as the wall temperature, pressure, and gas type. An adsorption-desorption model (e.g., the Langmuir adsorption model) is used to describe the probability of gas molecules desorbing from the surface. For the collision behavior of the gas molecules, a gas kinetic model (e.g., the Boltzmann equation) is used to simulate the gas molecule collision process, thereby obtaining the diffusion coefficient and viscosity coefficient of the gas molecules. Based on the simulation results, the gas flow characteristics of the fuel cell gas flow channel topology can be analyzed to obtain the transport characteristic parameters of the diffusion and flow of the gas molecules within the flow channel. Ultimately, the gas flow channel transport characteristic parameters corresponding to the fuel cell are obtained, including the diffusion coefficient and viscosity coefficient corresponding to the reactant gas molecules.

[0115] Step S232: performing a gas transmission constraint analysis on the gas flow channel topology simulation model corresponding to the fuel cell based on the gas flow channel transmission characteristic parameters corresponding to the fuel cell, so as to generate a gas flow channel transmission constraint condition corresponding to the fuel cell;

[0116] In an embodiment of the present invention, a gas transmission constraint analysis is performed based on the previously obtained gas flow channel transmission characteristic parameters. At this time, the topological structure of the gas flow channel is analyzed in detail with the help of fluid dynamics simulation software (such as ANSYS Fluent). By introducing gas flow constraint conditions and combining the diffusion coefficient and viscosity coefficient of the gas, the boundary conditions of pressure, temperature and humidity in the gas flow channel are defined to simulate the actual flow process of the gas in the flow channel. In order to ensure the accuracy and practicality of the transmission, the momentum, energy and mass conservation equations are used to perform constraint analysis to obtain the transmission constraint conditions of each area inside the flow channel. These constraint conditions include the speed limit of the gas flow, the temperature change range and the humidity change range, and finally the gas flow channel transmission constraint conditions corresponding to the fuel cell are generated.

[0117] Step S233: performing finite element simulation division on the gas flow channel topology structure simulation model corresponding to the fuel cell to obtain simulation unit models of each gas flow channel structure;

[0118] In an embodiment of the present invention, finite element division is performed on a simulation platform based on the topological structure of the fuel cell gas flow channel. This process usually uses computer-aided design (CAD) tools to model the flow channel geometry, and uses finite element meshing technology to perform detailed discretization on the flow channel area. In this step, the flow channel geometry model is first imported or generated, and then subdivided using a meshing tool (such as ANSYS Mesh) to ensure the quality and accuracy of the mesh. In order to ensure the accuracy of the simulation results, it is usually necessary to use a refined mesh method. A smaller mesh size is used in complex areas such as the bends of the flow channel or areas where the airflow changes drastically, while a larger mesh can be used in areas where the airflow is stable. During the division process, the topological relationship of the mesh should ensure that there is no overlap or interlacing, and the relative positions between the meshes need to ensure physical correctness, and finally, each gas flow channel structure simulation unit model is obtained.

[0119] Step S234: performing unit simulation numerical simulation on each gas flow channel structure simulation unit model based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution, and gas humidity distribution within each gas flow channel unit;

[0120] In an embodiment of the present invention, numerical simulation is performed on each gas flow channel unit based on the working environment parameters of the fuel cell, such as gas flow, pressure, temperature and humidity data. In specific implementation, unit-level simulation is performed using finite element analysis software (such as ANSYS Fluent). Combined with the previously generated gas flow channel unit model, the distribution characteristics of the gas in each flow channel unit are obtained through numerical calculation. First, steady-state or transient flow calculations are performed on each unit to solve important physical quantities such as gas flow velocity distribution, pressure field, temperature field and humidity field. During the simulation process, appropriate boundary conditions must be set, such as inlet flow, outlet pressure, wall heat flux, etc., to ensure the reliability of the simulation results. The distribution of gas flow, gas pressure, gas temperature and humidity in each unit is obtained through numerical solution, and finally the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution and gas humidity distribution in each gas flow channel unit are generated.

[0121] Step S235: Based on the gas flow channel transmission constraints corresponding to the fuel cell, a gas distribution flow field coupling simulation is performed on the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution and gas humidity distribution in each gas flow channel unit to generate a gas reaction distribution flow field corresponding to the fuel cell.

[0122] In an embodiment of the present invention, a flow field coupling simulation is performed based on the previously obtained gas flow channel transmission constraint conditions and the corresponding gas flow distribution data. This process adopts a flow field coupling algorithm (for example, a coupling model based on fluid dynamics and reaction kinetics) to obtain a comprehensive distribution flow field of the fuel cell gas reaction by synchronously calculating multiple physical processes such as gas flow, gas reaction and heat conduction. In the coupling simulation process, the interaction between the reaction gas and the electrode in the internal flow channel of the battery, as well as the change in gas reaction rate due to changes in temperature, pressure and humidity, are taken into account. The coupling equation is solved using a numerical method to accurately obtain the gas reaction distribution flow field. In this way, the impact of different gas flow channel configurations on the performance of the fuel cell can be evaluated, the flow field distribution can be optimized, and finally the gas reaction distribution flow field corresponding to the fuel cell is generated.

[0123] Furthermore, step S3 includes the following steps:

[0124] Step S31: obtaining the gas participation reaction rate and gas reaction energy loss corresponding to each distribution area through the corresponding reaction distribution area in the fuel cell;

[0125] In an embodiment of the present invention, the gas flow field of each reaction distribution area is measured and analyzed in the fuel cell to determine the gas participation reaction rate and gas reaction energy loss of each distribution area. First, a gas flow meter, a pressure sensor and a temperature and humidity sensor are used to monitor the gas in each reaction area inside the battery in real time, and the gas flow, pressure and temperature data of each area are obtained. Then, combined with the gas reaction kinetics model, the gas flow rate and temperature gradient in each reaction area are calculated to obtain the gas reaction rate and energy loss data of different areas, identify the energy loss position of each reaction area, and finally obtain the gas participation reaction rate and gas reaction energy loss corresponding to each distribution area.

[0126] Step S32: performing distribution gradient analysis on the gas flow and gas pressure corresponding to each distribution area to obtain the gas flow distribution gradient and gas pressure distribution gradient corresponding to each distribution area;

[0127] In an embodiment of the present invention, by performing distribution gradient analysis on the gas flow and pressure data in each distribution area, the changing trends of flow and pressure in different reaction areas are obtained, and by using numerical calculation tools, gradient analysis is performed based on the gas flow and pressure data in each area to obtain the gas flow distribution gradient and gas pressure distribution gradient. By comparing the changes in gas flow and pressure in different areas, the spatial distribution differences of flow and pressure can be clearly presented, and finally the gas flow distribution gradient and gas pressure distribution gradient corresponding to each distribution area are obtained.

[0128] Step S33: performing reaction rate impact assessment analysis on the gas participating reaction rate corresponding to each distribution area based on the gas flow distribution gradient and the gas pressure distribution gradient corresponding to each distribution area, and obtaining the flow reaction rate impact degree and the pressure reaction rate impact degree corresponding to each distribution area;

[0129] In an embodiment of the present invention, after obtaining the distribution gradient of gas flow and pressure, the sensitivity of the reaction rate to the flow and pressure gradient is analyzed to evaluate the influence of gas flow and pressure on the reaction rate. First, the reaction kinetics model is used to calculate the gas reaction rate in each region, and the influence is evaluated in combination with the flow and pressure gradient. The calculation process requires a numerical simulation method to simulate the flow behavior of the gas in each reaction region, evaluate the influence of flow and pressure changes in different regions on the reaction rate, and determine the specific influence of gas flow and pressure on the reaction rate based on the analysis results, where the influence of flow reaction rate is α = k(ΔQ) a , k is the reaction rate flow influence constant, ΔQ is the gas flow distribution gradient, a is the gas flow dependence index, and the pressure reaction rate influence degree is β=k'(ΔP) b , k' is the reaction rate pressure influence constant, ΔP is the gas pressure distribution gradient, and b is the gas pressure dependence index. Finally, the flow reaction rate influence degree and pressure reaction rate influence degree corresponding to each distribution area are obtained.

[0130] Step S34: Based on the gas reaction energy loss corresponding to each distribution area, the energy conversion efficiency of the corresponding reaction distribution area in the fuel cell is evaluated to obtain the gas reaction energy conversion efficiency corresponding to each distribution area; based on the gas reaction energy conversion efficiency corresponding to each distribution area, the reaction output load is evaluated and calculated using the reaction power load calculation formula for the flow reaction rate influence and the pressure reaction rate influence corresponding to each distribution area to obtain the gas reaction output power load corresponding to each distribution area;

[0131] In an embodiment of the present invention, the energy conversion efficiency of each distribution area in the fuel cell is evaluated by combining the gas reaction energy loss of each reaction area. First, based on the gas reaction energy loss of each reaction area, the energy efficiency of each area is evaluated using the energy conversion efficiency calculation formula. This step accurately calculates the gas reaction energy conversion efficiency of each area, identifies areas with large energy losses, and proposes optimization plans for these areas, thereby obtaining the gas reaction energy conversion efficiency corresponding to each distribution area. At the same time, after completing the energy efficiency evaluation, a suitable reaction power load calculation formula is formed by combining the time interval range parameters, gas reaction energy conversion efficiency, gas flow, gas pressure, flow reaction rate influence, pressure reaction rate influence, and related parameters to perform reaction output load evaluation calculation, clarify the contribution of each area to the battery performance, and finally obtain the gas reaction output power load corresponding to each distribution area.

[0132] Step S35: performing a cell reaction activity impact analysis on the corresponding reaction distribution areas in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, and obtaining the cell gas reaction activity impact efficiency corresponding to each distribution area.

[0133] In an embodiment of the present invention, the battery reaction activity impact analysis is performed based on the gas temperature and humidity data of each reaction area. First, the temperature and humidity changes of the gas inside the battery are monitored in real time using a temperature and humidity sensor, and the temperature and humidity data of different areas are collected. According to the experimental data and theoretical models, the reaction activity changes of the gas under different temperature and humidity conditions are evaluated. Further, through numerical simulation and optimization algorithms, the impact of temperature and humidity changes in each area on the battery reaction activity is quantitatively analyzed. The analysis results can help identify areas that are more sensitive to temperature and humidity changes, and thus provide a theoretical basis for achieving optimal regulation of battery reaction activity, and finally obtain the battery gas reaction activity impact efficiency corresponding to each distribution area.

[0134] Furthermore, the reactive power load calculation formula is specifically as follows:

[0135]

[0136] Where, ε i is the gas reaction output power load corresponding to the i-th distribution area, n is the total number of distribution areas, T is the time interval range parameter, t is the time variable parameter, η i is the gas reaction energy conversion efficiency corresponding to the i-th distribution area, F i (t) is the gas flow rate in the ith distribution area at time t, P i (t) is the gas pressure in the ith distribution area at time t, α iis the influence degree of the flow reaction rate corresponding to the i-th distribution area, β i is the influence degree of the pressure reaction rate corresponding to the i-th distribution area, and ξ is the correction coefficient of the gas reaction output power load.

[0137] The present invention obtains a reaction power load calculation formula by using a specific mathematical model and verifying it, which is used to evaluate the reaction output load of the flow reaction rate influence and the pressure reaction rate influence corresponding to each distribution area. The reaction power load calculation formula integrates multiple factors (such as gas reaction energy conversion efficiency, gas flow, gas pressure, etc.) to calculate the gas reaction output power load of each distribution area, which can accurately evaluate the power output of different areas, which is crucial for the optimization and performance evaluation of fuel cell systems. The time interval range parameter and time variable parameter in the formula make the calculation take into account the influence of dynamic changes. As time changes, the gas flow and pressure will change, and the reaction rate and power output will also be different. The flow reaction rate influence degree and the pressure reaction rate influence degree in the formula respectively reflect the influence of gas flow and gas pressure on the reaction rate. Gas flow and pressure are directly related to the reaction rate of the fuel cell, and changes in these two will affect the reaction power load. The formula helps to more accurately evaluate the reaction capacity of each area by weighting the influence of flow and pressure. In addition, the introduction of the correction coefficient can compensate for other non-ideal factors not taken into account in the calculation formula. It can adjust the calculation results of the reaction power load, making the calculation more consistent with the actual working conditions and enhancing the reliability and flexibility of the calculation. This formula takes into account the energy loss of the gas reaction by introducing the gas reaction energy conversion efficiency of each distribution area, which helps to make a detailed evaluation of the energy utilization efficiency of each area, thereby providing a strong basis for system optimization. In summary, this formula fully considers the gas reaction output power load ε corresponding to the i-th distribution area. i , the total number of distribution areas n, the time interval range parameter T, the time variable parameter t, the gas reaction energy conversion efficiency η corresponding to the i-th distribution area i , the gas flow rate F of the i-th distribution area at time t i (t), the gas pressure P of the i-th distribution area at time t i (t), the impact degree of the flow reaction rate corresponding to the i-th distribution area α i , the pressure reaction rate influence degree corresponding to the i-th distribution area β i , the correction coefficient of gas reaction output power load ξ, according to the gas reaction output power load ε corresponding to the i-th distribution area i The mutual correlation between the above parameters constitutes a functional relationship This formula can realize the reaction output load evaluation calculation process of the flow reaction rate influence degree and the pressure reaction rate influence degree corresponding to each distribution area. At the same time, by introducing the correction coefficient ξ of the gas reaction output power load, it can be adjusted according to the error situation occurring in the calculation process, thereby improving the accuracy and applicability of the reaction power load calculation formula.

[0138] Furthermore, step S35 includes the following steps:

[0139] Step S351: performing cell reaction activity measurement on corresponding reaction distribution areas within the fuel cell to obtain cell reaction activity distribution corresponding to each distribution area;

[0140] In an embodiment of the present invention, the reaction distribution area within the fuel cell is finely divided into multiple distribution areas according to the geometric structure of the battery, and the reaction activity measurement of each area is calculated separately. Specifically, the current density distribution, voltage distribution and their changes in each area within the battery can be measured, combined with the electrochemical reaction model within the battery, and the relationship between current density and reaction rate can be used to evaluate the reaction activity of each area. The higher the reaction activity value of the area, the more efficient the reaction process of the battery in that area. The battery management system (BMS) and the electrochemical model can be used for real-time data acquisition, and the reaction activity measurement is performed based on parameters such as current and voltage to obtain specific reaction activity data for each distribution area. In this way, by calculating the current density and the corresponding battery reaction rate of each area, detailed information on the battery reaction activity distribution can be obtained, and finally the battery reaction activity distribution corresponding to each distribution area can be obtained.

[0141] Step S352: performing a statistical analysis on the fluctuation amplitudes of the gas temperature and gas humidity corresponding to each distribution area to obtain the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area;

[0142] In an embodiment of the present invention, the gas temperature and humidity in each distribution area of ​​the fuel cell are monitored and fluctuations are analyzed. First, the gas temperature and humidity data of each distribution area are collected using a temperature and humidity sensor. Based on the feedback data from the sensor, the temperature and humidity fluctuation amplitude statistics are performed for each area. Specifically, the temperature and humidity data within a certain time interval are first recorded, and then the standard deviation or peak-to-valley value of these data is calculated to obtain the amplitude of the temperature and humidity fluctuations. This analysis can not only reveal the gas flow characteristics of each area, but also help determine the stability of the gas conditions in each area. Through dedicated data analysis tools (such as data analysis libraries in MATLAB or Python), the temperature and humidity change trends and amplitudes are visualized, and finally the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area are obtained.

[0143] Step S353: evaluating the battery reaction activity loss distribution corresponding to each distribution area based on the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area, so as to obtain the temperature fluctuation reaction activity loss and humidity fluctuation reaction activity loss corresponding to each distribution area;

[0144] In an embodiment of the present invention, the battery reaction activity loss is evaluated based on the statistical results of the gas temperature and humidity fluctuation amplitudes. By establishing a battery reaction model and combining the gas temperature and humidity fluctuation amplitudes, their effects on the battery reaction efficiency are evaluated. First, the effects of temperature and humidity changes on the internal reaction rate of the battery are analyzed, and the reaction loss is calculated using electrochemical reaction equations (such as the Nernst equation, the Tafel equation, etc.) combined with gas parameter fluctuations. Temperature fluctuations will cause fluctuations in the reaction rate, while humidity fluctuations will affect the ionic conductivity of the battery, thereby affecting the overall reaction activity of the battery. Based on this analysis, the reaction activity loss of each distribution area is evaluated. At this time, the battery reaction process can be accurately modeled through dynamic simulation tools or numerical calculation software (such as COMSOL, ANSYS, etc.), thereby quantifying the loss of battery reaction activity due to temperature and humidity fluctuations. The temperature fluctuation reaction activity loss is Among them, A is the exponential factor of the reaction rate, E0 is the activation energy, R is the gas constant, τ is the absolute temperature, ΔT is the temperature fluctuation amplitude, and the humidity fluctuation reaction activity loss is ΔH=k0*(f(H+Δh)-f(H)), where k0 is the reaction rate constant under standard humidity, H is the humidity parameter, Δh is the humidity fluctuation amplitude, f(H) is the effect function of humidity on the reaction rate, f(H)=H m , m is the influence coefficient determined by the specific catalytic reaction, and finally the temperature fluctuation reaction activity loss and humidity fluctuation reaction activity loss corresponding to each distribution area are obtained.

[0145] Step S354: Calculating the ratio of the temperature fluctuation reaction activity loss and the humidity fluctuation reaction activity loss corresponding to each distribution area to obtain the temperature-humidity reaction activity loss ratio corresponding to each distribution area;

[0146] In an embodiment of the present invention, by calculating the ratio between the reaction activity loss caused by temperature fluctuations and the reaction activity loss caused by humidity fluctuations, this ratio reflects the relative influence of temperature and humidity fluctuations on the battery reaction activity. The specific operation is to calculate the reaction activity loss caused by gas temperature fluctuations and the reaction activity loss caused by gas humidity fluctuations for each distribution area, and then calculate the ratio between the two. By comparing the temperature-humidity reaction activity loss ratios of different areas, it can be revealed which areas have greater losses under temperature fluctuations and which areas are more easily damaged in reaction activity under humidity fluctuations. The calculation of this ratio can be carried out with the help of mathematical modeling tools to ensure the accuracy and scientificity of the calculation, and finally the temperature-humidity reaction activity loss ratio corresponding to each distribution area is obtained.

[0147] Step S355: performing a battery reaction activity impact analysis on the battery reaction activity distribution corresponding to each distribution area based on the temperature-humidity reaction activity loss ratio corresponding to each distribution area, and obtaining the battery gas reaction activity impact efficiency corresponding to each distribution area.

[0148] In an embodiment of the present invention, the influence efficiency of battery reaction activity is analyzed by utilizing the calculated temperature and humidity reaction activity loss ratio. The purpose of this step is to evaluate the comprehensive influence efficiency of temperature and humidity fluctuations in each distribution area on battery reaction activity. Based on the aforementioned reaction activity loss ratio, the influence of these losses on the overall efficiency of the battery can be further analyzed. Specifically, a weighted average or multi-objective optimization method can be used to combine the loss ratios of each area with their respective importance for comprehensive evaluation. In this way, the gas reaction activity influence efficiency corresponding to each distribution area can be obtained. This step can also use numerical optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.) to further improve the working efficiency of the battery, ensure that the battery reaction activity reaches the optimal state under different climatic conditions and working environments, and finally obtain the battery gas reaction activity influence efficiency corresponding to each distribution area.

[0149] Furthermore, step S4 includes the following steps:

[0150] Step S41: quantifying the gas reaction anomaly in the reaction distribution area corresponding to the fuel cell using a gas reaction distribution anomaly calculation formula based on the gas reaction output power load corresponding to each distribution area and the cell gas reaction activity impact efficiency, to obtain the gas reaction distribution anomaly degree corresponding to each distribution area;

[0151] In an embodiment of the present invention, a suitable gas reaction distribution anomaly calculation formula is formed by combining the gas reaction output power load, gas reaction effective area, gas reaction frequency, battery gas reaction activity influence efficiency, gas reaction influence weight coefficient, gas reaction activity index attenuation factor, basic reaction inhibition degree, reaction frequency response constant and related parameters to quantify the gas reaction anomaly in the reaction distribution area corresponding to the fuel cell, so as to quantify the degree of anomaly in each area. The larger the anomaly value, the more uneven the gas reaction distribution. In this way, it is possible to identify which areas have uneven gas flow distribution or low reaction efficiency, and finally obtain the degree of gas reaction distribution anomaly corresponding to each distribution area.

[0152] Step S42: comparing and judging the degree of gas reaction distribution abnormality corresponding to the corresponding distribution area according to a preset gas reaction distribution abnormality threshold; if the degree of gas reaction distribution abnormality is less than the preset gas reaction distribution abnormality threshold, iteratively judging the degree of gas reaction distribution abnormality corresponding to the next distribution area; if the degree of gas reaction distribution abnormality is greater than or equal to the preset gas reaction distribution abnormality threshold, determining the corresponding distribution area as a fuel cell gas reaction uneven distribution area;

[0153] In an embodiment of the present invention, a preset gas reaction distribution abnormality threshold is used to determine whether there is a problem of uneven gas reaction in each distribution area. During implementation, a reasonable threshold is first set to determine the degree of abnormality in the gas reaction distribution. This threshold is usually obtained through experimental data or simulation analysis to ensure that it can accurately reflect the uniformity of the reaction distribution in fuel cell applications. Then, the degree of abnormality in the gas reaction distribution of each distribution area is compared in turn. If the degree of abnormality in a certain distribution area is less than the preset threshold, the next distribution area is checked; if the degree of abnormality in a certain distribution area is greater than or equal to the preset threshold, the area is marked as an uneven gas reaction distribution area. The uneven gas reaction distribution area is usually characterized by low gas reaction activity in the area and unstable power output, which leads to a decrease in battery efficiency. During the judgment process, the gas reaction conditions in multiple areas can be monitored in real time by sensors or data acquisition devices to ensure the accuracy of the judgment results.

[0154] Step S43: The gas flow rate of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel, so as to send a control instruction to the central control system according to the gas distribution corresponding to the fuel cell gas reaction uneven distribution area, and accurately control the corresponding opening of the adjustable micro valve according to the control instruction, change the corresponding geometric shape of the gas flow channel, and optimize the distribution of the reaction gas in the gas flow channel, so as to perform the corresponding reaction uneven distribution gas flow control work.

[0155] In an embodiment of the present invention, gas flow optimization control is achieved through adjustable microvalves pre-installed in the gas flow channel. During implementation, adjustable microvalves are pre-installed in the gas flow channel. These valves have precise control capabilities and can be finely adjusted according to gas flow requirements. The gas distribution status in each area of ​​the gas flow channel is monitored in real time by sensors. In particular, in areas identified as having uneven gas reaction distribution, the system calculates the most suitable gas flow and flow velocity distribution based on this real-time data. A central control system issues commands, and the opening of the microvalves is precisely adjusted according to the control commands. If the gas flow in a certain area is insufficient, the corresponding valve is instructed to open further to increase the gas flow. If the gas flow is too high, the valve is closed to limit the flow, thereby achieving the purpose of optimizing the gas flow distribution. To ensure more uniform gas distribution in the flow channel, the microvalves can adjust the flow direction and distribution of the reactant gases in real time, thereby improving the reaction efficiency and power output of the fuel cell. In this process, flow control not only depends on the geometry of the gas flow channel, but also needs to consider multiple factors such as gas reactivity and temperature. Through precise flow adjustment, the gas reaction in each area reaches the optimal state, and ultimately the corresponding uneven reaction distribution gas flow control is performed.

[0156] Furthermore, the calculation formula for the gas reaction distribution anomaly in step S41 is specifically:

[0157]

[0158]

[0159] Where Δ∈ i is the abnormal degree of gas reaction distribution corresponding to the i-th distribution area, ε i is the gas reaction output power load corresponding to the i-th distribution area, A i is the effective gas reaction area corresponding to the i-th distribution area, f is the gas reaction frequency, is the battery gas reaction activity affecting the efficiency of the ith distribution area at frequency f, is the reaction efficiency corresponding to the i-th distribution area under low frequency state, δ i is the reaction frequency dependence parameter corresponding to the ith distribution area, ρ is the gas reaction activity efficiency attenuation index, θ i is the gas reaction influence weight coefficient corresponding to the i-th distribution area, μ i is the gas reactivity index attenuation factor corresponding to the i-th distribution area, C i is the basic reaction inhibition degree corresponding to the i-th distribution area, γ i is the reaction frequency response constant corresponding to the ith distribution area, and ζ is the correction coefficient of the abnormal degree of gas reaction distribution.

[0160] The present invention uses a specific mathematical model and has been verified to obtain a gas reaction distribution anomaly calculation formula for quantifying gas reaction anomalies in the reaction distribution area corresponding to the fuel cell. The gas reaction distribution anomaly calculation formula uses multiple parameters (such as gas reaction frequency, effective area, battery gas reaction activity efficiency, etc.) to describe the gas reaction state of each distribution area, so that the degree of gas reaction distribution anomaly can be accurately quantified. In this way, the gas distribution status of each area can be clearly understood and which areas have uneven reaction problems can be determined. In the formula, the degree of gas reaction distribution anomaly is not only related to factors such as gas reaction output power load, reaction area area, and reaction frequency, but also combines multiple factors such as gas reaction activity efficiency, reaction frequency responsiveness, and reaction inhibition degree. These factors are integrated together through an accurate mathematical model, so that the calculation results can truly reflect the actual situation of the reaction distribution. Through factors such as the reaction frequency dependence parameter and the reaction activity attenuation factor in the formula, the reaction distribution of the fuel cell under different operating conditions can be dynamically evaluated. As the gas reaction frequency changes, the gas reaction activity will also change accordingly. The formula can calculate and adjust the gas distribution anomaly in real time to optimize the reaction efficiency of the fuel cell. The calculated degree of abnormality in the gas reaction distribution can be compared with a preset threshold to further determine which areas need to be optimized. At this time, the gas flow optimization control system can adjust the flow distribution according to the specific conditions of the gas flow channel and the degree of abnormality in the reaction distribution to ensure the balance of the gas reaction in each area, avoid incomplete or wasteful reactions, and improve the overall efficiency of the fuel cell. Through precise gas flow control, the fuel cell can operate in an efficient state, thereby avoiding over- or under-reactions in certain areas and reducing unnecessary energy waste. This refined regulation can improve the working efficiency of the fuel cell, extend the battery life, and maximize its output power. In addition, the formula includes a correction coefficient that provides flexibility for feedback correction of the degree of abnormality in the gas reaction distribution. This allows the gas flow control strategy to be adjusted in real time according to changes in the reaction distribution during actual use, further optimizing the reaction distribution and avoiding over-reliance on a single parameter or static model. In summary, the formula fully considers the degree of abnormality in the gas reaction distribution Δ∈ corresponding to the i-th distribution area. i , the gas reaction output power load ε corresponding to the i-th distribution area i , the effective gas reaction area A corresponding to the i-th distribution area i , gas reaction frequency f, the battery gas reaction activity corresponding to the i-th distribution area at frequency f affects the efficiency The reaction efficiency corresponding to the i-th distribution area under low frequency state The response frequency dependence parameter δ corresponding to the i-th distribution areai , gas reaction activity efficiency attenuation index ρ, gas reaction influence weight coefficient θ corresponding to the i-th distribution area i , the gas reactivity exponential attenuation factor μ corresponding to the i-th distribution area i , the basic reaction inhibition degree C corresponding to the i-th distribution area i , the frequency response constant γ corresponding to the i-th distribution area i , the correction coefficient ζ of the abnormal degree of gas reaction distribution, where the reaction efficiency corresponding to the i-th distribution area under the low frequency state is combined The response frequency dependence parameter δ corresponding to the i-th distribution area i The gas reaction activity efficiency attenuation index ρ and the gas reaction frequency f constitute a battery gas reaction activity influence efficiency corresponding to the i-th distribution area at the frequency f. Functional relationship According to the abnormal degree of gas reaction distribution corresponding to the i-th distribution area Δ∈ i The mutual correlation between the above parameters constitutes a functional relationship This formula can realize the quantification process of gas reaction anomalies in the reaction distribution area corresponding to the fuel cell. At the same time, by introducing the correction coefficient ζ of the degree of gas reaction distribution anomaly, it can be adjusted according to the errors occurring in the calculation process, thereby improving the accuracy and applicability of the gas reaction distribution anomaly calculation formula.

[0161] Furthermore, the present invention also provides a fuel cell gas flow field optimization control system based on automatic regulation control, which is used to execute the fuel cell gas flow field optimization control method based on automatic regulation control as described above. The fuel cell gas flow field optimization control system based on automatic regulation control includes:

[0162] The fuel cell gas parameter monitoring module is used to deploy gas flow sensors, pressure sensors, temperature sensors and humidity sensors at the gas inlet, flow channel and reaction area corresponding to the fuel cell, and use the gas flow sensors, pressure sensors, temperature sensors and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell in real time;

[0163] The gas flow field simulation and partitioning module is used to obtain the gas flow channel structural parameters corresponding to the fuel cell, and perform gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell to generate the gas reaction distribution flow field corresponding to the fuel cell; the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area are obtained through the gas reaction distribution flow field corresponding to the fuel cell;

[0164] A partitioned gas reaction load assessment module is used to assess the reaction output load of the corresponding reaction distribution area in the fuel cell based on the gas flow rate and gas pressure corresponding to each distribution area, so as to obtain the gas reaction output power load corresponding to each distribution area; and to analyze the cell reaction activity impact of the corresponding reaction distribution area in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, so as to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area;

[0165] The gas uneven distribution optimization control module is used to quantify the gas reaction anomaly in the corresponding reaction distribution area based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, and obtain the gas reaction distribution anomaly degree corresponding to each distribution area; determine the reaction uneven distribution of the gas reaction distribution flow field based on the gas reaction distribution anomaly degree corresponding to each distribution area to obtain the fuel cell gas reaction uneven distribution area; optimize the gas flow control of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

[0166] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0167] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. A fuel cell gas flow field optimization control method based on automatic regulation control, characterized in that: The following steps are involved: Step S1: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the gas inlet, flow channel, and reaction area corresponding to the fuel cell, and using the gas flow sensors, pressure sensors, temperature sensors, and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell in real time; Step S2: Obtaining gas flow channel structural parameters corresponding to the fuel cell, and performing a gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell; obtaining the gas flow, gas pressure, gas temperature, and gas humidity corresponding to each distribution area through the gas reaction distribution flow field corresponding to the fuel cell; Step S3: Based on the gas flow rate and gas pressure corresponding to each distribution area, a reaction output load evaluation is performed on the corresponding reaction distribution area in the fuel cell to obtain the gas reaction output power load corresponding to each distribution area; based on the gas temperature and gas humidity corresponding to each distribution area, a cell reaction activity impact analysis is performed on the corresponding reaction distribution area in the fuel cell to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area; Step S4: Based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, the corresponding reaction distribution area is quantified to obtain the gas reaction distribution anomaly degree corresponding to each distribution area; based on the gas reaction distribution anomaly degree corresponding to each distribution area, the reaction uneven distribution of the gas reaction distribution flow field is determined to obtain the fuel cell gas reaction uneven distribution area; the gas flow of the corresponding fuel cell gas reaction uneven distribution area in the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

2. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: deploying gas flow sensors, pressure sensors, temperature sensors, and humidity sensors at the corresponding gas inlets, flow channels, and reaction areas of the fuel cell; Step S12: using a gas flow sensor to monitor the flow of the fuel cell in real time to obtain gas flow data corresponding to the fuel cell; Step S13: using a pressure sensor to monitor the pressure of the fuel cell in real time to obtain gas pressure data corresponding to the fuel cell; Step S14: using a temperature sensor to monitor the temperature of the fuel cell in real time to obtain gas temperature data corresponding to the fuel cell; Step S15: using a humidity sensor to monitor the humidity of the fuel cell in real time to obtain gas humidity data corresponding to the fuel cell.

3. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: obtaining gas flow channel structural parameters corresponding to the fuel cell, including shape, size, microscopic surface roughness, micro-protrusions, and micro-depression position parameters corresponding to the gas flow channel; Step S22: performing topological simulation design on the gas flow channel corresponding to the fuel cell based on the structural parameters of the gas flow channel corresponding to the fuel cell, so as to generate a topological structure simulation model of the gas flow channel corresponding to the fuel cell; Step S23: performing a gas distribution flow field coupling simulation on the gas flow channel topology structure simulation model corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate a gas reaction distribution flow field corresponding to the fuel cell; Step S24: performing reaction distribution division on the gas reaction distribution flow field corresponding to the fuel cell to obtain various gas reaction distribution areas corresponding to the fuel cell; Step S25: extracting gas parameters of the corresponding gas reaction distribution flow field based on each gas reaction distribution area to obtain the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area.

4. The method for optimizing the fuel cell gas flow field based on automatic regulation control according to claim 3, characterized in that: Step S23 includes the following steps: Step S231: obtaining adsorption, desorption, and collision behaviors of reactant gas molecules in the corresponding gas flow channel of the fuel cell, and performing a gas flow channel characteristic analysis on a topological structure simulation model of the corresponding gas flow channel of the fuel cell based on the adsorption, desorption, and collision behaviors of the reactant gas molecules in the corresponding gas flow channel of the fuel cell, to obtain gas flow channel transmission characteristic parameters corresponding to the fuel cell, including diffusion coefficients and viscosity coefficients corresponding to the reactant gas molecules; Step S232: performing a gas transmission constraint analysis on the gas flow channel topology simulation model corresponding to the fuel cell based on the gas flow channel transmission characteristic parameters corresponding to the fuel cell, so as to generate a gas flow channel transmission constraint condition corresponding to the fuel cell; Step S233: performing finite element simulation division on the gas flow channel topology structure simulation model corresponding to the fuel cell to obtain simulation unit models of each gas flow channel structure; Step S234: performing unit simulation numerical simulation on each gas flow channel structure simulation unit model based on the gas flow data, gas pressure data, gas temperature data, and gas humidity data corresponding to the fuel cell, so as to generate the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution, and gas humidity distribution within each gas flow channel unit; Step S235: Based on the gas flow channel transmission constraints corresponding to the fuel cell, a gas distribution flow field coupling simulation is performed on the corresponding gas flow distribution, gas pressure distribution, gas temperature distribution and gas humidity distribution in each gas flow channel unit to generate a gas reaction distribution flow field corresponding to the fuel cell.

5. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: obtaining the gas participation reaction rate and gas reaction energy loss corresponding to each distribution area through the corresponding reaction distribution area in the fuel cell; Step S32: performing distribution gradient analysis on the gas flow and gas pressure corresponding to each distribution area to obtain the gas flow distribution gradient and gas pressure distribution gradient corresponding to each distribution area; Step S33: performing reaction rate impact assessment analysis on the gas participating reaction rate corresponding to each distribution area based on the gas flow distribution gradient and the gas pressure distribution gradient corresponding to each distribution area, and obtaining the flow reaction rate impact degree and the pressure reaction rate impact degree corresponding to each distribution area; Step S34: Based on the gas reaction energy loss corresponding to each distribution area, the energy conversion efficiency of the corresponding reaction distribution area in the fuel cell is evaluated to obtain the gas reaction energy conversion efficiency corresponding to each distribution area; based on the gas reaction energy conversion efficiency corresponding to each distribution area, the reaction output load is evaluated and calculated using the reaction power load calculation formula for the flow reaction rate influence and the pressure reaction rate influence corresponding to each distribution area to obtain the gas reaction output power load corresponding to each distribution area; Step S35: performing a cell reaction activity impact analysis on the corresponding reaction distribution areas in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, and obtaining the cell gas reaction activity impact efficiency corresponding to each distribution area.

6. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 5, characterized in that: The reactive power load calculation formula is specifically: Where, ε i is the gas reaction output power load corresponding to the i-th distribution area, n is the total number of distribution areas, T is the time interval range parameter, t is the time variable parameter, η i is the gas reaction energy conversion efficiency corresponding to the i-th distribution area, F i (t) is the gas flow rate in the ith distribution area at time t, P i (t) is the gas pressure in the ith distribution area at time t, α i is the influence degree of the flow reaction rate corresponding to the i-th distribution area, β i is the influence degree of the pressure reaction rate corresponding to the i-th distribution area, and ξ is the correction coefficient of the gas reaction output power load.

7. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 5, characterized in that: Step S35 includes the following steps: Step S351: performing cell reaction activity measurement on corresponding reaction distribution areas within the fuel cell to obtain cell reaction activity distribution corresponding to each distribution area; Step S352: performing a statistical analysis on the fluctuation amplitudes of the gas temperature and gas humidity corresponding to each distribution area to obtain the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area; Step S353: evaluating the battery reaction activity loss distribution corresponding to each distribution area based on the gas temperature fluctuation amplitude and gas humidity fluctuation amplitude corresponding to each distribution area, so as to obtain the temperature fluctuation reaction activity loss and humidity fluctuation reaction activity loss corresponding to each distribution area; Step S354: Calculating the ratio of the temperature fluctuation reaction activity loss and the humidity fluctuation reaction activity loss corresponding to each distribution area to obtain the temperature-humidity reaction activity loss ratio corresponding to each distribution area; Step S355: performing a battery reaction activity impact analysis on the battery reaction activity distribution corresponding to each distribution area based on the temperature-humidity reaction activity loss ratio corresponding to each distribution area, and obtaining the battery gas reaction activity impact efficiency corresponding to each distribution area.

8. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: quantifying the gas reaction anomaly in the reaction distribution area corresponding to the fuel cell using a gas reaction distribution anomaly calculation formula based on the gas reaction output power load corresponding to each distribution area and the cell gas reaction activity impact efficiency, to obtain the gas reaction distribution anomaly degree corresponding to each distribution area; Step S42: comparing and judging the degree of gas reaction distribution abnormality corresponding to the corresponding distribution area according to a preset gas reaction distribution abnormality threshold; if the degree of gas reaction distribution abnormality is less than the preset gas reaction distribution abnormality threshold, iteratively judging the degree of gas reaction distribution abnormality corresponding to the next distribution area; if the degree of gas reaction distribution abnormality is greater than or equal to the preset gas reaction distribution abnormality threshold, determining the corresponding distribution area as a fuel cell gas reaction uneven distribution area; Step S43: The gas flow rate of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field is optimized and controlled through the adjustable micro valve preset in the gas flow channel, so as to send a control instruction to the central control system according to the gas distribution corresponding to the fuel cell gas reaction uneven distribution area, and accurately control the corresponding opening of the adjustable micro valve according to the control instruction, change the corresponding geometric shape of the gas flow channel, and optimize the distribution of the reaction gas in the gas flow channel, so as to perform the corresponding reaction uneven distribution gas flow control work.

9. The fuel cell gas flow field optimization control method based on automatic regulation control according to claim 8, characterized in that: The calculation formula for the gas reaction distribution anomaly in step S41 is specifically: Where Δ∈ i is the abnormal degree of gas reaction distribution corresponding to the i-th distribution area, ε i is the gas reaction output power load corresponding to the i-th distribution area, A i is the effective gas reaction area corresponding to the i-th distribution area, f is the gas reaction frequency, is the battery gas reaction activity affecting the efficiency of the ith distribution area at frequency f, is the reaction efficiency corresponding to the i-th distribution area under low frequency state, δ i is the reaction frequency dependence parameter corresponding to the ith distribution area, ρ is the gas reaction activity efficiency attenuation index, θ i is the gas reaction influence weight coefficient corresponding to the i-th distribution area, μ i is the gas reactivity index attenuation factor corresponding to the i-th distribution area, C i is the basic reaction inhibition degree corresponding to the i-th distribution area, γ i is the reaction frequency response constant corresponding to the ith distribution area, and ζ is the correction coefficient of the abnormal degree of gas reaction distribution.

10. A fuel cell gas flow field optimization control system based on automatic regulation control, characterized in that: The method for optimizing the fuel cell gas flow field based on automatic regulation and control according to claim 1 is used to execute the method, wherein the fuel cell gas flow field optimization control system based on automatic regulation and control comprises: The fuel cell gas parameter monitoring module is used to deploy gas flow sensors, pressure sensors, temperature sensors and humidity sensors at the gas inlet, flow channel and reaction area corresponding to the fuel cell, and use the gas flow sensors, pressure sensors, temperature sensors and humidity sensors to monitor the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell in real time; The gas flow field simulation and partitioning module is used to obtain the gas flow channel structural parameters corresponding to the fuel cell, and perform gas distribution flow field coupling simulation on the gas flow channel structural parameters corresponding to the fuel cell based on the gas flow data, gas pressure data, gas temperature data and gas humidity data corresponding to the fuel cell to generate the gas reaction distribution flow field corresponding to the fuel cell; the gas flow, gas pressure, gas temperature and gas humidity corresponding to each distribution area are obtained through the gas reaction distribution flow field corresponding to the fuel cell; A partitioned gas reaction load assessment module is used to assess the reaction output load of the corresponding reaction distribution area in the fuel cell based on the gas flow rate and gas pressure corresponding to each distribution area, so as to obtain the gas reaction output power load corresponding to each distribution area; and to analyze the cell reaction activity impact of the corresponding reaction distribution area in the fuel cell based on the gas temperature and gas humidity corresponding to each distribution area, so as to obtain the cell gas reaction activity impact efficiency corresponding to each distribution area; The gas uneven distribution optimization control module is used to quantify the gas reaction anomaly in the corresponding reaction distribution area based on the gas reaction output power load corresponding to each distribution area and the battery gas reaction activity influence efficiency, and obtain the gas reaction distribution anomaly degree corresponding to each distribution area; determine the reaction uneven distribution of the gas reaction distribution flow field based on the gas reaction distribution anomaly degree corresponding to each distribution area to obtain the fuel cell gas reaction uneven distribution area; optimize the gas flow control of the fuel cell gas reaction uneven distribution area corresponding to the gas reaction distribution flow field through the adjustable micro valve preset in the gas flow channel to perform the corresponding reaction uneven distribution gas flow control work.

Images