Optimal design method and device based on performance evaluation of gas diffusion layer of fuel cell

Abstract

To provide an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell capable of not only selecting design of an optimum fuel cell product but also guiding a direction of optimum design of the fuel cell product.SOLUTION: An optimal design method of a gas diffusion layer of a fuel cell includes the steps of: determining an overall porosity of the gas diffusion layer of the fuel cell based on a production demand to obtain a plurality of porosity structures based on the overall porosity; obtaining a performance evaluation index of the gas diffusion layer of the fuel cell to establish a performance evaluation system of the gas diffusion layer of the fuel cell; calculating an evaluation score of the plurality of porosity structures in a performance evaluation system of the gas diffusion layer of the fuel cell by combining an evaluation function and a weight of the index; and determining an optimal design proposal from among the plurality of porosity structures based on the evaluation score.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present application relates to the field of fuel cell testing technology, and more particularly to an optimum design method and device based on performance evaluation of a gas diffusion layer of a fuel cell. [Background technology]

[0002] To improve the water management and thermal management performance of fuel cells, the structure of the gas diffusion layer needs to be continuously designed. For example, there are various design proposals for the gas diffusion layer structure with a porosity of 0.7.

[0003] Although the overall porosity is 0.7, the structure of each internal layer is different, and the porosity of each layer from top to bottom can vary linearly from large to small, linearly from small to large, randomly distributed, or evenly distributed, resulting in significant differences in the porosity of each layer. Different design options result in significant differences in the internal air-water-heat-electricity transfer characteristics.

[0004] A gas diffusion layer design with a non-uniform porosity distribution may have a relatively balanced output performance index, while a design with a graded porosity or ordered porosity structure may have a single objective or a specific index may be prominent. In other words, while satisfying the overall porosity design, there are various combinations of local porosity designs for each layer. However, when a single overall porosity is selected according to demand during production, how to design the local porosity of each layer to achieve optimal performance output is a key issue in current fuel cell optimal design. However, prior art lacks fuel cell optimal design proposals based on porosity performance index evaluation. Summary of the Invention

[0005] The main purpose of this application is to provide an optimal design plan based on performance evaluation of the gas diffusion layer of a fuel cell, and to solve the problem of optimizing the local porosity of a fuel cell in the prior art.

[0006] To achieve this goal, this application provides the following technical solutions:

[0007] A first aspect of the present invention is an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell, comprising: Determining the overall porosity of the gas diffusion layer of the fuel cell according to production demands, and obtaining a plurality of porosity structures based on the overall porosity; To obtain performance evaluation indexes for the gas diffusion layer of a fuel cell and to establish a performance evaluation system for the gas diffusion layer of a fuel cell; calculating an evaluation score for the plurality of porosity structures under a performance evaluation system for a gas diffusion layer of a fuel cell by combining the evaluation function and the index weight; and determining an optimal design plan from among the plurality of porosity structures based on the evaluation score.

[0008] A second aspect of the present invention is an optimum design device based on performance evaluation of a gas diffusion layer of a fuel cell, comprising: one or more processors; and a memory storing one or more programs, wherein the one or more programs are executed by the one or more processors, causing the one or more processors to realize an optimal design method based on performance evaluation of the gas diffusion layer of the fuel cell.

[0009] This application relates to the field of fuel cell testing, and more particularly to a method and apparatus for optimizing the design of a fuel cell gas diffusion layer based on performance evaluation. This method includes determining the overall porosity of the fuel cell gas diffusion layer based on production needs, obtaining multiple porosity structures based on the overall porosity, obtaining performance evaluation indicators for the fuel cell gas diffusion layer, establishing a performance evaluation system for the fuel cell gas diffusion layer, combining evaluation functions and index weights to calculate evaluation scores for the multiple porosity structures in the performance evaluation system for the fuel cell gas diffusion layer, and determining an optimal design from the multiple porosity structures based on the evaluation scores. This method not only selects the optimal fuel cell product design, but also clarifies the differences in performance indicators between different fuel cell product designs and addresses weaknesses, thereby providing guidance for the optimal design of the fuel cell product. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a workflow flowchart of an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram of a plurality of porosity structures in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a first embodiment of the present invention. [Figure 3] FIG. 3 is a schematic diagram showing a comparison of air permeabilities in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a first embodiment of the present invention. [Figure 4] FIG. 4 is a schematic diagram of a drainage capacity testing device in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a first embodiment of the present invention. [Figure 5] FIG. 5 is a schematic diagram showing the results of a compression ratio test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a first embodiment of the present invention. [Figure 6] FIG. 6 is a schematic diagram of the structure of an optimum design device based on performance evaluation of a gas diffusion layer of a fuel cell, according to a second embodiment of the present invention. [Figure 7]FIG. 7 is a schematic diagram showing the results of a thickness uniformity test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a third embodiment of the present invention. [Figure 8] FIG. 8 is a schematic diagram showing the results of an air permeability test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a third embodiment of the present invention. [Figure 9] FIG. 9 is a schematic diagram showing the results of a drainage capacity test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a third embodiment of the present invention. [Figure 10] FIG. 10 is a schematic diagram showing the results of a tensile strength test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell, according to a third embodiment of the present invention. [Figure 11] FIG. 11 is a schematic diagram showing the results of a compression characteristic test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell, according to a third embodiment of the present invention. [Figure 12] FIG. 12 is a schematic diagram showing the results of a resistivity test in the in-plane direction in the optimum design method based on the performance evaluation of the gas diffusion layer of the fuel cell according to the third embodiment of the present invention. [Figure 13] FIG. 13 is a schematic diagram showing the results of a vertical resistivity test in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a third embodiment of the present invention. [Figure 14] FIG. 14 is a schematic diagram showing the results of an experiment on acid corrosion resistance index in an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to a third embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] Next, the technical solutions of the present application will be described clearly and completely with reference to the figures of the embodiments of the present application. Obviously, the embodiments described herein are only a part of the present application and do not represent all the embodiments. Based on the embodiments of the present application, all other embodiments that can be obtained by those skilled in the art without any inventive efforts are included in the protection scope of the present application.

[0012] According to a first embodiment of the present invention, the present invention claims to protect an optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell, and is configured as follows, with reference to FIG. S1: Determine the overall porosity of the gas diffusion layer of the fuel cell based on production demand, and obtain multiple porosity structures based on the overall porosity. S2. Obtain performance evaluation indexes for the gas diffusion layer of fuel cells and establish a performance evaluation system for the gas diffusion layer of fuel cells. S3, the evaluation function and the index weight are combined to calculate the evaluation score in the performance evaluation system of the gas diffusion layer of the fuel cell with multiple porosity structures. S4: Based on the evaluation score, the optimal design plan is determined from among multiple porosity structures.

[0013] Furthermore, the multiple porosity structures include at least a first stage porosity structure, a second stage porosity structure, and an ordered porosity structure. In the first stage porosity structure, the porosity of each layer from top to bottom of the gas diffusion layer changes linearly from large to small. In the second stage porosity structure, the porosity of each layer from top to bottom of the gas diffusion layer changes linearly from small to large. In the ordered porosity structure, the porosity of each layer is uniformly distributed from top to bottom of the gas diffusion layer. Specifically, referring to FIG. 2, a first stage porosity structure, a second stage porosity structure, and an ordered porosity structure are shown in this order from left to right.

[0014] Furthermore, the performance evaluation indexes of the gas diffusion layer of the fuel cell include at least a characteristic performance index, a mechanical performance index, an electrical performance index, and a durability performance index. Characteristic performance indicators include the gas permeability and exhaust capacity of the fuel cell's gas diffusion layer. Mechanical performance indicators include the tensile strength and compressive properties of the fuel cell gas diffusion layers. Electrical performance indicators include the normal and in-plane conductivity of the fuel cell gas diffusion layer. The durability performance index includes the acid corrosion resistance of the gas diffusion layer of the fuel cell.

[0015] In this example, for a single gas diffusion layer, there is a large difference in mechanical performance between the top and bottom layers due to the different porosity combinations. Even when the same baking temperature is used in the production process, the performance of each carbon fiber is consistent, but differences in structure result in differences in overall performance.

[0016] The method further includes the following steps: The air permeability is the main performance index of the gas diffusion layer, and the performance difference of multiple porosity structures under the same pressure difference is compared using a permeameter by the equal pressure difference method.

[0017] In this example, as shown in FIG. 3, there is a large difference in permeability between the two same porosity designs, AA and BB, under a pressure difference of 20 Pa.

[0018] The method further includes the following steps: The breakthrough pressure of the test liquid water is used to represent the drainage capacity of the gas diffusion layer of the fuel cell. Before the test, red dye water is injected into the solution reservoir, and when the injected liquid level reaches the upper passage position of the solution reservoir, the one-way valve of the water injection line is closed. The water injection pipe is connected to the pressure pipe of the gas source, the gas diffusion layer of the fuel cell having a multi-porosity structure is sandwiched between the test jig, and a white water-absorbing filter is placed in the space above. Adjust the water supply line stop valve and the air source line pressure reducing valve to the appropriate pressure. Open the one-way valve and stop valve, slowly adjust the micro-pressure differential meter from low pressure to high pressure, and when the white water absorption filter turns red, take the pressure reading on the micro-pressure differential meter as the breakthrough pressure of the liquid water.

[0019] In this example, if the water produced by the fuel cell is not efficiently discharged, the gas transmission pathways may become clogged and the cell may become "submerged," so even under the same processing conditions, the gas diffusion layer has different drainage capabilities due to its structure. The diagram of the test equipment designed in this example is shown in Figure 4.

[0020] Due to factors such as capillary pressure within the gas diffusion layer, a certain breakthrough pressure is required for liquid water to drain from the bottom to the top. Therefore, the test uses the breakthrough pressure of the test liquid water to demonstrate the drainage capacity of the gas diffusion layer. Before the test, red dye water is injected into the solution reservoir. When the injected liquid level reaches the upper passage position of the solution reservoir, the one-way valve of the water injection line is closed. The water injection line is connected to the gas source pressure line. Gas diffusion layer samples with different structural designs are clamped in the test fixture shown in the following figure, and a white water-absorbing filter is placed in the space above. The water stop valve of the water injection line is opened. The pressure reducing valve of the gas source line is opened to adjust the appropriate pressure. The one-way valve and water stop valve are then opened. The micro-pressure differential gauge is adjusted (slowly from low pressure to high pressure) until the white water-absorbing filter turns red. The pressure reading on the micro-pressure differential gauge is recorded as the breakthrough pressure.

[0021] The method further includes the following steps: Tensile strength reflects the manufacturing process characteristics of the fuel cell gas diffusion layer, and its performance depends on the strength of the carbon fiber itself and the strength of the penetrating adhesive after carbonization. Tensile strength is tested using a universal testing machine.

[0022] The compression property test method is obtained by calculating the difference between the initial thickness of the gas diffusion layer of the fuel cell with multiple porosity structure under no pressure and the thickness after multiple compressions.

[0023] In this example, in addition to the initial compression performance, the repeated compression recovery performance of the gas diffusion layer is important for the fuel cell assembly process and ensuring consistency in performance.

[0024] The compression characteristics are tested by repeatedly applying pressure (e.g., 1.0 MPa) to the outside of the pressure plate.

[0025] Record the first compression ratio γ1, the second compression ratio γ2, the third compression ratio γ3, etc. The compression ratios are calculated using Equation (1).

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[0026] In a normal compression test, the initial compression ratio γ1 is used for calculation. However, when the sample is repeatedly compressed, the initial thickness changes significantly. Therefore, in this example, as shown in Figure 5, the initial thickness of the sample without pressure is calculated according to Equation (2).

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[0027] The method further includes the following: The acid corrosion resistance includes the thickness uniformity, in-plane resistivity, tensile strength, and air permeability of the gas diffusion layer of the fuel cell before and after acid corrosion.

[0028] In this example, resistivity is one of the most important indicators affecting the performance of the gas diffusion layer. Reducing resistivity effectively reduces the ohmic loss of the fuel cell and improves conductivity. The intuitive expression for ohmic loss is the path loss due to heat generation, which means that resistivity also affects the thermal management performance of the battery. Resistivity in the in-plane direction is affected by the product manufacturing process (e.g., the effects of fiber dispersion, carbonization, and graphitization). Resistivity in the perpendicular direction has a greater impact on battery performance due to the direction of electron conduction than resistivity in the in-plane direction. During testing, resistivity values ​​in the perpendicular direction under different pressures are typically used as representative values, which can also be used to determine pre-stress during assembly. For example, perpendicular resistivity at 1 MPa is common. Resistivity is tested using a standard resistance test device.

[0029] From the user and R&D perspectives, durability is an important factor in measuring the stability of gas diffusion layer performance and the lifespan of fuel cells. In this application, durability is evaluated using the thickness uniformity (measured by a thickness gauge) of gas diffusion layer samples before and after acid corrosion, as well as the change in in-plane resistivity, tensile strength, and air permeability (the percentage change before and after the durability test). The acid corrosion test involves placing the sample in a container containing a 15% H2O2 + 1 mol / LH2SO4 mixed solution and treating it in a constant-temperature water bath at 80°C for 20 days. During this process, the container containing the solution is sealed, and the amount of solution is regularly monitored. If insufficient, additional solution is added promptly.

[0030] Furthermore, step S3 also includes the following: An evaluation function for each performance evaluation index of the gas diffusion layer of the fuel cell is obtained, and an evaluation value for each performance evaluation index is calculated. Each performance evaluation index is weighted based on how important the performance of each index is to the fuel cell performance. The evaluation scores in the performance evaluation system for the gas diffusion layers of fuel cells with multiple porosity structures are calculated.

[0031] In this example, the selection of the optimal design plan among the structural design plans with different porosity distributions relies not only on the comprehensive evaluation index system, but also on the evaluation function and index weighting. Evaluation is performed based on the test results and the constructed score function / weighting, and the structural design plans with different porosity distributions are comprehensively scored to obtain the optimal plan. The maximum score for each index item is 100 points, which is multiplied by the weighting factor to obtain the final score.

[0032] Thickness uniformity is evaluated by the thickness variation coefficient x 1 (the standard deviation of thickness divided by the average thickness). In the structural design plan of different porosity distributions, the maximum value of the thickness variation coefficient Tmax is selected as the lower limit of the score, and the minimum value of the thickness variation coefficient Tmin is selected as the upper limit of the score. In other words, it is the maximum value (max) and minimum value (min) among the various distribution structures of each fixed porosity. However, if the maximum value meets the technical requirements of a first-class product, it can still receive full marks.

[0033] As shown in equation (3), the thickness uniformity evaluation function Q1 can obtain a minimum of 40 points and a maximum of 60 points if certain index conditions are met. However, if the thickness uniformity is very poor (for example, 2% or more), the structural design plan is likely to deviate from the lower limit of the design index, and the score will be 0 points.

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[0034] The air permeability x2 is typically 200 mL·mm / (cm 2 The maximum air permeability among the structural design plans with different porosity distributions is selected as the upper limit of the score (for example, 3000 mL mm / (cm 2 If the air permeability exceeds ≈ ...

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[0035] The drainage capacity is expressed as the breakthrough pressure x3, and the breakthrough pressure of liquid water is between approximately 1 kPa and 7 kPa under different test conditions. Therefore, the evaluation function Q3 is shown in equation (5).

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[0036] Typical tensile strength x4 is between 15MPa and 30MPa. In a tensile strength test, a sample is fixed in a testing machine, a tensile force is applied, and the tensile force at which the sample breaks is recorded. The tensile strength is calculated by dividing the tensile force at break by the width and fixed length of the sample. The tensile strength evaluation function Q4 is shown in equation (6).

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[0037] The evaluation function Q5 of the compressibility characteristic x5 is shown in Equation (7). Among the structural design plans with different porosity distributions, the maximum value θmax of the compressibility characteristic is selected as the lower limit of the score, and the minimum value θmin is selected as the upper limit of the score.

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[0038] Currently, the resistivity x6 in the in-plane direction is usually less than 30 mΩ·cm, and in some cases less than 5 mΩ·cm. The resistivity evaluation function Q6 in the in-plane direction is shown in equation (8).

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[0039] Currently, the normal resistivity x7 is usually between 200 mΩ·cm and 500 mΩ·cm. The normal resistivity evaluation function Q7 is shown in equation (9).

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[0040] The performance (acid corrosion resistance) of samples with different porosity distribution structural design plans is evaluated before and after durability testing. For example, durability performance is evaluated using thickness uniformity, resistivity in the plane direction, tensile strength, and the range of change in air permeability. The durability evaluation function Q8 is shown in Equation (10).

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[0041] where: i The i in the formula (10) is a number, and it takes the values ​​8, 9, 10, and 11. x8 is the thickness uniformity variation range, x9 is the resistivity variation range in the plane direction, and x 10 is the change in tensile strength, x 11 represents the range of change in air permeability.

[0042] After obtaining the evaluation function, a weighting ratio (based on the degree of importance of the performance of the indicator to the performance of the fuel cell) is allocated to each indicator, as shown in Table 1. [Table 1]

[0043] Structural design plans with different porosity distributions can be scored and the optimal design plan selected by using the evaluation function and the weighting ratio of the indicators. The overall performance score is calculated as follows: It is calculated based on the index scores and weighting ratios, and the calculation method is as follows:

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[0044] According to a second aspect of the present invention, the present invention claims protection for an optimum design device based on performance evaluation of a gas diffusion layer of a fuel cell. one or more processing devices; and a memory in which one or more programs are stored, the one or more programs being executed by one or more processing devices, causing the one or more processing devices to realize an optimal design method based on a performance evaluation of the gas diffusion layer of the fuel cell.

[0045] In the third embodiment of the present invention, the optimal design method based on the performance evaluation of the gas diffusion layer of a fuel cell selects test data for a first-stage porosity structure, a second-stage porosity structure, and an ordered porosity structure, which have the same porosity but different structural designs, to demonstrate a complete evaluation process.

[0046] The three samples were coded A, B, and C, respectively, and the thickness uniformity test results of the samples are shown in Figure 7.

[0047] Using equation (3), Tmin = 1.01% and Tmax = 2.42%. Therefore, the thickness uniformity score for sample A is 100 points, for sample B it is 0 points, and for sample C it is 68.48 points.

[0048] The air permeability test results of the samples are shown in Figure 8. Using equation (4), the air permeability score of sample A is 2.04 points, sample B is 100 points, and sample C is 19.2 points. The drainage capacity test results of the samples are shown in Figure 9. Using equation (5), the drainage capacity score of sample A is 13.67 points, sample B is 89.67 points, and sample C is 48 points. The tensile strength test results of the samples are shown in Figure 10. Using equation (6), the tensile strength score of sample A is 49.47 points, sample B is 10.2 points, and sample C is 100 points.

[0049] The compression property test results of the samples are shown in FIG. 11. When calculated using equation (7), the compression property score of sample A is 38.30 points, sample B is 0 points, and sample C is 60.70 points. The in-plane resistivity test results of the samples are shown in Figure 12, and using equation (8) the in-plane resistivity score of sample A is 58.80 points, sample B is 0 points, and sample C is 93.56 points. The normal resistivity test results of the samples are shown in Figure 13, and using equation (9) the normal resistivity score for sample A is 47.62 points, sample B is 22.60 points, and sample C is 89.80 points.

[0050] The experimental results of the acid corrosion resistance index are shown in Figure 14, which includes the test results of the thickness uniformity variation, in-plane resistivity variation, tensile strength variation, and air permeability variation for three samples with the same porosity but different structures.

[0051] Using equation (10), we calculate The thickness uniformity variation score for sample A was 48.17 points, for sample B it was 6.33 points, and for sample C it was 79.67 points. The score for the change in resistivity in the plane direction for sample A is 100 points, for sample B it is 0 points, and for sample C it is 100 points. The tensile strength change score for sample A was 10.83 points, sample B was 0 points, and sample C was 32.67 points. The air permeability change range score for sample A was 94.33 points, for sample B it was 100 points, and for sample C it was 62.17 points.

[0052] The results are combined with Table 1 to calculate the total score for each sample using equation (11), as shown in Table 2 below. [Table 2]

[0053] Therefore, using equation (11), the total score for sample A is calculated as follows: 6% × 100 + 10% × 2.04 + 12% × 13.67 + 8.5% × 49.47 + 12.5% ​​× 38.3 + 12% × 58.8 + 9% × 47.62 + 6% × 48.17 + 6% × 100 + 9% × 10.83 + 9% × 94.33 = 46.53 points. Similarly, the total score for sample B is 33.04 points, and the total score for sample C is 66.50 points. Therefore, under the same porosity, sample C exhibits superior performance.

[0054] This embodiment not only selects the optimal product design, but also clarifies the differences in performance indexes between different product designs and leads to the optimal design direction of the product by compensating for shortcomings.

[0055] Although the specific embodiments of the present invention have been described in detail above, they are merely examples, and the present application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or alternatives to the present invention are within the scope of the present application. Therefore, any equivalent conversions, modifications, improvements, etc. made within the scope of the spirit and principles of the present application should be included in the scope of the present application.

Claims

1. An optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell, comprising: Determining an overall porosity of a gas diffusion layer of a fuel cell based on production demand, and obtaining a plurality of porosity structures based on the overall porosity; To obtain performance evaluation indexes for the gas diffusion layer of a fuel cell and to establish a performance evaluation system for the gas diffusion layer of a fuel cell; calculating an evaluation score for the plurality of porosity structures based on a performance evaluation system for gas diffusion layers of fuel cells by combining an evaluation function and a weight of an index; determining an optimal design plan from among the plurality of porosity structures based on the evaluation score; the plurality of porosity structures include at least a first stage porosity structure, a second stage porosity structure, and an ordered porosity structure; The first step porosity structure is such that the porosity of each layer of the gas diffusion layer changes linearly from large to small from top to bottom, The second step porosity structure is such that the porosity of each layer of the gas diffusion layer changes linearly from small to large from top to bottom, The ordered porosity structure is such that the porosity of each layer of the gas diffusion layer is uniformly distributed from top to bottom, the performance evaluation indexes of the gas diffusion layer of the fuel cell include at least a characteristic performance index, a mechanical performance index, an electrical performance index, and a durability performance index; the characteristic performance indexes include the air permeability and drainage capacity of the gas diffusion layer of the fuel cell; the mechanical performance index includes tensile strength and compressive properties of a gas diffusion layer of the fuel cell; the electrical performance index includes a normal resistivity and an in-plane resistivity of a gas diffusion layer of the fuel cell; the durability performance index includes an acid corrosion resistance of a gas diffusion layer of the fuel cell; Calculating an evaluation score based on a performance evaluation system for a gas diffusion layer of a fuel cell for the plurality of porosity structures by combining the evaluation function and the weight of the indexes, Obtaining an evaluation function of each performance evaluation index under the gas diffusion layer of the fuel cell and calculating an evaluation value of each performance evaluation index; assigning an index weight to the value of each performance evaluation index based on the degree of importance of each index performance to the fuel cell performance; calculating an evaluation score for each of the plurality of porosity structures based on a performance evaluation system for a gas diffusion layer of a fuel cell; Further comprising: scoring the structural design plans with different porosity distributions using the evaluation function and the index weighting ratio to derive an optimal design plan; The overall performance score is calculated based on the index scores and weighting ratios, and the calculation formula is as follows: [0013] where Q is the overall performance evaluation score of the structural design plan with different porosity distributions, y ｉ is the ratio of the weighting of the i-th index.

2. 2. An optimum design method based on performance evaluation of a gas diffusion layer of a fuel cell according to claim 1, comprising: The gas permeability is a main performance index of the gas diffusion layer, and the method for optimal design based on performance evaluation of the gas diffusion layer of a fuel cell further comprises comparing the performance differences of multiple porosity structures under the same pressure difference using a permeability meter by a constant pressure difference method.

3. 3. The method for optimal design based on performance evaluation of a gas diffusion layer of a fuel cell according to claim 2, comprising: using a test liquid water breakthrough pressure to represent the drainage capacity of a gas diffusion layer of said fuel cell; Before the test, inject red dye water into the solution reservoir, and close the one-way valve of the water injection line when the injected liquid level reaches the upper passage position of the solution reservoir; Connecting the water injection line to a pressure line of an air source, sandwiching the gas diffusion layers of the fuel cell with the plurality of porosity structures in a test jig, and placing a white water-absorbing filter paper in the upper space position; Open the water stop valve of the water supply line and the pressure reducing valve of the air source line to adjust the pressure to the appropriate level. an optimization method for a gas diffusion layer of a fuel cell based on performance evaluation, the method further comprising: opening the one-way valve and the stop valve, slowly adjusting the micro-pressure differential meter from low pressure to high pressure, and recording the pressure on the micro-pressure differential meter as the liquid water breakthrough pressure when the white water-absorbing filter paper turns red.

4. 4. The method for optimal design based on performance evaluation of a gas diffusion layer of a fuel cell according to claim 3, comprising: The tensile strength reflects the manufacturing process characteristics of the gas diffusion layer of the fuel cell, and its performance depends on the strength of the carbon fiber itself and the strength of the penetrating adhesive after carbonization, and the tensile strength is tested using a universal testing machine; The method for optimizing design based on performance evaluation of a gas diffusion layer for a fuel cell further comprises: the compression characteristic test method being obtained by calculating the difference between the initial thickness of the gas diffusion layer of the fuel cell in a non-pressurized state and the thickness after multiple compressions of the gas diffusion layer of the fuel cell having the multiple porosity structures.

5. 5. The method for optimal design based on performance evaluation of a gas diffusion layer of a fuel cell according to claim 4, comprising: The method for optimizing design based on performance evaluation of a gas diffusion layer of a fuel cell, wherein the acid corrosion resistance includes the thickness uniformity, in-plane resistivity, tensile strength, and air permeability of the gas diffusion layer of the fuel cell before and after acid corrosion.

6. An optimum design device based on performance evaluation of a gas diffusion layer of a fuel cell, one or more processors; and a memory in which one or more programs are stored, the one or more programs being executed by the one or more processors, causing the one or more processors to realize the optimal design method based on performance evaluation of the gas diffusion layer of a fuel cell according to any one of claims 1 to 5.

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