Construction method for corrosion-resistance degree-mechanical property analysis model of metal material, and use thereof

Abstract

The present application relates to a construction method for a corrosion-resistance degree-mechanical property analysis model of a metal material, and the use thereof. The construction method for the analysis model comprises the following steps: using a metal material as a test object, and acquiring corrosion test experimental data sets at different equivalent corrosion time points under corrosion test conditions and mechanical property test experimental data sets at different corrosion degrees corresponding to the different equivalent corrosion time points; and respectively establishing an empirical relational expression of corrosion parameters changing with an equivalent corrosion time and an empirical relational expression of mechanical parameters changing with the equivalent corrosion time.

Description

Construction method and application of corrosion resistance-mechanical properties analysis model of metal materials

[0001] Related applications

[0002] This application claims priority to Chinese patent application number CN2023116080448, filed on November 27, 2023, entitled “Method and Application of Constructing Corrosion Resistance-Mechanical Properties Analysis Model of Metal Materials,” the entire text of which is hereby incorporated by reference. Technical Field

[0003] The present application relates to the fields of metal material corrosion resistance testing and analysis technology and battery technology, and further relates to a method for constructing and applying a corrosion resistance degree-mechanical property analysis model for metal materials, and further relates to a method for constructing a corrosion resistance degree-mechanical property analysis model for metal materials, an analysis method and analysis device for the service life of metal materials, an analysis method and analysis device for the mechanical properties of metal materials, computer equipment, computer-readable storage media, and electrical devices. Background Art

[0004] The statements herein merely provide background information related to the present application and do not necessarily constitute prior art.

[0005] The design and development of battery case materials place high demands on structural strength and corrosion resistance, which are crucial to the safe operation of batteries and even the entire electrical device. Taking fuel cell case materials as an example, current research on the corrosion behavior and mechanisms of fuel cell case materials often focuses solely on the electrochemical corrosion behavior of fuel cell case materials or the corrosion rate in different corrosive media, making it difficult to provide effective guidance for the design and development of fuel cell case materials.

[0006] Summary of the Invention

[0007] According to various embodiments and examples of the present application, the present application provides a method for constructing a corrosion resistance-mechanical properties analysis model for metal materials, a method and apparatus for analyzing the service life of metal materials, a method and apparatus for analyzing the mechanical properties of metal materials, a computer device, a computer-readable storage medium, and an electrical device. The corrosion resistance-mechanical properties analysis model for metal materials can be effectively used to predict the mechanical properties and assess 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 case materials.

[0008] In a first aspect, the present application provides a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material.

[0009] In some embodiments, the method for constructing the analysis model includes the following steps: using a metal material as the test object, obtaining experimental datasets of corrosion performance tests at different equivalent corrosion time points under corrosion test conditions, and experimental datasets of mechanical performance tests at different corrosion levels corresponding to the different equivalent corrosion time points; and establishing empirical relationships between corrosion parameters and mechanical parameters as a function of equivalent corrosion time. Furthermore, the corrosion test conditions can be used to simulate the target service environment.

[0010] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps:

[0011] Taking a 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 performance test experimental data set; wherein the corrosion test conditions are used to simulate the target service environment of the metal material; and the corrosion parameters include at least one of the corrosion degree and the corrosion rate;

[0012] 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.

[0013] Taking metal materials as test objects, corrosion test conditions are used to simulate the target service environment of metal materials, and corrosion performance test experimental data sets at different equivalent corrosion time points and mechanical performance test experimental data sets at different corrosion degrees corresponding to different equivalent corrosion time points are obtained. 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 for how at least one corrosion parameter, including the corrosion degree and corrosion rate, changes with the equivalent corrosion time and a second set of empirical relationships for how at least one mechanical parameter changes with the equivalent corrosion time are established, thereby constructing an analytical model between the corrosion resistance and mechanical properties of metal materials. This can help understand the corrosion mechanism of metal materials, and can be used to predict and analyze the mechanical properties of metal materials under target service conditions based on the corrosion behavior of metal materials, and to evaluate the service life of metal material structural parts under the target service environment.

[0014] Based on any appropriate embodiment of the present application, further, in some embodiments, the mechanical parameter includes at least one of tensile strength at break and elongation at break.

[0015] When the mechanical parameters in this method can include at least one of tensile fracture strength and fracture elongation, the corrosion resistance-mechanical properties analysis model of the metal material constructed can be applicable to metal material structures that are prone to failure due to tensile stress.

[0016] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameter includes yield strength.

[0017] By selecting appropriate parameters for fitting the functional relationship, it is beneficial to obtain a second set of empirical relationships with better fitting effect, which in turn is conducive to obtaining a more effective corrosion resistance-mechanical property analysis model.

[0018] Based on any suitable embodiment of the present application, further, in some embodiments, the construction method satisfies at least one of the following characteristics:

[0019] The metal material is an aluminum alloy material;

[0020] The metal material is a metal structural part, which can be an aluminum alloy structural part.

[0021] Based on any suitable embodiment of the present application, further, in some embodiments, the construction method satisfies at least one of the following characteristics:

[0022] 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;

[0023] 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.

[0024] The metal material can be an aluminum alloy material or a metal structural part, and further can be an aluminum alloy structural part. Due to the advantages of low density, high specific strength, excellent thermal stability, good machinability, low cost, etc., die-cast aluminum alloy can be used to prepare various parts of automobiles, including cylinder blocks, generator housings, fuel cell housings, various engine brackets, etc., but not limited to these. Among them, aluminum alloy materials can be applied to the field of battery technology and can be used as the main material (including constituent materials) of battery boxes or aluminum alloy structural parts in battery boxes. Therefore, the metal material can be a battery box material, and the battery box can include but is not limited to fuel cell boxes, and can also include but is not limited to lithium battery boxes; accordingly, the metal material can include at least a portion of the structural parts of the battery box. When corrosion parameters and mechanical parameters are obtained based on aluminum alloy materials, the corrosion resistance-mechanical properties analysis model of the metal material constructed can be applied to the mechanical property prediction and life assessment of aluminum alloy materials. At this time, it is also helpful to understand the white rust corrosion mechanism of aluminum alloy materials. When aluminum alloy materials are used as the main material or component material of battery boxes or structural parts in battery boxes, the corrosion resistance-mechanical properties analysis model of metal materials can be applied to the mechanical properties prediction and life assessment of battery boxes or structural parts in battery boxes.

[0025] Taking the fuel cell case as an example, this study can also help understand the white rust corrosion mechanism of fuel cell case materials. When testing fuel cell case materials, it is possible to analyze their corrosion behavior, determine the corrosion rates of different fuel cell case materials, and establish a relationship between the degree of corrosion and mechanical properties of fuel cell case materials. This has certain reference significance for the safe operation of fuel cells and even electrical devices that include fuel cells.

[0026] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion performance test experimental data set at least includes a corrosion performance test experimental data set under salt spray corrosion test conditions;

[0027] Optionally, the salt spray corrosion test conditions include at least one of the following salt spray conditions: one or more of a NaCl aqueous solution salt spray condition, an acetate salt spray condition, a copper salt accelerated acetate salt spray condition, and an alternating salt spray corrosion condition;

[0028] Further optionally, the salt spray corrosion test conditions include NaCl aqueous solution salt spray conditions.

[0029] Based on any suitable embodiment of the present application, further, in some embodiments, 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.

[0030] 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 performance analysis model of the metal material constructed can be applied to metal materials and their structural parts or products in service environments in the fields of road transportation, computer, electronic communication, and electrical appliances, and can also be applied to structural parts or products in related service environments such as electroplating, coating, packaging, and transportation equipment. Among them, the road transportation field may involve but is not limited to road vehicle electronic and electrical equipment, rail transportation 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, mainframes, computer components, medical equipment and other precision instruments and other 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; the electrical appliances may involve but is not limited to various types of household electrical appliances such as household appliances, lamps, transformers, instruments and meters, medical equipment and other equipment, products or their metal structural parts.

[0031] Without limitation, a model based on a corrosion performance test dataset obtained under NaCl aqueous solution salt spray conditions can be applied to determine the quality and uniformity of protective coatings and to compare differences in the salt spray corrosion resistance of samples with similar structures, but is not limited thereto. Without limitation, a model based on an acetate salt spray condition can be applied to coastal cities in the south and to harsh salt spray environments. Without limitation, a model based on a copper salt-accelerated acetate salt spray condition can be applied to harsh salt spray environments. Without limitation, a model based on an alternating salt spray corrosion condition can be applied to high temperature and high humidity environments.

[0032] For NaCl aqueous solution salt spray conditions, the aforementioned test conditions are helpful in determining the corrosion resistance of battery boxes, automotive parts, etc.

[0033] Based on any suitable embodiment of the present application, further, in some embodiments, 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:

[0034] For each of the corrosion parameters, segmented fitting is performed based on the corresponding corrosion performance test experimental data set. In 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 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, thereby obtaining the first set of empirical relationships.

[0035] 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. The fitting method for each segment can use a power function or a linear function. In this case, the fitting curve has a higher degree of consistency with the experimental test data set, and the model is more effective, but it is not limited to the aforementioned function types.

[0036] Based on any suitable embodiment of the present application, further, in some embodiments, in the first set of empirical relationships, the fitting method of the power function 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;

[0037] Optionally, a is a negative number.

[0038] 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;

[0039] Optionally, a is a real number selected from -0.001 to -0.8, further optionally, a is a real number selected from -0.001 to -0.5;

[0040] 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.

[0041] By selecting the appropriate fitting function type, it is beneficial to obtain the first set of empirical relationships with better fitting effect, and then obtain a more effective corrosion resistance-mechanical properties analysis model.

[0042] Based on any appropriate embodiment of the present application, further, in some embodiments, 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;

[0043] 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;

[0044] 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.

[0045] When the corrosion performance test dataset includes a dataset of corrosion performance test experiments conducted under electrochemical corrosion test conditions, the metal material corrosion resistance-mechanical property analysis model can be applied to the performance prediction and lifespan assessment of metal materials under electrochemical conditions. For example, but not limited to, the performance prediction and lifespan assessment of battery housings, and further applications include, but are not limited to, the performance prediction and lifespan assessment of fuel cell housings.

[0046] When the corrosion performance test experimental data set includes a corrosion performance test experimental data set 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 evaluation of the metal material in an environment contacting corrosive liquids.

[0047] 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-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of battery boxes with built-in electrolytes. Furthermore, it can include but is not limited to the performance prediction and life assessment of fuel cell boxes.

[0048] Based on any suitable embodiment of the present application, further, in some embodiments, the second set of empirical relationships for the mechanical parameters changing with the equivalent corrosion time established based on the mechanical properties test experimental data set includes:

[0049] For each of the mechanical parameters, segmented fitting is performed based on the corresponding mechanical performance 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.

[0050] The establishment of the second set of empirical relationships between the mechanical parameters and the equivalent corrosion time can be obtained by piecewise fitting for each mechanical parameter. The fitting method for each segment can use a power function or a linear function. In this case, the fitting curve has a higher degree of consistency with the experimental test data set, and the model is more effective, but it is not limited to the aforementioned function types.

[0051] Based on any suitable embodiment of the present application, further, in some embodiments, in the second set of empirical equations, the fitting method of the power function is y=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.

[0052] 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 -0.1 to -5, and m is a real number selected from 1 to 300;

[0053] Optionally, N is a real number selected from -0.01 to -0.5, further optionally, N is a real number selected from -0.01 to -0.2;

[0054] 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.

[0055] Based on any suitable embodiment of the present application, further, in some embodiments, the method for constructing the corrosion resistance-mechanical properties analysis model of the metal material also 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.

[0056] By establishing an empirical relationship between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment (which can be recorded as the third set of empirical relationships), the equivalent corrosion time can be converted into the service time under the target service environment, thereby more directly predicting the service life of metal materials and their structural parts or products.

[0057] Based on any suitable embodiment of the present application, further, in some embodiments, the method for constructing the corrosion resistance-mechanical properties analysis model of the 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, and the first set of empirical relationships includes the fourth set of empirical relationships.

[0058] By establishing an empirical relationship between the corrosion rate and the equivalent corrosion time under corrosion test conditions (which can be recorded as the fourth set of empirical relationships), the relationship between the corrosion behavior and mechanical properties of metal materials under the target service environment can be dynamically analyzed.

[0059] In a second aspect of the present application, a method for analyzing the service life of a metal material is provided, wherein the metal material is as defined in the first aspect of the present application.

[0060] In some embodiments, the method for analyzing the service life of the metal material comprises the following steps:

[0061] 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;

[0062] 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 formulas: a first set of empirical relationship formulas including the change of corrosion parameters of the corrosion degree with the equivalent corrosion time and a second set of empirical relationship formulas including the change of mechanical parameters with the equivalent corrosion time.

[0063] This method for analyzing the service life of a metal material selects mechanical parameters related to the failure behavior of the metal material based on the target service environment of the metal material, selects corrosion test conditions that can simulate the target service environment, and then obtains a test value of the corrosion degree of the metal material under the selected corrosion test conditions. Thus, the service life parameters of the metal material under the selected corrosion test conditions can be obtained based on the test value of the corrosion degree, the effective state threshold of the selected mechanical parameter, and a corrosion resistance-mechanical property analysis model for the metal material. The corrosion resistance-mechanical property analysis model for the metal material is based on the equivalent corrosion time and the mechanical properties at different corrosion degrees, and includes at least the following two relationship equations: a first set of empirical relationship equations for the variation of at least one of the corrosion parameters, namely, the corrosion degree and the corrosion rate, with the equivalent corrosion time, and a second set of empirical relationship equations for the variation of the aforementioned mechanical parameters with the equivalent corrosion time. This analysis method can be used effectively and accurately to analyze the service life of a metal material under the target service environment.

[0064] Based on any suitable embodiment of the present application, further, in some embodiments, the service life parameter at least includes equivalent corrosion time.

[0065] According to the above 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.

[0066] Based on any suitable embodiment of the present application, further, in some embodiments, obtaining 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-mechanical property analysis model of the metal material includes:

[0067] 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 relationship formulas between the equivalent corrosion time under the corrosion test conditions and the service time under the target service environment.

[0068] The remaining service time of the metal material can be obtained based on 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 properties analysis model of the metal material, and the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment, thereby realizing the predictive analysis of the remaining service life of the metal material.

[0069] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameters include at least two, and the failure response degree of the metal material is sorted in descending order according to each mechanical parameter, and the corrosion resistance-mechanical performance analysis model of the metal material is obtained according to the mechanical parameter with the highest sorting.

[0070] The failure response degree of the metal materials is ranked in descending order according to the mechanical parameters, and the corrosion resistance-mechanical performance analysis model of the metal material is obtained according to the mechanical parameter with the highest ranking, which can more effectively reflect the relationship between the corrosion behavior of the metal material and the mechanical performance failure under the target service environment.

[0071] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion resistance-mechanical properties analysis model of the metal material is constructed according to the construction method of the corrosion resistance-mechanical properties analysis model of the metal material described in the first aspect of the present application.

[0072] The corrosion resistance-mechanical properties analysis model involved in the aforementioned analysis method of the service life of metal materials can be constructed using the construction method in the first aspect of this application, and a relationship between the corrosion degree of metal materials and the mechanical properties including at least one mechanical parameter including tensile fracture strength and fracture elongation can be constructed.

[0073] In a third aspect of the present application, a service life analysis device for a metal material is provided, wherein the metal material is as defined in the first aspect of the present application.

[0074] In some embodiments, the service life analysis device for metal materials includes:

[0075] 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, determine corrosion test conditions capable of simulating the target service environment, and obtain a test value of the corrosion degree of the metal material under the corrosion test conditions;

[0076] A corrosion performance data processing module is used to obtain the service life parameters of the metal material under the corrosion test conditions based on 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 as defined in the first aspect or the second aspect of this application.

[0077] The service life analysis device for metal materials provided in the third aspect of the present application can be used to implement the service life analysis method for metal materials described in the second aspect of the present application.

[0078] In a fourth aspect of the present application, a method for analyzing the mechanical properties of a metal material is provided, wherein the metal material is as defined in the first aspect of the present application.

[0079] In some embodiments, the mechanical properties of the metal material include the following steps:

[0080] 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;

[0081] According to the test value of the corrosion degree, the target service life of the metal material, a third set of empirical relationship formulas 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, a preliminary predicted value of the mechanical parameter of the metal material after the metal material is used for the target service time under the corrosion test conditions is obtained; wherein the corrosion resistance-mechanical property analysis model of the metal material is as defined in the first aspect or the second aspect of the present application;

[0082] Compare the preliminary predicted value of the mechanical parameter with the effective state threshold of the mechanical parameter to obtain a 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 a predicted result that the metal material will fail before reaching the target service time.

[0083] The aforementioned method for analyzing the mechanical properties of a 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, thereby obtaining a test value of the corrosion degree of the metal material under the selected corrosion test conditions. Based on the test value of the corrosion degree, the target service life of the metal material, the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service life under the target service environment, and the corrosion resistance-mechanical properties analysis model of the metal material, a preliminary prediction of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions can be obtained. By comparing the preliminary prediction of the mechanical parameters with the effective state threshold of the mechanical parameters, a prediction result of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions can be obtained. If the preliminary prediction of the mechanical parameters is greater than or equal to the effective state threshold of the mechanical parameters, the effective prediction of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions is equal to the preliminary prediction; if the preliminary prediction of the mechanical parameters is less than the effective state threshold of the mechanical parameters, it means that the metal material has failed before reaching the target service life.

[0084] In a fifth aspect of the present application, a mechanical property analysis device for a metal material is provided, wherein the metal material is as defined in the first aspect of the present application.

[0085] In some embodiments, the mechanical properties analysis device of the metal material comprises:

[0086] a test 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, determine corrosion test conditions capable of simulating the target service environment, and obtain a test value of the corrosion degree of the metal material under the corrosion test conditions;

[0087] a test data processing module, configured to obtain preliminary predicted values ​​of the mechanical parameters of the metal material after the metal material has been used for the target service time under the corrosion test conditions based on 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 a corrosion resistance-mechanical property analysis model of the metal material; wherein the corrosion resistance-mechanical property analysis model of the metal material is as defined in the first aspect or the second aspect of the present application;

[0088] 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 a predicted result of the mechanical parameter of the metal material after 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, then the effective predicted value of the mechanical parameter of the metal material after the target service time under the corrosion test conditions is equal to the preliminary predicted value.

[0089] The mechanical properties analysis device for metal materials provided in the fifth aspect of the present application can be used to implement the mechanical properties analysis method for metal materials described in the fourth aspect of the present application.

[0090] In the sixth aspect of the present application, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for constructing a corrosion resistance-mechanical properties analysis model of the metal material described in the first aspect of the present application, 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.

[0091] In the seventh aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the method for constructing the corrosion resistance-mechanical properties analysis model of the metal material described in the first aspect of the present application, 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.

[0092] In another aspect of the present application, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the method for constructing a corrosion resistance-mechanical properties analysis model of the metal material described in the first aspect of the present application, 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.

[0093] In an eighth aspect of the present application, there is provided an electrical device, comprising:

[0094] A battery system comprising a battery case and a battery cell located inside the battery case, wherein the battery case comprises the metal material described in the first aspect of the present application; and

[0095] At least one of the service life analysis device for metal materials described in the third aspect of this application, the mechanical properties analysis device for metal materials described in the fifth aspect of this application, the computer equipment described in the sixth aspect of this application, and the computer-readable storage medium described in the seventh aspect of this application.

[0096] In some embodiments, the battery cells comprise fuel cell cells.

[0097] In some embodiments, the battery cells include lithium battery cells.

[0098] At least one of the aforementioned metal material service life analysis device, the aforementioned metal material mechanical property analysis device, computer equipment, computer-readable storage medium and computer program product can be set on the electrical setting to implement the aforementioned analysis model construction method, the aforementioned metal material service life analysis method or the aforementioned metal material mechanical property analysis method, which is conducive to achieving better management and maintenance of electrical devices, not only conducive to achieving safe maintenance of battery boxes in electrical devices, but also conducive to assisting in the design of battery boxes with longer service life.

[0099] The details of one or more embodiments and examples 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 description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] In order to better describe and illustrate the embodiments, examples or examples provided in this application, reference may be made to one or more drawings. The additional details or examples used to describe the drawings should not be considered as limiting the scope of the disclosed application, the currently described embodiments, examples or examples, and any of the currently understood best modes of these applications. Moreover, the same figure numbers are used to represent the same components in all the drawings. It should also be noted that the drawings are drawn in a simplified form and are only used to assist in the explanation of this application for convenience and clarity. The various dimensions of each component shown in the drawings are arbitrarily shown and may be accurate or not drawn to scale. For example, in order to make the illustration clearer, the dimensions of the components are appropriately exaggerated in some places in the drawings. Unless otherwise specified, the components in the drawings are not drawn to scale. This application does not limit every dimension of every component.

[0101] In the attached figure:

[0102] FIG1 is a flowchart of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to one embodiment of the present application.

[0103] FIG2 is a flowchart of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to an embodiment of the present application.

[0104] FIG3 is a flowchart of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to an embodiment of the present application.

[0105] FIG4 is a flowchart of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to an embodiment of the present application.

[0106] FIG5 is a flowchart of a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to an embodiment of the present application.

[0107] FIG6 is a flowchart of a method for analyzing the service life of a metal material according to an embodiment of the present application.

[0108] FIG7 is a schematic diagram of a service life analysis device for metal materials according to an embodiment of the present application.

[0109] FIG8 is a flowchart of a method for analyzing the mechanical properties of a metal material according to an embodiment of the present application.

[0110] FIG9 is a flowchart of a method for analyzing the mechanical properties of a metal material according to an embodiment of the present application.

[0111] FIG10 is a schematic diagram of a mechanical property analysis device for metal materials according to an embodiment of the present application.

[0112] FIG11 is a diagram showing the internal structure of a computer device according to an embodiment of the present application.

[0113] FIG12 is a schematic diagram of an electrical device in one embodiment of the present application.

[0114] Figure 13 shows the salt spray test results in some embodiments of the present application, and the macromorphology 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; each aluminum alloy material is sampled 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).

[0115] Figure 14 shows the salt spray test results in some embodiments of the present application, and the 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 (squares, ■), A380 (dots, ●), AlSi10MgMn (upper triangle, ▲) and AlSi9MnMoZr (lower triangle, ▼).

[0116] FIG15 is a fitting result diagram between the corrosion rate and the equivalent corrosion time of the A356.2 aluminum alloy subjected to a salt spray corrosion test in one embodiment of the present application.

[0117] FIG16 is a fitting result diagram between the corrosion rate and the equivalent corrosion time of the A380 aluminum alloy subjected to a salt spray corrosion test in one embodiment of the present application.

[0118] FIG17 is a fitting result diagram between the corrosion rate and the equivalent corrosion time of the AlSi10MgMn aluminum alloy in a salt spray corrosion test in one embodiment of the present application.

[0119] FIG18 is a fitting result diagram between the corrosion rate and the equivalent corrosion time of the AlSi9MnMoZr aluminum alloy in a salt spray corrosion test in one embodiment of the present application.

[0120] Figure 19 shows the experimental results and fitting results of the mechanical parameters and equivalent corrosion time of A356.2 aluminum alloy material subjected to salt spray corrosion test at different equivalent corrosion time points in some embodiments of the present application; wherein, the mechanical parameters involve tensile strength (which can be abbreviated as UTS), elongation at break (which can be abbreviated as El) and yield strength (which can be abbreviated as YS); wherein fit corresponds to the fitting curve.

[0121] FIG20 shows the experimental results and fitting results of mechanical parameters and equivalent corrosion time of A380 aluminum alloy material subjected to salt spray corrosion test at different equivalent corrosion time points in some embodiments of the present application.

[0122] Figure 21 shows the experimental results and fitting results of mechanical parameters and equivalent corrosion time of AlSi10MgMn aluminum alloy material subjected to salt spray corrosion test at different equivalent corrosion time points in some embodiments of the present application.

[0123] FIG22 shows the experimental results and fitting results of mechanical parameters and equivalent corrosion time of AlSi9MnMoZr aluminum alloy material subjected to salt spray corrosion test at different equivalent corrosion time points in some embodiments of the present application.

[0124] FIG23 is a schematic diagram of sample dimensions for a tensile test in one embodiment of the present application, in millimeters (mm), where R2.5 indicates a radius of 2.5 mm.

[0125] Figure 24 is a structural schematic diagram of the three-electrode system in the electrochemical corrosion testing equipment used in one embodiment of the present application, wherein R, mA and V represent a resistance meter, an ammeter and a voltammeter, 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 measurement data of the corrosion parameters.

[0126] Figure 25 shows the change curve of open circuit voltage (OCP, chemical formula, unit V) of four aluminum alloy materials over time, using 3.5wt% NaCl aqueous solution. The four aluminum alloy materials are A356.2 (squares, ■), A380 (dots, ●), AlSi10MgMn (upper triangle, ▲) and AlSi9MnMoZr (lower triangle, ▼).

[0127] Figure 26 shows the electrochemical corrosion test and analysis results in some embodiments of the present application, wherein (a) is the EIS Bode (AC impedance spectrum Bode plot); (b) is the Phase diagram (phase diagram), the horizontal axis corresponds to the frequency (unit is Hz (Hertz)), and the vertical axis corresponds to the phase angle (unit is ° (degree)); (c) is the Nyquist diagram; and (d) is the equivalent circuit diagram.

[0128] FIG27 is a potentiodynamic polarization curve of an electrochemical corrosion test in some embodiments of the present application, wherein the horizontal axis is the chemical formula (unit is V) and the vertical axis is the current density (unit is A / cm 2 ).

[0129] Figure 28 is a macroscopic morphology of the sample surface at different immersion corrosion times in the immersion corrosion test of some embodiments of the present application. From left to right, there are four aluminum alloy materials, (a) A356.2; (b) A380; (c) AlSi10MgMn; (d) AlSi9MnMoZr; from top to bottom, they correspond to the initial morphology when not corroded (0d, scale is 50mm), the macroscopic morphology at 10 days (10d), 20 days (20d) and 30 days (30d), respectively.

[0130] Figure 29 is a summary of the corrosion rates of four die-cast aluminum alloy materials at different immersion corrosion times in the immersion corrosion test of the embodiment shown in Figure 28 of the present application, wherein the four aluminum alloy materials are A356.2, A380, AlSi10MgMn and AlSi9MnMoZr.

[0131] Figure 30 is a relationship diagram of the corrosion rate versus corrosion time in the salt spray corrosion test of different aluminum alloy materials N1 and A380 in one embodiment of the present application. The corrosion rates I, II and III at different corrosion times represent the initial, middle and late corrosion stages, respectively.

[0132] Figure 31 is a relationship diagram of the change of mechanical parameters with corrosion time in the tensile test of aluminum alloy material N1 in one embodiment of the present application, including: (a) tensile stress-strain curve, corresponding to the initial state and the tensile stress-strain curves after 5 days (5d), 15 days (15d) and 25 days (25d) of corrosion; (b) fitting results of mechanical properties, including the results of tensile strength, elongation at break and yield strength and their fitting lines.

[0133] Description of reference numerals:

[0134] 310 is a corrosion performance data acquisition module, 320 is a corrosion performance data processing module; 510 is a test data acquisition module, 520 is a test data processing module, 530 is a mechanical performance classification and identification module; 6 is an electrical device; 131 is an auxiliary electrode, 132 is a working electrode, and 133 is a reference electrode. DETAILED DESCRIPTION

[0135] Below, some embodiments and examples of the method for constructing the corrosion resistance-mechanical properties analysis model of the metal material of the present application and its application are described in detail with appropriate reference to the accompanying drawings. However, there may be cases where unnecessary detailed descriptions are omitted. For example, there are cases where detailed descriptions of well-known matters and repeated descriptions of actually the same structures are omitted. This is to avoid the following description from becoming unnecessarily lengthy and to facilitate the understanding of those skilled in the art. In addition, the drawings and the following description are provided for those skilled in the art to fully understand the present application and are not intended to limit the subject matter described in the claims.

[0136] " scope " disclosed in the present application can be limited in the form of lower limit and upper limit, and given range is limited by selecting a lower limit and an upper limit, and the selected lower limit and upper limit define the boundary of special range. The scope limited in this way can be to include end value or not include end value, and any end value can be included or not included independently, and can be arbitrarily combined, that is, any lower limit can form a scope with any upper limit combination. For example, if the scope of 60-120 and 80-110 is listed for specific parameters, it is understood that the scope of 60-110 and 80-120 is also expected. In addition, if minimum range values ​​1 and 2 are listed, and if maximum range values ​​3,4 and 5 are also listed, then the following scope can all be expected: 1-3, 1-4, 1-5, 2-3, 2-4 and 2-5. In the present application, unless otherwise specified, numerical range " ab " represents the abbreviation of any real number combination between a and b, wherein a and b are all real numbers. For example, a numerical range of "0-5" indicates that all real numbers between "0-5" are listed herein, and "0-5" is merely an abbreviation for a combination of these values. Furthermore, when a parameter is expressed as an integer ≥ 2, this is equivalent to disclosing that the parameter is, for example, an integer of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, etc. For example, when a parameter is expressed as an integer selected from "2-10", this is equivalent to listing the integers 2, 3, 4, 5, 6, 7, 8, 9, and 10.

[0137] In this application, references to "plurality," "multiple," and "multiple items," unless otherwise specified, refer to a quantity greater than or equal to two. For example, "one or more" refers to one or greater than or equal to two. It is understood that references to "any number" of items refer to any suitable combination of multiple items, i.e., any combination of "any number" of items that is consistent with the present application and that allows for the implementation of the present application.

[0138] Unless otherwise specified, all embodiments and optional embodiments of the present application can be combined with each other to form a new technical solution.

[0139] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment or implementation of the present application. The appearance of such phrases in various locations in the specification does not necessarily refer to the same embodiment, nor does it necessarily refer to independent or alternative embodiments that are mutually exclusive with other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments. References to "implementations" herein have a similar understanding.

[0140] Those skilled in the art will appreciate that, in the methods of each embodiment or embodiment, the order in which each step is written does not mean a strict order of execution and constitutes any limitation to the implementation process, and the detailed order of execution of each step should be determined by its function and possible internal logic. Unless otherwise specified, all steps of the present application can be performed in sequence, or can be performed randomly, or can preferably be performed in sequence. For example, method M includes steps (a) and (b), indicating that method M may include steps (a) and (b) performed in sequence, or steps (b) and (a) performed in sequence. For another example, method M may also include step (c), indicating that step (c) can be added to method M in any order, for example, method M may include steps (a), (b) and (c), or steps (a), (c) and (b), or steps (c), (a) and (b), etc.

[0141] In this application, in open technical features or technical solutions described with words such as "contain," "include," and "include," unless otherwise specified, additional members other than the listed members are not excluded, and it can be regarded as providing both closed features or solutions consisting of the listed members and open features or solutions including additional members in addition to the listed members. For example, A includes a1, a2, and a3. Unless otherwise specified, it may also include other members or not. It can be regarded as providing both the feature or solution of "A consists of a1, a2, and a3" or "A is selected from a1, a2, and a3", and the feature or solution of "A includes not only a1, a2, and a3, but also other members."

[0142] In this application, unless otherwise specified, 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.

[0143] In this application, "optionally," "optional," and "optional" mean optional, that is, they refer to either option selected from the two parallel options of "yes" or "no." If multiple "options" appear in a technical solution, unless otherwise specified and there are no contradictions or mutual constraints, each "optional" is independent. Unless otherwise specified, the descriptions "optionally include," "optionally include," etc. in this application, using "optionally include" as an example, mean "may include or not include."

[0144] In this application, unless otherwise specified, the features or solutions corresponding to "and / or" include any one of two or more relevant listed items, and also include any and all combinations of the relevant listed items. "Any and all combinations" include any combination of any two relevant listed items, any more relevant listed items, or all relevant listed items. For example, "A and / or B" means the group consisting 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 A and B", and can also mean "including A, including B, or including A and B", which can be appropriately understood according to the sentence in which it is used.

[0145] As used herein, "combination thereof", "any combination thereof", "any combination thereof" and the like include all suitable combinations of any two or more of the listed items.

[0146] Herein, the “suitable” involved in “suitable combination”, “suitable method”, “any suitable method”, etc. shall be based on the technical solution that can implement this application.

[0147] Herein, the terms "preferred," "better," "more preferable," "suitable," and "good" are used solely to describe preferred implementations or examples and should not be construed as limiting the scope of protection of this application. If multiple "preferred" terms appear in a technical solution, each "preferred" term is considered independent unless otherwise specified and there are no contradictions or mutual constraints.

[0148] In this application, "further", "further", "particularly", "for example", "such as", "example", "for example", etc. are used for descriptive purposes to indicate differences in content, but should not be understood as limiting the scope of protection of this application.

[0149] In this application, the terms "first," "second," "third," "fourth," etc. in "the first aspect," "the second aspect," "the third aspect," "the fourth aspect," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or quantity, nor should they be understood as implicitly indicating the importance or quantity of the indicated technical features. Furthermore, "first," "second," "third," "fourth," etc. serve only as non-exhaustive enumeration and description, and should be understood not to constitute a closed-ended limitation on quantity.

[0150] In this application, the term "room temperature" generally refers to 4°C to 35°C, and may refer to 20°C ± 5°C. In some embodiments of this application, room temperature refers to 20°C to 30°C.

[0151] In this application, when referring to a data range, if the unit is followed only by the right endpoint, it means that the units of the left and right endpoints are the same. For example, "3~5h" or "3-5h" both mean that the units of the left endpoint "3" and the right endpoint "5" are both hours, and both have the same meaning as "3h~5h". Similarly, descriptions involving other parameters such as temperature and size are to be understood in the same manner.

[0152] The weight of the relevant components mentioned in the embodiments or examples of the present application can not only refer to the content of each component, but also represent the proportional relationship of the weights between the components. Therefore, as long as the content of the relevant components in the embodiments or examples of the present application is proportionally enlarged or reduced, it is within the scope described in the present application. Further, the weight involved in the embodiments or examples of the present application can be mass units known in the chemical industry such as μg, mg, g, and kg. Unless otherwise specified, 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 of the two is numerically equal to the corresponding weight ratio W1 / W2.

[0153] In this application, unless otherwise specified, wt% represents weight percentage by weight, which is numerically equal to the corresponding mass percentage by mass.

[0154] In this application, "greater than or equal to" and "greater 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, unless otherwise specified, "greater than or equal to" and "≥" can be regarded as providing two solutions of "greater than" and "equal to". In this application, unless otherwise specified, "less than or equal to" and "≤" can be regarded as providing two solutions of "less than" and "equal to".

[0155] In this application, exemplary descriptions such as "in some embodiments (or examples)" and "in one embodiment (or example)" may include 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.

[0156] Current research on the corrosion behavior and mechanism of fuel cell case materials often focuses solely on the electrochemical corrosion behavior of fuel cell case materials or the corrosion rate in different corrosive media, making it difficult to provide effective guidance for the design and development of fuel cell case materials. The lack of systematic and in-depth research on the corrosion behavior of fuel cell case materials is becoming increasingly apparent. For example, the white rust corrosion mechanism of fuel cell case materials is still unclear, the impact of metal materials (such as alloys) on the corrosion behavior of fuel cell case materials needs to be clarified, and there is no corresponding correlation research on the relationship between fuel cell case materials and their mechanical properties and service life.

[0157] According to various implementations and examples of the present application, the present application provides a method for constructing a corrosion resistance-mechanical properties analysis model for metal materials and its application. The application relates to an electrical device including a battery system.

[0158] According to various embodiments and examples of the present application, the present application provides a method for constructing a corrosion resistance-mechanical properties analysis model for metal materials, an analysis method and analysis device for the service life of metal materials, an analysis method and analysis device for the mechanical properties of metal materials, a computer device, a computer-readable storage medium, and an electrical device. The corrosion resistance-mechanical properties analysis model for metal materials can be effectively used for mechanical property prediction and service life assessment 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 case materials (such as fuel cell case materials).

[0159] In a first aspect of the present application, a method for constructing a corrosion resistance-mechanical properties analysis model for a metal material is provided. This construction method can be used to construct an analytical model between the corrosion resistance and mechanical properties of the metal material under corrosion test conditions simulating a target service environment, and can be used to predict the mechanical properties of the metal material. When the mechanical properties are mechanical properties related to the failure behavior of the metal material, this construction method can obtain an analytical model between the corrosion resistance and failure-related mechanical properties of the metal material under corrosion test conditions simulating the target service environment, and can be used for predictive analysis of the mechanical properties and service life assessment of the metal material.

[0160] In some embodiments, the present application provides a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material.

[0161] In some embodiments, the method for constructing the analysis model includes the following steps: using a metal material as the test object, obtaining experimental datasets of corrosion performance tests at different equivalent corrosion time points under corrosion test conditions, and experimental datasets of mechanical performance tests at different corrosion levels corresponding to the different equivalent corrosion time points; and establishing empirical relationships between corrosion parameters and mechanical parameters as a function of equivalent corrosion time. Furthermore, the corrosion test conditions can be used to simulate the target service environment.

[0162] Based on the experimental data set of corrosion performance test, the first set of empirical relationships between corrosion parameters and equivalent corrosion time can be established.

[0163] Based on the mechanical properties test experimental data set, a second set of empirical relationships between mechanical parameters and equivalent corrosion time can be established.

[0164] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps:

[0165] Using metal materials as test objects, we obtain experimental datasets of corrosion performance tests at different equivalent corrosion time points under corrosion test conditions, as well as experimental datasets of mechanical performance tests at different corrosion degrees corresponding to different equivalent corrosion time points. The corrosion test conditions are used to simulate the target service environment.

[0166] A first set of empirical relationships between corrosion parameters and equivalent corrosion time is established based on the corrosion performance test experimental data set, and a second set of empirical relationships between mechanical parameters and equivalent corrosion time is established based on the mechanical performance test experimental data set.

[0167] The analysis model can be effectively used for predicting the mechanical properties and evaluating the service life of metal materials, which may include aluminum alloy materials and further include battery box materials.

[0168] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps (see FIG1 ):

[0169] S110: Taking a 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 further obtaining test values ​​of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein the corrosion test conditions are used to simulate a target service environment of the metal material; and the corrosion parameters include at least one of a corrosion degree and a corrosion rate;

[0170] S120: establishing a first set of empirical relationships between corrosion parameters and equivalent corrosion time based on the corrosion performance test experimental data set, and establishing a second set of empirical relationships between mechanical parameters and equivalent corrosion time based on the mechanical performance test experimental data set.

[0171] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps (see FIG2 ):

[0172] S110: Taking a 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 further obtaining test values ​​of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein the corrosion test conditions are used to simulate a target service environment of the metal material; the corrosion parameters include at least one of corrosion degree and corrosion rate; and the mechanical parameters include at least one of tensile fracture strength and elongation at fracture;

[0173] S120: establishing a first set of empirical relationships between corrosion parameters and equivalent corrosion time based on the corrosion performance test experimental data set, and establishing a second set of empirical relationships between mechanical parameters and equivalent corrosion time based on the performance test experimental data set.

[0174] In this application, unless otherwise specified, "metal material" refers to a solid material with a certain macroscopic size, such as, but not limited to, a plate, a block, etc.

[0175] In this application, unless otherwise specified, "service environment" refers to the environment in which the metal material is located in actual application scenarios.

[0176] In this application, unless otherwise specified, "corrosion degree" refers to the degree of structural loss of a metal material relative to its pre-corroded state. The degree of corrosion can be characterized by, but is not limited to, "mass loss relative to its pre-corroded state." The greater the mass loss, the higher the degree of corrosion.

[0177] In this application, unless otherwise specified, "equivalent corrosion time" means that under corrosion test conditions that can simulate the target service environment, there is a certain correspondence between the corrosion test time experienced by the metal material and the service time under the target service environment. The service time can be indirectly reflected through the corrosion test time. Therefore, this corrosion test time is also called "equivalent corrosion time".

[0178] In this application, unless otherwise specified, "corrosion rate" refers to the amount of corrosion loss per unit time. Corrosion loss can be expressed in, but is not limited to, mass, volume, or line length (e.g., corrosion depth). The corrosion rate can be calculated by dividing the total amount of corrosion loss over a period by the duration of that period.

[0179] In this application, unless otherwise specified, "tensile strength at break" and "elongation at break" have the commonly known meanings in the art. "Tensile strength at break", which can also be expressed as tensile strength or ultimate tensile strength, refers to the maximum tensile stress that a sample can withstand in a tensile test, and is numerically equal to the tensile force that the sample withstands when it breaks under tensile force. "Elongation at break" refers to the percentage of the length deformation of the sample at tensile break 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 L0, a tensile force is applied in the length direction, and the tensile force F that the sample withstands when it breaks is equal to the original length. max The ratio of the cross-sectional area A is equal to the "tensile fracture strength", where "cross-sectional area" refers to the section perpendicular to the length direction of the sample; "fracture elongation" δ = (L-L0) × 100%, where L is the length of the sample when it breaks under tensile force.

[0180] Taking metal materials as test objects, corrosion test conditions are used to simulate the target service environment of metal materials, and corrosion performance test experimental data sets at different equivalent corrosion time points and mechanical performance test experimental data sets at different corrosion degrees corresponding to different equivalent corrosion time points are obtained. 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 for how at least one corrosion parameter, including the corrosion degree and corrosion rate, changes with the equivalent corrosion time and a second set of empirical relationships for how at least one mechanical parameter changes with the equivalent corrosion time are established, thereby constructing an analytical model between the corrosion resistance and mechanical properties of metal materials. This can help understand the corrosion mechanism of metal materials, and can be used to predict and analyze the mechanical properties of metal materials under target service conditions based on the corrosion behavior of metal materials, and to evaluate the service life of metal material structural parts under the target service environment.

[0181] Based on any appropriate embodiment of the present application, further, in some embodiments, the mechanical parameter includes at least one of tensile strength at break and elongation at break.

[0182] When the mechanical parameters in this method can include at least one of tensile fracture strength and fracture elongation, the corrosion resistance-mechanical properties analysis model of the metal material constructed can be applicable to metal material structures that are prone to failure due to tensile stress.

[0183] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameters in the mechanical properties test experimental data set include at least one of tensile strength and elongation at break, and optionally include yield strength.

[0184] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameters in the mechanical properties test experimental data set include at least tensile strength and elongation at break, and optionally also include yield strength.

[0185] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameter includes yield strength.

[0186] By selecting appropriate parameters for fitting the functional relationship, it is beneficial to obtain a second set of empirical relationships with better fitting effect, which in turn is conducive to obtaining a more effective corrosion resistance-mechanical property analysis model.

[0187] In this application, unless otherwise specified, a tensile test can be performed on an electronic tensile testing machine, for example, a Z20 TEW electronic tensile testing machine. In this application, unless otherwise specified, a loading rate during a tensile test can be 0.5 mm / min to 1.5 mm / min.

[0188] Without limitation, the tensile test may be performed using a sample having the dimensions shown in Figure 23. The sample dimensions in Figure 23 are plate-shaped tensile specimens having a length of 60 millimeters (mm) and a thickness of 2 mm.

[0189] As a non-restrictive measure, during a tensile test, the sample to be tested can be wrapped with 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 are taken every 24 hours for tensile performance testing. At least three parallel samples can be set for each test.

[0190] Salt spray corrosion testing can be performed using commonly used salt spray corrosion testing equipment in the art. Without limitation, the LP / YWX-250 model can be used. During the test, the sample can be placed on a V-shaped stand so that the salt spray can slowly and evenly fall on the sample surface.

[0191] In this application, unless otherwise specified, the corrosion rate may be represented by the average corrosion depth per unit time. Furthermore, the corrosion rate may be calculated as follows: Corrosion rate = (K×W) / (A×T×D) mm / y (I)

[0192] In formula (I): K = 8.64 × 10 4 , K is the time constant;

[0193] W is the mass difference before and after the test, in mg;

[0194] A is the test surface area, unit is cm 2 ;

[0195] T is the test time, in h;

[0196] D=2.7g / cm 3 , D is the density of the test sample.

[0197] In formula (I), the unit of corrosion rate is millimeter per year, which can be expressed as "mm / y".

[0198] Based on any suitable embodiment of the present application, further, in some embodiments, the metal material is an aluminum alloy material. The metal material can also be a metal structural part, and further can be an aluminum alloy structural part.

[0199] Based on any suitable embodiment of the present application, further, in some embodiments, the metal material is a battery case material, which can be any of the battery case materials. In some embodiments, the battery case material can include a fuel cell case material. In some embodiments, the battery case material can include a lithium battery case material.

[0200] In some embodiments, the metal material comprises at least a portion of a battery housing. In some embodiments, the battery housing structure may comprise at least a portion of a fuel cell housing. In some embodiments, the battery housing structure may comprise at least a portion of a lithium battery housing.

[0201] In this application, unless otherwise specified, a "structural member" can be an independent object or a part of a structure within an independent object. A "metal structural member" is a structural member made of metal.

[0202] In the application, unless otherwise specified, "battery case material" refers to the main material constituting the battery case, which is the main material of at least a portion of the structure of the battery case. The weight proportion of the battery case material in this portion of the structure may exceed 80%, further exceed 90%, and further approach 100% or be 100%. In some embodiments, the battery case material may refer to the constituent material of the battery case, that is, at least a portion of the structural components of the battery case are composed of this "battery case material".

[0203] In the application, unless otherwise specified, "fuel cell housing" refers to the housing containing the fuel cell monomers; "fuel cell housing material" refers to the main material constituting the fuel cell housing, which is the main material of at least a portion of the structure of the fuel cell housing. Unless otherwise specified, the weight percentage of the fuel cell housing material in this portion of the structure may exceed 80%, further exceed 90%, and further approach 100% or be 100%. In some embodiments, the fuel cell housing material may refer to the constituent material of the fuel cell housing, that is, at least a portion of the structural components of the fuel cell housing are composed of the "fuel cell housing material."

[0204] In this application, unless otherwise specified, "fuel cell" has the commonly known meaning in the art, meaning a chemical device that directly converts the chemical energy of a fuel into electrical energy. Fuel cell housings are exposed to various corrosive media in service environments, including moisture, rainfall, salt spray, and various organic and inorganic liquids used onboard or during cleaning.

[0205] Due to the advantages of low density, high specific strength, excellent thermal stability, good machinability, and low cost, die-cast aluminum alloys can be used to prepare various automotive parts, including cylinder blocks, generator housings, fuel cell boxes, various engine brackets, etc., but not limited to these.

[0206] The metal material can be an aluminum alloy material or a metal structural part, and further can be an aluminum alloy structural part. Due to the advantages of low density, high specific strength, excellent thermal stability, good machinability, low cost, etc., die-cast aluminum alloy can be used to prepare various parts of automobiles, including cylinder blocks, generator housings, fuel cell housings, various engine brackets, etc., but not limited to these. Among them, aluminum alloy materials can be applied to the field of battery technology and can be used as the main material (including constituent materials) of battery boxes or aluminum alloy structural parts in battery boxes. Therefore, the metal material can be a battery box material, and the battery box can include but is not limited to fuel cell boxes, and can also include but is not limited to lithium battery boxes; accordingly, the metal material can include at least a portion of the structural parts of the battery box. When corrosion parameters and mechanical parameters are obtained based on aluminum alloy materials, the corrosion resistance-mechanical properties analysis model of the metal material constructed can be applied to the mechanical property prediction and life assessment of aluminum alloy materials. At this time, it is also helpful to understand the white rust corrosion mechanism of aluminum alloy materials. When aluminum alloy materials are used as the main material or component material of battery boxes or structural parts in battery boxes, the corrosion resistance-mechanical properties analysis model of metal materials can be applied to the mechanical properties prediction and life assessment of battery boxes or structural parts in battery boxes.

[0207] Taking the fuel cell case as an example, this study can also help understand the white rust corrosion mechanism of fuel cell case materials. When testing fuel cell case materials, it is possible to analyze their corrosion behavior, determine the corrosion rates of different fuel cell case materials, and establish a relationship between the degree of corrosion and mechanical properties of fuel cell case materials. This has certain reference significance for the safe operation of fuel cells and even electrical devices that include fuel cells.

[0208] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion performance test experimental data set under corrosion test conditions includes at least a corrosion performance test experimental data set under salt spray corrosion test conditions. Without limitation, the salt spray corrosion test conditions may include at least one of the following salt spray conditions: NaCl aqueous solution salt spray conditions, acetate salt spray conditions, copper salt accelerated acetate salt spray conditions, and alternating salt spray corrosion conditions. In some embodiments, the salt spray corrosion test conditions include NaCl aqueous solution salt spray conditions.

[0209] 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 performance analysis model of the metal material constructed can be applied to metal materials and their structural parts or products in service environments in the fields of road transportation, computer, electronic communication, and electrical appliances, and can also be applied to structural parts or products in related service environments such as electroplating, coating, packaging, and transportation equipment. Among them, the road transportation field may involve but is not limited to road vehicle electronic and electrical equipment, rail transportation 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, mainframes, computer components, medical equipment and other precision instruments and other 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; the electrical appliances may involve but is not limited to various types of household electrical appliances such as household appliances, lamps, transformers, instruments and meters, medical equipment and other equipment, products or their metal structural parts.

[0210] Without limitation, a model based on a corrosion performance test dataset obtained under NaCl aqueous solution salt spray conditions can be applied to determine the quality and uniformity of protective coatings and to compare differences in the salt spray corrosion resistance of samples with similar structures, but is not limited thereto. Without limitation, a model based on an acetate salt spray condition can be applied to coastal cities in the south and to harsh salt spray environments. Without limitation, a model based on a copper salt-accelerated acetate salt spray condition can be applied to harsh salt spray environments. Without limitation, a model based on an alternating salt spray corrosion condition can be applied to high temperature and high humidity environments.

[0211] Based on any suitable embodiment of the present application, further, in some embodiments, the NaCl aqueous solution salt spray conditions include the following parameters: simulated salt spray conditions of a 3 wt % to 6 wt % NaCl aqueous solution at 34-36° C. In some embodiments, the NaCl aqueous solution salt spray conditions include the following parameters: simulated salt spray conditions of a 5 wt % NaCl aqueous solution at 35° C. In some embodiments, the NaCl aqueous solution salt spray conditions include the following parameters: simulated salt spray conditions of a 3.5 wt % NaCl aqueous solution at 35° C.

[0212] For NaCl aqueous solution salt spray conditions, the aforementioned test conditions are helpful in determining the corrosion resistance of battery boxes, automotive parts, etc.

[0213] Without limitation, the initial time when the sample is placed under the corrosion test conditions may be used as the first sampling time point.

[0214] Without limitation, when conducting a corrosion test, the sampling method for different equivalent corrosion time points can be as follows: the total test time (i.e., the duration of the preset time period) is ≥ 30 hours, and the time interval between adjacent sampling points can be ≥ 1 day. Without limitation, the sampling method can be as follows: the total test time is 600 hours, and sampling is performed every 24 hours; further, the first sampling point can be the starting time when the sample is placed under the corrosion test conditions. The sampling method can also be as follows: the total test time is 30 days, and sampling is performed every 10 days; further, the first sampling point can be the starting time when the sample is placed under the corrosion test conditions.

[0215] It is understood that when conducting corrosion testing experiments, samples may be optionally subjected to one or more of the following tests and analyses at any time point: macromorphology observation, micromorphology observation, corrosion rate analysis, etc. For example, one or more of the aforementioned tests and analyses may be performed every 1 to 10 days. In some embodiments, macromorphology observation, micromorphology observation, and corrosion rate analysis are performed every 10 days.

[0216] Without limitation, “macromorphology observation” can be performed using a stereo microscope, shadowless lamp observation, or other means.

[0217] Without limitation, "microscopic morphology observation" includes local morphology observation of a sample at different magnifications (e.g., 200-10,000x), and can be performed using a metallographic microscope, scanning electron microscope (SEM), or other means. Non-limiting examples include a CX40M metallographic microscope, a FEI NOVA NanoSEM 230 field emission scanning electron microscope, or the like.

[0218] Without limitation, for salt spray corrosion testing, sampling can be performed every 12 to 36 hours (e.g., every 24 hours) to obtain corrosion parameters and corresponding mechanical parameters, thereby obtaining a corrosion performance test data set and a mechanical performance test data set. The test duration can be ≥24 days, further ≥25 days, and further ≥30 days.

[0219] Without limitation, the sample size for salt spray corrosion test can be a block of 12mm×12mm×6mm. Without limitation, the non-test surface is wrapped with blue film. Before the salt spray corrosion test, a pretreatment including the following steps can be performed: grinding, polishing, ethanol cleaning and drying of the test surface. Before the salt spray corrosion test, the sample is weighed and the initial weight W0 is recorded. Unless otherwise specified, the following test parameters can be used: the total test duration is 600h, and samples are taken for testing and analysis every 24h during the test. Macromorphology observation and micromorphology observation can be performed first, and then the corrosion products on the surface of the sample are washed away and weighed again. The weighing result of the i-th sampling is recorded as Wi, and the test duration at the i-th sampling is recorded as Ti. W=Wi-W0, T=Ti can be substituted 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. Without limitation, chromic acid cleaning agent (20 g / L Cr2O3 + 50 mL / L H3PO4) can be used to wash away corrosion products on the sample surface.

[0220] Based on any suitable embodiment of the present application, further, in some embodiments, establishing a first set of empirical relationships between corrosion parameters and equivalent corrosion time based on a corrosion performance test experimental data set includes:

[0221] For each corrosion parameter, segmented fitting is performed based on the corresponding corrosion performance test experimental data set. In each fitting interval, the corresponding corrosion parameter is used as the dependent variable and the equivalent corrosion time is used as the independent variable. The power function or linear function is used for fitting respectively to construct the empirical relationship between the corresponding type of corrosion parameter and the equivalent corrosion time in each fitting interval, and the first set of empirical relationship is obtained.

[0222] 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. The fitting method for each segment can use a power function or a linear function. In this case, the fitting curve has a higher degree of consistency with the experimental test data set, and the model is more effective, but it is not limited to the aforementioned function types.

[0223] Based on any suitable embodiment of the present application, further, in some embodiments, in the first set of empirical relationships, the fitting method of the power function is y1=A·x B The fitting method 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.

[0224] 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 include 0.145, 0.755, 0.756, 0.125, 0.126, 0.134, etc. Non-limiting examples of B include -0.533, -0.531, -0.532, -0.681, -0.680, -0.688, etc. a may 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. Non-limiting examples of a include -0.124, -0.0132, -0.00171, -0.366, -0.668, etc. b may also be a real number selected from 0.001 to 0.02, and further may be a real number selected from 0.001 to 0.01, non-limiting examples of b include 0.00713, 0.00334, 0.0197, 0.0311, 0.00222, etc. Furthermore, in some embodiments, the corrosion rate is fitted, and even more specifically, the corrosion rate can be represented by the corrosion depth per unit time.

[0225] By selecting the appropriate fitting function type, it is beneficial to obtain the first set of empirical relationships with better fitting effect, and then obtain a more effective corrosion resistance-mechanical properties analysis model.

[0226] Depending on the corrosion parameters used for fitting, factors such as A, B, a, and b in the above function can be selected from different ranges. For any of these factors, the interval formed by any two exemplary point values ​​recorded in this application can be selected, as long as the interval is appropriate.

[0227] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion parameters in the corrosion performance test experimental data set include at least the corrosion rate.

[0228] Based on any suitable embodiment of the present application, further, in some embodiments, 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. Without limitation, the corrosion parameters in the corrosion performance test experimental data set under electrochemical corrosion test conditions may include at least one electrochemical corrosion parameter of self-corrosion potential and self-corrosion current. Without limitation, the corrosion parameters in the corrosion performance test experimental data set under immersion corrosion test conditions may include at least one of corrosion degree and corrosion rate.

[0229] When the corrosion performance test dataset includes a dataset of corrosion performance test experiments conducted under electrochemical corrosion test conditions, the metal material corrosion resistance-mechanical property analysis model can be applied to the performance prediction and lifespan assessment of metal materials under electrochemical conditions. For example, but not limited to, the performance prediction and lifespan assessment of battery housings, and further applications include, but are not limited to, the performance prediction and lifespan assessment of fuel cell housings.

[0230] When the corrosion performance test experimental data set includes a corrosion performance test experimental data set 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 evaluation of the metal material in an environment contacting corrosive liquids.

[0231] 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-mechanical property analysis model of the metal material can be applied to the performance prediction and life assessment of battery boxes with built-in electrolytes. Furthermore, it can include but is not limited to the performance prediction and life assessment of fuel cell boxes.

[0232] In some embodiments, the corrosion performance test experimental data set under corrosion test conditions includes a corrosion performance test experimental data set under electrochemical corrosion test conditions; further, the electrochemical corrosion test may include one or more of open circuit voltage test, AC impedance test, potentiodynamic polarization test, etc.; accordingly, the corrosion parameters in the corrosion performance test experimental data set may include one or more of open circuit voltage, impedance, etc.

[0233] The test equipment for performing electrochemical corrosion testing may include an electrochemical workstation and a three-electrode system, wherein the structural schematic diagram of the three-electrode system can be found in FIG24 . In a non-limiting manner, 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 serves as the working electrode, the silver-silver chloride (Ag-AgCl) electrode serves as the reference electrode, and the platinum (Pt) electrode serves as the auxiliary electrode; the electrolyte solution used can be a 3.5wt% NaCl aqueous solution; and the three-electrode system is placed in a Faraday shield box during the test.

[0234] Without limitation, the sample size for electrochemical corrosion testing can be a plate of 10 mm x 10 mm x 2 mm. The test surface area can be 1 cm 2 Before testing, the sample can be pretreated by the following steps: cold mounting with epoxy resin, sanding, polishing, ethanol cleaning, and drying.

[0235] Without limitation, the electrochemical corrosion test may include open circuit voltage (OCP) measurement and an alternating current impedance (EIS) test after the OCP has stabilized for a period of time (e.g., after the OCP has stabilized for 60 minutes), and further, measuring the electrochemical impedance spectrum of the sample at different AC frequencies. During the test, a 10mV AC sine wave can be used as the excitation voltage, and the test frequency can be controlled within 0.01Hz to 105Hz. Typically, the experimental results of the EIS can be fitted with an equivalent circuit, and the parameters of each component in the equivalent circuit diagram can be analyzed.

[0236] Without limitation, during the electrochemical corrosion test, a potentiodynamic polarization test may be performed after the AC impedance test. Furthermore, the following test parameters may be employed: starting from an OCP potential of -300 mV, scanning at a scan rate of 0.167 mV / s until the current exceeds 1 mA. Tafel fitting of the sample polarization characteristic data was performed using ZSimpWin v3.40 software.

[0237] In some embodiments, the corrosion performance test experimental dataset under corrosion test conditions includes a corrosion performance test experimental dataset under immersion corrosion test conditions. Without limitation, the corrosion parameters in the corrosion performance test experimental dataset under immersion corrosion test conditions may include at least one of corrosion severity and corrosion rate.

[0238] Without limitation, during the immersion corrosion test, sampling can be performed as follows: sampling can be performed every 10 days for a total test duration of 30 days. Furthermore, the first sampling point can be the start time of exposure of the sample to the corrosion test conditions. At each sampling point, the sample can optionally undergo one or more of the following tests and analyses, including but not limited to macroscopic morphology observation, microscopic morphology observation, and corrosion rate analysis.

[0239] In some embodiments, the immersion corrosion test includes the following steps: the total test time is 30 days, and samples are taken for testing every 10 days to test and analyze the macromorphology, micromorphology and corrosion rate of the samples.

[0240] Without limitation, the sample used for the immersion corrosion test may be a block of 15 mm×15 mm×2 mm, or a block of 50 mm×25 mm×2 mm, or a sample of other shapes required for testing.

[0241] Without limitation, the composition of the etching solution used to immerse the sample can be determined based on the corrosive environment in which the sample is to be tested. A 500 mL etching solution can be used. In some embodiments, the etching solution is a 3 wt % to 6 wt % NaCl aqueous solution, such as a 3 wt %, 3.5 wt %, 4 wt %, 4.5 wt %, 5 wt %, 5.5 wt %, or 6 wt % NaCl aqueous solution.

[0242] Without limitation, when conducting an immersion corrosion test, the ratio of the corrosive liquid to the sample test area can be maintained at greater than 0.2 mL / mm during the test. 2 .

[0243] Without limitation, prior to the immersion corrosion test, a pretreatment may be performed including the following steps: grinding and polishing the test surface, rinsing with deionized water and ethanol, drying, and weighing. After weighing, the sample may be stored in a desiccator for future use.

[0244] Without limitation, the immersion corrosion test includes: placing the sample in a container and adding 500 mL of corrosion solution. After sealing, the entire container is placed in a constant temperature water bath tank, and the temperature is set to 25°C. Samples are taken every 10 days (i.e., the test time is 10 days, 20 days, and 30 days respectively), and the macromorphology and micromorphology of the sample surface after corrosion are observed. Then, the corrosion products on the sample surface are removed, the sample mass before and after corrosion is compared, and the corresponding immersion corrosion rate is calculated according to formula (I). At least three parallel samples are set for each test.

[0245] In this application, as a time unit, unless otherwise specified, 1d means 1 day and 1h means 1 hour.

[0246] Based on any suitable embodiment of the present application, further, in some embodiments, a second set of empirical relationships for mechanical parameters varying with equivalent corrosion time is established based on a mechanical properties test experimental data set, including:

[0247] For each mechanical parameter, 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 power function or linear function is used for fitting respectively to construct the empirical relationship between the corresponding type of mechanical parameter and the equivalent corrosion time, and obtain the second set of empirical relationship.

[0248] The establishment of the second set of empirical relationships between the mechanical parameters and the equivalent corrosion time can be obtained by piecewise fitting for each mechanical parameter. The fitting method for each segment can use a power function or a linear function. In this case, the fitting curve has a higher degree of consistency with the experimental test data set, and the model is more effective, but it is not limited to the aforementioned function types.

[0249] Based on any suitable embodiment of the present application, further, in some embodiments, in the second set of empirical relationship formulas, the fitting method of the power function is y2=M·x N 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.

[0250] 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 can be selected from -0.1 to -1.5; m is a real number selected from 1 to 300. Non-limiting examples of M include 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 include -0.11, -0.07, -0.16, etc. Non-limiting examples of m include 269.59, 203.21, 9.69, 248.48, 134.55, 3.95, 248.21, 131.83, 8.31, etc. Non-limiting examples of n include -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.

[0251] By selecting the appropriate fitting function type, it is beneficial to obtain a second set of empirical relationships with better fitting effect, which in turn helps to obtain a more effective corrosion resistance-mechanical properties analysis model.

[0252] Depending on the mechanical parameters used for fitting, different ranges can be selected for factors such as M, N, m, and n in the above function. For any of these factors, an interval consisting of any two exemplary point values ​​described in this application can be selected, as long as the interval is appropriate, but not limited thereto. For example, when fitting the tensile strength at break (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 to 300, 80 to 300, 60 to 250, 80 to 250, 100 to 300, 100 to 250, 120 to 240, etc. For example, when fitting the elongation at break (El), n can be selected from any suitable range: 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 suitable range: 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 suitable range: -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 suitable range: 50 to 300, 80 to 300, 50 to 250, 80 to 250, 100 to 300, 100 to 250, 120 to 250, etc.

[0253] Based on any suitable embodiment of the present application, further, in some embodiments, the method for constructing a corrosion resistance-mechanical properties analysis model of a metal material also includes the following steps: establishing a third set of empirical relationships between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment.

[0254] By establishing an empirical relationship between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment (which can be recorded as the third set of empirical relationships), the equivalent corrosion time can be converted into the service time under the target service environment, thereby more directly predicting the service life of metal materials and their structural parts or products.

[0255] Without limitation, a third set of empirical relationships between the equivalent corrosion time under selected corrosion test conditions and the service time under the target service environment can be established based on existing standards, specifications, or conventional experience in the field. For example, a die-cast aluminum alloy part exposed to a salt spray corrosion environment for one day (d) can be equivalent to being corroded for more than one year (i.e., ≥1 year) under the actual service environment.

[0256] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps (see FIG3 ):

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

[0258] S120: A first set of empirical relationships between corrosion parameters and equivalent corrosion time is established based on the corrosion performance test experimental data set, and a second set of empirical relationships between mechanical parameters and equivalent corrosion time is established based on the mechanical performance test experimental data set; a third set of empirical relationships between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment is also established.

[0259] Based on any suitable embodiment of the present application, further, in some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model for a metal material includes the following steps: establishing a fourth set of empirical relationships between the corrosion rate and the equivalent corrosion time under corrosion test conditions. In this case, the first set of empirical relationships includes the fourth set of empirical relationships between the corrosion rate and the equivalent corrosion time under corrosion test conditions. In this case, the corrosion parameter in the corrosion performance test experimental data set includes the corrosion rate.

[0260] By establishing an empirical relationship between the corrosion rate and the equivalent corrosion time under corrosion test conditions (which can be recorded as the fourth set of empirical relationships), the relationship between the corrosion behavior and mechanical properties of metal materials under the target service environment can be dynamically analyzed.

[0261] The corrosion rate obtained from the test analysis can be fitted with the data points of the corresponding equivalent corrosion time.

[0262] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps (see FIG4 ):

[0263] S110: Taking a 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 further obtaining test values ​​of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein the corrosion test conditions are used to simulate a target service environment of the metal material; and the corrosion parameters include at least one of a corrosion degree and a corrosion rate;

[0264] S120: A first set of empirical relationships between corrosion parameters and equivalent corrosion time is established based on the corrosion performance test experimental data set, and a second set of empirical relationships between mechanical parameters and equivalent corrosion time is established based on the mechanical performance test experimental data set; wherein the first set of empirical relationships includes a fourth set of empirical relationships between corrosion rate and equivalent corrosion time under corrosion test conditions.

[0265] In some embodiments, a method for constructing a corrosion resistance-mechanical properties analysis model of a metal material is provided, comprising the following steps (see FIG5 ):

[0266] S110: Taking a 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 further obtaining test values ​​of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points to obtain a mechanical performance test experimental data set; wherein the corrosion test conditions are used to simulate a target service environment of the metal material; and the corrosion parameters include at least one of a corrosion degree and a corrosion rate;

[0267] S120: A first set of empirical relationships between corrosion parameters and equivalent corrosion time is established based on the corrosion performance test experimental data set, and a second set of empirical relationships between mechanical parameters and equivalent corrosion time is established based on the mechanical performance test experimental data set; a third set of empirical relationships between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment is also established; wherein the first set of empirical relationships includes a fourth set of empirical relationships between the corrosion rate under corrosion test conditions and the equivalent corrosion time.

[0268] In the embodiments shown in Figures 3, 4, and 5, the mechanical parameters used in the mechanical properties test experimental data set can be independently defined as described above. Furthermore, the mechanical parameters can include at least one of tensile strength and elongation at break. In some embodiments, the mechanical parameters include tensile strength at break and elongation at break. The mechanical parameters can include yield strength. In some embodiments, the mechanical parameters include yield strength. In some embodiments, the mechanical parameters include tensile strength at break, elongation at break, and yield strength.

[0269] In a second aspect of the present application, a method for analyzing the service life of a metal material is provided, which uses a corrosion resistance-mechanical properties analysis model of the metal material to analyze the service life of the metal material.

[0270] The metal material may be as defined in the first aspect of the present application.

[0271] In some embodiments, a method for analyzing the service life of a metal material is provided, comprising the following steps (see FIG6 ):

[0272] S210: Determining mechanical parameters related to 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;

[0273] S220: Obtain the service life parameters of the metal material under corrosion test conditions based on 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; wherein the corrosion resistance degree-mechanical property analysis model of the metal material includes at least the following relationship formulas: a first set of empirical relationship formulas including the change of corrosion parameters characterizing the corrosion degree with the equivalent corrosion time and a second set of empirical relationship formulas including the change of mechanical parameters with the equivalent corrosion time.

[0274] This method for analyzing the service life of a metal material selects mechanical parameters related to the failure behavior of the metal material based on the target service environment of the metal material, selects corrosion test conditions that can simulate the target service environment, and then obtains a test value of the corrosion degree of the metal material under the selected corrosion test conditions. Thus, the service life parameters of the metal material under the selected corrosion test conditions can be obtained based on the test value of the corrosion degree, the effective state threshold of the selected mechanical parameter, and a corrosion resistance-mechanical property analysis model for the metal material. The corrosion resistance-mechanical property analysis model for the metal material is based on the equivalent corrosion time and the mechanical properties at different corrosion degrees, and includes at least the following two relationship equations: a first set of empirical relationship equations for the variation of at least one of the corrosion parameters, namely, the corrosion degree and the corrosion rate, with the equivalent corrosion time, and a second set of empirical relationship equations for the variation of the aforementioned mechanical parameters with the equivalent corrosion time. This analysis method can be used effectively and accurately to analyze the service life of a metal material under the target service environment.

[0275] Based on any suitable embodiment of the present application, further, in some embodiments, the service life parameter at least includes equivalent corrosion time.

[0276] According to the above 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.

[0277] Based on any suitable embodiment of the present application, further, in some embodiments, 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, obtaining the service life parameter of the metal material under the corrosion test conditions includes:

[0278] 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 parameters, the corrosion resistance-mechanical properties analysis model of the metal material, and a third set of empirical relationships between the equivalent corrosion time under corrosion test conditions and the service time under the target service environment.

[0279] The remaining service time of the metal material can be obtained based on 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 properties analysis model of the metal material, and the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment, thereby realizing the predictive analysis of the remaining service life of the metal material.

[0280] Based on any suitable embodiment of the present application, further, in some embodiments, the mechanical parameters include at least two. Non-limitingly, the failure response of the metal material can be ranked from high to low according to the mechanical parameters, and a corrosion resistance-mechanical property analysis model of the metal material can be obtained based on the top-ranked mechanical parameter.

[0281] The failure response degree of metal materials is ranked in descending order according to the mechanical parameters, and the corrosion resistance-mechanical performance analysis model of metal materials is obtained according to the mechanical parameters with the highest ranking. This can more effectively reflect the relationship between the corrosion behavior of metal materials and mechanical performance failure in the target service environment.

[0282] Based on any suitable embodiment of the present application, further, in some embodiments, the corrosion resistance-mechanical properties analysis model of the metal material is constructed according to the construction method of the corrosion resistance-mechanical properties analysis model of the metal material described in the first aspect of the present application.

[0283] The corrosion resistance-mechanical properties analysis model involved in the aforementioned analysis method of the service life of metal materials can be constructed using the construction method in the first aspect of this application, and a relationship between the corrosion degree of metal materials and the mechanical properties including at least one mechanical parameter including tensile fracture strength and fracture elongation can be constructed.

[0284] In a third aspect of the present application, a service life analysis device for metal materials is provided, which includes: a corrosion performance data acquisition module 310 and a corrosion performance data processing module 320. Please refer to FIG7 .

[0285] The metal material may be as defined in the first aspect of the present application.

[0286] In some embodiments, a device for analyzing the service life of a metal material is provided, comprising:

[0287] The corrosion performance data acquisition module 310 is used to determine the mechanical parameters related to the failure behavior of the metal material based on the target service environment of the metal material, 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;

[0288] The corrosion performance data processing module 320 is used to obtain the service life parameters of the metal material under corrosion test conditions based on 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 can be as defined in the first aspect or the second aspect of this application.

[0289] The service life analysis device for metal materials provided in the third aspect of the present application can be used to implement the service life analysis method for metal materials provided in the second aspect of the present application.

[0290] In a fourth aspect of the present application, a method for analyzing the mechanical properties of a metal material is provided, which utilizes a corrosion resistance-mechanical properties analysis model of the metal material to analyze the mechanical properties of the metal material.

[0291] The metal material may be as defined in the first aspect of the present application.

[0292] In some embodiments, a method for analyzing the mechanical properties of a metal material is provided, comprising the following steps (see FIG8 and FIG9 ):

[0293] Determine the mechanical parameters related to the failure behavior of the metal material based on 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;

[0294] Preliminary predicted values ​​of the mechanical parameters of the metal material after the target service time under the corrosion test conditions are obtained based on the corrosion degree test value, the target service life 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 a corrosion resistance-mechanical property analysis model for the metal material; wherein the corrosion resistance-mechanical property analysis model for the metal material may be as defined in the first aspect or the second aspect of the present application;

[0295] 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; if the preliminary predicted value of the mechanical parameter is greater than or equal to the effective state threshold of the mechanical parameter, then 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, then output the predicted result that the metal material will fail before reaching the target service time.

[0296] The aforementioned method for analyzing the mechanical properties of a 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, thereby obtaining a test value of the corrosion degree of the metal material under the selected corrosion test conditions. Based on the test value of the corrosion degree, the target service life of the metal material, the empirical relationship between the equivalent corrosion time under the selected corrosion test conditions and the service life under the target service environment, and the corrosion resistance-mechanical properties analysis model of the metal material, a preliminary prediction of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions can be obtained. By comparing the preliminary prediction of the mechanical parameters with the effective state threshold of the mechanical parameters, a prediction result of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions can be obtained. If the preliminary prediction of the mechanical parameters is greater than or equal to the effective state threshold of the mechanical parameters, the effective prediction of the mechanical parameters of the metal material after the target service life under the selected corrosion test conditions is equal to the preliminary prediction; if the preliminary prediction of the mechanical parameters is less than the effective state threshold of the mechanical parameters, it means that the metal material has failed before reaching the target service life.

[0297] In a fifth aspect of the present application, a mechanical property analysis device for metal materials is provided (see FIG. 10 ), which includes: a test data acquisition module 510 , a test data processing module 520 and a mechanical property classification and identification module 530 .

[0298] The metal material may be as defined in the first aspect of the present application.

[0299] In some embodiments, a mechanical property analysis device for a metal material is provided, comprising:

[0300] The test data acquisition module 510 is 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, 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;

[0301] The test data processing module 520 is configured to obtain preliminary predicted values ​​of the mechanical parameters of the metal material after the metal material has been used for the target service time under the corrosion test conditions based on 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 a corrosion resistance-mechanical property analysis model for the metal material. The corrosion resistance-mechanical property analysis model for the metal material may be as defined in the first or second aspect of the present application.

[0302] The mechanical property classification and identification module 530 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 of the metal material after the 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, then the effective predicted value of the mechanical parameter of the metal material after the target service time under corrosion test conditions is equal to the preliminary predicted value.

[0303] The mechanical properties analysis device for metal materials provided in the fifth aspect of the present application can be used to implement the mechanical properties analysis method for metal materials provided in the fourth aspect of the present application.

[0304] In a sixth aspect of the present application, a computer device is provided.

[0305] In some embodiments, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for constructing a corrosion resistance-mechanical properties analysis model of a metal material described in the first aspect of the present application, 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 are implemented.

[0306] The computer device may be a terminal, and its internal structure diagram may be as shown in FIG11 . The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used 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 used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may 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, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0307] Those skilled in the art will understand that the structure shown in FIG11 is merely a block diagram of a portion of the structure 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 shown in the figure, or combine certain components, or have a different arrangement of components.

[0308] In the seventh aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for constructing a corrosion resistance-mechanical properties analysis model of metal materials described in the first aspect of the present application, the method for analyzing the service life of metal materials described in the second aspect of the present application, or the method for analyzing the mechanical properties of metal materials described in the fourth aspect are implemented.

[0309] In another aspect of the present application, a computer program product is provided, comprising a computer program, characterized in that when the computer program is executed by a processor, the steps of the construction method of the first aspect of the present application or the analysis method of the second aspect or the fourth aspect of the present application are implemented.

[0310] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned method implementation can be implemented by instructing the relevant hardware through a computer program, and 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-mentioned method implementations. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may 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). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0311] In an eighth aspect of the present application, an electrical device including a battery system is provided.

[0312] In some embodiments, the electrical device comprises:

[0313] 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 the first aspect of the present application; and

[0314] At least one of the service life analysis device for metal materials described in the third aspect of this application, the mechanical properties analysis device for metal materials described in the fifth aspect of this application, the computer equipment described in the sixth aspect of this application, and the computer-readable storage medium described in the seventh aspect of this application.

[0315] In this application, unless otherwise specified, a "battery cell" refers to a basic unit that can realize the mutual conversion of chemical energy and electrical energy.

[0316] In some embodiments, the battery cells include fuel cell cells. In this case, the corresponding battery system may be a fuel cell system, and the corresponding battery housing may be a fuel cell housing.

[0317] In this application, unless otherwise specified, "fuel cell" has the commonly known meaning in the art and refers to a chemical device that directly converts the chemical energy of a fuel into electrical energy. "Fuel cell" refers to a cell that directly converts the chemical energy of a fuel into electrical energy. In this application, unless otherwise specified, "fuel cell housing" refers to a housing containing fuel cell cells.

[0318] In some embodiments, the electrical device is a fuel electrical device, which includes: a fuel cell system, which includes a fuel cell box and a fuel cell monomer located inside the fuel cell box, wherein the fuel cell box includes the metal material defined in the first aspect of this application.

[0319] In some embodiments, the battery cells include lithium battery cells. In this case, the corresponding battery system may be a lithium battery system, and the corresponding battery box may be a lithium battery box.

[0320] In this application, unless otherwise specified, "lithium battery" has the commonly known meaning in the art and refers to a type of battery whose active ions include lithium ions. "Lithium battery cell" refers to a battery cell whose active ions include lithium ions. A lithium battery can be a lithium-ion secondary battery. In this application, unless otherwise specified, "lithium battery housing" refers to a battery housing containing lithium battery cells.

[0321] In some embodiments, the electrical device includes: a lithium battery system, which includes a lithium battery case and lithium battery cells located inside the lithium battery case, wherein the lithium battery case includes the metal material defined in the first aspect of the present application.

[0322] Electrical devices 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 and satellites, energy storage systems, etc., but are not limited to these.

[0323] As an electrical device, a battery can be selected according to its usage requirements.

[0324] FIG12 shows an example of an electric device, which may be a pure electric vehicle, a hybrid electric vehicle, or a plug-in hybrid electric vehicle.

[0325] Another example device may be a mobile phone, a tablet computer, a notebook computer, etc. Such a device is generally required to be lightweight and thin, and may use a secondary battery as a power source.

[0326] At least one of the aforementioned metal material service life analysis device, the aforementioned metal material mechanical property analysis device, computer equipment, computer-readable storage medium and computer program product can be set on the electrical setting to implement the aforementioned analysis model construction method, the aforementioned metal material service life analysis method or the aforementioned metal material mechanical property analysis method, which is conducive to achieving better management and maintenance of electrical devices, not only conducive to achieving safe maintenance of battery boxes in electrical devices, but also conducive to assisting in the design of battery boxes with longer service life.

[0327] Below, some embodiments of the present application are described. The embodiment described below is exemplary, is only used to explain the present application, and cannot be construed as limiting the present application. In the embodiment, if no technology or condition is indicated, it is carried out according to the description above, or according to the technology or condition described in the document in this area or according to the product specification. Reagents used or instruments are not indicated by the manufacturer, and are conventional products that can be obtained commercially, or can be prepared in a conventional manner by commercially available products.

[0328] In the following examples, room temperature refers to 20°C to 30°C.

[0329] 1. Test samples:

[0330] Fuel cell cases made of four aluminum alloys—A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr—were cut to specific sizes and used as test specimens for corrosion and tensile testing. The elemental compositions of the four aluminum alloys can be found in Table 1.

[0331] All aluminum alloys can be prepared using the following method based on the elemental composition shown in Table 1: First, pure aluminum ingots are added to the melting furnace. Other components are then added in batches based on their melting points. Subsequent raw materials are added only after the first batch has melted. After melting, the ingot is allowed to stand for slag removal, and a refining agent is added. After slag removal, some of the components are added, and the ingot is cast into a mold to obtain an ingot of the target size. The ingot is then allowed to stand for slag removal, then water-cooled to room temperature. This yields the target-sized aluminum alloy for battery cases, also referred to as a die-cast aluminum alloy sample.

[0332] Table 1. Elemental composition of four aluminum alloy materials (units in the table are mass percentage wt%)

[0333] In Table 1, “-” indicates that it was not detected and can be considered as not contained according to the conventional composition, and “Bal.” indicates that it is a matrix element.

[0334] 2. Construction of corrosion resistance-mechanical properties analysis model based on salt spray corrosion test

[0335] 1. Salt spray corrosion test method

[0336] The test was conducted at 35°C using a 3.5 wt% NaCl aqueous solution.

[0337] The macromorphology, micromorphology, corrosion mass loss and corrosion rate of the box material were analyzed every 24 hours for a total test time of 600 hours.

[0338] Before the test, the fuel cell box of known alloy material type was cut into 15mm×15mm×2mm blocks, and the non-test surface was wrapped with blue film. The test surface was ground, polished and dried and then weighed W0. The total test time was 600h. During the test, a batch of samples were taken every 24h for observation of the surface macromorphology and micromorphology. After observation, chromic acid cleaner (20g / L Cr2O3+50mL / L H3PO4) was used to remove the corrosion products on the surface of the sample and weigh it again to calculate the corrosion rate and observe the morphology. The test time of the i-th sampling was recorded as Ti, and the weight at the i-th sampling was recorded as Wi. At least three parallel samples were set for each test.

[0339] 2. Test methods

[0340] (1) Macromorphology testing method

[0341] Samples: The corrosion time points for sampling were as described above.

[0342] Instrument: Shadowless lamp observation.

[0343] (2) Micromorphology testing method

[0344] Samples: The corrosion time points for sampling were as described above.

[0345] Instrument: NOVANanoSEM 230 low vacuum ultrahigh resolution field emission electron microscope.

[0346] Method: The probe type (det) is ETD. Taking Figure 13 as an example, the accelerating voltage (HV) is 5 kV and the working distance is 30 mm.

[0347] (3) Corrosion mass loss and corrosion rate analysis methods

[0348] The quality loss of the i-th sampling is W=W0-Wi.

[0349] The corrosion rate Ri at the time of sampling for the i-th time can be substituted into formula (I) to calculate: Corrosion rate = (K×W) / (A×Ti×D)mm / y (I)

[0350] In formula (I): K = 8.64 × 10 4 , K is the time constant;

[0351] W is the mass difference before and after the test = W0-Wi, in mg;

[0352] A is the test surface area, unit is cm 2 , here is 1.5cm×1.5cm=2.25cm 2 ;

[0353] Ti is the test time of the i-th sampling, in h;

[0354] D=2.7g / cm 3 , D is the density.

[0355] "mm / y" means millimeters per year.

[0356] (4) Establish the first set of empirical relationships between corrosion parameters and equivalent corrosion time

[0357] The total test time is divided into three time periods, and the following functions are used for fitting respectively, and the function with better fitting effect is selected.

[0358] Optional function 1: y1 = A·x B ;

[0359] Optional function 2: y1 = a + b · x;

[0360] 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.

[0361] Reduced Chi-Sqr, R 2 and adjusted R 2 At least one of them is used to evaluate the fitting effect. Among them, Reduced Chi-Sqr is equivalent to the residual mean square RSS / dof in Anova. The closer the Reduced Chi-Sqr is to 1, the better the fitting effect is. It is mainly used in nonlinear fitting. 2 is the coefficient of determination (COD), the closer it is to 1, the better the fitting effect. 2 According to SPSSAU linear regression, the closer the value is to 1, the better the fitting effect is.

[0362] 3. Analysis of salt spray corrosion test results

[0363] Figure 13 shows the macromorphology (first row) and micromorphology of four aluminum alloys at different equivalent corrosion times from the salt spray test results: (a) A356.2; (b) A380; (c) AlSi10MgMn; and (d) AlSi9MnMoZr. The surface macromorphology of the four die-cast aluminum alloys at different corrosion times reveals that A380 alloy corrodes most severely, with a high accumulation of white corrosion products. The other three die-cast aluminum alloys corrode relatively slowly, with relatively few surface corrosion products, similar to the electrochemical test results. For A356.2 and A380 alloys, the alloy surface is rapidly covered with corrosion products after a short corrosion time (1-6 days), presumably due to the occurrence of general corrosion. The accumulation area and thickness of surface corrosion products increase with corrosion time, and the sample surface exhibits a transition from a dark, initially corroded surface to a large accumulation of white corrosion products. For AlSi10MgMn and AlSi9MnMoZr alloy materials, in the early stage of corrosion (1d-6d), the sample surface mainly showed local pitting pits, and corrosion products accumulated more near the pitting pits, which was presumably due to the protection of the passivation film on the surface; in the middle stage of corrosion (7d-18d), the corrosion further expanded, the passivation film was destroyed, and gradually showed uniform corrosion; in the late stage of corrosion (19d-24d), more and more positions on the sample surface were covered by corrosion products until the entire surface was covered.

[0364] Micromorphological images of four aluminum alloys (A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr) at different equivalent corrosion time points during the salt spray test, including microstructure images of the four die-cast aluminum alloy samples at the early and late stages of the salt spray corrosion test (not shown). At the initial corrosion stage (1 day), the A356.2 and A380 alloys exhibited uniform corrosion throughout, while the A380 alloy exhibited significantly more severe corrosion and a greater number of corrosion products. The AlSi10MgMn and AlSi9MnMoZr alloys primarily exhibited pitting corrosion, with the AlSi10MgMn alloy exhibiting more pronounced pitting, similar to the electrochemical corrosion results. At the final corrosion stage (25 days), all four alloys exhibited uniform corrosion, with corrosion products essentially covering the sample surface and accumulating. The A380 alloy exhibited more and thicker corrosion products, followed by the AlSi10MgMn alloy, while the A356.2 alloy and the AlSi9MnMoZr alloy exhibited similar corrosion patterns.

[0365] Micromorphological images of four aluminum alloys (A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr) after 10 days of salt spray corrosion testing, including microstructure images of the die-cast aluminum alloy after corrosion product removal (not shown), show varying degrees of corrosion in the α-Al matrix of all four alloys. The presence of numerous dispersed Si particles in the A356.2 alloy, while not directly participating in the corrosion reaction, accelerates matrix corrosion. The presence of Si particles also makes it difficult for a dense oxide film to form on the alloy surface, leading to more pronounced α-Al corrosion around the Si particles. As corrosion develops and spreads, the Si particles may even flake off. Numerous corrosion pits are observed around the Al-Si eutectic structure of the A380 alloy. This is because the presence of the Al2Cu phase near the Al-Si eutectic further exacerbates the intergranular corrosion tendency of the Al-Si eutectic. In addition, a small amount of Cu solid solution in the matrix will increase the potential difference between the intergranular and intragranular, and the potential of the Al2Cu phase is relatively positive. At the same time, 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 a cathode phase, forming an electrochemical micro-battery with the nearby Cu-rich matrix phase and Al2Cu phase, causing the Cu-poor solid solution matrix phase to continuously corrode, resulting in the disappearance of grain boundaries. 15 (FeMn)3Si2 phase and Al in AlSi9MnMoZr alloy 12The potential of the Mn3Si2 phase is similar to that of the matrix. Therefore, after the passive film is destroyed, the AlSi10MgMn and AlSi9MnMoZr alloys experience more severe corrosion at the grain boundaries and Al-Si eutectic phase boundaries. Because the passive film of the AlSi9MnMoZr alloy is more stable and more difficult to destroy, the corrosion level at the grain boundaries and Al-Si eutectic phase boundaries is more pronounced in the AlSi10MgMn alloy.

[0366] Figure 14 shows the experimental 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 stage I (0-13d), the corrosion rate of A356.2 alloy is higher than that of AlSi10MgMn and AlSi9MnMoZr alloys. In stage II (14d-22d), as the passive film ruptures and localized corrosion behavior intensifies, the corrosion rates of AlSi10MgMn alloy and AlSi9MnMoZr alloy gradually increase, while the corrosion rate of A356.2 alloy basically remains at around 0.05mm / y. In stage III (23-25 ​​days), the oxide film produced by self-passivation of AlSi10MgMn and AlSi9MnMoZr alloys was almost completely destroyed, and the galvanic corrosion caused by the second phase was intensified, so the corrosion rate of AlSi10MgMn and AlSi9MnMoZr alloys increased significantly.

[0367] Figures 15-18 show the fitting results between the corrosion rate and equivalent corrosion time for the four aluminum alloy materials shown in Figure 14, respectively, subjected to salt spray corrosion testing. After performing segmented fitting on the corrosion rates of the four die-cast aluminum alloys, the fitting curves generally agree with the experimental results. An empirical relationship between the corrosion rate and equivalent corrosion time was established (the first set of empirical relationships, also forming the fourth set of empirical relationships). The fitting results for the four samples are shown in Table 2.

[0368] Table 2. Parameters related to the fitting results of the empirical relationship between the corrosion rate and equivalent corrosion time of the four aluminum alloy materials in Figures 15 to 18

[0369] 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 ” was obtained by SPSSAU linear regression.

[0370] Based on the above empirical formula, during the service life of die-cast aluminum alloy parts, the corresponding equivalent corrosion time x can be substituted according to the corrosive medium and service time to calculate the corresponding corrosion rate y, which has certain guiding significance for the evaluation of product service life.

[0371] Taking Shanghai, China as an example, one day of exposure of die-cast aluminum alloy parts to a salt spray corrosion environment is equivalent to more than one year of corrosion in a real environment (equivalent to establishing a third set of empirical relationships between the equivalent corrosion time under the selected corrosion test conditions and the service time under the target service environment). Based on the first set of empirical relationships from formulas (3-1) to (3-9), a conservative 25-year corrosion rate prediction model for four die-cast aluminum alloy parts can be established.

[0372] 4. Tensile test method

[0373] (1) Sample size, as shown in FIG23 , in millimeters (mm), where R2.5 indicates a radius of 2.5 mm.

[0374] (2) Testing instrument: Z20 TEW electronic universal material testing machine.

[0375] (3) Test and analysis methods:

[0376] Tensile specimens of four die-cast aluminum alloys were wrapped with blue film, retaining only the test surface. The test lasted 600 hours, with samples collected every 24 hours for tensile testing. Each test was performed with at least three replicates.

[0377] Mechanical properties tests were performed on tensile specimens at different corrosion stages to obtain stress-strain curves, which were then analyzed to obtain tensile strength (UTS, also known as tensile strength or ultimate tensile strength), elongation at break (El), and yield strength (YS).

[0378] (4) Establishing a second set of empirical relationships between mechanical parameters and equivalent corrosion time

[0379] The total test time is divided into three time periods, and the following functions are used for fitting respectively, and the function with better fitting effect is selected.

[0380] Optional function 1: y2 = M x N ;

[0381] Optional function 2: y2 = m + n·x;

[0382] Among them, 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.

[0383] Reduced Chi-Sqr, R 2 and adjusted R 2 At least one of them evaluates the fitting effect.

[0384] (5) The first set of empirical relationships and the second set of empirical relationships constitute the empirical model of the relationship between corrosion degree and mechanical properties.

[0385] (6) Test analysis results

[0386] Figures 19 to 22 show the experimental and fitting results of mechanical parameters and equivalent corrosion time at different equivalent corrosion time points in salt spray corrosion tests on four aluminum alloy materials, A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr. The mechanical parameters include tensile strength (UTS), elongation at break (El), and yield strength (YS).

[0387] According to test results, the yield strength and tensile strength of the A380 alloy show a rapid decline with increasing corrosion time, which is particularly evident in the initial corrosion period (1-4 days), with the yield strength and tensile strength dropping to 77.5% and 76% of their pre-corrosion values, respectively. Subsequently, the rate of performance degradation slows, with the yield strength and tensile strength ultimately dropping to 65.4% and 52.5% of their pre-corrosion values, respectively. The yield strength and tensile strength of the A356.2, AlSi10MgMn, and AlSi9MnMoZr alloys show a relatively steady decline, with the yield strength and tensile strength of the A356.2 alloy dropping to 84.3% and 82.6% of their pre-corrosion values, respectively; the yield strength and tensile strength of the AlSi10MgMn alloy dropping to 84.4% and 75.6%, respectively; and the yield strength and tensile strength of the AlSi9MnMoZr alloy dropping to 85.8% and 80.3%, respectively. In addition, when the corrosion time is 23 days, the tensile strength of the AlSi9MnMoZr alloy only drops to 87.5% of the pre-corrosion level, which is higher than that of the other three alloys (A356.2: 86.4%; A380: 62.9%; AlSi10MgMn: 81.4%), indicating that when the corrosion time is short, the AlSi9MnMoZr alloy has the best corrosion resistance, while the A380 alloy has always shown the worst corrosion resistance.

[0388] Compared with the yield strength and tensile strength, the elongation of the four die-cast aluminum alloys showed a rapid decline with the increase of corrosion time. The elongation of A356.2, A380, AlSi10MgMn and AlSi9MnMoZr alloys dropped to 38.6%, 25.6%, 41.5% and 25.8% of the pre-corrosion value, 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, corrosion products begin to form on the alloy surface, and Cl - The corrosion of the alloy continues, creating weak areas within the alloy that easily become stress concentration areas, thereby promoting the initiation and expansion of cracks during the tensile process. As the corrosion time increases, the number of weak areas within the alloy caused by corrosion increases, greatly promoting the initiation and expansion of cracks during the tensile process, resulting in a significant decrease in the alloy's plastic deformation capacity.

[0389] The three mechanical parameters UTS, El, and YS of the four die-cast aluminum alloys were fitted, as shown in Figures 19-22 and Table 3. The empirical relationships between the yield strength, ultimate tensile strength, and elongation of the four alloys and the corrosion equivalent time are shown in Formulas (4-1) to (4-12), respectively, as shown in Table 3. It can be found that there is no significant deviation between the fitting curves and the test results, and R 2 With the adjusted R 2 The YS, UTS and El represent the yield strength, ultimate tensile strength and elongation respectively.

[0390] Table 3. The second set of empirical relationships between mechanical parameters and equivalent corrosion time

[0391] 5. Correlation analysis between corrosion degree and mechanical parameters

[0392] As corrosion progresses, the mechanical properties of the material decrease. Generally speaking, the factors that affect mechanical properties are complex. For battery boxes, the special application environment of the battery box has a high degree of influence on corrosion resistance. The mechanical properties of metal materials can be predicted and the service life can be evaluated by using corrosion performance as a link.

[0393] Comparing the corrosion rate-equivalent corrosion time curves in Figures 15-18 and the mechanical parameter-equivalent corrosion time curves in Figures 19-22, it can be found that the response behavior of the corrosion rate and mechanical parameters to the equivalent corrosion time is quite different. This makes it difficult to effectively reflect the corrosion failure behavior of the sample using only the corrosion rate-equivalent corrosion time curve. Simply determining the corrosion rate cannot determine the extent of its impact on the service life. The above embodiment establishes a corresponding relationship between corrosion performance and service life by establishing a relationship between corrosion rate and mechanical properties.

[0394] Disadvantages of other analysis models: There are many factors that influence the attenuation of mechanical properties. In addition to corrosion factors, some environmental factors such as temperature, humidity, and electrolyte type can also affect mechanical properties, which makes it difficult to construct a prediction model that only includes mechanical performance parameters.

[0395] According to the tensile fracture analysis at different corrosion levels, it was found that there is a strong correlation between the corrosion level and the mechanical parameters, which verifies the feasibility of using the corrosion level-mechanical parameter analysis model established above to predict mechanical properties or service life.

[0396] Tensile fracture characterization method: scanning electron microscopy (SEM) technology, NOVA NanoSEM 230 low vacuum ultra-high resolution field emission electron microscope.

[0397] The fracture morphologies of four die-cast aluminum alloys, A356.2, A380, AlSi10MgMn, and AlSi9MnMoZr, were observed using scanning electron microscopy (SEM) before salt spray corrosion. The fracture of the A356.2 alloy exhibited dimples of varying sizes and cleavage steps, indicating a quasi-cleavage fracture pattern. The fracture surface of the A380 alloy exhibited large cleavage planes with virtually no dimples, demonstrating distinct brittle fracture characteristics. The fracture morphologies of the AlSi10MgMn and AlSi9MnMoZr alloys exhibited small cleavage facets roughly aligning with the grain size. This is because, in polycrystalline materials, while the macroscopic fracture surface is nearly perpendicular to the direction of maximum tensile stress, the cleavage planes of individual grains in the microstructure are not always perpendicular to the tensile stress. Furthermore, a small number of terraced cleavage steps and river-like patterns were observed on the fracture surface, along with tear ridges resulting from plastic deformation, indicating some plastic deformation.

[0398] The morphology of the fracture center (Core) and the fracture edge (Edge) close to the test surface of four die-cast aluminum alloy materials at different corrosion times (5d, 15d, 25d) can be observed by SEM technology.

[0399] The fracture morphology of the A356.2 alloy material at different corrosion times during the salt spray corrosion test: As the corrosion time increases, the morphology of the center of the fracture of the A356.2 alloy is very similar, still a quasi-cleavage morphology with dimples, but the number of dimples becomes smaller and less obvious. The fracture at 25 days is basically a cleavage morphology. The fracture edge of the A356.2 alloy is different. Many gray corrosion products appear on the fracture surface, and the defect area in the fracture gradually increases, and many small voids can be observed. As the corrosion time increases, the volume of the voids gradually increases and the number gradually increases. The strength of these defect locations will drop significantly, and it is easy for stress to accumulate, leading to the initiation and expansion of cracks, thereby significantly reducing the elongation of the A356.2 alloy.

[0400] The fracture morphology of the A380 alloy at different corrosion times during salt spray corrosion testing: The fracture morphology of the A380 alloy differs from that of the A356.2 alloy. The center of the fracture of the A380 alloy exhibits a cleavage fracture with the presence of corrosion products, indicating deeper corrosion. The cleavage step on the fracture surface gradually widens with increasing corrosion time. As corrosion progresses, the distinctions between the individual facets gradually disappear, and a large cleavage step forms where multiple parallel or nearly parallel dissociation planes of varying heights meet. Large cleavage planes initially appear at the fracture edge. As corrosion progresses, these planes crack into smaller facets, with numerous elongated microcracks forming between the facets. This indicates that corrosion has extended deep into the grains of the A380 alloy, resulting in numerous cracks extending from the surface deep into the grains. Consequently, its elongation decreases significantly. Furthermore, the presence of numerous corrosion products at the center of the fracture indicates deeper corrosion, leading to an increasing number of internal defects such as cracks, significantly impacting strength.

[0401] The fracture morphology of the AlSi10MgMn alloy material at different corrosion times during salt spray corrosion testing: there are many cleavage facets in the center of the fracture, 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 in the center of the fracture, which is particularly obvious when the corrosion time is longer (15d and 25d). Gray corrosion products are also observed at the edge of the fracture. As the corrosion progresses, the edge of the fracture splits from the larger cleavage steps into small planes separated by cracks. Compared with the A380 alloy, its number of corrosion products and small planes are less, indicating that it has better corrosion resistance.

[0402] Fracture morphologies of the AlSi9MnMoZr alloy at different corrosion times during salt spray corrosion testing: Compared to the AlSi10MgMn alloy, the fracture center exhibits numerous fine dimples and pronounced tear ridges, indicating greater plastic deformation. Dimple formation is a key characteristic of plastic fracture; greater numbers and smaller dimples indicate a greater plastic deformation capacity, leading to higher elongation than the AlSi10MgMn alloy. Furthermore, even at a relatively short corrosion time (5 days), numerous dimples and cleavage steps are still observed at the fracture edge, suggesting that the performance degradation of the AlSi9MnMoZr alloy is not significant at this time. With increasing corrosion time, the fracture edge morphology gradually transitions to a cleavage morphology, and a small amount of corrosion products begins to appear at the edge. At a longer corrosion time (25 days), numerous fine pores appear at the edge, but microcracks are minimal. Therefore, macroscopically, the yield strength and tensile strength of the AlSi9MnMoZr alloy do not decrease significantly, while the elongation decreases rapidly.

[0403] The above analysis results show that, under corrosive environments, for alloy samples exhibiting different mechanical failure behaviors and resulting in different fracture morphologies, there is a strong correlation between mechanical properties and equivalent corrosion time. Therefore, the aforementioned method for constructing a corrosion severity-mechanical parameter analysis model has a certain degree of universality, and the resulting analysis model can effectively analyze mechanical properties or service life.

[0404] 3. Electrochemical corrosion test

[0405] 1. Test analysis method

[0406] Electrochemical corrosion includes: open circuit voltage test, AC impedance test, and potentiodynamic polarization test.

[0407] Before the test, the die-cast aluminum alloy was cut into samples of 10 mm × 10 mm × 2 mm and the samples were cold mounted with epoxy resin to ensure that only 1 cm of the exposed area was 2 The test surface is also ground with sandpaper, then polished with a polishing agent until the sample surface is neat and bright, cleaned with ethanol, and dried for later use.

[0408] During the test, the open circuit voltage (OCP) of the sample was first measured. After the OCP stabilized for 60 minutes, the sample was subjected to an alternating current impedance spectroscopy (EIS) to measure the electrochemical impedance spectroscopy at different AC frequencies. A 10mV AC sine wave was used as the excitation voltage, and the test frequency was controlled within 0.01 to 105Hz.

[0409] After the test, the EIS results were fitted with an equivalent circuit to analyze the parameters of each component in the equivalent circuit diagram. Following the AC impedance test, the sample was subjected to potentiodynamic polarization testing. The scan rate was 0.167 mV / s, starting from an OCP potential of -300 mV, until the current exceeded 1 mA. After the test, the polarization characteristics of the sample were then Tafel fitted using ZSimpWin v3.40 software.

[0410] The structural diagram of the three-electrode system in the electrochemical corrosion test equipment used is shown in Figure 24. R, mA, and V represent the resistance meter, ammeter, and voltammeter, 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.

[0411] 2. Test results

[0412] Figure 25 shows the time-dependent curves of the open-circuit voltage (OCP) of the four die-cast aluminum alloys. The OCP values ​​of the four die-cast aluminum alloys stabilize at 300 s and remain stable at 1800 s, with minimal fluctuation. Changes in OCP values ​​are related to the formation of a 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 affect the formation of the surface layer and the surface reactions.

[0413] The AC impedance test results of four die-cast aluminum alloys can be found in Figure 26 and Table 4. Figures (a) and (b) show the Bode plot of the AC impedance spectrum (EIS), (c) the Nyquist plot, and (d) the equivalent circuit diagram. The Bode plots in Figure 26 (a) and the Phase plots in Figure 26 (b) show that the AlSi10MgMn alloy exhibits the highest impedance and phase angle at both low and high frequencies, followed by the A356.2 and A380 alloys, and finally the AlSi9MnMoZr alloy. The Nyquist plot (Figure 26 (c)) shows that all four alloys exhibit suppressed capacitance loops. The AlSi10MgMn alloy has the largest capacitance loop diameter, demonstrating superior capacitance performance and higher charge transfer resistance. The EIS test results were fitted to the specific component parameters using the equivalent circuit diagram in Figure 26 (d), as shown in Table 4.

[0414] In the equivalent circuit diagram, R s Represents the solution resistance associated with the corrosion solution used in the test, R sl 、Rct Respectively represent the surface resistance and charge transfer resistance of each alloy as the working electrode. 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 indicator to evaluate the degree of closeness between the actual experiment and the theoretical calculation. Q1 and Q2 represent the capacitance of the surface layer and the charge transfer layer during the establishment of the corrosion cell, corresponding to n1 and n2 respectively. The results show that because the corrosion solution is 3.5wt% NaCl solution, the R s 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, so the EIS result is only an analysis of the impending corrosion from the perspective of electrochemical thermodynamics. For some thermodynamically unstable metals, such as Al, Mg, Cr, etc., self-passivation will occur under appropriate conditions and transform from non-corrosion-resistant alloys to corrosion-resistant alloys. Therefore, studying corrosion behavior only from a thermodynamic point of view is one-sided, and the thermodynamic stability of die-cast aluminum alloy materials in corrosive media must also be considered. According to experimental data, AlSi9MnMoZr alloy will self-passivate in 3.5wt% NaCl solution and has excellent corrosion resistance.

[0415] Table 4. Equivalent circuit parameters

[0416] Figure 27 shows the potentiodynamic polarization curves of the electrochemical corrosion test. Table 5 lists the relevant potentiodynamic polarization parameters calculated based on the Tafel extrapolation method. corr ) are -0.450V, -0.415V, -0.585V, and -0.981V, respectively, which are very close to the OCP values. Based on the electrochemical corrosion behavior, these four die-cast aluminum alloy materials can be divided into two categories: one is the alloy with no obvious passivation, including A356.2 alloy and A380 alloy; the other has a significant passivation area, including AlSi10MgMn alloy and AlSi9MnMoZr alloy.

[0417] For the former alloys without obvious passivation, when evaluating the corrosion resistance, the corrosion current density (I corr ), I corr Low value, R p The alloys with higher E values ​​have better corrosion resistance. Through Tafel fitting, it can be found that the E values ​​of A356.2 and A380 alloys are corrVery close, but the I of A356.2 alloy corr Only about a quarter of A380, but its polarization resistance R p It is more than twenty times that of A380. Therefore, the corrosion resistance of A356.2 alloy is much better than that of A380 alloy.

[0418] For the latter, there is a significant passivation area. When studying its corrosion resistance, the passivation area of ​​the alloy should be analyzed. The corrosion current density (Current Density) slowly increases with the positive shift of the potential (potential) in the passivation area, which means that the expansion of the corrosion behavior is greatly slowed down. The passivation area prevents the development of corrosion behavior until the potential reaches the breakdown potential (E b ), the passive film is completely destroyed and corrosion begins to intensify. The results show that AlSi9MnMoZr alloy has a more obvious passive zone, E b It is -0.411V, which is higher than AlSi10MgMn alloy (-0.430V). corr Lower than AlSi9MnMoZr alloy, but the latter has a more stable passivation zone, which greatly slows down the expansion of corrosion behavior and has better corrosion resistance. c and B a are the cathode reaction slope and the anode reaction slope of Tafel fitting, respectively. c Both higher than B a , indicating that the electrochemical reaction is mainly controlled by the cathode process.

[0419] Table 5. Tafel fitting parameters

[0420] Regarding the surface morphology of the alloys after dynamic polarization, the A356.2 and A380 alloys exhibited primarily uniform corrosion, with the A380 alloy showing more corrosion products than the A356.2 alloy, further confirming its poor corrosion resistance. The AlSi10MgMn and AlSi9MnMoZr alloys exhibited primarily pitting corrosion after polarization due to the presence of a surface passive film. Furthermore, the pitting pits of the AlSi10MgMn alloy were larger and deeper than those of the AlSi9MnMoZr alloy, indicating that the passive film of the AlSi9MnMoZr alloy is more difficult to destroy, consistent with the results of the dynamic potential polarization curves.

[0421] Therefore, the parameters characterizing the degree of corrosion in electrochemical corrosion tests can also be used to construct a corrosion resistance-mechanical properties analysis model.

[0422] 4. Immersion corrosion test

[0423] 1. Test analysis method

[0424] Staged immersion corrosion involves analyzing the macromorphology, micromorphology, and corrosion rate of the box material every 10 days for a total test time of 30 days. In the application, 1 day = 1 day.

[0425] The sample for the immersion corrosion test may be a block of 15 mm x 15 mm x 2 mm.

[0426] Before the test, the test surface was ground and polished, then rinsed with deionized water and ethanol in turn. After drying and weighing, the sample was placed in a desiccator for storage and standby use. During the test, the sample was placed in a container and 500 mL of corrosion solution was added. The composition of the corrosion solution is: 3.5 wt% NaCl aqueous solution. After sealing, the entire container was placed in a constant temperature water bath tank with the temperature set to 25°C. Samples were taken every 10 days (i.e., the test time was 10 days, 20 days, and 30 days respectively) to observe the macroscopic and microscopic morphologies of the sample surface after corrosion. Subsequently, the corrosion products on the sample surface were removed, the sample mass before and after corrosion was compared, and the corresponding immersion corrosion rate was calculated. Three parallel samples were set for each test.

[0427] 2. Test results analysis

[0428] Immersion corrosion tests were conducted for 10, 20, and 30 days. The surface macromorphology of the samples at different immersion corrosion times can be seen in Figure 28. After immersion in a 3.5 wt% NaCl solution, the surfaces of all four die-cast aluminum alloys were covered with obvious corrosion products. Compared to the appearance of the samples before corrosion, the surfaces of the samples became rougher, with a black corrosion layer and gray pitting corrosion products. Furthermore, the corrosion products of A380 (Figure 28(b)) and AlSi10MgMn alloy (Figure 28(c)) were more obvious, indicating that their corrosion resistance was inferior to that of A356.2 (Figure 28(a)) and AlSi9MnMoZr alloy (Figure 28(d)). The A380 alloy had the most corrosion products on its surface, regardless of whether the samples were immersed for 10, 20, or 30 days, indicating that the A380 alloy had the worst corrosion resistance. After 10 days of immersion corrosion, the corrosion macromorphologies of the A356.2, AlSi10MgMn, and AISi9MnMoZr alloys were similar. However, after 20 and 30 days of immersion corrosion, the A356.2 alloy exhibited better corrosion resistance. However, due to the destruction of the passive film and the intensification of pitting corrosion, the AlSi10MgMn and AISi9MnMoZr alloys showed a large amount of white corrosion products on their surfaces. The surface of the AlSi10MgMn alloy had a larger area of ​​spotted white corrosion products, indicating that the AlSi9MnMoZr alloy had better corrosion resistance, which is consistent with the salt spray corrosion results.

[0429] The immersion corrosion rate was calculated based on the weight loss of the samples before and after immersion corrosion. The analysis results can be found in Figure 29. When the immersion time increased from 10 days to 20 days and 30 days, the corrosion rates of the four alloy materials increased to varying degrees. This is because as corrosion continues, more and more defects appear on the alloy surface, and corrosive Cl- is more easily adsorbed at these defects, thereby accelerating corrosion. After immersion in a 3.5wt% NaCl aqueous solution for 10 days, the corrosion rates of the A356.2, A380, AlSi10MgMn, and AlSi10MgMn alloys were 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 early stages of corrosion. After 30 days of immersion, the corrosion rates of A356.2, A380, AlSi10MgMn, and AlSi10MgMn alloys were 0.094 mm / y, 0.232 mm / y, 0.141 mm / y, and 0.111 mm / y, respectively, indicating that A356.2 alloy exhibited better corrosion resistance in the longer immersion corrosion test. The degradation of the passive film and the intensification of pitting corrosion were the main reasons for the decreased corrosion resistance of the AlSi9MnMoZr alloy.

[0430] Therefore, the parameters related to the corrosion degree in the immersion corrosion test can also be used to construct a corrosion resistance-mechanical properties analysis model.

[0431] 5. Application of Model Building Method

[0432] (1) Test samples and test methods

[0433] An aluminum alloy sample (referred to as N1) was used, and the composition of the alloy material can be found in Table 6.

[0434] Table 6. Nominal composition and actual composition of aluminum alloy sample N1

[0435] The element contents in Table 6 refer to the mass percentage in the aluminum alloy material, in wt%.

[0436] Taking the Mn element as an example, the corresponding ingredients of the Mn element are recorded as "Mn ingredients".

[0437] The ingredients of each element are: AlSi 20 (Si ingredients), AlCu 50 (Cu ingredient), AlTi5 (Ti ingredient), Zn (Zn ingredient), Mg (Mg ingredient), AlMn 10 (Mn ingredient), AlSr 10 (Sr ingredients) and Al. Taking 1 kilogram (kg) as an example, the Zn burn-out rate is 12% and the Mg burn-out rate is 15%.

[0438] The Fe element is introduced during the preparation process and is an inevitable impurity element rather than an active addition.

[0439] Aluminum alloy material N1 was prepared by the following method:

[0440] (1) First, add pure aluminum ingots to a smelting furnace and heat to 740°C. After the temperature is maintained and melted, add Mn ingredients. After Mn is melted, add Cu ingredients. After the temperature drops to 710°C, add Si ingredients, Ti ingredients, Zn ingredients, and Sr ingredients and melt them. After the above elements are melted, add Mg ingredients. After the Mg ingredients are melted, let them stand and slag, add refining agents, and after slag removal, add Ti ingredients and Sr ingredients. Finally, cast and mold to obtain an ingot of preset size. The preset size is the sample size required for the test.

[0441] (2) The ingot is kept at 550°C for 2 hours and then cooled to room temperature (20°C to 30°C) with water. The obtained aluminum alloy material is a die-cast aluminum alloy sample. The aluminum alloy material can be used as the main material or component material of a battery case, including but not limited to the main material or component material of a lithium battery case, a fuel cell case, etc.

[0442] An inductively coupled plasma optical emission spectrometer (ICP, Avio 5000) was used for elemental analysis to accurately measure the actual composition of the aluminum alloy. The ICP test results showed that the actual composition of the aluminum alloy was very close to its nominal composition, indicating good melting results.

[0443] (2) Test method:

[0444] The test conditions and sampling time points of the salt spray corrosion test, tensile test, electrochemical corrosion test and immersion test are the same as those in the previous second, third and fourth parts.

[0445] (3) Test analysis results

[0446] The empirical relationship model between corrosion rate and equivalent corrosion time (the first set of empirical relationships) is shown in formulas (5-1 to 5-3), which can be found in Table 7 and Figure 30. It can be found that using the function y = a·b x After fitting the corrosion rate piecewise with the function y=a+b·x, the fitting results are basically consistent with the experimental results.

[0447] The results of the fitting of the relationship between mechanical properties and corrosion time can be found in Figure 31 and the second set of empirical relationships between mechanical parameters and equivalent corrosion time in Table 8. The fitting results are generally consistent with the experimental results.

[0448] Table 7.

[0449] Table 8.

[0450] The above description of various embodiments and examples tends to emphasize the differences between the various embodiments and examples. The same or similar aspects can be referenced to each other and will not be repeated here for the sake of brevity.

[0451] The technical features of the various embodiments and examples described above can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments and examples are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0452] It should be noted that the present application is not limited to the above-mentioned embodiments and examples. The above-mentioned embodiments and examples are only examples, and within the scope of the technical solution of the present application, embodiments that have substantially the same structure as the technical idea and exert the same effect are all included in the technical scope of the present application. The above-described embodiments and examples only express several embodiments of the present application, and the description thereof is relatively detailed, but it cannot be understood as a limitation on the scope of the patent. In addition, without departing from the scope of the subject matter of the present application, other methods of applying various modifications that can be thought of by those skilled in the art to the embodiments or examples, and combining some of the constituent elements in the embodiments or examples to construct the embodiments are also included in the scope of the present application.

Claims

1. A method for constructing a corrosion resistance-mechanical properties analysis model of a metal material, comprising the following steps: Taking metal materials as test objects, the test values ​​of corrosion parameters at different equivalent corrosion time points under corrosion test conditions are obtained to obtain a corrosion performance test experimental data set, and the test values ​​of mechanical parameters at different corrosion degrees corresponding to the different equivalent corrosion time points are obtained to obtain a 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 metal materials according to claim 1, wherein: The mechanical parameter includes at least one of tensile strength at break and elongation at break.

3. The method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to claim 1 or 2, wherein: 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, which satisfies 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 a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 4, which satisfies 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, wherein: 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, wherein: 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 metal materials according to claim 7, wherein: 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 a corrosion resistance-mechanical properties analysis model of a metal material according to claim 8, wherein: 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, wherein: 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, wherein: The second set of empirical relationships between the mechanical parameters and the equivalent corrosion time established 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 a corrosion resistance-mechanical properties analysis model of a metal material according to claim 11, wherein: 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 a corrosion resistance-mechanical properties analysis model of a metal material according to claim 12, wherein: 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 the corrosion resistance-mechanical properties analysis model of the metal material according to any one of claims 1 to 13 further comprises 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.

15. A method for constructing a corrosion resistance-mechanical properties analysis model of a metal material according to any one of claims 1 to 14, comprising the following steps: establishing a fourth set of empirical equations between the corrosion rate and the equivalent corrosion time under the corrosion test conditions, wherein the first set of empirical equations includes the fourth set of empirical equations.

16. A method for analyzing the service life of a metal material, wherein: 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, wherein: 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, wherein: The method of obtaining 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 includes: 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, wherein: 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, wherein: 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 service life analysis device for metal materials, wherein: The metal material is as defined in any one of claims 1 to 3; The service life analysis device of the metal material comprises: The corrosion performance data acquisition module is 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 mechanical parameters related to the failure behavior of the metal material according to the target service environment of the metal material. The test value of the corrosion degree 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 a metal material, wherein: 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 a metal material, wherein: 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, wherein: 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, wherein: 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, comprising: 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, wherein: The battery cells include fuel cell cells.

28. The electrical device according to claim 26, wherein: The battery cells include lithium battery cells.

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