Construction method and application of corrosion resistance degree-mechanical property analysis model of metal material

Abstract

The invention relates to a construction method and application of a corrosion resistance degree-mechanical property analysis model of a metal material. The application relates to an electric device comprising a battery system. The construction method of the analysis model comprises the following steps: taking a metal material as a test object, and obtaining a corrosion performance test experiment data set at different equivalent corrosion time points under a corrosion test condition and a mechanical performance test experiment data set at different corrosion degrees corresponding to the different equivalent corrosion time points; based on the corrosion performance test experiment data set, a first group of empirical relational expressions of corrosion parameters changing along with the equivalent corrosion time are established, based on the mechanical performance test experiment data set, a second group of empirical relational expressions of mechanical parameters changing along with the equivalent corrosion time are also established, and the corrosion test conditions are used for simulating a target service environment. The analysis model can be effectively used for mechanical property prediction and service life evaluation of the metal material, and the metal material can comprise an aluminum alloy material and can further comprise a battery box body material.

Description

Technical Field

[0001] The present application relates to the technical fields of corrosion resistance test and analysis of metal materials and battery technology, further relates to a construction method and application of a corrosion resistance-mechanical property analysis model for metal materials, and more particularly relates to a construction method of a corrosion resistance-mechanical property analysis model for metal materials, an analysis method and device for the service life of metal materials, an analysis method and device for the mechanical properties of metal materials, a computer device, a computer-readable storage medium, and an electrical device. Background Art

[0002] The statements herein only provide background information related to the present application and do not necessarily constitute prior art.

[0003] The design and development of battery box materials have high requirements for both structural strength and corrosion resistance, which are crucial for the safe operation of the battery and even the entire electrical device. Taking the fuel cell box material as an example, the current research on the corrosion behavior and mechanism of fuel cell box materials often only focuses on the electrochemical corrosion behavior of fuel cell box materials or the corrosion rate in different corrosion media, and it is difficult to provide effective guidance for the design and development of fuel cell box materials. Summary of the Invention

[0004] In view of the above problems, the present application provides a construction method of a corrosion resistance-mechanical property analysis model for metal materials, an analysis method and device for the service life of metal materials, an analysis method and device for the mechanical properties of metal materials, a computer device, a computer-readable storage medium, and an electrical device. The corrosion resistance-mechanical property analysis model for metal materials can be effectively used for predicting the mechanical properties and evaluating the service life of metal materials. The metal materials involved may include, but are not limited to, aluminum alloy materials, and may also include, but are not limited to, battery box materials.

[0005] In a first aspect, the present application provides a construction method of a corrosion resistance-mechanical property analysis model for metal materials, which includes the following steps:

[0006] Taking the metal material as a test object, obtaining test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain a corrosion performance test experimental data set, and also obtaining test values of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain a mechanical property test experimental data set; wherein, the corrosion test conditions are used to simulate the target service environment of the metal material; the corrosion parameters include at least one of corrosion degree and corrosion rate;

[0007] Based on the corrosion performance test experimental data set, a first set of empirical relationships between the corrosion parameters and the equivalent corrosion time is established, and based on the mechanical performance test experimental data set, a second set of empirical relationships between the mechanical parameters and the equivalent corrosion time is established.

[0008] Taking metal materials as the test objects, simulating the target service environment of the metal materials under corrosion test conditions, obtaining the corrosion performance test experimental data set at different equivalent corrosion time points and the mechanical performance test experimental data set at different corrosion degrees corresponding to different equivalent corrosion time points. Using the equivalent corrosion time under corrosion test conditions and the mechanical properties at different corrosion degrees as a link, a first set of empirical relationships between corrosion parameters including at least one of the corrosion degree and the corrosion rate and the equivalent corrosion time and a second set of empirical relationships between at least one mechanical parameter and the equivalent corrosion time are established, thereby constructing an analysis model between the corrosion resistance and the mechanical properties of the metal materials, which can help understand the corrosion mechanism of the metal materials, and can be used to predict and analyze the mechanical properties of the metal materials under the target service conditions according to the corrosion behavior of the metal materials, and evaluate the service life of the metal material structural parts in the target service environment.

[0009] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameter includes at least one of the tensile fracture strength and the fracture elongation.

[0010] When the mechanical parameter in this method can include at least one of the tensile fracture strength and the fracture elongation, the established corrosion resistance-mechanical property analysis model of the metal material is applicable to metal material structural parts that are prone to failure due to tensile stress.

[0011] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameter includes the yield strength.

[0012] By selecting appropriate parameters for the fitting function relationship, it is beneficial to obtain a second set of empirical relationships with better fitting effects, and further beneficial to obtain a more effective corrosion resistance-mechanical property analysis model.

[0013] Based on any suitable implementation manner of the present application, further, in some implementation manners, the construction method satisfies at least one of the following characteristics:

[0014] The metal material is an aluminum alloy material;

[0015] The metal material is a metal structural part, and can be an aluminum alloy structural part.

[0016] Based on any suitable implementation manner of the present application, further, in some implementation manners, the construction method satisfies at least one of the following characteristics:

[0017] The metal material is any one of the battery box materials; optionally, the battery box materials include fuel cell box materials; optionally, the battery box materials include lithium battery box materials.

[0018] The metal material includes at least a part of the structural members of the battery box; optionally, the battery box structural members include at least a part of the structural members of the fuel cell box; optionally, the battery box structural members include at least a part of the structural members of the lithium battery box.

[0019] The metal material can be an aluminum alloy material or a metal structural member, and further can be an aluminum alloy structural member. Since die-cast aluminum alloy has the advantages of low density, high specific strength, excellent thermal stability, good machinability, low cost, etc., it can be used to prepare various parts of an automobile, including cylinder blocks, generator housings, fuel cell boxes, various engine brackets, etc., but not limited thereto. Among them, the aluminum alloy material can be applied to the battery technology field and can be used as the main material (including the composition material) of the battery box or the aluminum alloy structural member in the battery box. Therefore, the metal material can be the battery box material, and the battery box can include but not be limited to the fuel cell box, and can also include but not be limited to the lithium battery box; correspondingly, the metal material can include at least a part of the structural members of the battery box. When obtaining the corrosion parameters and mechanical parameters based on the aluminum alloy material, the corrosion resistance-mechanical property analysis model of the metal material constructed can be applied to the mechanical property prediction and life assessment of the aluminum alloy material. At this time, it is also helpful to understand the white rust corrosion mechanism of the aluminum alloy material. When the aluminum alloy material is used as the main material or composition material of the battery box or the structural member in the battery box, the corrosion resistance-mechanical property analysis model of the metal material can be applied to the mechanical property prediction and life assessment of the battery box or the structural member in the battery box.

[0020] Taking the fuel cell box as an example, it is also helpful to understand the white rust corrosion mechanism of the fuel cell box material. When taking the fuel cell box material as the test object, the corrosion behavior of the fuel cell box material can be analyzed, the corrosion rates of different fuel cell box materials can be determined, the relationship between the corrosion degree and mechanical properties of the fuel cell box material can be established, which has certain reference significance for the safe operation of fuel cells and even electrical devices including fuel cells.

[0021] Based on any suitable implementation manner of the present application, further, in some implementation manners, the corrosion performance test experimental data set at least includes the corrosion performance test experimental data set under salt spray corrosion test conditions;

[0022] Optionally, the salt spray corrosion test conditions include at least one of the following salt spray conditions: NaCl aqueous solution salt spray condition, acetate salt spray condition, copper salt accelerated acetate salt spray condition, cyclic salt spray corrosion condition, or a combination thereof.

[0023] Further optionally, the salt spray corrosion test conditions include the NaCl aqueous solution salt spray condition.

[0024] Based on any suitable embodiment of the present application, further, in some embodiments, the NaCl aqueous solution salt spray condition includes the following parameters: a simulated salt spray condition of a 3 wt% - 6 wt% NaCl aqueous solution at 34 - 36°C.

[0025] When the corrosion performance test experimental data set includes at least the corrosion performance test experimental data set under the salt spray corrosion test conditions, the corrosion resistance - mechanical property analysis model of the metal material constructed can be applicable to metal materials, their structural components or products in service environments in fields such as the road traffic field, computer field, electronic communication field, electrical appliance field, etc., and can also be applicable to structural components or products in related service environments such as electroplating, coating, packaging boxes, transportation equipment, etc. Among them, the road traffic field may involve but is not limited to road vehicle electronic and electrical equipment, rail transit locomotive and vehicle equipment and devices, automotive parts and other equipment or their metal structural components; the computer field may involve but is not limited to computers, display screens, hosts, computer components, medical equipment and other precision instruments, equipment, products or their metal structural components; the electronic communication field may involve but is not limited to mobile phones, radio frequency devices, electronic communication components, printed circuit boards (PCBs), printed circuit board assemblies (PCBAs) and other equipment, products or their metal structural components; electrical appliances may involve but is not limited to various household electrical appliances, lamps, transformers and other household electrical appliances, instruments and meters, medical devices and other equipment, products or their metal structural components.

[0026] Non - restrictively, the model based on the NaCl aqueous solution salt spray condition to obtain the corrosion performance test experimental data set can be applied to distinguish the quality and uniformity of protective coatings and to compare the differences in the salt spray corrosion resistance of specimens with similar structures, but is not limited thereto. Non - restrictively, the model based on the acetate salt spray condition to obtain the corrosion performance test experimental data set can be applied to southern coastal cities, salt spray environments with relatively harsh conditions, etc.; non - restrictively, the model based on the copper salt accelerated acetate salt spray condition to obtain the corrosion performance test experimental data set can be applied to salt spray environments with harsh conditions, etc.; non - restrictively, the model based on the cyclic salt spray corrosion condition to obtain the corrosion performance test experimental data set can be applied to high - temperature and high - humidity environments, etc.

[0027] For the NaCl aqueous solution salt spray condition, the aforementioned test conditions are beneficial for distinguishing the corrosion resistance of battery boxes, automotive parts, etc.

[0028] Based on any suitable implementation manner of the present application, further, in some implementation manners, the establishment of the first set of empirical relationships between the corrosion parameters and the equivalent corrosion time based on the corrosion performance test experimental data set includes:

[0029] For each of the corrosion parameters in the corrosion parameters, respectively perform piecewise fitting based on the corresponding corrosion performance test experimental data set. For each piecewise fitting interval, use the corresponding corrosion parameter as the dependent variable and the equivalent corrosion time as the independent variable, and perform fitting in the form of a power function or a linear function respectively to construct the empirical relationship between the corresponding type of corrosion parameter and the equivalent corrosion time in each piecewise fitting interval, and obtain the first set of empirical relationships.

[0030] The establishment of the first set of empirical relationships between the corrosion parameters and the equivalent corrosion time can be obtained by piecewise fitting for each corrosion parameter respectively. The fitting method for each piece can adopt a power function or a linear function. At this time, the fitting curve has a higher degree of coincidence with the experimental test data set, and the model is more effective, but is not limited to the aforementioned function types.

[0031] Based on any suitable implementation manner of the present application, further, in some implementation manners, in the first set of empirical relationships, the fitting manner of the power function is y1 = A·x B , and the fitting manner of the linear function is y1 = a + b·x; where x is the equivalent corrosion time, y1 is the corrosion parameter, A is a positive number, B is a negative number, b is a positive number, and a is a real number;

[0032] Optionally, a is a negative number.

[0033] Based on any suitable implementation manner of the present application, further, in some implementation manners, A is a real number selected from 0.01 to 1.00, B is a real number selected from -0.3 to -0.8, b is a real number selected from 0.001 to 0.05, and a is a real number selected from 0.02 to -0.8;

[0034] Optionally, a is a real number selected from -0.001 to -0.8, and further optionally, a is a real number selected from -0.001 to -0.5;

[0035] Optionally, b is a real number selected from 0.001 to 0.02, and further optionally, b is a real number selected from 0.001 to 0.01.

[0036] By selecting a suitable fitting function type, it is beneficial to obtain a first set of empirical relationships with better fitting effects, and further obtain a more effective corrosion resistance-mechanical property analysis model.

[0037] Based on any suitable implementation manner of the present application, further, in some implementation manners, the corrosion performance test experimental data set includes at least one of the corrosion performance test experimental data set under electrochemical corrosion test conditions and the corrosion performance test experimental data set under immersion corrosion test conditions;

[0038] Optionally, the corrosion parameters in the corrosion performance test experimental data set under electrochemical corrosion test conditions include at least one of the self-corrosion potential and the self-corrosion current;

[0039] Optionally, the corrosion parameters in the corrosion performance test experimental data set under immersion corrosion test conditions include at least one of the corrosion degree and the corrosion rate.

[0040] When the corrosion performance test experimental data set includes the corrosion performance test experimental data set under electrochemical corrosion test conditions, the corrosion resistance degree-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of the metal material in an electrochemical environment. For example, but not limited to, the performance prediction and life assessment of a battery box, and further, it can include, but not limited to, the performance prediction and life assessment of a fuel cell box.

[0041] When the corrosion performance test experimental data set includes the corrosion performance test experimental data set under immersion corrosion test conditions, the corrosion resistance degree-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of the metal material in an environment in contact with a corrosive liquid.

[0042] When the corrosion performance test experimental data set includes both the corrosion performance test experimental data set under electrochemical corrosion test conditions and the corrosion performance test experimental data set under immersion corrosion test conditions, the corrosion resistance degree-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of a battery box with an electrolyte built in, and further, it can include, but not limited to, the performance prediction and life assessment of a fuel cell box.

[0043] Based on any suitable implementation manner of the present application, further, in some implementation manners, the establishment of the second set of empirical relationships between the mechanical parameters and the equivalent corrosion time based on the mechanical performance test experimental data set includes:

[0044] For each mechanical parameter in the mechanical parameters, piecewise fitting is respectively performed based on the corresponding mechanical performance test experimental data set. Each fitting interval takes the corresponding mechanical parameter as the dependent variable and the equivalent corrosion time as the independent variable, and fitting is respectively performed in the form of a power function or a linear function to construct the empirical relationship between the corresponding type of mechanical parameter and the equivalent corrosion time, and the second set of empirical relationships is obtained.

[0045] The establishment of the second set of empirical relationships for the variation of mechanical parameters with equivalent corrosion time can be obtained for each mechanical parameter separately through piecewise fitting. The fitting method for each segment can use a power function or a linear function. At this time, the fitting curve has a higher degree of coincidence with the experimental test data set, and the model is more effective, but is not limited to the aforementioned function types.

[0046] Based on any suitable implementation manner of the present application, further, in some implementation manners, in the second set of empirical relationships, the fitting manner of the power function is y = M·x N , and the fitting manner of the linear function is y2 = m + n·x; where x is the equivalent corrosion time, y2 is the mechanical parameter, M is a positive number, N is a negative number, n is a negative number, and m is a positive number.

[0047] Based on any suitable implementation manner of the present application, further, in some implementation manners, M is a real number selected from 1 to 250, N is a real number selected from -0.01 to -1, n is a real number selected from -0.1 to -5, and m is a real number selected from 1 to 300;

[0048] Optionally, N is a real number selected from -0.01 to -0.5, and further optionally, N is a real number selected from -0.01 to -0.2;

[0049] Optionally, n is a real number selected from -1 to -3; optionally, n is a real number selected from -0.5 to -1.5; optionally, n is a real number selected from -0.05 to -0.5.

[0050] Based on any suitable implementation manner of the present application, further, in some implementation manners, the method for constructing the corrosion resistance-mechanical property analysis model of the metal material further includes the following steps: establishing a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment.

[0051] By establishing an empirical relationship (which can be denoted as the third set of empirical relationships) between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, the equivalent corrosion time can be converted into the service time under the target service environment, so as to more directly predict the service life of the metal material and its structural parts or products.

[0052] Based on any suitable implementation manner of the present application, further, in some implementation manners, the method for constructing the corrosion resistance-mechanical property analysis model of the metal material includes the following steps: establishing a fourth set of empirical relationships between the corrosion rate under the corrosion test conditions and the equivalent corrosion time, and the first set of empirical relationships includes the fourth set of empirical relationships.

[0053] By establishing an empirical relationship between the corrosion rate and the equivalent corrosion time under corrosion test conditions (which can be denoted as the fourth set of empirical relationships), the correlation between the corrosion behavior and mechanical properties of metallic materials in the target service environment can be dynamically analyzed.

[0054] In a second aspect of the present application, there is provided a method for analyzing the service life of a metallic material, where the metallic material is as defined in the first aspect of the present application.

[0055] In some embodiments, the method for analyzing the service life of the metallic material comprises the following steps:

[0056] Determine mechanical parameters related to the failure behavior of the metallic material according to the target service environment of the metallic material, and determine corrosion test conditions capable of simulating the target service environment, and obtain test values of the corrosion degree of the metallic material under the corrosion test conditions;

[0057] Obtain service life parameters of the metallic material under the corrosion test conditions according to the test values of the corrosion degree, the effective state threshold of the mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metallic material; wherein, the corrosion resistance-mechanical property analysis model of the metallic material at least comprises the following relationships: a first set of empirical relationships in which corrosion parameters representing the corrosion degree vary with the equivalent corrosion time and a second set of empirical relationships in which the mechanical parameters vary with the equivalent corrosion time.

[0058] The method for analyzing the service life of the metallic material selects mechanical parameters related to the failure behavior of the metallic material based on the target service environment of the metallic material, and selects corrosion test conditions capable of simulating the target service environment, and then obtains test values of the corrosion degree of the metallic material under the selected corrosion test conditions, so that service life parameters of the metallic material under the selected corrosion test conditions can be obtained according to the test values of the corrosion degree, the effective state threshold of the selected mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metallic material. The corrosion resistance-mechanical property analysis model of the metallic material takes the equivalent corrosion time and the mechanical properties at different corrosion degrees as a link, and at least comprises the following two relationships: a first set of empirical relationships in which corrosion parameters including at least one of the corrosion degree and the corrosion rate vary with the equivalent corrosion time and a second set of empirical relationships in which the aforementioned mechanical parameters vary with the equivalent corrosion time. This analysis method can be effectively and accurately used to analyze the service life of metallic materials in the target service environment.

[0059] Based on any suitable embodiment of the present application, further, in some embodiments, the service life parameters at least include the equivalent corrosion time.

[0060] According to the foregoing analysis method, at least the equivalent corrosion time parameter of the metal material can be obtained, which can reflect the service life of the metal material.

[0061] Based on any suitable implementation manner of the present application, further, in some implementation manners, obtaining the service life parameter of the metal material under the corrosion test condition according to the test value of the corrosion degree, the effective state threshold of the mechanical parameter, and the corrosion resistance-mechanical property analysis model of the metal material includes:

[0062] According to the test value of the corrosion degree, the effective state threshold of the mechanical parameter, the corrosion resistance-mechanical property analysis model of the metal material, and the third set of empirical relationships between the equivalent corrosion time under the corrosion test condition and the service time under the target service environment, obtain the remaining service time of the metal material.

[0063] The remaining service time of the metal material can be obtained according to the test value of the corrosion degree of the metal material, the effective state threshold of the mechanical parameter related to the failure behavior of the metal material, the corrosion resistance-mechanical property analysis model of the metal material, and the empirical relationship between the equivalent corrosion time under the selected corrosion test condition and the service time under the target service environment, so as to realize the prediction and analysis of the remaining service life of the metal material.

[0064] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameter includes at least two types. Sort the mechanical parameters in descending order according to the degree of failure response of the metal material, and obtain the corrosion resistance-mechanical property analysis model of the metal material according to the mechanical parameter ranked first.

[0065] Sort the mechanical parameters in descending order according to the degree of failure response of the metal material to the metal material, and obtain the corrosion resistance-mechanical property analysis model of the metal material according to the mechanical parameter ranked first, which can more effectively reflect the correlation between the corrosion behavior of the metal material and the failure of mechanical properties under the target service environment.

[0066] Based on any suitable implementation manner of the present application, further, in some implementation manners, the corrosion resistance-mechanical property analysis model of the metal material is constructed according to the construction method of the corrosion resistance-mechanical property analysis model of the metal material described in the first aspect of the present application.

[0067] The corrosion resistance-mechanical property analysis model involved in the foregoing analysis method of the service life of the metal material can be constructed by using the construction method in the first aspect of the present application, and a relationship between the corrosion degree of the metal material and the mechanical properties of at least one mechanical parameter including tensile fracture strength and fracture elongation can be constructed.

[0068] In the third aspect of the present application, a service life analysis device for a metal material is provided, where the metal material is defined as in the first aspect of the present application.

[0069] In some embodiments, the service life analysis device for the metal material includes:

[0070] A corrosion performance data acquisition module, configured to determine mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine corrosion test conditions capable of simulating the target service environment, and acquire test values of the corrosion degree of the metal material under the corrosion test conditions;

[0071] A corrosion performance data processing module, configured to obtain service life parameters of the metal material under the corrosion test conditions according to the test values of the corrosion degree, the effective state threshold of the mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metal material; wherein, the corrosion resistance-mechanical property analysis model of the metal material is defined as in the first aspect or the second aspect of the present application.

[0072] The service life analysis device for the metal material provided in the third aspect of the present application can be used to implement the analysis method for the service life of the metal material described in the second aspect of the present application.

[0073] In the fourth aspect of the present application, an analysis method for the mechanical properties of a metal material is provided, where the metal material is defined as in the first aspect of the present application.

[0074] In some embodiments, the analysis method for the mechanical properties of the metal material includes the following steps:

[0075] Determine mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine corrosion test conditions capable of simulating the target service environment, and acquire test values of the corrosion degree of the metal material under the corrosion test conditions;

[0076] According to the test values of the corrosion degree, the target service time of the metal material, the third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metal material, obtain a preliminary predicted value of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions; wherein, the corrosion resistance-mechanical property analysis model of the metal material is defined as in the first aspect or the second aspect of the present application;

[0077] Compare the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter to obtain the prediction result of the mechanical parameter of the metallic material after using the target service time under the corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, output the preliminary predicted value as the effective predicted value of the mechanical parameter of the metallic material after using the target service time under the corrosion test conditions; if the preliminary predicted value of the mechanical parameter is less than the effective state threshold of the mechanical parameter, output the prediction result that the metallic material fails before reaching the target service time.

[0078] The analysis method of the mechanical properties of the aforementioned metallic material selects the mechanical parameters related to the failure behavior of the metallic material based on the target service environment of the metallic material, and selects the corrosion test conditions that can simulate the target service environment, and then obtains the test value of the corrosion degree of the metallic material under the selected corrosion test conditions. Thus, according to the test value of the corrosion degree, the target service time of the metallic material, the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metallic material, the preliminary predicted value of the mechanical parameter of the metallic material after using the target service time under the selected corrosion test conditions can be obtained. By comparing the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter, the prediction result of the mechanical parameter of the metallic material after using the target service time under the selected corrosion test conditions can be obtained. If the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, the effective predicted value of the mechanical parameter of the metallic material after using the target service time under the selected corrosion test conditions is equal to the preliminary predicted value; while if the preliminary predicted value of the mechanical parameter is less than the effective state threshold of the mechanical parameter, it means that the metallic material fails before reaching the target service.

[0079] In the fifth aspect of the present application, a device for analyzing the mechanical properties of a metallic material is provided, and the metallic material is as defined in the first aspect of the present application.

[0080] In some embodiments, the device for analyzing the mechanical properties of the metallic material includes:

[0081] A test data acquisition module, configured to determine the mechanical parameters related to the failure behavior of the metallic material according to the target service environment of the metallic material, determine the corrosion test conditions that can simulate the target service environment, and acquire the test value of the corrosion degree of the metallic material under the corrosion test conditions;

[0082] A test data processing module, configured to obtain a preliminary predicted value of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions according to the test value of the corrosion degree, the target service time of the metal material, the third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metal material; wherein, the corrosion resistance-mechanical property analysis model of the metal material is defined as in the first aspect or the second aspect of the present application;

[0083] A mechanical property classification and identification module, configured to compare the preliminary predicted value of the mechanical parameters with the effective state threshold of the mechanical parameters to obtain a prediction result of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameters is greater than or equal to the effective state threshold of the mechanical parameters, the effective predicted value of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions is equal to the preliminary predicted value.

[0084] The mechanical property analysis device of the metal material provided in the fifth aspect of the present application can be used to implement the analysis method of the mechanical properties of the metal material described in the fourth aspect of the present application.

[0085] In a sixth aspect of the present application, a computer device is provided, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for constructing the corrosion resistance-mechanical property analysis model of the metal material described in the first aspect of the present application, or the method for analyzing the service life of the metal material described in the second aspect of the present application, or the method for analyzing the mechanical properties of the metal material described in the fourth aspect of the present application.

[0086] In a seventh aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method for constructing the corrosion resistance-mechanical property analysis model of the metal material described in the first aspect of the present application, or the method for analyzing the service life of the metal material described in the second aspect of the present application, or the method for analyzing the mechanical properties of the metal material described in the fourth aspect of the present application.

[0087] In yet another aspect of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, it implements the steps of the method for constructing the corrosion resistance-mechanical property analysis model of the metal material described in the first aspect of the present application, or the method for analyzing the service life of the metal material described in the second aspect of the present application, or the method for analyzing the mechanical properties of the metal material described in the fourth aspect of the present application.

[0088] In an eighth aspect of the present application, there is provided an electrical device, which includes:

[0089] a battery system, which includes a battery box body and battery cells located inside the battery box body, wherein the battery box body includes the metal material described in the first aspect of the present application; and

[0090] at least one of the service life analysis device of the metal material described in the third aspect of the present application, the mechanical property analysis device of the metal material described in the fifth aspect of the present application, the computer device described in the sixth aspect of the present application, and the computer-readable storage medium described in the seventh aspect of the present application.

[0091] In some embodiments, the battery cells include fuel cell cells.

[0092] In some embodiments, the battery cells include lithium battery cells.

[0093] At least one of the service life analysis device of the aforementioned metal material, the mechanical property analysis device of the aforementioned metal material, the computer device, the computer-readable storage medium, and the computer program product can be provided on the electrical device to implement the aforementioned analysis model construction method, the analysis method for the service life of the aforementioned metal material, or the analysis method for the mechanical properties of the aforementioned metal material, which is beneficial to achieving better management and maintenance of the electrical device, not only beneficial to achieving the safety maintenance of the battery box body in the electrical device, but also beneficial to assisting in designing a battery box body with a longer service time.

[0094] Details of one or more embodiments of the present application are set forth in the following drawings and description. Other features, objects, and advantages of the present application will become apparent from the specification, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] To better describe and illustrate the embodiments, examples, or instances provided by the present application, one or more drawings may be referred to. Additional details or examples used to describe the drawings should not be considered as limiting the scope of any of the disclosed applications, the currently described embodiments, examples, or instances, and the currently understood best mode of these applications. Moreover, in all the drawings, the same reference numerals are used to represent the same components. It should also be noted that the drawings are all drawn in a simplified form and are only used for conveniently and clearly assisting in the description of the present application. The various dimensions of each component shown in the drawings are arbitrarily shown, which may be accurate or may not be drawn to actual scale. For example, in order to make the illustration clearer, the dimensions of some components in the drawings are appropriately exaggerated. Unless otherwise specified, the components in the drawings are not drawn to scale. The present application does not limit each dimension of each component.

[0096] In the drawings:

[0097] Figure 1 Flow chart of a method for constructing a corrosion resistance - mechanical property analysis model of a metal material according to an embodiment of the present application.

[0098] Figure 2 Flow chart of a method for constructing a corrosion resistance - mechanical property analysis model of a metal material according to an embodiment of the present application.

[0099] Figure 3 Flow chart of a method for constructing a corrosion resistance - mechanical property analysis model of a metal material according to an embodiment of the present application.

[0100] Figure 4 Flow chart of a method for constructing a corrosion resistance - mechanical property analysis model of a metal material according to an embodiment of the present application.

[0101] Figure 5 Flow chart of a method for constructing a corrosion resistance - mechanical property analysis model of a metal material according to an embodiment of the present application.

[0102] Figure 6 Flow chart of a method for analyzing the service life of a metal material according to an embodiment of the present application.

[0103] Figure 7 Schematic diagram of a device for analyzing the service life of a metal material according to an embodiment of the present application.

[0104] Figure 8 Flow chart of a method for analyzing the mechanical properties of a metal material according to an embodiment of the present application.

[0105] Figure 9 Flow chart of a method for analyzing the mechanical properties of a metal material according to an embodiment of the present application.

[0106] Figure 10 Schematic diagram of a device for analyzing the mechanical properties of a metal material according to an embodiment of the present application.

[0107] Figure 11 Internal structure diagram of a computer device according to an embodiment of the present application.

[0108] Figure 12 Schematic diagram of an electrical device according to an embodiment of the present application.

[0109] Figure 13Salt spray test results in some embodiments of the present application, macroscopic morphology diagrams of four aluminum alloy materials at different equivalent corrosion time points from the 1st day to the 24th day; (a) A356.2; (b) A380; (c) AlSi10MgMn; (d) AlSi9MnMoZr; Samples of each aluminum alloy material are taken every day. The first row from left to right corresponds to the 1st day (1d) to the 6th day (6d), the second row from left to right corresponds to the 7th day (7d) to the 12th day (12d), the third row from left to right corresponds to the 13th day (13d) to the 18th day (18d), and the fourth row from left to right corresponds to the 19th day (19d) to the 24th day (24d).

[0110] Figure 14 Salt spray test results in some embodiments of the present application, experimental results of mass loss and corrosion rate of four aluminum alloy materials at different equivalent corrosion time points. The four aluminum alloy materials are A356.2 (square, ■), A380 (dot, ●), AlSi10MgMn (upper triangle, ▲), and AlSi9MnMoZr (lower triangle, ▼).

[0111] Figure 15 Fitting result diagram between the corrosion rate and the equivalent corrosion time of A356.2 aluminum alloy in a salt spray corrosion test in an embodiment of the present application.

[0112] Figure 16 Fitting result diagram between the corrosion rate and the equivalent corrosion time of A380 aluminum alloy in a salt spray corrosion test in an embodiment of the present application.

[0113] Figure 17 Fitting result diagram between the corrosion rate and the equivalent corrosion time of AlSi10MgMn aluminum alloy in a salt spray corrosion test in an embodiment of the present application.

[0114] Figure 18 Fitting result diagram between the corrosion rate and the equivalent corrosion time of AlSi9MnMoZr aluminum alloy in a salt spray corrosion test in an embodiment of the present application.

[0115] Figure 19 In some embodiments of the present application, experimental results and fitting results of mechanical parameters and equivalent corrosion time of A356.2 aluminum alloy material in a salt spray corrosion test at different equivalent corrosion time points; Among them, the mechanical parameters involve tensile strength (which can be abbreviated as UTS), elongation (which can be abbreviated as El), and yield strength (which can be abbreviated as YS); Among them, fit corresponds to the fitting curve.

[0116] Figure 20In some embodiments of the present application, the experimental results and fitting results of the mechanical parameters and equivalent corrosion time of the A380 aluminum alloy material during the salt spray corrosion test at different equivalent corrosion time points.

[0117] Figure 21 In some embodiments of the present application, the experimental results and fitting results of the mechanical parameters and equivalent corrosion time of the AlSi10MgMn aluminum alloy material during the salt spray corrosion test at different equivalent corrosion time points.

[0118] Figure 22 In some embodiments of the present application, the experimental results and fitting results of the mechanical parameters and equivalent corrosion time of the AlSi9MnMoZr aluminum alloy material during the salt spray corrosion test at different equivalent corrosion time points.

[0119] Figure 23 Schematic diagram of the sample size for the tensile test in an embodiment of the present application, with the unit being millimeters (mm). Among them, R2.5 represents a radius of 2.5 millimeters.

[0120] Figure 24 Schematic diagram of the structure of the three - electrode system in the electrochemical corrosion test equipment used in an embodiment of the present application. Among them, R, mA, and V represent a resistor, an ammeter, and a volt - ammeter respectively. The combination of the three can be understood as an electrochemical workstation. By adjusting the given voltage and current, the signal of the sample can be collected as the measurement data of the corrosion parameters.

[0121] Figure 25 Curve of the open - circuit potential (OCP, chemical formula, unit: V) of four aluminum alloy materials changing with time. A 3.5wt% NaCl aqueous solution is used. The four aluminum alloy materials are A356.2 (square, ■), A380 (dot, ●), AlSi10MgMn (upper triangle, ▲), and AlSi9MnMoZr (lower triangle, ▼).

[0122] Figure 26 Electrochemical corrosion test and analysis results in some embodiments of the present application. Among them, (a) is the EIS Bode (Bode plot of alternating current impedance spectroscopy); (b) is the Phase diagram (phase diagram), the horizontal axis corresponds to the frequency (unit: Hz (Hertz)), and the vertical axis corresponds to the phase angle (unit: ° (degree)); (c) is the Nyquist diagram; (d) is the equivalent circuit diagram.

[0123] Figure 27 Potentiodynamic polarization curve of the electrochemical corrosion test in some embodiments of the present application. The horizontal axis is the chemical formula (unit: V), and the vertical axis is the current density (unit: A / cm 2 )

[0124] Figure 28 This is the macroscopic surface morphology diagram of samples at different immersion corrosion times in the immersion corrosion test of some embodiments of this application. From left to right are four aluminum alloy materials: (a) A356.2; (b) A380; (c) AlSi10MgMn; (d) AlSi9MnMoZr. From top to bottom are the initial morphologies when not corroded (0d, scale bar is 50 mm), and the macroscopic morphology diagrams at 10 days (10d), 20 days (20d), and 30 days (30d).

[0125] Figure 29 This application Figure 28 This is the summary diagram of the corrosion rates of four die-cast aluminum alloy materials at different immersion corrosion times in the immersion corrosion test of the embodiments shown in this application. Among them, the four aluminum alloy materials are A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr respectively.

[0126] Figure 30 This is the relationship diagram of the corrosion rate varying with the corrosion time in the salt spray corrosion test of different aluminum alloy materials N1 and A380 in an embodiment of this application. The corrosion rates I, II, and III at different corrosion times represent the initial stage, middle stage, and late stage of corrosion respectively.

[0127] Figure 31 This is the relationship diagram of the mechanical parameters varying with the corrosion time in the tensile test of aluminum alloy material N1 in an embodiment of this application. Among them, (a) is the tensile stress-strain curve, corresponding to the initial state and the tensile stress-strain curves at 5 days (5d), 15 days (15d), and 25 days (25d) of corrosion; (b) is the fitting result of the mechanical properties, including the results of the tensile fracture strength, elongation, and yield strength and their fitting lines.

[0128] Explanation of reference numerals:

[0129] 310 is the corrosion performance data acquisition module, 320 is the corrosion performance data processing module; 510 is the test data acquisition module, 520 is the test data processing module, 530 is the mechanical property classification and recognition module; 6 is the electrical device; 131 is the auxiliary electrode, 132 is the working electrode, and 133 is the reference electrode. Detailed implementation manners

[0130] Hereinafter, some embodiments of the method for constructing and applying the corrosion resistance-mechanical property analysis model of the metal material of the present application are described in detail with appropriate reference to the accompanying drawings. However, there may be cases where unnecessary details are omitted. For example, there are cases where details of well-known matters are omitted and repeated descriptions of actually identical structures are omitted. This is to prevent the following description from becoming unnecessarily lengthy and to facilitate the understanding of those skilled in the art. In addition, the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present application and are not intended to limit the subject matter recited in the claims.

[0131] The "range" disclosed in the present application can be defined in the form of a lower limit and an upper limit. A given range is defined by selecting a lower limit and an upper limit, and the selected lower limit and upper limit define the boundary of a particular range. The range defined in this way can include or not include the end values, and any one of the end values can be independently included or not included, and can be combined arbitrarily, that is, any lower limit can be combined with any upper limit to form a range. For example, if ranges of 60 - 120 and 80 - 110 are listed for a specific parameter, ranges of 60 - 110 and 80 - 120 are also contemplated. In addition, if the minimum range values 1 and 2 are listed, and if the maximum range values 3, 4, and 5 are also listed, the following ranges are all contemplated: 1 - 3, 1 - 4, 1 - 5, 2 - 3, 2 - 4, and 2 - 5. In the present application, unless otherwise specified, the numerical range "a - b" represents an abbreviated representation of any real number combination between a and b, where a and b are both real numbers. For example, the numerical range "0 - 5" means that all real numbers between "0 - 5" have been fully listed herein, and "0 - 5" is only an abbreviated representation of these numerical combinations. Additionally, when a certain parameter is expressed as an integer ≥2, it is equivalent to disclosing that the parameter is, for example, the integers 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, etc. For example, when a certain parameter is expressed as an integer selected from "2 - 10", it is equivalent to listing the integers 2, 3, 4, 5, 6, 7, 8, 9, and 10.

[0132] In the present application, when referring to "multiple", "multiple kinds", "multiple items", etc., unless otherwise specified, it means greater than 2 or equal to 2 in quantity. For example, "one or more kinds" means one kind or greater than or equal to two kinds. It can be understood that when referring to "any number of" items, it refers to any suitable combination of multiple items, that is, the "any number of" items are combined in a non-conflicting and implementable manner for the present application.

[0133] If there is no special instruction, all embodiments and optional embodiments of the present application can be combined with each other to form a new technical solution.

[0134] References to "embodiments" in this specification mean that specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment or implementation of the present application. The phrase may not necessarily refer to the same embodiment each time it appears in the specification, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments. Similar understanding applies to "implementations" mentioned in this specification.

[0135] Those skilled in the art can understand that in the methods of each implementation or embodiment, the written order of each step does not mean a strict execution order that constitutes any limitation to the implementation process. The detailed execution order of each step should be determined by its function and possible internal logic. Without special instructions, all steps of the present application can be carried out sequentially, randomly, and preferably sequentially. For example, if method M includes steps (a) and (b), it means that method M can include steps (a) and (b) carried out sequentially, or steps (b) and (a) carried out sequentially. For another example, if method M further includes step (c), it means that step (c) can be added to method M in any order. For example, method M can include steps (a), (b), and (c), or steps (a), (c), and (b), or steps (c), (a), and (b), etc.

[0136] In the present application, in an open technical feature or technical solution described with words such as "containing", "comprising", "including", etc., without other instructions, additional members other than the listed members are not excluded, and it can be regarded as providing both a closed feature or solution composed of the listed members and an open feature or solution that also includes additional members outside the listed members. For example, if A includes a1, a2, and a3, without other instructions, it can also include other members or not include additional members, and it can be regarded as providing both a feature or solution of "A is composed of a1, a2, and a3" or "A is selected from a1, a2, and a3", and a feature or solution of "A not only includes a1, a2, and a3, but also includes other members".

[0137] In the present application, without other instructions, A (such as B) means that B is a non-limiting example of A, and it can be understood that A is not limited to B.

[0138] In this application, "optionally", "optional", and "option" mean something that may or may not be present, that is, any one selected from two parallel options of "present" or "absent". If "optional" appears multiple times in a technical solution, without special instructions and without contradictions or mutual restrictions, each "optional" is independent. Without other instructions, descriptions such as "optionally include" and "optionally contain" in this application, taking "optionally include" as an example, mean "may include or may not include".

[0139] In this application, without other instructions, the features or solutions corresponding to "and / or" include any one of two or more related listed items, and also include any and all combinations of the related listed items. "Any and all combinations" include combinations of any two related listed items, any more related listed items, or all related listed items. For example, "A and / or B" represents the group composed of A, B, and "the combination of A and B". Among them, "including A and / or B" can mean "including A, including B, and including the combination of A and B", or it can also mean "including A, including B, or including the combination of A and B", which can be appropriately understood according to the sentence where it is located.

[0140] As used herein, "its combination", "any combination thereof", "any combination mode thereof", etc. include all suitable combination modes of any two or more of the listed items.

[0141] In this text, the "suitable" involved in "suitable combination mode", "suitable mode", "any suitable mode", etc. is subject to being able to implement the technical solution of this application.

[0142] In this text, "preferred", "better", "more preferable", "it is advisable", "relatively good", etc. are only used to describe implementation manners or embodiments with better effects, and it should be understood that they do not constitute a limitation on the protection scope of this application. If "preferred" appears multiple times in a technical solution, without special instructions and without contradictions or mutual restrictions, each "preferred" is independent.

[0143] In this application, "further", "even further", "especially", "for example", "such as", "example", "exemplification", etc. are used for descriptive purposes and represent differences in content, but should not be understood as a limitation on the protection scope of this application.

[0144] In this application, in "the first aspect", "the second aspect", "the third aspect", "the fourth aspect", etc., the terms "first", "second", "third", "fourth", etc. are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or quantity, nor can they be understood as implicitly indicating the importance or quantity of the indicated technical features. Moreover, "first", "second", "third", "fourth", etc. only serve the purpose of non-exhaustive enumerative description, and it should be understood that they do not constitute a closed limitation on quantity.

[0145] In this application, the term "room temperature" generally refers to 4°C to 35°C, and can refer to 20°C ± 5°C. In some embodiments of this application, room temperature refers to 20°C to 30°C.

[0146] In this application, for units related to data ranges, if the unit is only attached after the right endpoint, it means that the units of the left endpoint and the right endpoint are the same. For example, 3 to 5h or 3 - 5h both indicate that the units of the left endpoint "3" and the right endpoint "5" are both h (hours), and both have the same meaning as 3h to 5h. In addition, similar descriptions for other parameters such as temperature and size are understood in the same way.

[0147] In the embodiments or examples of this application, the weight of the relevant components mentioned not only can refer to the content of each component, but also can represent the proportional relationship of the weights between each component. Therefore, as long as the content of the relevant components in the embodiments or examples of this application is scaled up or down proportionally, it is within the scope described in this application. Further, the weight involved in the embodiments or examples of this application can be mass units well-known in the chemical industry such as μg, mg, g, kg, etc. Without other instructions, the mass ratio is equal to the corresponding weight ratio. For example, if the mass of substance A is m1 and the weight is W1, and the mass of substance B is m2 and the weight is W2, then the mass ratio m1 / m2 is numerically equal to the corresponding weight ratio W1 / W2.

[0148] In this application, without other instructions, wt% represents the weight percentage by weight, and is numerically equal to the corresponding mass percentage by mass.

[0149] In this application, "greater than or equal to" and "more than or equal to" can both be expressed as "≥", "less than or equal to" and "less than or equal to" can both be expressed as "≤", "greater than" can be equivalently expressed as ">", and "less than" can be equivalently expressed as "<". In this application, without other instructions, "greater than or equal to" and "≥" can be regarded as also providing two options of "greater than" and "equal to". In this application, without other instructions, "less than or equal to" and "≤" can be regarded as also providing two options of "less than" and "equal to".

[0150] In this application, exemplary descriptions such as "in some embodiments" or "in one embodiment" may cover, but are not limited to, the following meanings: These solutions can be combined with other solutions in a suitable manner to form new technical solutions.

[0151] Currently, the research on the corrosion behavior and mechanism of fuel cell box materials often only focuses on the electrochemical corrosion behavior of fuel cell box materials or the corrosion rate in different corrosion media, which is difficult to provide effective guidance for the design and development of fuel cell box materials. The problem that the research on the corrosion behavior of fuel cell box materials is not systematic and in-depth is becoming more and more obvious. For example, the white rust corrosion mechanism of fuel cell box materials is not clear, the influence of metal materials (such as alloy materials) on the corrosion behavior of fuel cell box materials remains to be clarified, and there is no corresponding correlation study on the relationship between the fuel cell box materials and their mechanical properties and service life.

[0152] This application provides a method for constructing an analysis model of the corrosion resistance degree - mechanical properties of metal materials, an analysis method and device for the service life of metal materials, an analysis method and device for the mechanical properties of metal materials, a computer device, a computer-readable storage medium, and an electrical device. The analysis model of the corrosion resistance degree - mechanical properties of metal materials can be effectively used for predicting the mechanical properties and evaluating the service life of metal materials. The metal materials involved may include, but are not limited to, aluminum alloy materials, and may also include, but are not limited to, battery box materials (such as fuel cell box materials).

[0153] In the first aspect of this application, a method for constructing an analysis model of the corrosion resistance degree - mechanical properties of metal materials is provided. This construction method can be used to construct an analysis model between the corrosion degree and mechanical properties of metal materials under corrosion test conditions simulating the target service environment, and can be used for predicting the mechanical properties of metal materials. When the mechanical property is a mechanical property related to the failure behavior of the metal material, this construction method can obtain an analysis model between the corrosion degree and the failure-related mechanical properties of the metal material under the corrosion test conditions simulating the target service environment, and can be used for predicting the mechanical properties analysis and service life evaluation of the metal material.

[0154] In some embodiments, this application provides a method for constructing an analysis model of the corrosion resistance degree - mechanical properties of metal materials, which includes the following steps:

[0155] Taking the metal material as the test object, obtaining a corrosion performance test experimental data set at different equivalent corrosion time points and a mechanical property test experimental data set at different corrosion degrees corresponding to different equivalent corrosion time points under the corrosion test conditions; wherein, the corrosion test conditions are used to simulate the target service environment;

[0156] Based on the experimental data set of corrosion performance tests, a first set of empirical relationships for the variation of corrosion parameters with equivalent corrosion time is established. Also, based on the experimental data set of mechanical property tests, a second set of empirical relationships for the variation of mechanical parameters with equivalent corrosion time is established.

[0157] This analysis model can be effectively used for predicting the mechanical properties and evaluating the service life of metallic materials, which may include aluminum alloy materials, and further may include battery box materials.

[0158] In some embodiments, a method for constructing an analysis model of the corrosion resistance - mechanical properties of metallic materials is provided, which includes the following steps (see Figure 1 ):

[0159] S110: Taking the metallic material as the test object, obtaining the test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain an experimental data set of corrosion performance tests, and also obtaining the test values of mechanical parameters at different corrosion degrees corresponding to different equivalent corrosion time points to obtain an experimental data set of mechanical property tests; wherein, the corrosion test conditions are used to simulate the target service environment of the metallic material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate;

[0160] S120: Based on the experimental data set of corrosion performance tests, a first set of empirical relationships for the variation of corrosion parameters with equivalent corrosion time is established. Also, based on the experimental data set of mechanical property tests, a second set of empirical relationships for the variation of mechanical parameters with equivalent corrosion time is established.

[0161] In some embodiments, a method for constructing an analysis model of the corrosion resistance - mechanical properties of metallic materials is provided, which includes the following steps (see Figure 2 ):

[0162] S110: Taking the metallic material as the test object, obtaining the test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain an experimental data set of corrosion performance tests, and also obtaining the test values of mechanical parameters at different corrosion degrees corresponding to different equivalent corrosion time points to obtain an experimental data set of mechanical property tests; wherein, the corrosion test conditions are used to simulate the target service environment of the metallic material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate; the mechanical parameters include at least one of the tensile fracture strength and the fracture elongation rate;

[0163] S120: Based on the experimental data set of corrosion performance tests, a first set of empirical relationships for the variation of corrosion parameters with equivalent corrosion time is established. Also, based on the experimental data set of performance tests, a second set of empirical relationships for the variation of mechanical parameters with equivalent corrosion time is established.

[0164] In this application, unless otherwise specified, "metal material" refers to solid materials with certain macroscopic dimensions, such as, but not limited to, plate bodies, block bodies, etc.

[0165] In this application, unless otherwise specified, "service environment" refers to the environment in which the metal material is located in the actual application scenario.

[0166] In this application, unless otherwise specified, "corrosion degree" refers to the degree of structural loss of the metal material relative to when it is not corroded, and can be characterized by, but not limited to, "mass loss relative to when not corroded". The greater the mass loss, the higher the corrosion degree.

[0167] In this application, unless otherwise specified, "equivalent corrosion time" means that under the corrosion test conditions that can simulate the target service environment, there is a certain corresponding relationship between the corrosion test time experienced by the metal material and the service time in the target service environment. The service time situation can be indirectly reflected through the corrosion test time. Therefore, this corrosion test time is also called "equivalent corrosion time".

[0168] In this application, unless otherwise specified, "corrosion rate" represents the amount of corrosion loss per unit time. The amount of corrosion loss can be represented in, but not limited to, the following ways: mass, volume, linear length (such as corrosion depth), etc. The corrosion rate can be obtained by dividing the total loss amount within a period of time by the duration of this time period.

[0169] In this application, unless otherwise specified, both "tensile fracture strength" and "elongation at break" have well-known meanings in the art. "Tensile fracture strength", which can also be denoted as tensile strength or ultimate tensile strength, refers to the maximum tensile stress that a sample can withstand in a tensile test, and numerically equals the tensile force that the sample withstands when it breaks under the tensile force. "Elongation at break" refers to the percentage of the length deformation of the sample at the time of tensile fracture relative to the original length, where the original length refers to the length of the sample when no tensile force is applied. For a sample with a certain length L 0 When a tensile force is applied in the length direction, the ratio of the tensile force F max borne by the sample when it breaks to the cross-sectional area A is equal to the "tensile fracture strength". "Cross-section" refers to the section perpendicular to the length direction of the sample; "elongation at break" δ=(L - L 0 )×100%, where L is the length of the sample when it breaks under the tensile force.

[0170] Taking metal materials as the test objects, simulating the target service environment of metal materials under corrosion test conditions, obtaining the experimental data sets of corrosion performance tests at different equivalent corrosion time points and the experimental data sets of mechanical property tests at different corrosion degrees corresponding to different equivalent corrosion time points, using the equivalent corrosion time under corrosion test conditions and the mechanical properties at different corrosion degrees as the link, establishing the first set of empirical relationships of corrosion parameters including at least one of corrosion degree and corrosion rate varying with the equivalent corrosion time and the second set of empirical relationships of at least one mechanical parameter varying with the equivalent corrosion time, thereby constructing an analysis model between the corrosion resistance and mechanical properties of metal materials, which can help understand the corrosion mechanism of metal materials, predict and analyze the mechanical properties of metal materials under target service conditions according to the corrosion behavior of metal materials, and evaluate the service life of metal material structures under the target service environment.

[0171] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameter includes at least one of tensile fracture strength and fracture elongation.

[0172] When the mechanical parameter in this method can include at least one of tensile fracture strength and fracture elongation, the established corrosion resistance-mechanical property analysis model of metal materials is applicable to metal material structures that are prone to failure due to tensile stress.

[0173] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameters in the experimental data set of mechanical property tests include at least one of tensile fracture strength and fracture elongation, and may also optionally include yield strength.

[0174] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameters in the experimental data set of mechanical property tests include at least tensile fracture strength and fracture elongation, and may also optionally include yield strength.

[0175] Based on any suitable implementation manner of the present application, further, in some implementation manners, the mechanical parameter includes yield strength.

[0176] By selecting appropriate parameters for fitting the functional relationship, it is beneficial to obtain a better-fitting second set of empirical relationships, and further beneficial to obtain a more effective corrosion resistance-mechanical property analysis model.

[0177] In the present application, unless otherwise specified, the tensile test can be carried out on an electronic tensile testing machine. For example, it can be carried out on a Z20 TEW electronic tensile testing machine. In the present application, unless otherwise specified, the loading rate during the tensile test can be 0.5 mm / min to 1.5 mm / min.

[0178] Non - restrictively, samples with the following dimensions can be used for tensile tests. Figure 23 Samples shown in Figure 23 are plate - shaped tensile specimens with a length of 60 millimeters (mm) and a thickness of 2 mm. Figure 23 The sample size in Figure 23 is a plate - shaped tensile specimen with a length of 60 millimeters (mm) and a thickness of 2 mm.

[0179] Non - restrictively, when conducting a tensile test, the tensile sample to be tested can be wrapped with a blue film, leaving only the test surface. The total test duration can be set to 600 hours (h). During the test, a batch of samples can be taken every 24 h for tensile property testing, and at least three parallel samples can be set for each test.

[0180] Salt spray corrosion test experiments can be carried out using commonly used salt spray corrosion test equipment in the art. Non - restrictively, salt spray corrosion test equipment of model LP / YWX - 250 can be used. During the test, the sample can be placed on a V - shaped bracket so that the salt spray can slowly and evenly fall on the surface of the sample.

[0181] In this application, unless otherwise specified, the corrosion rate can be characterized by the average corrosion depth per unit time. Further, the corrosion rate can be calculated in the following manner:

[0182] Corrosion rate=(K×W) / (A×T×D) mm / y (I)

[0183] In formula (I): K = 8.64×10 4 , where K is the time constant;

[0184] W is the mass difference before and after the test, and the unit is mg;

[0185] A is the test surface area, and the unit is cm 2 ;

[0186] T is the test time, and the unit is h;

[0187] D = 2.7 g / cm 3 , where D is the density of the test sample.

[0188] In formula (I), the unit of the corrosion rate is millimeters per year, which can be denoted as "mm / y".

[0189] Based on any suitable embodiment of this application, further, in some embodiments, the metal material is an aluminum alloy material. The metal material can also be a metal structural member, and further can be an aluminum alloy structural member.

[0190] Based on any suitable embodiment of this application, further, in some embodiments, the metal material is a battery box material, and can be any one of the battery box materials. In some embodiments, the battery box material can include a fuel cell box material. In some embodiments, the battery box material includes a lithium - ion battery box material.

[0191] In some embodiments, the metal material includes at least a part of the structural members of the battery box. In some embodiments, the structural members of the battery box may include at least a part of the structural members of the fuel cell box. In some embodiments, the structural members of the battery box may include at least a part of the structural members of the lithium battery box.

[0192] In this application, unless otherwise specified, a "structural member" can be an independent object or a part of the structure within an independent object. A "metal structural member" is a structural member made of metal material.

[0193] In this application, unless otherwise specified, "battery box material" refers to the main material that constitutes the battery box, which is the main material of at least a part of the structure of the battery box. The mass ratio of the battery box material in this part of the structure can exceed 80%, further exceed 90%, and even be closer to 100% or be 100%. In some embodiments, the battery box material may refer to the constituent materials of the battery box, that is, at least a part of the structural members of the battery box are made of this "battery box material".

[0194] In this application, unless otherwise specified, a "fuel cell box" refers to a battery box with fuel cell monomers installed inside; "fuel cell box material" refers to the main material that constitutes the fuel cell box, which is the main material of at least a part of the structure of the fuel cell box. Unless otherwise specified, the mass ratio of the fuel cell box material in this part of the structure can exceed 80%, further exceed 90%, and even be closer to 100% or be 100%. In some embodiments, the fuel cell box material may refer to the constituent materials of the fuel cell box, that is, at least a part of the structural members of the fuel cell box are made of this "fuel cell box material".

[0195] In this application, unless otherwise specified, a "fuel cell" has its well-known meaning in the art and refers to a chemical device that directly converts the chemical energy of a fuel into electrical energy. The service environment where the fuel cell box is located is likely to come into contact with various corrosive media, including moisture, rainfall, salt spray, and various organic and inorganic liquids used during vehicle operation or cleaning.

[0196] Due to the advantages of die-cast aluminum alloy such as low density, high specific strength, excellent thermal stability, good machinability, and low cost, it can be used to prepare various automotive components, including cylinder blocks, generator housings, fuel cell boxes, various engine brackets, etc., but not limited to these.

[0197] The metallic material can be an aluminum alloy material or a metallic structural member, and further can be an aluminum alloy structural member. Due to the advantages of die-cast aluminum alloy such as low density, high specific strength, excellent thermal stability, good machinability, and low cost, it can be used to prepare various parts of an automobile, including cylinder blocks, generator housings, fuel cell boxes, various engine brackets, etc., but not limited thereto. Among them, the aluminum alloy material can be applied to the field of battery technology and can be used as the main material (including constituent materials) of the battery box or the aluminum alloy structural member in the battery box. Therefore, the metallic material can be the material of the battery box, and the battery box can include but not be limited to fuel cell boxes, and can also include but not be limited to lithium battery boxes; correspondingly, the metallic material can include at least a part of the structural members of the battery box. When obtaining corrosion parameters and mechanical parameters based on the aluminum alloy material, the corrosion resistance-mechanical property analysis model of the metallic material constructed can be applicable to the mechanical property prediction and life assessment of the aluminum alloy material. At this time, it is also helpful to understand the white rust corrosion mechanism of the aluminum alloy material. When the aluminum alloy material is used as the main material or constituent material of the battery box or the structural member in the battery box, the corrosion resistance-mechanical property analysis model of the metallic material can be applicable to the mechanical property prediction and life assessment of the battery box or the structural member in the battery box.

[0198] Taking the fuel cell box as an example, it can also help to understand the white rust corrosion mechanism of the fuel cell box material. When taking the fuel cell box material as the test object, the corrosion behavior of the fuel cell box material can be analyzed, the corrosion rates of different fuel cell box materials can be determined, the relationship between the corrosion degree and mechanical properties of the fuel cell box material can be established, which has certain reference significance for the safe operation of fuel cells and even electrical devices including fuel cells.

[0199] Based on any suitable implementation manner of the present application, further, in some implementation manners, the corrosion performance test experimental data set under corrosion test conditions at least includes the corrosion performance test experimental data set under salt spray corrosion test conditions. Non-limitingly, the salt spray corrosion test conditions can include at least one of the following salt spray conditions: NaCl aqueous solution salt spray condition, acetate salt spray condition, copper salt accelerated acetate salt spray condition, cyclic salt spray corrosion condition, or a combination of one or more of them. In some implementation manners, the salt spray corrosion test conditions include the NaCl aqueous solution salt spray condition.

[0200] When the corrosion performance test experimental data set includes at least the corrosion performance test experimental data set under salt spray corrosion test conditions, the corrosion resistance-mechanical property analysis model of the metal material constructed can be applied to metal materials, their structural parts or products in service environments such as the road traffic field, the computer field, the electronic communication field, and the electrical appliance field, and can also be applied to structural parts or products in related service environments such as electroplating, coating, packaging boxes, and transportation equipment. Among them, the road traffic field may involve but is not limited to road vehicle electronic and electrical equipment, rail transit locomotive and vehicle equipment and devices, automotive parts and other equipment or their metal structural parts; the computer field may involve but is not limited to computers, display screens, hosts, computer components, medical equipment and other precision instruments, equipment, products or their metal structural parts; the electronic communication field may involve but is not limited to mobile phones, radio frequency devices, electronic communication components, printed circuit boards (PCBs), printed circuit board assemblies (PCBAs) and other equipment, products or their metal structural parts; electrical appliances may involve but is not limited to various household electrical appliances, lamps, transformers and other household electrical appliances, equipment, instruments, medical devices and other equipment, products or their metal structural parts.

[0201] Non-limitingly, the model for obtaining the corrosion performance test experimental data set based on the salt spray conditions of an NaCl aqueous solution can be applied to discriminating the quality and uniformity of protective coatings and for comparing the differences in the salt spray corrosion resistance of specimens with similar structures, but is not limited thereto. Non-limitingly, the model for obtaining the corrosion performance test experimental data set based on acetic acid salt spray conditions can be applied to coastal cities in the south, salt spray environments with relatively harsh conditions, etc.; non-limitingly, the model for obtaining the corrosion performance test experimental data set based on copper salt accelerated acetic acid salt spray conditions can be applied to salt spray environments with harsh conditions, etc.; non-limitingly, the model for obtaining the corrosion performance test experimental data set based on alternating salt spray corrosion conditions can be applied to high-temperature and high-humidity environments, etc.

[0202] Based on any suitable implementation manner of the present application, further, in some implementation manners, the salt spray conditions of the NaCl aqueous solution include the following parameters: the simulated salt spray conditions of an NaCl aqueous solution with a concentration of 3 wt% to 6 wt% at 34 to 36 °C. In some implementation manners, the salt spray conditions of the NaCl aqueous solution include the following parameters: the simulated salt spray conditions of an NaCl aqueous solution with a concentration of 5 wt% at 35 °C. In some implementation manners, the salt spray conditions of the NaCl aqueous solution include the following parameters: the simulated salt spray conditions of an NaCl aqueous solution with a concentration of 3.5 wt% at 35 °C.

[0203] For the salt spray conditions of the NaCl aqueous solution, the foregoing test conditions are conducive to discriminating the corrosion resistance of battery boxes, automotive parts, etc.

[0204] Non-limitingly, the starting time when the sample is placed under the corrosion test conditions can be used as the first sampling time point.

[0205] Without limitation, when conducting the corrosion test experiment, the sampling methods at different equivalent corrosion time points can be as follows: the total test time (i.e., the duration of the preset time period) ≥ 30 h, and the time interval between adjacent sampling points can be ≥ 1 day. Without limitation, the following sampling methods can be adopted: the total test time is 600 h, and sampling is carried out every 24 h; further, the first sampling point can be the starting time when the sample is placed under the corrosion test conditions. The following sampling method can also be adopted: the total test time is 30 days, and sampling is carried out every 10 days; further, the first sampling point can be the starting time when the sample is placed under the corrosion test conditions.

[0206] It can be understood that when conducting the corrosion test experiment, when sampling at any time point, the sample can also be optionally subjected to one or more of the following test analyses: macroscopic morphology observation, microscopic morphology observation, corrosion rate analysis, etc. For example, one or more of the foregoing test analyses can be carried out every 1 to 10 days. In some embodiments, macroscopic morphology observation, microscopic morphology observation, and corrosion rate analysis are carried out every 10 days.

[0207] Without limitation, "macroscopic morphology observation" can be carried out by means such as a stereoscopic microscope and shadowless lamp observation.

[0208] Without limitation, "microscopic morphology observation" includes the local morphology of the sample at different magnification multiples (such as 200 to 10,000 times), and means such as a metallographic microscope and a scanning electron microscope (SEM) can be used for microscopic morphology observation. Without limitation, a CX40M metallographic microscope, a field emission scanning electron microscope FEI NOVA NanoSEM 230, etc. can be used.

[0209] Without limitation, for the salt spray corrosion test, sampling can be carried out every 12 h to 36 h (such as every 24 h) to obtain corrosion parameters and corresponding mechanical parameters, so as to obtain a corrosion performance test experiment data set and a mechanical performance test experiment data set. The test duration can be ≥ 24 days, further ≥ 25 days, and still further ≥ 30 days.

[0210] Non - restrictively, the sample size for the salt spray corrosion test can be a block of 12 mm × 12 mm × 6 mm. Non - restrictively, the non - test surface is wrapped with a blue film. Before the salt spray corrosion test, pretreatment including the following steps can be carried out: grinding, polishing, ethanol cleaning and drying of the test surface. Weigh the sample before the salt spray corrosion test and record the initial weight W0. Unless otherwise specified, the following test parameters can be used: the total test duration is 600 h, and samples are taken for test analysis every 24 h during the test. Macroscopic morphology observation and microscopic morphology observation can be carried out first, then the corrosion products on the sample surface are washed off, and the sample is weighed again. The weighing result of the i - th sampling is denoted as Wi, and the test duration at the i - th sampling is denoted as Ti. It is possible to substitute W = Wi - W0 and T = Ti into the previous formula (I) to obtain the corrosion rate at the i - th sampling. Unless otherwise specified, at least three parallel samples are set for each test. Non - restrictively, chromic acid cleaner (20 g / L of Cr 2 O 3 + 50 mL / L of H 3 PO 4 ) can be used to wash off the corrosion products on the sample surface.

[0211] Based on any suitable implementation manner of the present application, further, in some implementation manners, the first set of empirical relationships for the corrosion parameters varying with the equivalent corrosion time established based on the corrosion performance test experimental data set includes:

[0212] For each corrosion parameter among the corrosion parameters, segmented fitting is respectively carried out based on the corresponding corrosion performance test experimental data set. For each fitting interval, the corresponding corrosion parameter is used as the dependent variable, and the equivalent corrosion time is used as the independent variable. Fitting is respectively carried out in the form of a power function or a linear function to construct the empirical relationship between the corresponding type of corrosion parameter and the equivalent corrosion time for each fitting interval, and the first set of empirical relationships is obtained.

[0213] The establishment of the first set of empirical relationships for the corrosion parameters varying with the equivalent corrosion time can be obtained by segmented fitting for each corrosion parameter respectively. The fitting method for each segment can adopt a power function or a linear function. At this time, the fitting curve has a higher degree of coincidence with the experimental test data set, and the model is more effective, but is not limited to the aforementioned function types.

[0214] Based on any suitable implementation manner of the present application, further, in some implementation manners, in the first set of empirical relationships, the fitting manner of the power function is y1 = A·x B , and the fitting manner of the linear function is y1 = a + b·x; where x is the equivalent corrosion time, y1 is the corrosion parameter, A is a positive number, B is a negative number, b is a positive number, and a is a negative number.

[0215] Based on any suitable embodiment of the present application, further, in some embodiments, A is a real number selected from 0.01 to 1.00, B is a real number selected from -0.3 to -0.8, b is a real number selected from 0.001 to 0.05, and a is a real number selected from 0.02 to -0.8. Further, non-limiting examples of A are 0.145, 0.755, 0.756, 0.125, 0.126, 0.134, etc. Non-limiting examples of B are -0.533, -0.531, -0.532, -0.681, -0.680, -0.688, etc. a can also be a real number selected from the following ranges: -0.001 to -0.8, -0.001 to -0.7, -0.001 to -0.5, etc., and non-limiting examples of a are -0.124, -0.0132, -0.00171, -0.366, -0.668, etc. b can also be a real number selected from 0.001 to 0.02, and further can be a real number selected from 0.001 to 0.01, and non-limiting examples of b are 0.00713, 0.00334, 0.0197, 0.0311, 0.00222, etc. Further, in some embodiments, the corrosion rate is fitted, and further, the corrosion rate can be represented by the corrosion depth per unit time.

[0216] By selecting a suitable type of fitting function, it is beneficial to obtain a first set of empirical relationships with better fitting effects, and then obtain a more effective corrosion resistance-mechanical property analysis model.

[0217] According to different corrosion parameters used for fitting, factors such as A, B, a, b, etc. in the above functions can be selected from different ranges. For any one of these factors, it can be selected from the interval formed by any two exemplary point values recorded in the present application, as long as the interval is appropriate.

[0218] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion parameters in the corrosion performance test experimental dataset at least include the corrosion rate.

[0219] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion performance test experimental dataset includes at least one of the corrosion performance test experimental dataset under electrochemical corrosion test conditions and the corrosion performance test experimental dataset under immersion corrosion test conditions. Non-limitingly, the corrosion parameters in the corrosion performance test experimental dataset under electrochemical corrosion test conditions can include at least one electrochemical corrosion parameter such as the self-corrosion potential and the self-corrosion current. Non-limitingly, the corrosion parameters in the corrosion performance test experimental dataset under immersion corrosion test conditions can include at least one of the corrosion degree and the corrosion rate.

[0220] When the experimental dataset of corrosion performance test includes the experimental dataset of corrosion performance test under electrochemical corrosion test conditions, the corrosion resistance-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of metal materials in an electrochemical environment. For example, but not limited to, the performance prediction and life assessment of battery boxes. Further, it can include, but not limited to, the performance prediction and life assessment of fuel cell boxes.

[0221] When the experimental dataset of corrosion performance test includes the experimental dataset of corrosion performance test under immersion corrosion test conditions, the corrosion resistance-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of metal materials in an environment in contact with corrosive liquids.

[0222] When the experimental dataset of corrosion performance test includes both the experimental dataset of corrosion performance test under electrochemical corrosion test conditions and the experimental dataset of corrosion performance test under immersion corrosion test conditions, the corrosion resistance-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of battery boxes with built-in electrolyte. Further, it can include, but not limited to, the performance prediction and life assessment of fuel cell boxes.

[0223] In some embodiments, the experimental dataset of corrosion performance test under corrosion test conditions includes the experimental dataset of corrosion performance test under electrochemical corrosion test conditions. Further, the electrochemical corrosion test can include one or more of open circuit voltage test, alternating current impedance test, potentiodynamic polarization test, etc. Correspondingly, the corrosion parameters in the experimental dataset of corrosion performance test can include one or more of open circuit voltage, impedance, etc.

[0224] The test equipment for electrochemical corrosion test can include an electrochemical workstation and a three-electrode system. The structural schematic diagram of the three-electrode system can be referred to Figure 24 . Without limitation, different excitation signals can be given to the three-electrode system by the electrochemical workstation, and the corresponding response signals can be recorded to establish the electrochemical corrosion behavior of the sample to be tested. In some non-limiting embodiments, in the three-electrode system, the sample to be tested is used as the working electrode, the silver-silver chloride (Ag-AgCl) electrode is used as the reference electrode, and the platinum (Pt) electrode is used as the auxiliary electrode. The electrolyte solution used can be 3.5wt% NaCl aqueous solution. During the test, the three-electrode system is placed in a Faraday shielding box.

[0225] Without limitation, the sample size for electrochemical corrosion test can be a plate with dimensions of 10mm×10mm×2mm. The test surface area can be 1cm 2 . Before the test, the sample can be pretreated by the following steps: cold mounting with epoxy resin, sanding, polishing, cleaning with ethanol, and drying.

[0226] Non - restrictively, the electrochemical corrosion test can include open - circuit potential (OCP) measurement and alternating current impedance (EIS) test after the OCP has stabilized for a period of time (such as 60 minutes). Further, the electrochemical impedance spectra of the sample at different alternating current frequencies are measured. During the test, a 10 - mV alternating current sine wave can be used as the excitation voltage, and the test frequency can be controlled within the range of 0.01 Hz to 105 Hz. Generally, an equivalent circuit can be used to fit the experimental results of EIS, and then the parameters of each component in the equivalent circuit diagram are analyzed.

[0227] Non - restrictively, in the electrochemical corrosion test procedure, a potentiodynamic polarization test can also be carried out after the alternating current impedance test. Further, the following test parameters can be adopted: starting from the potential of OCP - 300 mV, scanning at a scanning rate of 0.167 mV / s until the current is greater than 1 mA. The ZSimpWin v3.40 software is used to perform Tafel fitting on the polarization characteristic data of the sample.

[0228] In some embodiments, the experimental data set of the corrosion performance test under corrosion test conditions includes the experimental data set of the corrosion performance test under immersion corrosion test conditions. Non - restrictively, the corrosion parameters in the experimental data set of the corrosion performance test under immersion corrosion test conditions can include at least one of the degree of corrosion and the corrosion rate.

[0229] Non - restrictively, when carrying out the immersion corrosion test, the following sampling method can be adopted: the total test time is 30 days, and sampling is carried out every 10 days; further, the first sampling point can be the starting time when the sample is placed under the corrosion test conditions. Each sampling point can optionally perform one or more of the following test analyses on the sample: macroscopic morphology observation, microscopic morphology observation, analysis of the corrosion rate, etc.

[0230] In some embodiments, the immersion corrosion test includes the following steps: the total test time is 30 days, sampling is carried out every 10 days, and the macroscopic morphology, microscopic morphology and corrosion rate of the sample can be tested and analyzed.

[0231] Non - restrictively, the sample used for the immersion corrosion test can be a block with dimensions of 15 mm×15 mm×2 mm, or a block with dimensions of 50 mm×25 mm×2 mm, or other shaped specimens to be tested.

[0232] Non - restrictively, the composition of the corrosion solution for soaking the sample can be determined according to the corrosion environment in which the sample to be tested is located. 500 mL of the corrosion solution can be used. In some embodiments, the corrosion solution is an aqueous solution of 3 wt% - 6 wt% NaCl, such as an aqueous solution of 3 wt%, 3.5 wt%, 4 wt%, 4.5 wt%, 5 wt%, 5.5 wt% or 6 wt% NaCl, etc.

[0233] Non - restrictively, when conducting the immersion corrosion test, during the test process, the ratio of the corrosion solution to the test area of the sample can be maintained greater than 0.2 mL / mm 2 .

[0234] Non - restrictively, before conducting the immersion corrosion test, a pretreatment including the following steps can be carried out: grinding and polishing the test surface, rinsing successively with deionized water and ethanol, drying, and weighing. After weighing, the sample can be placed in a desiccator for storage and standby.

[0235] Non - restrictively, conducting the immersion corrosion test includes: placing the sample in a container, adding 500 mL of the corrosion solution. After sealing, the entire container is placed in a constant - temperature water bath tank, and the temperature is set at 25°C. Samples are taken every 10 d (i.e., the test times are 10 d, 20 d, 30 d), and the macroscopic and microscopic morphologies of the surface of the corroded sample are observed. Then, the corrosion products on the surface of the sample are removed, the masses of the sample before and after corrosion are compared, and the corresponding immersion corrosion rate is calculated according to formula (I). At least three parallel samples are set for each test.

[0236] In this application, when used as a time unit, unless otherwise specified, 1 d refers to 1 day and 1 h refers to 1 hour.

[0237] Based on any suitable embodiment of the present application, further, in some embodiments, establishing the second set of empirical relationships between mechanical parameters and equivalent corrosion time based on the mechanical property test experimental data set includes:

[0238] For each mechanical parameter among the mechanical parameters, piece - wise fitting is respectively carried out based on the corresponding mechanical property test experimental data set. For each piece - wise fitting interval, the corresponding mechanical parameter is used as the dependent variable and the equivalent corrosion time is used as the independent variable, and fitting is respectively carried out in the form of a power function or a linear function to construct the empirical relationship between the corresponding type of mechanical parameter and the equivalent corrosion time, and the second set of empirical relationships is obtained.

[0239] The establishment of the second set of empirical relationships between mechanical parameters and equivalent corrosion time can be obtained by piece - wise fitting for each mechanical parameter respectively. The fitting method for each piece can adopt a power function or a linear function. At this time, the fitting curve has a higher degree of coincidence with the experimental test data set, and the model is more effective, but is not limited to the aforementioned function types.

[0240] Based on any suitable embodiment of the present application, further, in some embodiments, in the second set of empirical relationships, the fitting method of the power function is y2 = M·x N , and the fitting method of the linear function is y2 = m + n·x; where x is the equivalent corrosion time, y2 is the mechanical parameter, M is a positive number, N is a negative number, n is a negative number, and m is a positive number.

[0241] Based on any suitable embodiment of the present application, further, in some embodiments, M is a real number selected from 1 to 250; N is a real number selected from -0.01 to -1; n is a real number selected from -0.05 to -5, and further optionally a real number selected from -0.1 to -1.5; m is a real number selected from 1 to 300. Non-limiting examples of M are 233.54, 152.16, 1.60, etc. N can also be a real number selected from -0.01 to -0.5, and further can be a real number selected from -0.01 to -0.2; non-limiting examples of N are -0.11, -0.07, -0.16, etc. Non-limiting examples of m are 269.59, 203.21, 9.69, 248.48, 134.55, 3.95, 248.21, 131.83, 8.31, etc. Non-limiting examples of n are -1.44, -1.06, -0.15, -1.91, -0.40, -0.08, -1.61, -0.73, -0.19, etc. n can also be a real number selected from the following ranges: -0.05 to -4, -0.05 to -3, -0.05 to -2, -1 to -2, -1 to -2, -0.5 to -1.5, -0.05 to -0.5, etc.

[0242] By selecting a suitable fitting function type, it is beneficial to obtain a second set of empirical relationships with better fitting effects, and further beneficial to obtain a more effective corrosion resistance - mechanical property analysis model.

[0243] According to different mechanical parameters used for fitting, factors such as M, N, m, and n in the above functions can select different ranges. For any one of these factors, it can be selected from the interval formed by any two exemplary point values described in this application, as long as the interval is appropriate, but not limited thereto. For example, when fitting the ultimate tensile strength (UTS), n can be selected from any of the following appropriate ranges: -0.05 to -5, -0.1 to -5, -0.2 to -5, -0.05 to -4, -0.1 to -4, -0.2 to -4, -0.05 to -3, -0.1 to -3, -0.2 to -3, -0.3 to -3, etc., and m can be selected from any of the following appropriate ranges: 60 - 300, 80 - 300, 60 - 250, 80 - 250, 100 - 300, 100 - 250, 120 - 240, etc. For example, when fitting the elongation at break (El), n can be selected from any of the following appropriate ranges: 0.05 to -0.5, -0.05 to -0.4, -0.05 to -0.3, -0.05 to -0.2, -0.06 to -0.2, etc., and m can be selected from any of the following appropriate ranges: 0.1 - 50, 0.1 - 30, 0.1 - 20, 0.1 - 10, 0.5 - 50, 0.5 - 30, 0.5 - 20, 0.5 - 10, 1 - 50, 1 - 30, 1 - 20, 1 - 10, etc. For example, when fitting the yield strength (YS), n can be selected from any of the following appropriate ranges: -0.05 to -5, -0.1 to -5, -0.2 to -5, -0.5 to -5, -0.05 to -4, -0.1 to -4, -0.2 to -4, -0.5 to -4, -0.05 to -3, -0.1 to -3, -0.2 to -3, -0.3 to -3, -0.5 to -3, -0.8 to -2.5, -0.8 to -2.4, -0.8 to -2.0, etc., and m can be selected from any of the following appropriate ranges: 50 - 300, 80 - 300, 50 - 250, 80 - 250, 100 - 300, 100 - 250, 120 - 250, etc.

[0244] Based on any suitable embodiment of the present application, further, in some embodiments, the method for constructing the corrosion resistance - mechanical property analysis model of the metal material further includes the following steps: establishing a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time in the target service environment.

[0245] By establishing an empirical relationship (which can be denoted as the third set of empirical relationships) between the equivalent corrosion time under the corrosion test conditions and the service time in the target service environment, the equivalent corrosion time can be converted into the service time in the target service environment, so as to more directly predict the service life of the metal material and its structural components or products.

[0246] Optionally, a third set of empirical relationships can be established between the equivalent corrosion time under selected corrosion test conditions and the service time in the target service environment according to existing standards, specifications, or general experience in the art. For example, 1 day (d) of salt spray corrosion environment for die-cast aluminum alloy parts can be equivalent to more than one year (i.e., ≥ 1 year) of corrosion in its actual service environment.

[0247] In some embodiments, a method for constructing a corrosion resistance-mechanical property analysis model of a metal material is provided, which includes the following steps (see Figure 3 ):

[0248] S110: Taking the metal material as the test object, obtaining the test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain a corrosion performance test experimental data set, and also obtaining the test values of mechanical parameters at different corrosion degrees corresponding to different equivalent corrosion time points to obtain a mechanical property test experimental data set; wherein, the corrosion test conditions are used to simulate the target service environment of the metal material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate.

[0249] S120: Establishing a first set of empirical relationships between the corrosion parameters and the equivalent corrosion time based on the corrosion performance test experimental data set, and also establishing a second set of empirical relationships between the mechanical parameters and the equivalent corrosion time based on the mechanical property test experimental data set; also establishing a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time in the target service environment.

[0250] Based on any suitable embodiment of the present application, further, in some embodiments, the method for constructing a corrosion resistance-mechanical property analysis model of a metal material includes the following steps: establishing a fourth set of empirical relationships between the corrosion rate and the equivalent corrosion time under the corrosion test conditions. At this time, the first set of empirical relationships described above includes the fourth set of empirical relationships between the corrosion rate and the equivalent corrosion time under the corrosion test conditions. At this time, the corrosion parameters in the corrosion performance test experimental data set include the corrosion rate.

[0251] By establishing the empirical relationship between the corrosion rate and the equivalent corrosion time under the corrosion test conditions (which can be denoted as the fourth set of empirical relationships), the correlation between the corrosion behavior and the mechanical properties of the metal material in the target service environment can be dynamically analyzed.

[0252] The data points of the corrosion rate obtained from the test analysis and the corresponding equivalent corrosion time can be subjected to fitting analysis.

[0253] In some embodiments, a method for constructing a corrosion resistance-mechanical property analysis model of a metal material is provided, which includes the following steps (see Figure 4 ):

[0254] S110: Taking a metallic material as a test object, obtaining test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain a corrosion performance test experimental data set, and also obtaining test values of mechanical parameters at different corrosion degrees corresponding to different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein, the corrosion test conditions are used to simulate the target service environment of the metallic material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate;

[0255] S120: Based on the corrosion performance test experimental data set, establishing a first set of empirical relationships for the corrosion parameters varying with the equivalent corrosion time, and also based on the mechanical performance test experimental data set, establishing a second set of empirical relationships for the mechanical parameters varying with the equivalent corrosion time; wherein, the first set of empirical relationships includes a fourth set of empirical relationships between the corrosion rate under the corrosion test conditions and the equivalent corrosion time.

[0256] In some embodiments, a method for constructing a corrosion resistance degree - mechanical property analysis model of a metallic material is provided, which includes the following steps (refer to Figure 5 ):

[0257] S110: Taking a metallic material as a test object, obtaining test values of corrosion parameters at different equivalent corrosion time points under corrosion test conditions to obtain a corrosion performance test experimental data set, and also obtaining test values of mechanical parameters at different corrosion degrees corresponding to different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein, the corrosion test conditions are used to simulate the target service environment of the metallic material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate;

[0258] S120: Based on the corrosion performance test experimental data set, establishing a first set of empirical relationships for the corrosion parameters varying with the equivalent corrosion time, and also based on the mechanical performance test experimental data set, establishing a second set of empirical relationships for the mechanical parameters varying with the equivalent corrosion time; also establishing a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time in the target service environment; wherein, the first set of empirical relationships includes a fourth set of empirical relationships between the corrosion rate under the corrosion test conditions and the equivalent corrosion time.

[0259] Figure 3 , Figure 4 and Figure 5In the embodiments shown, independently of each other, the mechanical parameters in the construction of the mechanical property test experimental data set can refer to the foregoing definitions. Further, the mechanical parameters may include at least one of the tensile fracture strength and the fracture elongation rate. In some of these embodiments, the mechanical parameters include the tensile fracture strength and the fracture elongation rate. The mechanical parameters may include the yield strength. In some of these embodiments, the mechanical parameters include the yield strength. In some embodiments, the mechanical parameters include the tensile fracture strength, the fracture elongation rate, and the yield strength.

[0260] In a second aspect of the present application, there is provided an analysis method for the service life of a metal material, which analyzes the service life of the metal material by using a corrosion resistance-mechanical property analysis model of the metal material.

[0261] The metal material may be defined as in the first aspect of the present application.

[0262] In some embodiments, there is provided an analysis method for the service life of a metal material, which includes the following steps (which can refer to Figure 6 ):

[0263] S210: Determine the mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine the corrosion test conditions capable of simulating the target service environment, and obtain the test value of the corrosion degree of the metal material under the corrosion test conditions;

[0264] S220: Obtain the service life parameters of the metal material under the corrosion test conditions according to the test value of the corrosion degree, the effective state threshold of the mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metal material; wherein, the corrosion resistance-mechanical property analysis model of the metal material at least includes the following relational expressions: including a first set of empirical relational expressions in which the corrosion parameters characterizing the corrosion degree change with the equivalent corrosion time and a second set of empirical relational expressions in which the mechanical parameters change with the equivalent corrosion time.

[0265] The analysis method for the service life of the metal material selects mechanical parameters related to the failure behavior of the metal material based on the target service environment of the metal material, and selects corrosion test conditions that can simulate the target service environment. Furthermore, the test value of the corrosion degree of the metal material under the selected corrosion test conditions is obtained. Thus, the service life parameters of the metal material under the selected corrosion test conditions can be obtained according to the test value of the corrosion degree, the effective state threshold of the selected mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metal material. The corrosion resistance-mechanical property analysis model of the metal material takes the equivalent corrosion time and the mechanical properties at different corrosion degrees as the link, and at least includes the following two relational expressions: the first set of empirical relational expressions in which the corrosion parameter including at least one of the corrosion degree and the corrosion rate changes with the equivalent corrosion time, and the second set of empirical relational expressions in which the aforementioned mechanical parameters change with the equivalent corrosion time. This analysis method can be effectively and accurately used to analyze the service life of the metal material in the target service environment.

[0266] Based on any suitable embodiment of the present application, further, in some embodiments, the service life parameters at least include the equivalent corrosion time.

[0267] According to the aforementioned analysis method, at least the equivalent corrosion time parameter of the metal material can be obtained, which can reflect the service life situation of the metal material.

[0268] Based on any suitable embodiment of the present application, further, in some embodiments, obtaining the service life parameters of the metal material under the corrosion test conditions according to the test value of the corrosion degree, the effective state threshold of the mechanical parameters, and the corrosion resistance-mechanical property analysis model of the metal material includes:

[0269] Obtaining the remaining service time of the metal material according to the test value of the corrosion degree, the effective state threshold of the mechanical parameters, the corrosion resistance-mechanical property analysis model of the metal material, and the third set of empirical relational expressions between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment.

[0270] The remaining service time of the metal material can be obtained according to the test value of the corrosion degree of the metal material, the effective state threshold of the mechanical parameters related to the failure behavior of the metal material, the corrosion resistance-mechanical property analysis model of the metal material, and the empirical relational expressions between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment, so as to realize the predictive analysis of the remaining service life of the metal material.

[0271] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameters include at least two. Without limitation, the failure response degrees of the metal material to each mechanical parameter can be sorted from high to low in sequence, and the corrosion resistance degree - mechanical property analysis model of the metal material can be obtained according to the mechanical parameter ranked first.

[0272] Sorting the failure response degrees of the metal material to each mechanical parameter from high to low in sequence, and obtaining the corrosion resistance degree - mechanical property analysis model of the metal material according to the mechanical parameter ranked first can more effectively reflect the correlation between the corrosion behavior and the mechanical property failure of the metal material in the target service environment.

[0273] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion resistance degree - mechanical property analysis model of the metal material is constructed according to the construction method of the corrosion resistance degree - mechanical property analysis model of the metal material described in the first aspect of the present application.

[0274] The corrosion resistance degree - mechanical property analysis model involved in the foregoing analysis method of the service life of the metal material can be constructed by using the construction method in the first aspect of the present application, and a relational expression between the corrosion degree of the metal material and the mechanical property including at least one mechanical parameter among the tensile fracture strength and the fracture elongation rate can be constructed.

[0275] In the third aspect of the present application, a device for analyzing the service life of a metal material is provided, which includes: a corrosion performance data acquisition module 310 and a corrosion performance data processing module 320. Refer to Figure 7 .

[0276] The metal material can be defined as in the first aspect of the present application.

[0277] In some embodiments, a device for analyzing the service life of a metal material is provided, which includes:

[0278] A corrosion performance data acquisition module 310, configured to determine mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine corrosion test conditions capable of simulating the target service environment, and acquire test values of the corrosion degree of the metal material under the corrosion test conditions;

[0279] A corrosion performance data processing module 320, configured to obtain service life parameters of the metal material under the corrosion test conditions according to the test values of the corrosion degree, the effective state threshold of the mechanical parameters, and the corrosion resistance degree - mechanical property analysis model of the metal material; wherein, the corrosion resistance degree - mechanical property analysis model of the metal material can be defined as in the first aspect or the second aspect of the present application.

[0280] The service life analysis device of the metal material provided in the third aspect of the present application can be used to implement the analysis method of the service life of the metal material provided in the second aspect of the present application.

[0281] In the fourth aspect of the present application, an analysis method for the mechanical properties of a metal material is provided, which analyzes the mechanical properties of the metal material by using a corrosion resistance-mechanical property analysis model of the metal material.

[0282] The metal material can be defined as in the first aspect of the present application.

[0283] In some embodiments, an analysis method for the mechanical properties of a metal material is provided, which includes the following steps (see Figure 8 and Figure 9 ):

[0284] Determine the mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine the corrosion test conditions that can simulate the target service environment, and obtain the test value of the corrosion degree of the metal material under the corrosion test conditions;

[0285] According to the test value of the corrosion degree, the target service time of the metal material, the third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metal material, obtain the preliminary predicted value of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions; wherein, the corrosion resistance-mechanical property analysis model of the metal material can be defined as in the first aspect or the second aspect of the present application;

[0286] Compare the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter to obtain the prediction result of the mechanical parameter of the metal material after using the target service time under the corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, output the preliminary predicted value as the effective predicted value of the mechanical parameter of the metal material after using the target service time under the corrosion test conditions; if the preliminary predicted value of the mechanical parameter is less than the effective state threshold of the mechanical parameter, output the prediction result that the metal material fails before reaching the target service time.

[0287] The analysis method of the mechanical properties of the aforementioned metal material selects mechanical parameters related to the failure behavior of the metal material based on the target service environment of the metal material, and selects corrosion test conditions that can simulate the target service environment, so as to obtain the test value of the corrosion degree of the metal material under the selected corrosion test conditions. Therefore, according to the test value of the corrosion degree, the target service time of the metal material, the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metal material, the preliminary predicted value of the mechanical parameters of the metal material after using the target service time under the selected corrosion test conditions can be obtained. By comparing the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter, the prediction result of the mechanical parameter of the metal material after using the target service time under the selected corrosion test conditions can be obtained. If the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, the effective predicted value of the mechanical parameter of the metal material after using the target service time under the selected corrosion test conditions is equal to the preliminary predicted value; if the preliminary predicted value of the mechanical parameter is less than the effective state threshold of the mechanical parameter, it means that the metal material fails before reaching the target service life.

[0288] In the fifth aspect of the present application, a device for analyzing the mechanical properties of a metal material is provided (see Figure 10 ), which includes: a test data acquisition module 510, a test data processing module 520, and a mechanical property classification and identification module 530.

[0289] The metal material can be defined as in the first aspect of the present application.

[0290] In some embodiments, a device for analyzing the mechanical properties of a metal material is provided, which includes:

[0291] The test data acquisition module 510 is used to determine mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material, determine corrosion test conditions that can simulate the target service environment, and obtain the test value of the corrosion degree of the metal material under the corrosion test conditions;

[0292] The test data processing module 520 is used to obtain the preliminary predicted value of the mechanical parameters of the metal material after using the target service time under the corrosion test conditions according to the test value of the corrosion degree, the target service time of the metal material, the third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance-mechanical property analysis model of the metal material; wherein, the corrosion resistance-mechanical property analysis model of the metal material can be defined as in the first aspect or the second aspect of the present application;

[0293] A mechanical property classification and identification module 530 is configured to compare a preliminary predicted value of a mechanical parameter with an effective state threshold of the mechanical parameter, so as to obtain a prediction result of the mechanical parameter of the metallic material after using a target service time under corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, the effective predicted value of the mechanical parameter of the metallic material after using the target service time under corrosion test conditions is equal to the preliminary predicted value.

[0294] The mechanical property analysis device of the metallic material provided in the fifth aspect of the present application can be used to implement the analysis method of the mechanical properties of the metallic material provided in the fourth aspect of the present application.

[0295] In the sixth aspect of the present application, a computer device is provided.

[0296] In some embodiments, a computer device is provided, including a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the method for constructing a corrosion resistance-mechanical property analysis model of the metallic material described in the first aspect of the present application, or the analysis method of the service life of the metallic material described in the second aspect of the present application, or the analysis method of the mechanical properties of the metallic material described in the fourth aspect of the present application are implemented.

[0297] The computer device may be a terminal, and its internal structure diagram may be as Figure 11 shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Wherein, the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is configured to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, a method for determining the battery performance of an energy storage system is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device may be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0298] Those skilled in the art can understand that Figure 11 the structure shown in merely represents a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0299] In a seventh aspect of the present application, there is provided a computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method for constructing a corrosion resistance-mechanical property analysis model of a metal material described in the first aspect of the present application, or the method for analyzing the service life of a metal material described in the second aspect of the present application, or the method for analyzing the mechanical properties of a metal material described in the fourth aspect of the present application.

[0300] In yet another aspect of the present application, there is provided a computer program product comprising a computer program, characterized in that when the computer program is executed by a processor, it implements the steps of the construction method in the first aspect of the present application or the analysis methods in the second or fourth aspects of the present application.

[0301] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0302] In the eighth aspect of the present application, there is provided an electrical device including a battery system.

[0303] In some embodiments, the electrical device includes:

[0304] A battery system, which includes a battery box body and battery cells located inside the battery box body. Among them, the battery box body includes the metal material defined in the first aspect of the present application; and

[0305] At least one of the service life analysis device of the metal material described in the third aspect of the present application, the mechanical property analysis device of the metal material described in the fifth aspect of the present application, the computer device described in the sixth aspect of the present application, and the computer-readable storage medium described in the seventh aspect of the present application.

[0306] In the present application, unless otherwise specified, a "battery cell" refers to a basic unit capable of converting chemical energy and electrical energy into each other.

[0307] In some embodiments, the battery cell includes a fuel cell cell. At this time, the corresponding battery system can be a fuel cell system, and the corresponding battery box body can be a fuel cell box body.

[0308] In the present application, unless otherwise specified, a "fuel cell" has the well-known meaning in the art and refers to a chemical device that directly converts the chemical energy of a fuel into electrical energy. A "fuel cell cell" refers to a battery cell that directly converts the chemical energy of a fuel into electrical energy. In the present application, unless otherwise specified, a "fuel cell box body" refers to a battery box body in which fuel cell type battery cells are installed.

[0309] In some embodiments, the electrical device is a fuel-powered electrical device, which includes: a fuel cell system, which includes a fuel cell box body and fuel cell cells located inside the fuel cell box body. Among them, the fuel cell box body includes the metal material defined in the first aspect of the present application.

[0310] In some embodiments, the battery cell includes a lithium battery cell. At this time, the corresponding battery system can be a lithium battery system, and the corresponding battery box body can be a lithium battery box body.

[0311] In the present application, unless otherwise specified, a "lithium battery" has the well-known meaning in the art and refers to a type of battery in which the active ions include lithium ions. A "lithium battery cell" refers to a battery cell in which the active ions include lithium ions. A lithium battery can be a lithium-ion secondary battery. In the present application, unless otherwise specified, a "lithium battery box body" refers to a battery box body in which lithium battery type battery cells are installed.

[0312] In some embodiments, an electrical device includes: a lithium battery system, which includes a lithium battery box body and lithium battery cells located inside the lithium battery box body. Among them, the lithium battery box body includes the metal material defined in the first aspect of the present application.

[0313] The electrical device may include mobile devices (such as mobile phones, laptops, etc.), electric vehicles (such as pure electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, electric bicycles, electric scooters, electric golf carts, electric trucks, etc.), electric trains, ships, satellites, energy storage systems, etc., but is not limited thereto.

[0314] As the electrical device, the battery can be selected according to its usage requirements.

[0315] Figure 12 is an electrical device as an example. The electrical device is a pure electric vehicle, a hybrid electric vehicle, or a plug-in hybrid electric vehicle, etc.

[0316] Another example of the device can be a mobile phone, a tablet computer, a laptop computer, etc. This device usually requires thinness and lightness, and a secondary battery can be used as the power source.

[0317] At least one of the service life analysis device of the foregoing metal material, the mechanical property analysis device of the foregoing metal material, a computer device, a computer-readable storage medium, and a computer program product can be set on the electrical device to implement the foregoing analysis model construction method, the analysis method of the service life of the foregoing metal material, or the analysis method of the mechanical properties of the foregoing metal material, which is beneficial to achieving better management and maintenance of the electrical device, not only beneficial to achieving the safety maintenance of the battery box body in the electrical device, but also beneficial to assisting in designing a battery box body with a longer service life.

[0318] Hereinafter, some embodiments of the present application will be described. The embodiments described below are exemplary and are only used to explain the present application and should not be construed as a limitation of the present application. For those not specified in the embodiments in terms of techniques or conditions, they shall be carried out according to the descriptions above, or according to the techniques or conditions described in the literature in the art, or according to the product specifications. For reagents or instruments not specified in terms of the manufacturer, they are all conventional products that can be obtained through commercial purchase, or can be prepared in a conventional manner from commercially available products.

[0319] In the following embodiments, room temperature refers to 20°C to 30°C.

[0320] I. Test samples:

[0321] Fuel cell boxes made of four aluminum alloy materials, namely A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr, are cut into certain sizes and used as test samples for corrosion tests and tensile tests. The elemental compositions of the four aluminum alloy materials can be referred to in Table 1.

[0322] Among them, each type of aluminum alloy can be prepared by the following method according to the elemental composition shown in Table 1: In a melting furnace, first add pure aluminum ingots, and then add them to the melting furnace in batches according to the melting point differences of other constituent elements. After the previously added raw materials are melted, continue to add the subsequent raw materials. After melting, let it stand and skim the slag, add a refining agent, skim the slag again, add some constituent elements after skimming the slag, and pour and mold in a mold to obtain an ingot of the target size. Let the ingot stand and keep warm, and then water-cool it to room temperature to obtain the aluminum alloy material for the fuel cell box of the target size, which is also denoted as the die-cast aluminum alloy sample.

[0323] Table 1. Elemental compositions of four aluminum alloy materials (the unit in the table is mass percentage wt%)

[0324] Alloy type Si Cu Mg Fe Mn Zn Ti Other elements Al A356.2 6.5-7.5 ≤0.1 0.30-0.45 ≤0.12 ≤0.05 ≤0.05 ≤0.2 - Bal. A380 7.5-9.5 3.0-4.0 ≤0.1 ≤2.0 ≤0.5 ≤3.0 - Sn: ≤ 0.35 Bal. AlSi10MgMn 8.5-10.5 ＜0.05 0.17-0.90 0.2-0.3 0.20-0.50 - - Cr:0.1-0.2 Bal. AlSi9MnMoZr 8.5-10.5 0.05 0.06 ≤0.6 0.35-0.60 ≤0.07 ≤0.15 Zr:≤0.3 Bal.

[0325] In Table 1, "-" indicates not detected, and according to the conventional composition, it can be regarded as not containing, and "Bal." indicates the matrix element.

[0326] II. Construct a corrosion resistance-mechanical property analysis model based on salt spray corrosion tests

[0327] 1. Salt spray corrosion test method

[0328] Use a 3.5 wt% NaCl aqueous solution and test at 35 °C.

[0329] Every 24 h, analyze the macroscopic morphology, microscopic morphology, corrosion mass loss, and corrosion rate from the box materials with a total test time of 600 h.

[0330] Before the test, cut the fuel cell box with known alloy material types into blocks of 15 mm × 15 mm × 2 mm, and wrap the non-test surfaces with blue film. Polish, buff, and dry the test surfaces and then weigh them as W0. The total test duration is 600 h. During the test, take a batch of samples every 24 h for the observation of surface macroscopic morphology and microscopic morphology. After observation, use chromic acid cleaner (20 g / L Cr 2 O 3 + 50 mL / L H 3 PO 4 ) to remove the corrosion products on the sample surface and weigh again to calculate the corrosion rate and conduct morphology observation. The test duration for the i-th sampling is denoted as Ti, and the weighing at the i-th sampling is denoted as Wi. Set at least three parallel samples for each test.

[0331] 2. Test Methods

[0332] (1) Macroscopic Morphology Test Method

[0333] Sample: The sampled corrosion time points are as described above.

[0334] Instrument: Observation under shadowless lamp.

[0335] (2) Microscopic Morphology Test Method

[0336] Sample: The sampled corrosion time points are as described above.

[0337] Instrument: NOVA NanoSEM 230 low-vacuum ultra-high resolution field emission electron microscope.

[0338] Method: The probe type (det) is ETD. Taking Figure 13 as an example, the acceleration voltage (HV) is 5 kV and the working distance is 30 mm.

[0339] (3) Corrosion Mass Loss and Corrosion Rate Analysis Method

[0340] The mass loss W of the i-th sampling = W0 - Wi.

[0341] The corrosion rate Ri at the i-th sampling can be calculated by substituting into formula (I):

[0342] Corrosion rate = (K × W) / (A × Ti × D) mm / y (I)

[0343] In formula (I): K = 8.64 × 10 4 , K is the time constant;

[0344] W is the mass difference before and after the test = W0 - Wi, with the unit of mg;

[0345] A is the test surface area, with the unit of cm 2 , here it is 1.5 cm × 1.5 cm = 2.25 cm 2 ;

[0346] Ti is the test time of the i-th sampling, with the unit of h;

[0347] D = 2.7 g / cm 3 , D is the density.

[0348] "mm / y" represents millimeters per year.

[0349] (4) Establish the first set of empirical relationships for corrosion parameters varying with equivalent corrosion time

[0350] The total test time is divided into three time periods, and the functions described below are used for fitting respectively, and the function with better fitting effect is selected.

[0351] Optional function 1: y1 = A·x B ;

[0352] Optional function 2: y1 = a + b·x;

[0353] Among them, x is the equivalent corrosion time, y1 is the corrosion parameter, A is a positive number, B is a negative number, b is a positive number, and a is a real number.

[0354] The fitting effect can be evaluated by at least one of Reduced Chi-Sqr, R 2 and adjusted R 2 . Among them, Reduced Chi-Sqr is equivalent to the residual mean square RSS / dof in Anova. The closer Reduced Chi-Sqr is to 1, the better the fitting effect, which is mainly used in non-linear fitting. R 2 is the coefficient of determination (COD). The closer it is to 1, the better the fitting effect. "Adjusted R 2 " is obtained from the linear regression of SPSSAU. The closer this value is to 1, the better the fitting effect.

[0355] 3. Analysis of salt spray corrosion test results

[0356] Figure 13Macrographs (first row) and micrographs of four aluminum alloy materials at different equivalent corrosion time points in the salt spray test results; (a) A356.2; (b) A380; (c) AlSi10MgMn; (d) AlSi9MnMoZr. It can be found from the surface macrographs of the four die-cast aluminum alloy samples at different corrosion times that among the four aluminum alloy materials, the A380 alloy is corroded most severely, with more white corrosion products accumulated on the samples, while the other three die-cast aluminum alloys are corroded relatively slowly and have relatively less surface corrosion products, which is similar to the results of the electrochemical test. For the A356.2 and A380 alloy materials, when the corrosion time is short (1d - 6d), the alloy surface is quickly covered by corrosion products, presumably due to the occurrence of general corrosion. The stacking area and thickness of the surface corrosion products both increase continuously with the extension of the corrosion time, and the sample surface shows the characteristic of transitioning from the initially corroded dark color to being covered by a large amount of white corrosion products. For the AlSi10MgMn and AlSi9MnMoZr alloy materials, in the initial stage of corrosion (1d - 6d), the sample surface mainly shows local pitting corrosion pits, and more corrosion products accumulate near the pitting corrosion pits, presumably due to the protection of the passive film on the surface; in the middle stage of corrosion (7d - 18d), the corrosion further expands, the passive film is damaged, and it gradually shows uniform corrosion; in the late stage of corrosion (19d - 24d), more and more positions on the sample surface are covered by corrosion products until the entire surface is covered.

[0357] Regarding the micrographs of four aluminum alloy materials (A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr) at different equivalent corrosion time points in the salt spray test, including the microstructural diagrams (not shown) of the four die-cast aluminum alloy samples in the early and late stages of the salt spray corrosion test. In the initial stage of corrosion (1d), the A356.2 and A380 alloys show a general and uniform corrosion morphology, and the A380 alloy is significantly more severely corroded with more corrosion products. The AlSi10MgMn and AlSi9MnMoZr alloys mainly show pitting corrosion, and the pitting corrosion of the AlSi10MgMn alloy is more obvious, which is similar to the results of electrochemical corrosion. In the final stage of corrosion (25d), general and uniform corrosion occurs on the surfaces of all four alloys, and the corrosion products basically cover the sample surfaces and accumulate. The surface corrosion products of the A380 alloy are more and thicker, followed by the AlSi10MgMn alloy, while the A356.2 alloy and the AlSi9MnMoZr alloy are relatively close.

[0358] Microscopic morphology diagrams of four aluminum alloy materials (A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr) after removing corrosion products after 10 days of salt spray corrosion test include microscopic structure diagrams of die-cast aluminum alloy after removing corrosion products (not shown). The α-Al matrix of the four alloy materials has all corroded to varying degrees. Since a large number of Si particles are dispersed in the A356.2 alloy, although the Si particles cannot directly participate in the corrosion reaction, they will accelerate the corrosion of the matrix. Due to the presence of Si particles, it is also difficult to form a dense oxide film on the alloy surface, resulting in more obvious corrosion of the matrix α-Al around the Si particles. And with the occurrence and expansion of corrosion, the Si particles will even flake off. A large number of corrosion pits are distributed around the Al-Si eutectic structure of the A380 alloy because the Al 2 Cu phase is distributed near the Al-Si eutectic structure, further exacerbating the intergranular corrosion tendency of the Al-Si eutectic structure. In addition, the solid solution of a small amount of Cu in the matrix will increase the potential difference between the grain boundaries and the grain interior, and the potential of the Al 2 Cu phase is relatively positive, and the potential of the matrix phase with a higher Cu content is also relatively positive. At this time, the matrix with a lower Cu content will act as the cathode phase, and together with the nearby Cu-rich matrix phase and Al 2 Cu phase forms an electrochemical microcell locally, causing the matrix phase part of the Cu-poor solid solution to corrode continuously and resulting in the disappearance of the grain boundaries. In the AlSi10MgMn alloy, the potential of the Al 15 (FeMn) 3 Si 2 phase and in the AlSi9MnMoZr alloy, the potential of the Al 12 Mn 3 Si 2 phase is similar to the potential of the matrix. Therefore, after the passivation film is damaged, the corrosion at the grain boundaries and the phase boundaries of the Al-Si eutectic structure of the AlSi10MgMn and AlSi9MnMoZr alloys is relatively severe. Since the passivation film of the AlSi9MnMoZr alloy is more stable and more difficult to be damaged, this characteristic of the corrosion degree at the grain boundaries and the phase boundaries of the Al-Si eutectic structure in the AlSi10MgMn alloy is more obvious.

[0359] Figure 14Experimental results of mass loss and corrosion rate of four aluminum alloy materials at different equivalent corrosion time points in the salt spray test. The corrosion weight loss and corrosion rate of A380 alloy are much higher than those of the other three alloys, further confirming its poor corrosion resistance. In the first stage (0 - 13d), the corrosion rate of A356.2 alloy is higher than that of AlSi10MgMn and AlSi9MnMoZr alloys. In the second stage (14d - 22d), with the rupture of the passivation film and the intensification of local corrosion behavior, the corrosion rates of AlSi10MgMn alloy and AlSi9MnMoZr alloy gradually increase, while the corrosion rate of A356.2 alloy basically remains at about 0.05 mm / y. In the third stage ((23 - 25d), the oxide film generated by self-passivation of AlSi10MgMn and AlSi9MnMoZr alloys is almost completely destroyed, and the galvanic corrosion caused by the second phase intensifies. Therefore, the corrosion rates of AlSi10MgMn and AlSi9MnMoZr alloys increase significantly.

[0360] Figures 15 - 18 Respectively Figure 14 Figure showing the fitting results between the corrosion rate and equivalent corrosion time of four aluminum alloy materials in the salt spray corrosion test. After segmentally fitting the corrosion rates of the four die-cast aluminum alloys, the fitting curves basically conform to the test results. An empirical relationship between the corrosion rate and equivalent corrosion time is established (the first set of empirical relationships, and also the fourth set of empirical relationships), and the fitting results of the four samples are shown in Table 2.

[0361] Table 2. Figures 15 to 18 Relevant parameters of the fitting results of the empirical relationship between the corrosion rate and equivalent corrosion time of four aluminum alloy materials in

[0362]

[0363] In Table 2, Reduced Chi-Sqr is equivalent to the residual mean square RSS / dof in Anova; R 2 is the coefficient of determination (COD); "Adjusted R 2 " is obtained according to the linear regression of SPSSAU.

[0364] Based on the above empirical formula, during the service process of die-cast aluminum alloy parts, the corresponding equivalent corrosion time x can be substituted according to the corrosion medium and service time, and the corresponding corrosion rate y can be calculated, which has certain guiding significance for the evaluation of product service life.

[0365] Taking Shanghai, China as an example, the salt spray corrosion of die-cast aluminum alloy parts for 1 day is equivalent to their corrosion in the real environment for more than one year (equivalent to establishing the third set of empirical relationships between the equivalent corrosion time under the selected corrosion test conditions and the service time in the target service environment). According to the first set of empirical relationships in formulas (3-1) to (3-9), a conservative corrosion rate prediction model for four die-cast aluminum alloy parts over 25 years can be established.

[0366] 4. Tensile Test Method

[0367] (1) Sample size, as Figure 23 shown, in millimeters (mm), where R2.5 represents a radius of 2.5 millimeters.

[0368] (2) Testing instrument: Z20 TEW electronic universal material testing machine.

[0369] (3) Testing and analysis method:

[0370] Wrap the tensile samples of four die-cast aluminum alloys with blue film, leaving only the test surface. The total test duration is 600h. During the test, a batch of samples is taken every 24h for tensile property testing, and at least three parallel samples are set for each test.

[0371] Conduct mechanical property tests on tensile specimens at different corrosion stages to obtain stress-strain curves, and then analyze to obtain the tensile strength (which can be abbreviated as UTS, or also referred to as the ultimate tensile strength), elongation (which can be abbreviated as El), and yield strength (which can be abbreviated as YS).

[0372] (4) Establish the second set of empirical relationships between mechanical parameters and equivalent corrosion time

[0373] Divide the total test time into three time periods, and use the following functions for fitting respectively, and select the function with better fitting effect.

[0374] Optional function 1: y2 = M·x N ;

[0375] Optional function 2: y2 = m + n·x;

[0376] where x is the equivalent corrosion time, y2 is the mechanical parameter, M is a positive number, N is a negative number, n is a negative number, and m is a positive number.

[0377] The fitting effect can be evaluated using at least one of Reduced Chi-Sqr, R 2 and adjusted R 2 .

[0378] (5) The first set of empirical relationships and the second set of empirical relationships constitute an empirical model of the relationship between the corrosion degree and mechanical properties.

[0379] (6) Test analysis results

[0380] Figures 19 to 22 They are the experimental results and fitting results of the mechanical parameters and equivalent corrosion time of four aluminum alloy materials A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr in salt spray corrosion tests at different equivalent corrosion time points; among them, the mechanical parameters involve the ultimate tensile strength (UTS), elongation at break (El), and yield strength (YS).

[0381] According to the test analysis results, the yield strength and tensile strength of the A380 alloy show a rapid downward trend with the increase of corrosion time, which is particularly obvious in the initial stage of corrosion (1 - 4d). The yield strength and tensile strength decrease to 77.5% and 76% of that before corrosion respectively; subsequently, the rate of performance attenuation slows down, and finally the yield strength and tensile strength decrease to 65.4% and 52.5% of that before corrosion respectively. The attenuation rates of the yield strength and tensile strength of the A356.2, AlSi10MgMn, and AlSi9MnMoZr alloys are relatively stable. The yield strength and tensile strength of the A356.2 alloy decrease to 84.3% and 82.6% of that before corrosion respectively, the yield strength and tensile strength of the AlSi10MgMn alloy decrease to 84.4% and 75.6% of that before corrosion respectively, and the yield strength and tensile strength of the AlSi9MnMoZr alloy decrease to 85.8% and 80.3% of that before corrosion respectively. In addition, when the corrosion time is 23d, the tensile strength of the AlSi9MnMoZr alloy only decreases to 87.5% of that before corrosion, which is higher than the other three alloys (A356.2: 86.4%; A380: 62.9%; AlSi10MgMn: 81.4%), indicating that the AlSi9MnMoZr alloy has the best corrosion resistance when the corrosion time is short, while the A380 alloy always shows the worst corrosion resistance.

[0382] Compared with the yield strength and tensile strength, the elongation of the four die-cast aluminum alloys shows a rapid downward trend with the increase of corrosion time. The elongation of the A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr alloys decreases to 38.6%, 25.6%, 41.5%, and 25.8% of that before corrosion respectively, indicating that the loss of alloy elongation caused by corrosion is much greater than the impact on strength. This is because, after corrosion occurs, while corrosion products begin to form on the alloy surface, Cl -Continuously invading the interior of the alloy, it creates weak zones within the alloy, which are extremely likely to become stress concentration areas, thus promoting the initiation and propagation of cracks during the tensile process. As the corrosion time prolongs, more and more weak zones are brought about by corrosion inside the alloy, greatly promoting the initiation and propagation of cracks during the tensile process, resulting in a significant decline in the plastic deformation ability of the alloy.

[0383] For the fitting of three mechanical parameters UTS, El, and YS of four die-cast aluminum alloys, reference can be made to Figures 19 - 22 and Table 3. The empirical relationship formulas between the yield strength, ultimate tensile strength, and elongation of the four alloys and the equivalent corrosion time are shown in Formulas (4-1) to (4-12) respectively, and reference can be made to Table 3. It can be found that there is no obvious deviation between the fitting curve and the test results, and both R 2 and the adjusted R 2 are relatively high, basically above 0.9, and some can reach 0.99. Therefore, an empirical relationship model between the corrosion degree and mechanical properties is established, where YS, UTS, and El represent the yield strength, ultimate tensile strength, and elongation respectively.

[0384] Table 3. The second set of empirical relationship formulas for the variation of mechanical parameters with equivalent corrosion time

[0385]

[0386] 5. Correlation analysis between corrosion degree and mechanical parameters

[0387] With the progress of corrosion, it leads to a decline in the mechanical properties of the material; generally speaking, the factors influencing mechanical properties are complex. For the battery box, the special application environment of the battery box has a high impact on corrosion resistance, so it is possible to analyze the prediction of the mechanical properties of metal materials and evaluate the service life through the corrosion performance as a link.

[0388] Compare Figures 15 - 18 the corrosion rate - equivalent corrosion time variation curve and Figures 19 - 22 the mechanical parameter - equivalent corrosion time variation curve. It can be found that the response behaviors of the corrosion rate and mechanical parameters to the equivalent corrosion time have significant differences, which leads to the fact that it is difficult to effectively reflect the corrosion failure behavior of the sample only by using the corrosion rate - equivalent corrosion time variation curve alone. Simply determining the corrosion rate cannot determine its influence degree on the service life. The above embodiments establish the corresponding relationship between corrosion performance - service life by establishing the relationship between corrosion rate and mechanical properties.

[0389] Disadvantages of other analysis models: There are many influences on the attenuation of mechanical properties. In addition to corrosion factors, some environmental factors such as temperature, humidity, and electrolyte type will also influence mechanical properties, which makes it difficult to construct a prediction model that only contains mechanical property parameters.

[0390] Based on the tensile fracture analysis at different corrosion degrees, it is found that there is a strong correlation between the corrosion degree and mechanical parameters, verifying the feasibility of predicting mechanical properties or service life using the established corrosion degree-mechanical parameter analysis model mentioned above.

[0391] Tensile fracture characterization method: Scanning Electron Microscope (SEM) technology, NOVA NanoSEM 230 low-vacuum ultra-high resolution field emission electron microscope.

[0392] The fracture morphologies of four die-cast aluminum alloy materials, A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr, before salt spray corrosion can be observed by SEM technology. For the fracture surface of A356.2 alloy, dimples of various sizes and cleavage steps can be observed, so its fracture mode is quasi-cleavage fracture. There are large-area splitting surfaces on the fracture surface of A380 alloy, and basically no dimple morphology, with obvious brittle fracture characteristics. The fracture morphologies of AlSi10MgMn and AlSi9MnMoZr alloys are cleavage facets roughly the same size as the grain size. This is because in polycrystals, although the macroscopic fracture surface is approximately perpendicular to the direction of the maximum tensile stress, the cleavage planes of each grain in the microstructure are not all perpendicular to the tensile stress. In addition, a small amount of terraced cleavage steps and river-like patterns are observed on the fracture surface, and there are also tearing edges produced by plastic deformation, indicating that a certain amount of plastic deformation has occurred.

[0393] The fracture morphologies of the four die-cast aluminum alloy materials at the center (Core) and the edge (Edge) of the fracture near the test surface at different corrosion times (5d, 15d, 25d) can be observed by SEM technology.

[0394] The fracture morphologies of A356.2 alloy material during salt spray corrosion test at different corrosion times: As the corrosion time increases, the fracture morphologies at the center of the A356.2 alloy fracture are very similar, still being quasi-cleavage morphologies with dimples, but the number of dimples is decreasing and becoming less obvious. The fracture at 25d is basically a cleavage morphology. The fracture edge of A356.2 alloy is different. There are many gray corrosion products on the fracture surface, and the defect areas in the fracture are gradually increasing. Many small holes can be observed. As the corrosion time increases, the volume of the holes gradually becomes larger and the number gradually increases. The strength at these defect positions will decrease significantly, and it is easy to accumulate stress, leading to the initiation and propagation of cracks, thus causing a significant decrease in the elongation of A356.2 alloy.

[0395] Fracture morphology of A380 alloy material at different corrosion times during salt spray corrosion test: The fracture morphology of A380 alloy material is different from that of A356.2 alloy. The center of the A380 alloy fracture is cleavage fracture, and there are also certain corrosion products, indicating that its corrosion depth is relatively deep. As the corrosion time increases, the cleavage steps on the fracture surface gradually become larger. Due to the occurrence of corrosion, the difference between different small facets gradually disappears, and large cleavage steps are formed after multiple parallel or nearly parallel cleavage planes of different heights meet. At the fracture edge, a relatively large splitting surface first appears, and then as the corrosion spreads, the splitting surface cracks into small planes, and many slender microcracks appear between the small planes, indicating that the corrosion has extended into the grains of the A380 alloy, resulting in a large number of cracks extending from the surface into the grains of the A380 alloy, so its elongation rate decreases significantly. In addition, due to the appearance of more corrosion products at the fracture center, it proves that the corrosion is relatively deep, and more and more cracks and other defects appear inside the alloy, which has a greater impact on the strength.

[0396] Fracture morphology of AlSi10MgMn alloy material at different corrosion times during salt spray corrosion test: There are many cleavage small facets at the fracture center, and some dimples can be seen when the corrosion time is short (5d), which is a quasi-cleavage fracture morphology. In addition, a small amount of voids appear at the fracture center, which is particularly obvious when the corrosion time is long (15d and 25d). Gray corrosion products are also observed at the fracture edge. As the corrosion progresses, the fracture edge splits from larger cleavage steps into small planes separated by cracks. Compared with the A380 alloy, the number of its corrosion products and small planes is less, indicating that it has better corrosion resistance.

[0397] Fracture morphology of AlSi9MnMoZr alloy material at different corrosion times during salt spray corrosion test: Compared with the AlSi10MgMn alloy, there are many small dimples and obvious tearing ridges at the fracture center, indicating that it has more plastic deformation. Dimples are the main feature of plastic fracture. The more the number of dimples and the smaller their size, the stronger the plastic deformation ability of the material, so its elongation rate is higher than that of the AlSi10MgMn alloy. In addition, at the fracture edge when the corrosion time is short (5d), more dimples and cleavage steps can still be observed. Therefore, when the corrosion time is short, the performance attenuation of the AlSi9MnMoZr alloy is not serious. As the corrosion time increases, the fracture edge morphology gradually transitions to cleavage morphology, and a small amount of corrosion products also begin to appear at the edge. When the corrosion time is long (25d), many small holes appear at the edge, but the number of microcracks is small. Therefore, macroscopically, the yield strength and tensile strength of the AlSi9MnMoZr alloy do not decrease significantly, while the elongation rate decreases rapidly.

[0398] From the above analysis results, it can be seen that in a corrosive environment, for alloy samples with different mechanical failure behaviors and different fracture morphologies, there is a strong correlation between mechanical properties and equivalent corrosion time. Therefore, the construction method of the corrosion degree-mechanical parameter analysis model established above has a certain universality, and the constructed analysis model can effectively analyze mechanical properties or service life.

[0399] III. Electrochemical Corrosion Test

[0400] 1. Test Analysis Method

[0401] Electrochemical corrosion includes: open circuit voltage test, alternating current impedance test, and potentiodynamic polarization test.

[0402] Before the test, the die-cast aluminum alloy was cut into samples with dimensions of 10 mm × 10 mm × 2 mm, and the samples were cold-mounted with epoxy resin to ensure that only the test surface with an area of 1 cm 2 was exposed after cold mounting. The test surface was also polished successively with sandpaper and then polished with a polishing agent until the surface of the sample was clean and bright. After cleaning the surface with ethanol, it was dried and reserved for use.

[0403] During the test, first, the open circuit voltage (OCP) of the sample was measured. After the OCP was stable for 60 min, an alternating current impedance test (EIS) was performed on the sample to measure the electrochemical impedance spectrum of the sample at different alternating current frequencies. When testing, a 10 mV alternating current sine wave was used as the excitation voltage, and the test frequency was controlled within 0.01 - 105 Hz.

[0404] After the test, the results of the EIS were fitted with an equivalent circuit, and the parameters of each component in the equivalent circuit diagram were analyzed. After the alternating current impedance experiment, a potentiodynamic polarization test was performed on the sample. Scanning started from the potential of OCP - 300 mV at a scanning rate of 0.167 mV / s until the current was greater than 1 mA. After the test, the polarization characteristics of the sample were Tafel-fitted using ZSimpWin v3.40 software.

[0405] The structural schematic diagram of the three-electrode system in the electrochemical corrosion test equipment used is as Figure 24 shown, where R, mA, and V represent a rheostat, an ammeter, and a voltmeter respectively. The combination of the three can be understood as an electrochemical workstation. By adjusting the given voltage and current, the signals of the sample can be collected as measurement data of corrosion parameters.

[0406] 2. Test Results

[0407] The variation curves of the open circuit voltage (OCP) of the four aluminum alloy materials with time can be referred to Figure 25The OCP values of the four die-cast aluminum alloy materials tend to be stable at 300 s, and the potential remains stable at 1800 s with very little fluctuation. The change in the OCP value is related to the formation of the surface layer, which can control subsequent electrochemical reactions. The OCP values of A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr alloys are -0.474 V, -0.457 V, -0.603 V, and -1.009 V, respectively, indicating that the different microstructures of the four die-cast aluminum alloys have changed the formation of their surface layers and surface reactions.

[0408] The results of the alternating current impedance tests of the four die-cast aluminum alloys can be referred to Figure 26 and Table 4. Among them, (a) is the Bode plot (EIS Bode plot) of the alternating current impedance spectrum, (b) is the phase diagram (phase plot), (c) is the Nyquist plot (Nyquist plot); (d) is the equivalent circuit diagram. From Figure 26 the (a) Bode curve in Figure 26 and the (b) Phase curve in Figure 26 it can be seen that whether at low frequency or high frequency, the AlSi10MgMn alloy exhibits the highest impedance and phase angle, followed by the A356.2 and A380 alloys, and finally the AlSi9MnMoZr alloy. In the Nyquist plot ( Figure 26 (c) in

[0409] ), all four alloy materials show a suppressed capacitance loop. The AlSi10MgMn alloy has the largest capacitance loop diameter, showing better capacitance performance and higher charge transfer resistance. By Figure 26 fitting the specific parameters of each component to the test results of EIS using the equivalent circuit diagram in (d) in

[0409] , the results can be referred to Table 4.

[0409] In the equivalent circuit diagram, R s represents the solution resistance related to the corrosion solution used in the test, and R sl , R ct represent the surface layer resistance and charge transfer resistance of each alloy as the working electrode, respectively. In addition, the deviation of the capacitance in EIS from the ideal capacitance behavior is represented by the constant phase element (CPE), and n is used as an index to evaluate the degree of closeness between the actual test and the theoretical calculation. Q 1 and Q 2 represent the capacitances of the surface layer and the charge transfer layer during the establishment of the corrosion cell, corresponding to n 1 and n 2 , respectively. The results show that because the corrosion solution is 3.5 wt% NaCl solution, the R s of the four alloys is very close. Whether it is R sl or R ct, all showed the characteristics of AlSi10MgMn > A356.2 > A380 > AlSi9MnMoZr, indicating that AlSi10MgMn exhibited the best corrosion resistance among the four during the establishment of the corrosion cell. In the EIS test, the alloy was not corroded. Therefore, the EIS results are only an analysis of the impending corrosive behavior from the perspective of electrochemical thermodynamics. For some metals that are thermodynamically unstable, self-passivation may occur under appropriate conditions, transforming from a corrosion-susceptible alloy to a corrosion-resistant alloy, such as Al, Mg, Cr, etc. Therefore, studying corrosion behavior only from a thermodynamic perspective is one-sided, and the thermodynamic stability of die-cast aluminum alloy materials in the corrosion medium also needs to be considered. According to the experimental data, the AlSi9MnMoZr alloy will undergo self-passivation in a 3.5 wt% NaCl solution and has excellent corrosion resistance.

[0410] Table 4. Equivalent circuit parameter table

[0411] Aluminum alloy material type <![CDATA[R s / Ω]]> <![CDATA[Q 1 / μF]]> <![CDATA[n 1 > <![CDATA[R sl / kΩ]]> <![CDATA[R ct / kQ]]> <![CDATA[Q 2 / μF]]> <![CDATA[n 2 > A356.2 12.64 116.0 0.901 14.3 7.79 14.7 0.923 A380 12.37 91.4 0.985 4.67 5.59 12.5 0.965 AlSi10MgMn 14.26 131.2 0.918 35.1 12.8 17.5 0.969 AlSi9MnMoZr 11.28 35.9 0.928 1.83 1.33 8.1 0.935

[0412] Figure 27 is the potentiodynamic polarization curve for electrochemical corrosion testing. Table 5 lists the relevant potentiodynamic polarization parameters calculated based on the Tafel extrapolation method. The corrosion potentials (Ecorr) of A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr alloys are -0.450 V, -0.415 V, -0.585 V, and -0.981 V respectively, which are very close to the OCP values. According to the electrochemical corrosion behavior, these four die-cast aluminum alloy materials can be divided into two categories: one is the alloy without obvious passivation, including A356.2 alloy and A380 alloy; the other has a significant passivation region, including AlSi10MgMn alloy and AlSi9MnMoZr alloy.

[0413] For the former alloy without obvious passivation, when evaluating the corrosion resistance, the corrosion current density (I corr ) of the alloy can be mainly compared. The alloy with a lower I corr value and a higher R p value has better corrosion resistance. Through Tafel fitting, it can be found that the Ecorr of A356.2 and A380 alloys are very close, but the Icorr of A356.2 alloy is only about one-fourth of that of A380, and its polarization resistance R p is more than twenty times that of A380. Therefore, the corrosion resistance of A356.2 alloy is much better than that of A380 alloy.

[0414] For the latter with a significant passivation region, when studying its corrosion resistance, the passivation region of the alloy should be analyzed. The corrosion current density slowly increases as the potential in the passivation region shifts positively, which means that the expansion of the corrosion behavior is greatly slowed down. The passivation region prevents the development of the corrosion behavior until the potential reaches the breakdown potential (Eb), at which point the passivation film is completely destroyed and the corrosion begins to intensify. The results show that the AlSi9MnMoZr alloy has a more obvious passivation region, with an Eb of -0.411 V, higher than that of the AlSi10MgMn alloy (-0.430 V). Even though the Icorr of the AlSi10MgMn alloy is lower than that of the AlSi9MnMoZr alloy, the latter has a more stable passivation region, which greatly slows down the expansion of the corrosion behavior and has better corrosion resistance. In addition, B c and B a represent the cathodic reaction slope and anodic reaction slope of the Tafel fitting respectively. The B c of all four alloys is higher than B a , indicating that the electrochemical reaction is mainly controlled by the cathodic process.

[0415] Table 5. Tafel fitting parameter table

[0416] Aluminum alloy material type A356.2 A380 AlSi10MgMn AlSi9MnMoZr <![CDATA[E corr (V)]]> -0.450 -0.417 -0.585 -0.981 <![CDATA[I corr (μA / cm 2 )]]> 0.446 1.79 0.74 2.12 <![CDATA[R p (kΩ·cm 2 )]]> 168 7.08 372 12.5 <![CDATA[B a (mV / dec)]]> 127 24.6 171 98.8 <![CDATA[B c (mV / dec)]]> 166 355 226 158

[0417] Regarding the surface morphology of the alloy materials after dynamic polarization, after polarization, the surface morphology of the A356.2 and A380 alloys mainly shows uniform corrosion, and the corrosion products on the surface of the A380 alloy are more than those of the A356.2 alloy, further confirming its poor corrosion resistance. After polarization, the surface morphology of the AlSi10MgMn and AlSi9MnMoZr alloys mainly shows the characteristics of pitting corrosion due to the presence of the surface passivation film. In addition, compared with the AlSi9MnMoZr alloy, the pitting pits of the AlSi10MgMn alloy are larger and deeper, indicating that the passivation film of the AlSi9MnMoZr alloy is more difficult to be destroyed, which is consistent with the results of the dynamic potential polarization curve.

[0418] Therefore, it is also possible to use the parameters characterizing the degree of corrosion in the electrochemical corrosion test to construct a corrosion resistance-mechanical property analysis model.

[0419] IV. Immersion corrosion test

[0420] 1. Test analysis method

[0421] The stage immersion corrosion includes analyzing the macroscopic morphology, microscopic morphology and corrosion rate from the box materials with a total test time of 30 d every 10 d. In the application, 1 d = 1 day.

[0422] The samples for immersion corrosion test can be blocks with dimensions of 15mm×15mm×2mm.

[0423] Before the test, after grinding and polishing the test surface, rinse it successively with deionized water and ethanol. After drying and weighing, place the specimen in a desiccator for storage and standby. During the test, put the sample into a container and add 500 mL of corrosion solution. The composition of the corrosion solution is: 3.5 wt% aqueous NaCl solution. After sealing, place the entire container in a constant temperature water bath tank with the temperature set at 25 °C. Take the specimens once every 10 days (i.e., the test times are 10 days, 20 days, and 30 days respectively), and observe the macroscopic and microscopic morphologies of the surface of the corroded samples. Subsequently, remove the corrosion products on the surface of the samples, compare the masses of the samples before and after corrosion, calculate the corresponding immersion corrosion rate, and set three parallel samples for each test.

[0424] 2. Analysis of Test Results

[0425] The immersion corrosion test was carried out for 10 days, 20 days, and 30 days respectively. The macroscopic morphologies of the surfaces of the samples with different immersion corrosion times can be referred to Figure 28 . After immersion in 3.5 wt% NaCl solution, obvious corrosion products cover the surfaces of all four die-cast aluminum alloys. Compared with the appearance of the samples before corrosion, the surface of the corroded samples becomes rough, with a black corrosion layer appearing and accompanied by gray dot-like corrosion products. In addition, the corrosion products of A380 ( Figure 28 in (b)) and AlSi10MgMn alloy ( Figure 28 in (c)) are more obvious, indicating that their corrosion resistance is inferior to that of A356.2 ( Figure 28 in (a)) and AlSi9MnMoZr alloy ( Figure 28 in (d)). Whether it is the samples for 10 days, 20 days, or 30 days, the corrosion products on the surface of A380 alloy are the most, indicating that A380 alloy has the worst corrosion resistance. When immersed for 10 days, the macroscopic corrosion morphologies of A356.2, AlSi10MgMn, and AISi9MnMoZr alloys are similar. When immersed for 20 days and 30 days, A356.2 alloy shows better corrosion resistance. For AlSi10MgMn and AISi9MnMoZr alloys, due to the destruction of the passive film and the aggravation of pitting corrosion, a large amount of white corrosion products appear on the surface. The coverage area of the spot-like white corrosion products on the surface of AlSil0MgMn alloy is larger, indicating that AlSi9MnMoZr alloy has better corrosion resistance, which is consistent with the salt spray corrosion results.

[0426] Calculate the immersion corrosion rate based on the weight loss results of the samples before and after immersion corrosion. The analysis results can be referred to Figure 29When the immersion time changes from 10 d to 20 d and 30 d, the corrosion rates of the four alloy materials all increase to varying degrees. This is because, with the continuous occurrence of corrosion, the number of defect positions on the alloy surface increases, and the corrosive Cl- is more likely to adsorb on the defect positions, thus accelerating the corrosion. After immersion in 3.5 wt% NaCl aqueous solution for 10 d, the corrosion rates of A356.2, A380, AlSi10MgMn, and AlSi10MgMn alloys are 0.058 mm / y, 0.149 mm / y, 0.064 mm / y, and 0.048 mm / y respectively, indicating that the AlSi9MnMoZr alloy has the best corrosion resistance in the initial stage of corrosion. After immersion for 30 d, the corrosion rates of A356.2, A380, AlSi10MgMn, and AlSi10MgMn alloys are 0.094 mm / y, 0.232 mm / y, 0.141 mm / y, and 0.111 mm / y respectively, indicating that the A356.2 alloy has better corrosion resistance in the longer-term immersion corrosion test. The destruction of the passivation film and the aggravation of pitting corrosion behavior are the main reasons for the decrease in the corrosion resistance of the AlSi9MnMoZr alloy.

[0427] Therefore, it is also possible to construct a corrosion resistance-mechanical property analysis model using the parameters related to the degree of corrosion in the immersion corrosion test.

[0428] V. Application of the model construction method

[0429] (I) Test samples and test methods

[0430] Aluminum alloy samples (denoted as N1) are used, and the composition of the alloy materials can be referred to in Table 6.

[0431] Table 6. Nominal and actual compositions of aluminum alloy sample N1

[0432]

[0433] The element contents in Table 6 refer to the mass percentage content in the aluminum alloy material, with the unit of wt%.

[0434] Taking the Mn element as an example, the corresponding ingredient of the Mn element is denoted as "Mn ingredient".

[0435] The ingredient groups of each element are: AlSi 20 (Si ingredient), AlCu 50 (Cu ingredient), AlTi 5 (Ti ingredient), Zn (Zn ingredient), Mg (Mg ingredient), AlMn 10 (Mn ingredient), AlSr 10 (Sr ingredient) and Al. Taking 1 kilogram (kg) as an example, the burning loss rate of Zn is 12%, and the burning loss rate of Mg is 15%.

[0436] Introduced during the preparation process of Fe element, it is an inevitable impurity element rather than an actively added one.

[0437] The aluminum alloy material N1 is prepared by the following method:

[0438] (1) First, add pure aluminum ingots into a melting furnace and heat to 740 °C. After holding for melting, add Mn ingredients. After Mn melts, add Cu ingredients. When the temperature drops to 710 °C, add Si ingredients, ingredient Ti, Zn ingredients, and Sr ingredients for melting. After the above elements melt, add Mg ingredients. After the Mg ingredients melt, let it stand and skim the slag, add a refining agent, skim the slag again, add ingredient Ti and Sr ingredients, and finally obtain an ingot of a preset size through casting. Among them, the preset size is the size of the sample required for the experiment.

[0439] (2) Let the ingot stand and hold at 550 °C for 2 h, then water-cool to room temperature (20 °C - 30 °C), and the obtained aluminum alloy material is a die-cast aluminum alloy sample. This aluminum alloy material can be used as the main material or component material of a battery box, including but not limited to being used as the main material or component material of a lithium battery box, a fuel cell box, etc.

[0440] Elemental analysis is carried out using an inductively coupled plasma optical emission spectrometer (ICP instrument, Avio 5000) to accurately measure the actual composition of the aluminum alloy material. The ICP test results show that the actual composition of the aluminum alloy material is very close to its nominal composition, indicating good melting effect.

[0441] (II) Test method:

[0442] The test conditions of the salt spray corrosion test, tensile test, electrochemical corrosion test, and immersion test, as well as the setting of the sampling time points, are the same as those in the previous second, third, and fourth parts.

[0443] (III) Test analysis results

[0444] The empirical relationship model between the corrosion rate and the equivalent corrosion time (the first set of empirical relationships) is shown in formulas (5-1 to 5-3), and reference can be made to Table 7 and Figure 30 . It can be found that after piecewise fitting the corrosion rate using the function y = a·b x and the function y = a + b·x, the fitting results are basically consistent with the test results.

[0445] The fitting results of the relationship curve between the mechanical properties and the corrosion time can be referred to Figure 31 and the second set of empirical relationships of the mechanical parameters varying with the equivalent corrosion time in Table 8. The fitting results are basically consistent with the test results.

[0446] Table 7.

[0447] Fitting result (the first set of empirical relationships) Range of values for equivalent corrosion time (days) Formula number <![CDATA[y N1 = 0.105x -0.447 > x∈(0,15) (5-1) <![CDATA[y N1 = 0.002x + 0.019]]> x∈(15,22) (5-2) <![CDATA[y N1 = 0.016x - 0.307]]> x∈(22,25) (5-3)

[0448] Table 8.

[0449] Fitting result (the second set of empirical relationships) Formula number <![CDATA[YS N1 =-0.902x + 124.889]]> (5-4) <![CDATA[UTS N1 =-2.879x + 235.557]]> (5-5) <![CDATA[El N1 =-0.141x + 5.459]]> (5-6)

[0450] The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments. For their similarities, reference can be made to each other. For the sake of brevity, they will not be elaborated herein again.

[0451] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0452] It should be noted that this application is not limited to the above embodiments. The above embodiments are only examples. Embodiments with the same composition and the same effect in terms of technical idea within the technical solution scope of this application are all included in the technical scope of this application. The above-described embodiments only represent several embodiments of this application, and their descriptions are relatively detailed, but they should not be construed as a limitation on the patent scope. In addition, within the scope not departing from the gist of this application, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways constructed by combining some of the constituent elements in the embodiments are also included in the scope of this application.

Claims

1. A method for constructing a corrosion resistance-mechanical properties analysis model for metal materials. It is characterized in that The steps include: Taking the metal material as the test object, obtaining the test values ​​of the corrosion parameters at different equivalent corrosion time points under the corrosion test conditions to obtain the corrosion performance test experimental data set, and also obtaining the test values ​​of the mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain the mechanical performance test experimental data set; wherein the corrosion test conditions are used to simulate the target service environment of the metal material; the corrosion parameters include at least one of the corrosion degree and the corrosion rate; A first set of empirical relationships between the corrosion parameters and the equivalent corrosion time is established based on the corrosion performance test experimental data set, and a second set of empirical relationships between the mechanical parameters and the equivalent corrosion time is established based on the mechanical performance test experimental data set.

2. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 1, It is characterized in that The mechanical parameter includes at least one of tensile strength at break and elongation at break.

3. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 1 or 2, It is characterized in that The mechanical parameters include yield strength.

4. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 3, It is characterized in that Satisfy at least one of the following characteristics: The metal material is an aluminum alloy material; The metal material is a metal structural part, which can be an aluminum alloy structural part.

5. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to any one of claims 1 to 4, It is characterized in that Satisfy at least one of the following characteristics: The metal material is any one of the battery case materials; optionally, the battery case material includes a fuel cell case material; optionally, the battery case material includes a lithium battery case material; The metal material includes at least a portion of the structural components of a battery case; optionally, the battery case structural components include at least a portion of the structural components of a fuel cell case; optionally, the battery case structural components include at least a portion of the structural components of a lithium battery case.

6. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 5, It is characterized in that The corrosion performance test experimental data set at least includes a corrosion performance test experimental data set under salt spray corrosion test conditions; Optionally, the salt spray corrosion test conditions include at least one of the following salt spray conditions: one or more of NaCl aqueous solution salt spray conditions, acetate salt spray conditions, copper salt accelerated acetate salt spray conditions, and alternating salt spray corrosion conditions; Optionally, the salt spray corrosion test conditions include NaCl aqueous solution salt spray conditions; Optionally, the NaCl aqueous solution salt spray condition includes the following parameters: simulated salt spray conditions of 3wt% to 6wt% NaCl aqueous solution at 34 to 36°C.

7. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 6, It is characterized in that The first set of empirical relationships between the corrosion parameters and the equivalent corrosion time established based on the corrosion performance test experimental data set includes: For each of the corrosion parameters, segmented fitting is performed based on the corresponding corrosion performance test experimental data set. Each fitting interval takes the corresponding corrosion parameter as the dependent variable and the equivalent corrosion time as the independent variable. The fitting is performed in the form of a power function or a linear function to construct an empirical relationship between the corresponding type of corrosion parameter and the equivalent corrosion time in each fitting interval, and the first group of empirical relationships is obtained.

8. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 7, It is characterized in that In the first set of empirical equations, the power function fitting method is y1 = A·x B , the fitting method of the linear function is y1=a+b·x; wherein x is the equivalent corrosion time, y1 is the corrosion parameter, A is a positive number, B is a negative number, b is a positive number, and a is a real number; Optionally, a is a negative number.

9. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 8, It is characterized in that A is a real number selected from 0.01 to 1.00, B is a real number selected from -0.3 to -0.8, b is a real number selected from 0.001 to 0.05, and a is a real number selected from 0.02 to -0.8; Optionally, a is a real number selected from -0.001 to -0.8, and further optionally, a is a real number selected from -0.001 to -0.5; Optionally, b is a real number selected from 0.001 to 0.02, and further optionally, b is a real number selected from 0.001 to 0.

01.

10. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 9, It is characterized in that The corrosion performance test experimental data set includes at least one of a corrosion performance test experimental data set under electrochemical corrosion test conditions and a corrosion performance test experimental data set under immersion corrosion test conditions; Optionally, the corrosion parameters in the corrosion performance test experimental data set under the electrochemical corrosion test conditions include at least one of self-corrosion potential and self-corrosion current; Optionally, the corrosion parameters in the corrosion performance test experimental data set under the immersion corrosion test conditions include at least one of corrosion degree and corrosion rate.

11. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 10, It is characterized in that The second set of empirical relationships for establishing the mechanical parameters changing with the equivalent corrosion time based on the mechanical properties test experimental data set includes: For each of the mechanical parameters, segmented fitting is performed based on the corresponding mechanical properties test experimental data set. In each fitting interval, the corresponding mechanical parameter is used as the dependent variable and the equivalent corrosion time is used as the independent variable. The fitting is performed in the form of a power function or a linear function to construct an empirical relationship between the corresponding type of mechanical parameter and the equivalent corrosion time, thereby obtaining the second set of empirical relationships.

12. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 11, It is characterized in that In the second set of empirical equations, the power function fitting method is y2=M·x N The fitting method of the linear function is y2=m+n·x; wherein x is the equivalent corrosion time, y2 is the mechanical parameter, M is a positive number, N is a negative number, n is a negative number, and m is a positive number.

13. The method for constructing the corrosion resistance-mechanical properties analysis model of the metal material according to claim 12, It is characterized in that M is a real number selected from 1 to 250, N is a real number selected from -0.01 to -1, n is a real number selected from -0.05 to -5, and m is a real number selected from 1 to 300; Optionally, N is a real number selected from -0.01 to -0.5, and further optionally, N is a real number selected from -0.01 to -0.2; Optionally, n is a real number selected from -1 to -3; Optionally, n is a real number selected from -0.5 to -1.5; Optionally, n is a real number selected from -0.05 to -0.

5.

14. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 13, It is characterized in that The following steps are also included: establishing a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment.

15. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 14, It is characterized in that The method comprises the following steps: establishing a fourth set of empirical relationships between the corrosion rate and the equivalent corrosion time under the corrosion test conditions, wherein the first set of empirical relationships comprises the fourth set of empirical relationships.

16. A method for analyzing the service life of metal materials. It is characterized in that The metal material is as defined in any one of claims 1 to 3; The analysis method of the service life of the metal material comprises the following steps: Determining mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determining corrosion test conditions that can simulate the target service environment, and obtaining a test value of the corrosion degree of the metal material under the corrosion test conditions; According to the test value of the corrosion degree, the effective state threshold of the mechanical parameter and the corrosion resistance degree-mechanical property analysis model of the metal material, the service life parameter of the metal material under the corrosion test conditions is obtained; wherein the corrosion resistance degree-mechanical property analysis model of the metal material includes at least the following relationship: a first set of empirical relationship formulas including the variation of the corrosion parameters of the corrosion degree with the equivalent corrosion time and a second set of empirical relationship formulas including the variation of the mechanical parameters with the equivalent corrosion time.

17. The method for analyzing the service life of a metal material according to claim 16, It is characterized in that The service life parameter at least includes equivalent corrosion time.

18. The method for analyzing the service life of a metal material according to claim 16 or 17, It is characterized in that The obtaining of the service life parameter of the metal material under the corrosion test conditions according to the test value of the corrosion degree, the effective state threshold of the mechanical parameter and the corrosion resistance degree-mechanical property analysis model of the metal material comprises: The remaining service time of the metal material is obtained based on the test value of the corrosion degree, the effective state threshold of the mechanical parameter, the corrosion resistance-mechanical properties analysis model of the metal material, and a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment.

19. The method for analyzing the service life of a metal material according to any one of claims 16 to 18, It is characterized in that The mechanical parameters include at least two types, and the failure response degree of the metal material is ranked from high to low according to each mechanical parameter, and the corrosion resistance-mechanical performance analysis model of the metal material is obtained according to the most ranked mechanical parameter.

20. The method for analyzing the service life of a metal material according to any one of claims 16 to 19, It is characterized in that The corrosion resistance degree-mechanical property analysis model of the metal material is constructed according to the construction method of the corrosion resistance degree-mechanical property analysis model of the metal material according to any one of claims 1 to 15.

21. A device for analyzing the service life of metal materials, It is characterized in that The metal material is as defined in any one of claims 1 to 3; The service life analysis device of the metal material comprises: A corrosion performance data acquisition module, used to determine the mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine the corrosion test conditions that can simulate the target service environment, and obtain the test value of the corrosion degree of the metal material under the corrosion test conditions; A corrosion performance data processing module is used to obtain the service life parameters of the metal material under the corrosion test conditions according to the test value of the corrosion degree, the effective state threshold of the mechanical parameter and the corrosion resistance degree-mechanical performance analysis model of the metal material; wherein the corrosion resistance degree-mechanical performance analysis model of the metal material is defined in any one of claims 1 to 20.

22. A method for analyzing the mechanical properties of metal materials. It is characterized in that The metal material is as defined in any one of claims 1 to 3; The method for analyzing the mechanical properties of the metal material comprises the following steps: Determining mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determining corrosion test conditions that can simulate the target service environment, and obtaining a test value of the corrosion degree of the metal material under the corrosion test conditions; According to the test value of the corrosion degree, the target service time of the metal material, a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance degree-mechanical property analysis model of the metal material, a preliminary prediction value of the mechanical parameter of the metal material after the target service time under the corrosion test conditions is obtained; wherein the corrosion resistance degree-mechanical property analysis model of the metal material is defined in any one of claims 1 to 20; Compare the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter to obtain the predicted result of the mechanical parameter after the metal material is used for the target service time under the corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, output the preliminary predicted value as the effective predicted value of the mechanical parameter after the metal material is used for the target service time under the corrosion test conditions; if the preliminary predicted value of the mechanical parameter is less than the effective state threshold of the mechanical parameter, output the predicted result that the metal material fails before reaching the target service time.

23. An analytical device for the mechanical properties of metal materials, It is characterized in that The metal material is as defined in any one of claims 1 to 3; The analysis device for the mechanical properties of the metal material comprises: A test data acquisition module, used to determine the mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material and determine the corrosion test conditions that can simulate the target service environment, and obtain the test value of the corrosion degree of the metal material under the corrosion test conditions; A test data processing module, for obtaining a preliminary prediction value of the mechanical parameter of the metal material after the metal material has been used for the target service time under the corrosion test conditions according to the test value of the corrosion degree, the target service time of the metal material, a third set of empirical relationships between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment, and the corrosion resistance degree-mechanical property analysis model of the metal material; wherein the corrosion resistance degree-mechanical property analysis model of the metal material is defined in any one of claims 1 to 20; A mechanical property classification and identification module is used to compare the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter to obtain the predicted result of the mechanical parameter after the metal material is used for a target service time under the corrosion test conditions; wherein, if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, then the effective predicted value of the mechanical parameter after the metal material is used for a target service time under the corrosion test conditions is equal to the preliminary predicted value.

24. A computer device comprising a memory and a processor, wherein the memory stores a computer program, It is characterized in that When the processor executes the computer program, it implements the steps of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material as described in any one of claims 1 to 15, a method for analyzing the service life of a metal material as described in any one of claims 16 to 20, or a method for analyzing the mechanical properties of a metal material as described in claim 22.

25. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, it implements the steps of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material as described in any one of claims 1 to 15, a method for analyzing the service life of a metal material as described in any one of claims 16 to 20, or a method for analyzing the mechanical properties of a metal material as described in claim 22.

26. An electrical device, It is characterized in that include: A battery system comprising a battery case and a battery cell located inside the battery case, wherein the battery case comprises the metal material defined in any one of claims 1 to 3; and At least one of the service life analysis device of the metal material according to claim 21, the mechanical properties analysis device of the metal material according to claim 23, the computer device according to claim 24 and the computer readable storage medium according to claim 25.

27. The electrical device according to claim 26, It is characterized in that The battery cells include fuel cell cells.

28. The electrical device according to claim 26, It is characterized in that The battery cells include lithium battery cells.

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