A gas diffusion layer aging attenuation prediction method based on offline and online combination

Abstract

The present application relates to the field of fuel cell technology, and in particular to a method for predicting the aging attenuation of a gas diffusion layer based on a combination of offline and online methods, wherein the method obtains the gas diffusion layer to be predicted and the initial performance, performs offline and online aging attenuation bench cycle tests respectively, and records the test time; after the test, the attenuation performance of the gas diffusion layer to be predicted is collected; offline performance tests are performed on samples after the offline aging test and samples after the test stack is disassembled one by one to obtain the average performance of the gas diffusion layer to be predicted at this time; the aging attenuation acceleration factor set of the offline durability test and the online bench durability cycle test is calculated and averaged to obtain the final acceleration factor combination, and then the final acceleration factor is obtained by adding and averaging. The present invention realizes the combination of the offline aging durability test and the online bench cycle test of the gas diffusion layer, establishes the correlation between offline and online, realizes the prediction of the online bench cycle life, and saves research and development costs.

Description

Technical Field

[0001] The present application relates to the field of fuel cell technology, and in particular to a method for predicting gas diffusion layer aging attenuation based on a combination of offline and online methods. Background Art

[0002] Durability is one of the key core factors affecting the commercialization of fuel cells. The ability of fuel cells to support long-term stable operation is a prerequisite for enhancing consumer confidence and achieving large-scale vehicle installation and operation.

[0003] At present, fuel cells are in a stage of continuous improvement in technology maturity, and their durability is directly affected by the performance of key component materials. The judgment of product durability can be carried out through actual vehicle operation or bench cycle testing, but both actual vehicle operation and bench cycle will incur high time and economic costs to complete the selection and matching test of key component materials. Although offline single material testing is low-cost and high-efficiency, it is difficult to reflect the operating conditions of actual vehicle operation or bench cycle testing, resulting in a split between offline and online performance. Summary of the invention

[0004] To achieve the above objectives, this application provides the following technical solutions:

[0005] According to a first aspect of the present invention, the present invention claims a method for predicting aging attenuation of a gas diffusion layer based on a combination of offline and online methods, comprising:

[0006] Acquiring a gas diffusion layer to be predicted and initial properties of the gas diffusion layer to be predicted;

[0007] Loading the gas diffusion layer to be predicted into a plurality of test fuel cells of equal power and size;

[0008] Performing a durability aging attenuation bench cycle test on each test stack according to the set actual vehicle operating conditions, and recording the cycle test time of each test stack;

[0009] After the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time;

[0010] The gas diffusion layer to be predicted is subjected to an offline durability test, and the offline durability test time is recorded; after the test is completed, the second attenuation average performance of the gas diffusion layer to be predicted after the offline durability test is collected;

[0011] Calculate and obtain the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack bench according to the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted;

[0012] Calculate and obtain an aging attenuation acceleration factor set for an offline durability test and an online bench durability cycle test according to the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted;

[0013] The final acceleration factor combination is obtained by adding and averaging the corresponding indicators of the aging attenuation acceleration factor set, and then the final acceleration factor is obtained by adding and averaging.

[0014] Furthermore, the obtaining of the gas diffusion layer to be predicted and the initial performance of the gas diffusion layer to be predicted further includes:

[0015] The test indexes of the gas diffusion layer to be predicted include thickness H, tensile strength T, roughness R, contact angle C, plane direction resistivity E, and air permeability P;

[0016] The initial performance of the gas diffusion layer to be predicted is recorded as X;

[0017] (1);

[0018] The performance of the gas diffusion layer to be predicted after aging attenuation is set to ;

[0019] The test indicators of the gas diffusion layer to be predicted after aging attenuation include thickness H ', tensile strength T ', roughness R ', contact angle C ', plane direction resistivity E ', permeability P ';

[0020] (2);

[0021] At this time, the GDL aging attenuation amplitude is :

[0022] ;

[0023] (3).

[0024] Furthermore, the gas diffusion layer to be predicted is loaded into a plurality of test stacks of equal power and size, and further comprises:

[0025] The number of the battery stack is recorded as N;

[0026] N=[N 1 ,N 2 ,N 3 ……] (4);

[0027] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0028] Furthermore, the endurance aging attenuation bench cycle test is performed on each test stack according to the set actual vehicle operating conditions, and the cycle test time of each test stack is recorded, and the test also includes:

[0029] The time of each stack cycle test is recorded as T;

[0030] T=[T 1 , T 2 , T 3 ……] (5).

[0031] Furthermore, after the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time, further comprising:

[0032] The first attenuation average performance X of the gas diffusion layer to be predicted after multiple endurance cycles of the test stack bench N They are:

[0033] (6);

[0034] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0035] Furthermore, the calculation of the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack bench according to the first attenuation average performance and the initial performance of the gas diffusion layer to be predicted also includes:

[0036] The aging attenuation of GDL after multiple battery stack endurance cycles is:

[0037] (7);

[0038] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0039] Furthermore, the method further comprises:

[0040] The second attenuation average performance X of the gas diffusion layer to be predicted after the offline durability test L for

[0041] (8)

[0042] At the same time, the aging attenuation amplitude of the gas diffusion layer to be predicted obtained by the offline durability test is

[0043] (9).

[0044] Furthermore, the aging attenuation acceleration factor set for the offline durability test and the online bench durability cycle test is calculated and obtained based on the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted, and further includes:

[0045] By dividing the difference between each variable and the initial performance in formula (8) by the difference between each variable and the initial performance in formula (6), the aging attenuation acceleration factor set θ for offline durability test and online bench durability cycle test is obtained:

[0046] (10).

[0047] Furthermore, the method of adding and averaging the corresponding indicators of the aging attenuation acceleration factor set to obtain a final acceleration factor combination, and then adding and averaging to obtain the final acceleration factor, further includes:

[0048] The corresponding indicators are added to obtain the average value to obtain the final acceleration factor combination, and then the final acceleration factor is obtained by adding and averaging. ;

[0049] (11) ;

[0050] In formula (11), all indicators are set to be sensitive to durability aging attenuation, and t represents the offline test time.

[0051] The present application relates to the field of fuel cell technology, and in particular to a method for predicting the aging attenuation of a gas diffusion layer based on a combination of offline and online, obtaining the gas diffusion layer to be predicted and the initial performance, performing offline and online aging attenuation bench cycle tests respectively and recording the test time; collecting the attenuation performance of the gas diffusion layer to be predicted after the test; performing offline performance tests on the samples after the offline aging test and the samples after the test stack is disassembled one by one, respectively, to obtain the average performance of the gas diffusion layer to be predicted at this time; calculating and obtaining the aging attenuation acceleration factor set of the offline durability test and the online bench durability cycle test and adding and averaging them to obtain the final acceleration factor combination, and then adding and averaging to obtain the final acceleration factor. The present invention realizes the combination of the offline aging durability test and the online bench cycle test of the gas diffusion layer, establishes the correlation between offline and online, realizes the prediction of the online bench cycle life, and saves research and development costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A workflow diagram of a method for predicting gas diffusion layer aging attenuation based on a combination of offline and online methods as claimed in an embodiment of the present application;

[0053] Figure 2A schematic diagram of the division of a gas diffusion layer to be predicted based on a gas diffusion layer aging attenuation prediction method combined with offline and online methods as claimed in an embodiment of the present application;

[0054] Figure 3 A schematic diagram of thickness test results after online bench cycle durability and offline durability tests of a gas diffusion layer aging attenuation prediction method based on a combination of offline and online methods claimed in an embodiment of the present application;

[0055] Figure 4 A schematic diagram of the average results of three sample thicknesses after online bench cycling and offline endurance tests of a gas diffusion layer aging attenuation prediction method based on a combination of offline and online methods as claimed in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] The terms "first", "second" and "third" in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" can explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0058] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] As one of the core components of the membrane electrode, the gas diffusion layer (GDL) of the fuel cell undertakes core functions such as air permeability, drainage, electrical conductivity, and thermal conductivity. This application proposes a multi-zone discrete prediction method for the aging attenuation acceleration factor of the gas diffusion layer that combines offline and online, realizing the combination of offline aging durability testing of the gas diffusion layer and online bench cycle testing. By determining the acceleration factor, the correlation between offline and online is established. The prediction of the online bench cycle life can be achieved through offline material level testing, thereby saving R&D costs.

[0060] According to the first embodiment of the present invention, the present invention claims a method for predicting the aging attenuation of a gas diffusion layer based on a combination of offline and online methods, referring to Figure 1 ,include:

[0061] Acquiring a gas diffusion layer to be predicted and initial properties of the gas diffusion layer to be predicted;

[0062] Loading the gas diffusion layer to be predicted into a plurality of test fuel cells of equal power and size;

[0063] Performing a durability aging attenuation bench cycle test on each test stack according to the set actual vehicle operating conditions, and recording the cycle test time of each test stack;

[0064] After the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time;

[0065] The gas diffusion layer to be predicted is subjected to an offline durability test, and the offline durability test time is recorded; after the test is completed, the second attenuation average performance of the gas diffusion layer to be predicted after the offline durability test is collected;

[0066] Calculate and obtain the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack bench according to the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted;

[0067] Calculate and obtain an aging attenuation acceleration factor set for an offline durability test and an online bench durability cycle test according to the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted;

[0068] The final acceleration factor combination is obtained by adding and averaging the corresponding indicators of the aging attenuation acceleration factor set, and then the final acceleration factor is obtained by adding and averaging.

[0069] In this embodiment, a GDL sample of a certain type developed or selected independently is selected for offline performance testing. Due to the different active areas of the stack design, the size of the installed GDL is also different. The size of the GDL of this model is marked as S, such as S=110cm 2 Since the reaction uniformity of the inlet and outlet of the GDL after loading into the fuel cell stack is different, the aging attenuation amplitude in the later stage is also different. The aging attenuation of the local area cannot represent the overall aging attenuation. Therefore, the GDL of size S is divided into a number of grid areas of the same size, such as Figure 2 As shown in the figure, it is divided into 25 grids of the same size. Three pieces are selected for testing and the numerical average is recorded as the initial performance of GDL. In order to avoid the test error caused by edge effect, as shown in the figure, Figure 2 As shown, some areas close to the edge are discarded, such as the middle size is 100cm after discarding the edge. 2 .

[0070] Furthermore, the obtaining of the gas diffusion layer to be predicted and the initial performance of the gas diffusion layer to be predicted further includes:

[0071] The test indexes of the gas diffusion layer to be predicted include thickness H, tensile strength T, roughness R, contact angle C, plane direction resistivity E, and air permeability P;

[0072] The initial performance of the gas diffusion layer to be predicted is recorded as X;

[0073] (1);

[0074] The performance of the gas diffusion layer to be predicted after aging attenuation is set to ;

[0075] The test indicators of the gas diffusion layer to be predicted after aging attenuation include thickness H ', tensile strength T ', roughness R ', contact angle C ', plane direction resistivity E ', permeability P ';

[0076] (2);

[0077] At this time, the GDL aging attenuation amplitude is :

[0078] ;

[0079] (3).

[0080] Furthermore, the gas diffusion layer to be predicted is loaded into a plurality of test stacks of equal power and size, and further comprises:

[0081] The number of the battery stack is recorded as N;

[0082] N=[N 1 ,N 2 ,N 3 ……] (4);

[0083] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0084] Furthermore, the endurance aging attenuation bench cycle test is performed on each test stack according to the set actual vehicle operating conditions, and the cycle test time of each test stack is recorded, and the test also includes:

[0085] The time of each stack cycle test is recorded as T;

[0086] T=[T1, T2, T3……] (5).

[0087] In this embodiment, T1=1000h, T2=1500h, T3=2000h, etc. are set;

[0088] The actual vehicle operating conditions are set to be cyclic conditions in accordance with the national standard GB / Z 44116-2024.

[0089] Furthermore, after the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time, further comprising:

[0090] The first attenuation average performance XN of the gas diffusion layer to be predicted after the endurance cycles of the test stack benches are respectively:

[0091] (6);

[0092] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0093] Furthermore, the step of calculating and obtaining the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack warning bench based on the average performance and initial performance of the gas diffusion layer to be predicted also includes:

[0094] The aging attenuation of GDL after multiple battery stack endurance cycles is:

[0095] (7);

[0096] Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks.

[0097] Furthermore, the method further comprises:

[0098] The second attenuation average performance X of the gas diffusion layer to be predicted after the offline durability test L for

[0099] (8)

[0100] At the same time, the aging attenuation amplitude of the gas diffusion layer to be predicted obtained by the offline durability test is

[0101] (9).

[0102] In this embodiment, offline aging acceleration methods such as electrochemical oxidation, freeze-thaw cycle, hot and cold shock, cyclic compression and other methods are used for offline durability testing. For example, the high-temperature acidic oxidation mixed accelerated aging method is: the sample is placed in a solution at a constant temperature of 80°C, and the concentration of ultrapure water is 1 mol / L H 2 SO 4 and 15% H 2 O 2 After sealing, perform aging test for a certain time t hours, then take it out, such as t=500h, and then soak and clean it with deionized water, dry it and perform test analysis again.

[0103] Furthermore, the aging attenuation acceleration factor set for the offline durability test and the online bench durability cycle test is calculated and obtained based on the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted, and further includes:

[0104] By dividing the difference between each variable and the initial performance in formula (8) by the difference between each variable and the initial performance in formula (6), the aging attenuation acceleration factor set θ for offline durability test and online bench durability cycle test is obtained:

[0105] (10).

[0106] It can be seen from formula (10) that each acceleration factor contains multiple indicators: thickness H, tensile strength T, roughness R, contact angle C, plane direction resistivity E, change rate of air permeability P and test time ratio, which is a combination of composite indicators to reduce the prediction error of a single indicator. Compare the calculation results of the same indicator numbered N1, N2, and N3 in formula (10), because N 1 、N 2 、N 3 The duration of endurance operation varies greatly. If the indicator remains basically unchanged, it means that the indicator is not sensitive to durability aging attenuation, and the indicator will not be used for subsequent calculations.

[0107] Furthermore, the method of adding and averaging the corresponding indicators of the aging attenuation acceleration factor set to obtain a final acceleration factor combination, and then adding and averaging to obtain the final acceleration factor, further includes:

[0108] The corresponding indicators are added to obtain the average value to obtain the final acceleration factor combination, and then the final acceleration factor is obtained by adding and averaging. ;

[0109] (11) ;

[0110] In formula (11), all indicators are set to be sensitive to durability aging attenuation, and t represents the offline test time.

[0111] Among them, in this embodiment, after random sampling, GDL samples are subjected to offline acid corrosion or other methods of durability testing (time is t) and after loading the rear frame durability cycle test (time is T). The former is to perform performance tests on the samples after offline testing in turn to obtain offline performance data set 1, and the latter is to disassemble the stack and remove the GDL samples for offline testing to obtain offline performance data set 2. The relationship between data sets 1 and 2 is established to predict the aging attenuation of the gas diffusion layer.

[0112] In this embodiment, the middle 100mm×100mm of the sample with a size of about 110mm×110mm is taken as the data test area to avoid the test error caused by the edge effect. Then each 100mm×100mm interval is evenly divided into 25 grids for testing. Figure 3 As shown, the size of the entire test area is 100mm×100mm, and the horizontal and vertical axes display scale areas (20mm, 40mm, 60mm, 80mm). Figure 3A multi-zone discrete method is used to represent different locations in the battery stack, which is composed of 25 discrete values, and then the average of the measured values ​​of the 25 grids is calculated. Then multiple samples are measured using the same method, and the average value of multiple samples is calculated, such as 3 samples. The average value is as follows Figure 4 Similarly, for multiple samples such as tensile strength, roughness, contact angle, plane direction resistivity, air permeability, etc., the average values ​​after online bench cycle and offline durability test are shown in Table 1.

[0113] Table 1: Index test values ​​after online bench cycle and offline durability test

[0114]

[0115] The average initial performance of GDL in formula (1) is denoted by X.

[0116] X=[242.1, 18.8, 6.5, 148, 17.1, 2246.5]

[0117] The performance XN of the GDL after aging attenuation after three battery stack bench endurance cycles (1000h, 1500h, 2000h) are:

[0118] XN 1 =[238.6, 16.8, 6.6, 146, 16.2, 2278.9]

[0119] XN 2 =[236.2, 15.9, 6.6, 145, 15.4, 2297.8]

[0120] XN 3 =[234.8, 14.2, 6.6, 143, 14.2, 2312.5]

[0121] Formula (10) The aging attenuation acceleration factor set θ for the offline durability test and the online bench durability cycle test is shown in Table 2;

[0122] Table 2 Experimental values ​​of aging attenuation acceleration factor set

[0123]

[0124] The corresponding indicators marked in gray in the above table have not changed and are all 1.00, indicating that the indicator is not sensitive to durability aging attenuation, and therefore is not used as an acceleration factor calculation.

[0125] Therefore, the final acceleration factor combination obtained using formula (11) is :

[0126] ;

[0127] Therefore, the acceleration factor of the offline aging endurance test and the online bench cycle test of this method is 6.19, that is, one hour of offline test is equivalent to 6.19 hours of online bench cycle endurance test.

[0128] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0129] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

[0130] The specific implementation methods of the invention are described in detail above, but they are only examples, and the present application is not limited to the specific implementation methods described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the present application, and therefore, the equalization, modification, and improvement made without departing from the spirit and principle of the present application should be included in the scope of the present application.

Claims

1. A method for predicting gas diffusion layer aging attenuation based on a combination of offline and online methods, characterized in that: include: Acquiring a gas diffusion layer to be predicted and initial properties of the gas diffusion layer to be predicted; Loading the gas diffusion layer to be predicted into a plurality of test fuel cells of equal power and size; Performing a durability aging attenuation bench cycle test on each test stack according to the set actual vehicle operating conditions, and recording the cycle test time of each test stack; After the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time; Performing an offline durability test on the gas diffusion layer to be predicted, and recording the offline durability test time; After completion, collecting the second attenuation average performance of the gas diffusion layer to be predicted after the offline durability test; Calculate and obtain the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack bench according to the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted; Calculate and obtain an aging attenuation acceleration factor set for an offline durability test and an online bench durability cycle test according to the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted; According to the corresponding indicators of the aging attenuation acceleration factor set, the average value is added to obtain the final acceleration factor combination, and then the final acceleration factor is obtained by adding and averaging; The obtaining of the gas diffusion layer to be predicted and the initial performance of the gas diffusion layer to be predicted also includes: The test indexes of the gas diffusion layer to be predicted include thickness H, tensile strength T, roughness R, contact angle C, plane direction resistivity E, and air permeability P; The initial performance of the gas diffusion layer to be predicted is recorded as X; （1）； The performance of the gas diffusion layer to be predicted after aging attenuation is set to ; The test indicators of the gas diffusion layer to be predicted after aging attenuation include thickness H ', tensile strength T ', roughness R ', contact angle C ', plane direction resistivity E ', permeability P '; （2）； At this time, the GDL aging attenuation amplitude is : ； (3); The gas diffusion layer to be predicted is loaded into a plurality of test fuel cells of equal power and size, and further comprising: The number of the battery stack is recorded as N; N=[N1,N2,N3…](4); Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks; The method further includes performing a durability aging attenuation bench cycle test on each test stack according to the set actual vehicle operating conditions, and recording the cycle test time of each test stack. The time of each stack cycle test is recorded as T; T = [T1, T2, T3…] (5); After the cycle test is completed, the test stacks after multiple aging and attenuation at different cycle test times are disassembled piece by piece, and the respective gas diffusion layers to be predicted are taken out for performance testing to obtain the first attenuation average performance of the gas diffusion layers to be predicted at this time, further comprising: The first attenuation average performance X of the gas diffusion layer to be predicted after multiple endurance cycles of the test stack bench N They are: （6）； Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks; The step of calculating and obtaining the aging attenuation amplitude of the gas diffusion layer to be predicted after each endurance cycle of the test stack bench based on the first attenuation average performance and the initial performance of the gas diffusion layer to be predicted also includes: The aging attenuation of GDL after multiple battery stack endurance cycles is: (7)； Among them, 1, 2, and 3 represent the numbers of the 1st, 2nd, and 3rd battery stacks; The method further includes: The second attenuation average performance X of the gas diffusion layer to be predicted after the offline durability test L for (8) At the same time, the aging attenuation amplitude of the gas diffusion layer to be predicted obtained by the offline durability test is (9); The step of calculating and obtaining an aging attenuation acceleration factor set for an offline durability test and an online bench durability cycle test based on the aging attenuation amplitude, the first attenuation average performance, the second attenuation average performance and the initial performance of the gas diffusion layer to be predicted further includes: By dividing the difference between each variable and the initial performance in formula (8) by the difference between each variable and the initial performance in formula (6), the aging attenuation acceleration factor set θ for offline durability test and online bench durability cycle test is obtained: (10); The method of adding and averaging the corresponding indicators of the aging attenuation acceleration factor set to obtain a final acceleration factor combination, and then adding and averaging to obtain a final acceleration factor, further includes: The corresponding indicators are added to obtain the average value to obtain the final acceleration factor combination, and then the final acceleration factor is obtained by adding and averaging. ; (11)； In formula (11), all indicators are set to be sensitive to durability aging attenuation, and t represents the offline test time.

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