Weld seam reliability evaluation method, device and computer equipment

Abstract

The weld reliability evaluation method, device and computer equipment provided by this application, when evaluating the weld reliability of a target lithium battery, first determine the static fatigue strength and dynamic fatigue strength of the target lithium battery according to the expansion force data and the battery shell area of the target lithium battery, and then predict in advance the dynamic and static fatigue damage of the battery within the target service cycle; for example, predicting the static fatigue strength and the target service cycle through a static fatigue damage model to obtain the reduction in burst strength, and predicting the dynamic fatigue strength, the target service cycle and the initial burst strength through a dynamic remaining strength model to obtain the dynamic remaining burst strength. Therefore, this application can determine the final remaining burst strength of the target lithium battery after the target service cycle through the dynamic and static fatigue damage predicted by these two models, and then evaluate the reliability of the battery weld, thereby significantly improving the accuracy of the evaluation results.

Description

Technical Field

[0001] The present application relates to the technical field of lithium batteries, and particularly to a method and device for evaluating the reliability of weld seams and a computer device. Background Art

[0002] In the structure and operation mechanism of lithium batteries, the weld seam, as a key part connecting the outer shell and the cover plate, its reliability is directly related to the overall performance and safety of the battery. During the charge and discharge cycle of the lithium battery, the electrodes inside the wound core will experience periodic changes in thickening and restoration, resulting in reciprocating bulging and restoration of the outer shell, especially the surface parallel to the electrodes, and thus generating dynamic mechanical fatigue damage at the weld seam position. At the same time, during the long-term storage of the battery, side reactions will still occur inside the battery. The occurrence of side reactions will generate gas, increasing the internal pressure of the battery, and exerting a certain pulling force on the weld seam. At the same time, the stable form of the electrode will also exert a continuous static resistance force on the weld seam, causing static fatigue damage to the weld seam. Therefore, during the actual service process of the weld seam, the battery weld seam is affected by both dynamic damage and static damage.

[0003] Since the reliability of the weld seam is directly related to whether the battery will experience electrolyte leakage, performance degradation, and even safety accidents, it is particularly important to accurately and reliably evaluate the weld seam. Through the reliability evaluation of the weld seam, the life performance of the weld seam under different working conditions can be predicted, potential safety hazards can be discovered in a timely manner, and a scientific basis can be provided for the design optimization of the battery. However, the current evaluation of weld seam reliability lacks exploration of the dynamic and static fatigue damage of lithium batteries, resulting in relatively low accuracy of the evaluation results. Summary of the Invention

[0004] The purpose of the present application is to at least solve one of the above technical defects, especially the technical defect that the evaluation of weld seam reliability in the prior art lacks exploration of the dynamic and static fatigue damage of lithium batteries, resulting in relatively low accuracy of the evaluation results.

[0005] The present application provides a method for evaluating the reliability of weld seams, the method comprising:

[0006] Obtain a target lithium battery, and determine the expansion force data, the area of the battery outer shell, and the initial burst strength of the target lithium battery, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery within a target service cycle based on the expansion force data and the area of the battery outer shell;

[0007] Input the static fatigue strength and the target service cycle into a preset static fatigue damage model to obtain the amount of decrease in burst strength output by the static fatigue damage model;

[0008] Determine the fatigue ratio of the target lithium battery based on the target service life cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength to obtain the dynamic remaining burst strength of the target lithium battery;

[0009] Determine the final remaining burst strength of the target lithium battery according to the burst strength decrease amount and the dynamic remaining burst strength, and evaluate the weld reliability of the target lithium battery based on the final remaining burst strength.

[0010] Optionally, the expansion force data includes the full charge expansion force, the storage expansion force, and the full discharge expansion force;

[0011] The determining of the static fatigue strength and the dynamic fatigue strength of the target lithium battery within the target service life cycle based on the expansion force data and the battery housing area includes:

[0012] Determine the pre-tightening force of the target lithium battery, and use a static fatigue strength algorithm to calculate the full charge expansion force, the storage expansion force, the pre-tightening force, and the battery housing area to obtain the static fatigue strength of the target lithium battery within the target service life cycle;

[0013] Use a dynamic fatigue strength algorithm to calculate the full charge expansion force, the full discharge expansion force, and the battery housing area to obtain the dynamic fatigue strength of the target lithium battery within the target service life cycle.

[0014] Optionally, the static fatigue strength algorithm includes:

[0015]

[0016] where, represents the static fatigue strength; represents the full charge expansion force; represents the storage expansion force; represents the pre-tightening force; represents the battery housing area.

[0017] Optionally, the dynamic fatigue strength algorithm includes:

[0018]

[0019] where, represents the full charge expansion force; represents the full discharge expansion force; represents the battery housing area.

[0020] Optionally, the expression of the static fatigue damage model includes:

[0021]

[0022] Wherein, represents the decrease in burst strength output by the static fatigue damage model; represents the ambient temperature; Pt represents the static fatigue strength, characterizing the pressure holding pressure; t represents the pressure holding time of the target lithium battery during the target service cycle.

[0023] Optionally, determining the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength includes:

[0024] Determining the weld fatigue life corresponding to the dynamic fatigue strength according to a preset S-N curve, and determining the weld fatigue times of the target lithium battery according to the target service cycle;

[0025] Calculating the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

[0026] Optionally, the expression of the dynamic remaining strength model includes:

[0027]

[0028] Wherein, represents the dynamic remaining burst strength output by the dynamic remaining strength model; represents the initial burst strength; represents the dynamic fatigue strength; represents the fatigue ratio.

[0029] Optionally, evaluating the weld reliability of the target lithium battery based on the final remaining burst strength includes:

[0030] Judging whether the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength;

[0031] If so, it is confirmed that the weld of the target lithium battery is reliable during the target service cycle;

[0032] If not, it is confirmed that the weld of the target lithium battery is unreliable during the target service cycle.

[0033] The present application also provides a weld reliability evaluation device, including:

[0034] A fatigue strength determination module, configured to obtain a target lithium battery, and determine the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery during the target service cycle based on the expansion force data and the battery housing area;

[0035] A static fatigue strength decline prediction module, configured to input the static fatigue strength and the target service cycle into a preset static fatigue damage model, and obtain the amount of decline in burst strength output by the static fatigue damage model;

[0036] A remaining strength prediction module, configured to determine the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength, so as to obtain the dynamic remaining burst strength of the target lithium battery;

[0037] A reliability evaluation module, configured to determine the final remaining burst strength of the target lithium battery according to the amount of decline in burst strength and the dynamic remaining burst strength, and evaluate the weld reliability of the target lithium battery based on the final remaining burst strength.

[0038] This application also provides a computer device, including: one or more processors, and a memory;

[0039] Computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the one or more processors, the steps of the weld reliability evaluation method described in any one of the above embodiments are executed.

[0040] It can be seen from the above technical solutions that the embodiments of this application have the following advantages:

[0041] The weld reliability evaluation method, device and computer equipment provided by this application can, when evaluating the weld reliability of a target lithium battery, first determine the expansion force data, battery shell area and initial burst strength of the target lithium battery, so as to determine the static fatigue strength and dynamic fatigue strength of the target lithium battery according to the expansion force data and the battery shell area, which are used as the basic data for predicting the damage of dynamic and static fatigue strength. Then, the static fatigue strength and the target service cycle can be input into a preset static fatigue damage model to obtain the amount of burst strength reduction output by the static fatigue damage model, so as to predict in advance the static fatigue damage of the weld of the target lithium battery within the target service cycle. At the same time, this application can also determine the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, fatigue ratio and initial burst strength to obtain the dynamic remaining burst strength, so as to realize the advance prediction of the dynamic fatigue damage of the weld of the target lithium battery within the target service cycle. Finally, the final remaining burst strength can be determined according to the amount of burst strength reduction and the dynamic remaining burst strength, and the weld reliability of the target lithium battery can be evaluated based on the final remaining burst strength. Through this method, this application can predict in advance the dynamic and static fatigue damage of the target lithium battery within the target service cycle through the static fatigue damage model and the dynamic remaining strength model, and use it to evaluate the reliability of the battery weld, thus significantly improving the accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic flowchart of a weld reliability evaluation method provided by an embodiment of this application;

[0044] Figure 2 It is a schematic curve diagram of the change of expansion force during the cyclic process provided by an embodiment of this application;

[0045] Figure 3 It is a schematic diagram of the relationship between the battery expansion force and the number of battery cycles provided by an embodiment of this application;

[0046] Figure 4 It is a schematic curve diagram of the change of expansion force during the storage process provided by an embodiment of this application;

[0047] Figure 5Schematic diagram of the relationship between ambient temperature and burst strength provided by an embodiment of the present application;

[0048] Figure 6 Schematic diagram of the relationship between holding pressure strength and burst strength provided by an embodiment of the present application;

[0049] Figure 7 Schematic diagram of the relationship between holding pressure time and burst strength provided by an embodiment of the present application;

[0050] Figure 8 Schematic diagram of the relationship between fatigue ratio and dynamic remaining burst strength provided by an embodiment of the present application;

[0051] Figure 9 Schematic diagram of the curve of the change in the static fatigue strength of the battery during service provided by an embodiment of the present application;

[0052] Figure 10 Schematic diagram of the curve of the change in the dynamic fatigue strength of the battery during service provided by an embodiment of the present application;

[0053] Figure 11 Schematic diagram of the structure of an S-N curve provided by an embodiment of the present application;

[0054] Figure 12 Schematic diagram of the structure of a weld reliability evaluation device provided by an embodiment of the present application;

[0055] Figure 13 Schematic diagram of the internal structure of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0056] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0057] Since the reliability of the weld directly relates to whether the battery will experience electrolyte leakage, performance degradation, and even safety accidents, it is particularly important to accurately and reliably evaluate the weld. By evaluating the reliability of the weld, the life performance of the weld under different working conditions can be predicted, potential safety hazards can be discovered in a timely manner, and a scientific basis can be provided for the design optimization of the battery. However, the current weld reliability evaluation lacks the exploration of dynamic and static fatigue damage of lithium batteries, resulting in relatively low accuracy of the evaluation results.

[0058] Based on this, the present application proposes the following technical solutions. For details, please refer to the following text:

[0059] In one embodiment, as Figure 1 shown, Figure 1 is a schematic flow chart of a method for evaluating the reliability of a weld seam provided by an embodiment of the present application; the present application provides a method for evaluating the reliability of a weld seam, which specifically includes the following:

[0060] S110: Obtain a target lithium battery, and determine the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery during the target service cycle based on the expansion force data and the battery housing area.

[0061] In this step, when the computer device evaluates the weld seam reliability of the target lithium battery, it can first determine the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery, and then determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery during the target service cycle based on the expansion force data and the battery housing area, and use them as the basic data for predicting the dynamic and static fatigue strength damage.

[0062] Among them, the expansion force data refers to the force generated by the volume expansion caused by the electrochemical reaction during the charge and discharge process of the lithium battery. This expansion force changes continuously with different stages of the charge and discharge process. Therefore, the expansion force data can include expansion forces at different stages such as full charge expansion force, full discharge expansion force, and storage expansion force. Specifically, the expansion force data can be the change data of the full charge expansion force, the full discharge expansion force, and the storage expansion force during the service cycle, that is, a relationship curve with the service cycle as the independent variable and the full charge expansion force, the full discharge expansion force, and the storage expansion force as the dependent variables respectively, and the size of the expansion force inside the battery case is reflected through this relationship. In addition, the battery housing area in the present application refers to the area of the lithium battery housing parallel to the larger side of the electrode plate. For example, for a square shell lithium battery, the battery housing area can be the area of the largest side of the housing; the initial burst strength refers to the tensile or shear strength of the weld seam when it is just produced, and it is a basic index for evaluating the weld seam quality; the target service cycle refers to the expected working time or the number of charge and discharge cycles of the lithium battery in actual use. It should be noted that the method for obtaining the initial burst strength is as follows: ventilate the inside of the battery, the air pressure inside the battery will gradually increase, and when the weld seam cracks and leaks air, the air pressure inside the battery is the burst strength of the weld seam.

[0063] It can be understood that when a lithium battery is just produced, the weld seam has an initial burst strength. When the weld seam is under a certain pressure for a certain period of time at a certain temperature, static fatigue damage will occur, resulting in a decrease in the weld seam strength. After the lithium battery is put into use, during the charging and discharging process, in the charging stage, the electrode sheets that make up the battery core will thicken, and in the discharging stage, the electrode sheets that make up the battery core will recover somewhat. The change in the thickness of the electrode sheets during this process will cause the battery housing parallel to the electrode sheets to bulge outwards and then recover, bulge outwards and then recover again, in a cyclic period change similar to the breathing effect, resulting in dynamic fatigue damage to the welding position between the battery housing and the cover plate in the lithium battery. Based on this, the computer device can obtain the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery as the basic data for fatigue strength prediction, and then can predict in advance the static fatigue strength and dynamic fatigue strength of the target lithium battery within the target service life cycle.

[0064] Specifically, the computer device can directly measure and obtain the battery housing area and the initial burst strength, and the expansion force data can be obtained through single-battery stage charging and discharging cycle tests and monitoring. In a specific implementation, the computer device can select a lithium iron phosphate 166Ah battery to form a battery pack and place the battery pack in a constant temperature room at 25°C in an energy storage station for operation; the charging and discharging process of the battery pack is as follows:

[0065] Step 1: Discharge the battery pack at a constant current of 1C until the voltage reaches 2.5V, and the discharge time is about 1 hour;

[0066] Step 2: Leave the discharged battery pack for 30 minutes;

[0067] Step 3: Charge the battery pack step by step until the voltage reaches 3.65V, and the charging time is about 1 hour; among them, the step charging includes: constant current charging at 1.5C for 12 minutes, constant current charging at 1C for 30 minutes, constant current charging at 0.5C for 12 minutes, and constant current charging at 0.33C until 3.65V;

[0068] Step 4: Leave the fully charged battery pack for 30 minutes.

[0069] In the above implementation, C represents the rate, 1C = 166A; when the battery pack completes one process from Step 1 to Step 4, it means that the battery has cycled once. It should be noted that as the service time of the battery increases, the battery performance decreases. Therefore, under the same state during the charging and discharging process of the battery, the expansion force will gradually increase with time, and the overall change trend of the expansion force during the charging and discharging process is the same.

[0070] Schematically, as Figure 2 and Figure 3 shown, Figure 2 is a schematic diagram of the change curve of the expansion force during the cycle process provided by the embodiment of the present application.Figure 3 This is a schematic diagram showing the relationship between the swelling force of a battery and the number of battery cycles provided by an embodiment of the present application. Specifically, Figure 2 Take the battery for two cycles, that is, draw the variation curves of the swelling force and the charge-discharge rate for two charge-discharge cycles to observe the actual variation of the swelling force. Among them, a negative rate indicates discharge, a rate of 0 indicates standby, and a positive rate indicates charging. From Figure 2 it can be seen that during the charging process of the battery, the swelling force shows an increasing trend; during the standby process, the swelling force basically remains unchanged; while during the discharging process, the swelling force shows a decreasing trend. Figure 3 Take the maximum and minimum values during each charge-discharge process within the service life cycle. Among them, the maximum value is the swelling force after the battery is charged, that is, the full charge swelling force, and the minimum value is the swelling force after the battery is discharged, that is, the full discharge swelling force. Assume that the target service life cycle of the present application is 10 years, with one charge-discharge per day and the rest of the time being the storage time of the battery. Then the relationship curves of the full charge swelling force and the full discharge swelling force of the target lithium battery changing with time within the service life cycle are as Figure 3 shown, where the solid line is the full charge swelling force curve and the dashed line is the full discharge swelling force curve.

[0071] In addition, as Figure 4 shown, Figure 4 This is a schematic curve diagram showing the change of the swelling force during the storage process provided by an embodiment of the present application, which can be obtained through actual measurement; Figure 4 It exemplifies the change of the swelling force of the target lithium battery of a 166Ah single cell during storage at 25°C and 100% SOC state, that is, the relationship between the storage swelling force of the target lithium battery changing with time within the service life cycle. Specifically, during the storage time of the target lithium battery within the service life cycle, due to the interaction between internal materials such as the positive and negative electrode materials and the electrolyte and the external environment such as temperature and humidity, as well as the possible slow chemical reactions occurring inside the battery, it will cause a slight change in the overall size of the winding core inside the battery case, thereby generating a storage swelling force, which will also affect the stability and actual service life cycle of the target lithium battery.

[0072] S120: Input the static fatigue strength and the target service life cycle into a preset static fatigue damage model to obtain the decrease in the burst strength output by the static fatigue damage model.

[0073] In this step, after determining the static fatigue strength of the target lithium battery through step 110, the computer device can obtain the pre-established static fatigue damage model, and then input the static fatigue strength and the target service life cycle into this static fatigue damage model, and then the decrease in the burst strength output by the static fatigue damage model can be obtained, so as to realize the early prediction of the static fatigue damage of the target lithium battery within the target service life cycle.

[0074] Specifically, the static fatigue damage model of the present application is established through experimental design and is used to describe the relationship between the decrease in the burst strength of the lithium battery weld seam, the ambient temperature, the holding pressure (static fatigue strength), and the holding time. The specific experimental design process is as follows:

[0075] Step 1: Determine the burst strength of the lithium battery weld seam in the initial state.

[0076] In this step, select multiple welded parts between the battery case and the battery cover plate. The number of selected parts can be 10. Then, successively test the burst strength of each welded part. Next, remove the welded parts corresponding to the outliers in the test results, and calculate the average value of the burst strength of the remaining welded parts as the burst strength of the lithium battery weld seam in the initial state.

[0077] Step 2: Determine the relationship between the temperature and the burst strength of the lithium battery weld seam.

[0078] In this step, place the welded parts in different ambient temperatures and leave them for a fixed time. Then, test the burst strength of the weld seams of the welded parts, and analyze the relationship between the decrease in burst strength and the ambient temperature. Among them, the ambient temperature can be set according to a certain gradient, such as 25°C, 60°C, 100°C, 140°C, 180°C, 220°C. Then, place multiple samples at each ambient temperature and leave them for one hour. The number of samples placed can be 3 or 5, and there is no limit here. After the experiment, measure the burst strength of the weld seams of each welded part again, and calculate the decrease in burst strength. The decrease in burst strength is equal to the burst strength of the weld seam in the initial state minus the burst strength after being left at a certain temperature. Finally, analyze the relationship between the decrease in burst strength of the weld seam and the ambient temperature according to the measurement results. Schematically, as Figure 5 shown, Figure 5 is a schematic diagram of the relationship between the ambient temperature and the burst strength provided by the embodiment of the present application; it can be seen from Figure 5 that there is a linear relationship between the decrease in burst strength of the lithium battery weld seam and the ambient temperature.

[0079] Step 3: Determine the relationship between the holding pressure and the burst strength of the lithium battery weld seam.

[0080] In this step, the welded part is sealed, and a certain air pressure is introduced inside the housing and the cover plate, so that the weld seam is under a certain pressure, that is, the pressure holding pressure. Then, it is left for a fixed time at a certain ambient temperature. Among them, the pressure holding pressure can be set according to a certain gradient, such as 0.2 Mpa, 0.4 MPa, 0.6 MPa, 0.8 MPa, 1 MPa, 1.2 MPa. 3-5 samples are placed under each pressure holding pressure. The ambient temperature can be 60 °C, and the leaving time can be 1 hour. After the experiment, the burst strength of the welded part is tested, and then the relationship between the decrease in burst strength and the pressure holding pressure is analyzed according to the test results. Schematically, as Figure 6 shown, Figure 6 is a schematic diagram of the relationship between the pressure holding strength and the burst strength provided by the embodiment of the present application; from Figure 6 it can be seen that there is an exponential relationship between the decrease in the burst strength of the lithium battery weld seam and the pressure holding pressure.

[0081] Step 4: Determine the relationship between the pressure holding time and the burst strength of the lithium battery weld seam.

[0082] In this step, the welded part is sealed, and the weld seam is left for different times at a certain ambient temperature and a certain pressure holding pressure. The time under a certain pressure here is called the pressure holding time. Among them, the pressure holding time can be set according to a certain gradient, such as 1 h, 2 h, 3 h, 4 h, 5 h, 6 h. 3-5 samples are placed under each pressure holding time. The pressure holding pressure can be 0.6 MPa, or half of the burst strength in the initial state, and the ambient temperature can be 60 °C. After the experiment, the burst strength of the welded part is tested, and then the relationship between the decrease in burst strength and the pressure holding time is analyzed according to the test results. Schematically, as Figure 7 shown, Figure 7 is a schematic diagram of the relationship between the pressure holding time and the burst strength provided by the embodiment of the present application; from Figure 7 it can be seen that there is a logarithmic relationship between the decrease in the burst strength of the lithium battery weld seam and the pressure holding time.

[0083] Based on the above experimental results, the computer device can build a static fatigue damage model according to the relationship between the ambient temperature, pressure holding pressure (static fatigue strength), pressure holding time of the lithium battery weld seam and the decrease in burst strength. Therefore, when the computer device inputs the static fatigue strength and the target service life cycle into the static fatigue damage model, the decrease in burst strength output by the static fatigue damage model can be directly obtained. Among them, the pressure holding time of the target lithium battery can be calculated through the target service life cycle, that is, the leaving time of the target lithium battery during the target service life cycle.

[0084] S130: Determine the fatigue proportion of the target lithium battery based on the target service life cycle and the dynamic fatigue strength, and use the preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, fatigue proportion, and initial burst strength, so as to obtain the dynamic remaining burst strength of the target lithium battery.

[0085] In this step, after determining the dynamic fatigue strength of the target lithium battery through step S110, based on the target service life cycle and the initial burst strength, the computer device can determine the fatigue proportion of the target lithium battery based on the target service life cycle and the dynamic fatigue strength, and obtain the pre-established dynamic remaining strength model. Then, input the dynamic fatigue strength, fatigue proportion, and initial burst strength into the dynamic remaining strength model to obtain the dynamic remaining burst strength output by the dynamic remaining strength model, realizing the early prediction of static fatigue damage of the target lithium battery within the target service life cycle.

[0086] Among them, the fatigue proportion refers to the proportion of the fatigue load that the weld has withstood relative to its design life at the target strength level, which is used to convert the complex fatigue damage process of the weld into a quantifiable and intuitively understandable parameter, and it can be calculated based on the target service life cycle and the dynamic fatigue strength.

[0087] Specifically, the dynamic remaining strength model of this application is established through designed experiments and is used to describe the relationship between the fatigue proportion of the lithium battery weld and the dynamic remaining burst strength. During the experiment, welded parts with different dynamic fatigue strengths and different fatigue proportions can be selected, and then the welds are directly burst, and the dynamic remaining burst strength of the welded parts is recorded. According to the experimental results, the computer device can statistically obtain the relationship between the fatigue proportion and the dynamic remaining burst strength. The experimental design here can be shown in the following table:

[0088]

[0089] Schematically, as Figure 8 shown, Figure 8 is a schematic diagram of the relationship between the fatigue proportion and the dynamic remaining burst strength provided by an embodiment of this application; Figure 8 The example shows the experimental results obtained by bursting the welds according to the above table experimental design. After determining the remaining burst strength corresponding to different fatigue proportions in the welded parts with dynamic fatigue strengths of 0.3 MPa and 0.26 MPa, the computer device can also perform curve fitting on the burst data of the two dynamic fatigue strengths respectively, and determine the relationship between the fatigue proportion and the dynamic remaining burst strength according to the fitting results.

[0090] Based on the above experimental results, the computer device can build a dynamic remaining strength model according to the relationship between the fatigue ratio of the lithium battery weld seam and the dynamic remaining burst strength. Therefore, after inputting the dynamic fatigue strength, fatigue ratio, and initial burst strength into the dynamic remaining strength model, the computer device can directly obtain the dynamic remaining burst strength output by the dynamic remaining strength model.

[0091] S140: Determine the final remaining burst strength of the target lithium battery according to the burst strength decrease amount and the dynamic remaining burst strength, and evaluate the weld seam reliability of the target lithium battery based on the final remaining burst strength.

[0092] In this step, through steps S120 and S130, the burst strength decrease amount and the dynamic remaining burst strength of the target lithium battery are obtained. The computer device can calculate the final remaining burst strength of the target lithium battery according to the burst strength decrease amount and the dynamic remaining burst strength, and then can evaluate the weld seam reliability of the target lithium battery based on the final remaining burst strength.

[0093] It can be understood that the burst strength decrease amount reflects the attenuation of the anti-destruction ability of the lithium battery weld seam during the battery storage process, and is an important parameter for evaluating the degree of weld seam fatigue damage, which can reflect the attenuation situation of the weld seam in a static environment; while the dynamic remaining burst strength is the remaining strength value of the weld seam during the fatigue cycle, which can reflect the actual load-bearing capacity of the weld seam in a dynamic environment. Therefore, through these two parameters, the computer device can accurately calculate the final remaining burst strength of the target lithium battery and use it as a basic index for evaluating the weld seam reliability of the target lithium battery.

[0094] Specifically, the final remaining burst strength can directly reflect the ultimate destructive force that the weld seam can withstand after experiencing cumulative fatigue damage, and can provide a scientific basis for predicting the reliability and remaining service life of the weld seam. Among them, when the final remaining burst strength is relatively high, it indicates that the damage to the lithium battery weld seam is small and the reliability is high; on the contrary, when the final remaining burst strength is relatively low, it indicates that the damage to the lithium battery weld seam is large and there is a risk of weld seam failure. Therefore, measures such as repair or replacement need to be taken.

[0095] In the above embodiments, when evaluating the weld reliability of the target lithium battery, the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery can be determined first, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery according to the expansion force data and the battery housing area, which serve as the basic data for predicting the dynamic and static fatigue strength damage. Then, the static fatigue strength and the target service life cycle can be input into a preset static fatigue damage model to obtain the amount of burst strength reduction output by the static fatigue damage model, thereby predicting in advance the static fatigue damage of the weld of the target lithium battery within the target service life cycle. At the same time, the present application can also determine the fatigue ratio of the target lithium battery based on the target service life cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength to obtain the dynamic remaining burst strength, so as to realize the advance prediction of the dynamic fatigue damage of the weld of the target lithium battery within the target service life cycle. Finally, the final remaining burst strength can be determined according to the amount of burst strength reduction and the dynamic remaining burst strength, and the weld reliability of the target lithium battery can be evaluated based on the final remaining burst strength. Through this method, the present application can predict in advance the dynamic and static fatigue damage of the target lithium battery within the target service life cycle through the static fatigue damage model and the dynamic remaining strength model, and use them to evaluate the reliability of the battery weld, thereby significantly improving the accuracy of the evaluation results.

[0096] In one embodiment, the expansion force data in step S110 may include the full charge expansion force, the storage expansion force, and the full discharge expansion force; wherein, the process of determining the static fatigue strength and the dynamic fatigue strength of the target lithium battery within the target service life cycle according to the expansion force data and the battery housing area may include:

[0097] S111: Determine the pre-tightening force of the target lithium battery, and use the static fatigue strength algorithm to calculate the full charge expansion force, the storage expansion force, the pre-tightening force, and the battery housing area to obtain the static fatigue strength of the target lithium battery within the target service life cycle.

[0098] S112: Use the dynamic fatigue strength algorithm to calculate the full charge expansion force, the full discharge expansion force, and the battery housing area to obtain the dynamic fatigue strength of the target lithium battery within the target service life cycle.

[0099] In this embodiment, when calculating the static and dynamic fatigue strengths, the computer device may first obtain the full charge expansion force, storage expansion force, and full discharge expansion force in the expansion force data, and determine the pre-tightening force of the target lithium battery, so that the static fatigue strength algorithm can be used to calculate the full charge expansion force, storage expansion force, pre-tightening force, and battery housing area, and obtain the static fatigue strength of the target lithium battery within the target service cycle; at the same time, the computer device can also use the dynamic fatigue strength algorithm to calculate the full charge expansion force, full discharge expansion force, and battery housing area, and obtain the dynamic fatigue strength of the target lithium battery within the target service cycle.

[0100] It should be noted that during the charge and discharge process of the lithium battery, a fixture needs to be attached, and a certain force is applied to the fixture to generate a certain extrusion force on the lithium battery. Here, the extrusion force is the pre-tightening force.

[0101] It can be understood that the static fatigue strength algorithm is mainly used to evaluate the fatigue strength of the target lithium battery under a constant load, that is, the fatigue strength generated during storage; since the battery in the target lithium battery is stored after being fully charged, it is only affected by the full charge expansion force, storage expansion force, and pre-tightening force. Therefore, the computer device can directly calculate the full charge expansion force, storage expansion force, warning force, and battery housing area through this static fatigue strength algorithm, and obtain the static fatigue strength of the target lithium battery within the target service cycle.

[0102] In addition, the dynamic fatigue strength algorithm is mainly used to evaluate the fatigue strength of the target lithium battery under repeated or rapidly changing loads, that is, the dynamically changing fatigue strength generated during the charge and discharge cycle. Therefore, the computer device can directly calculate the full charge expansion force, full discharge expansion force, and battery housing area through this static fatigue strength algorithm, and obtain the dynamic fatigue strength of the target lithium battery within the target service cycle.

[0103] It should be noted that since the dynamic fatigue strength is constantly changing during the battery cycle, after the computer calculates the dynamic fatigue strength of the target lithium battery within the target service cycle, it can also calculate its average value and use the calculated average value as the basic data for subsequent fatigue damage prediction.

[0104] In one embodiment, the static fatigue strength algorithm in step S111 may include:

[0105]

[0106] In the formula, represents the static fatigue strength; represents the full charge expansion force; represents the storage expansion force; represents the pre-tightening force; represents the battery housing area.

[0107] In this embodiment, it can be seen from the change data of the expansion force during the cycle process of Figure 2 that the expansion force of the 166Ah single cell is the largest when fully charged, and the target lithium battery for energy storage is stored after being fully charged, that is, the expansion force of the target lithium battery during storage is the sum of the full charge expansion force of the single cell and the storage expansion force of the single cell; and the static fatigue strength of the lithium battery weld is the pressure received by the weld when the battery is stored. Therefore, when the computer device calculates the static fatigue strength of the target lithium battery, it can subtract the pre-tightening force before the single cell test from the sum of the full charge expansion force and the storage expansion force, and then divide by the battery housing area. The result obtained is the static fatigue strength. It should be noted that adding the full charge expansion force and the storage expansion force will increase the part corresponding to the storage expansion force during the charge and discharge process, so as to increase the calculation redundancy and improve the data reliability. The specific calculation results can be as Figure 9 shown. Figure 9 Fig.

[0108] In one embodiment, the dynamic fatigue strength algorithm in step S112 may include:

[0109]

[0110] In the formula, represents the full charge expansion force; represents the full discharge expansion force; represents the battery housing area. Through the above algorithm, the amplitude similar to the breathing effect can be represented to simulate the source of fatigue damage through the periodic amplitude change.

[0111] In this embodiment, since the force received by the weld during the battery cycle process changes dynamically, the pressure received by the weld also changes dynamically. Therefore, the dynamic fatigue strength received by the weld is the pressure value, so its dynamic fatigue strength is the difference between the full charge expansion force and the full discharge expansion force divided by the battery housing area. The specific calculation results can be as Figure 10 shown. Figure 10 Fig.

[0112] In one embodiment, the expression of the static fatigue damage model in step S120 may include:

[0113]

[0114] In the formula, represents the decrease in burst strength output by the static fatigue damage model; represents the ambient temperature; Pt represents the static fatigue strength, characterizing the pressure holding pressure; t represents the pressure holding time of the target lithium battery during the target service cycle.

[0115] In a specific implementation, the target lithium battery works in a constant temperature room at 25 °C, that is, T = 25 °C; since the target lithium battery is charged and discharged once a day during the target service cycle of 10 years, and the remaining time is all storage time, that is, t = 21.5 h, and according to Figure 9 the pressure holding pressure of the target lithium battery can be determined, that is, Pt = Substituting these data into the static fatigue damage model, the decrease in burst strength of the target lithium battery during the target service cycle can be obtained = 0.035 MPa.

[0116] In one embodiment, the process of determining the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength in step S130 may include:

[0117] S141: Determine the weld fatigue life corresponding to the dynamic fatigue strength according to the preset S-N curve, and determine the weld fatigue times of the target lithium battery according to the target service cycle.

[0118] S142: Calculate the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

[0119] In this embodiment, when the computer device determines the fatigue ratio of the target lithium battery, it can first determine the weld fatigue life corresponding to the dynamic fatigue strength according to the preset S-N curve, and determine the weld fatigue times of the target lithium battery according to the target service cycle, and then calculate the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

[0120] It is understandable that the S-N curve refers to the relationship curve between dynamic fatigue strength and weld fatigue life. To elaborate, when constructing the S-N curve, a computer device can apply a periodically varying dynamic fatigue strength to the lithium battery weld. The change frequency of this dynamic fatigue strength is fixed, and the maximum value is called S. Then, when the weld cracks and leaks air, record the number of times N that the dynamic fatigue strength varies periodically. N is also called the fatigue life of the weld under the fatigue strength S. Here, different fatigue strength S values can be set to obtain the fatigue life N values corresponding to different fatigue strengths S, and an S-N curve is established. That is, for each set S value, the computer device can measure the value of N when the weld corresponding to S ruptures, thereby obtaining different S1, N1, S2, N2..., and plotting and generating the S-N curve. Each N value represents the maximum number of battery cycles under this dynamic fatigue strength S.

[0121] Among them, the change frequency of the dynamic fatigue strength can be scaled down proportionally according to the charge and discharge frequency of a single battery. To increase the efficiency of subsequent experiments, this application can combine Figure 2 the expansion force data, scale down the change of the expansion force during the cycle process over time proportionally, and divide it into 4 stages, specifically as follows:

[0122] Stage 1: 0 - 10s, the expansion force gradually increases, equivalent to the battery charging process of the target lithium battery, and the expansion force gradually increases. Specifically, the expansion force can increase from zero to the maximum value;

[0123] Stage 2: 10 - 15s, the expansion force remains unchanged, equivalent to the battery storage process of the target lithium battery, and the expansion force remains unchanged;

[0124] Stage 3: 15 - 20s, the expansion force gradually decreases, equivalent to the battery discharging process of the target lithium battery, and the expansion force gradually decreases. Specifically, the expansion force can decrease from the maximum value to zero;

[0125] Stage 4: 25 - 30s, the expansion force remains unchanged, equivalent to the battery storage process of the target lithium battery, and the expansion force remains unchanged.

[0126] The time of the expansion force change in each of the above stages is proportional to the time of the battery cycle process of the target lithium battery; and because of the dynamic fatigue strength , therefore, the change frequency of the dynamic fatigue strength is the same as the change frequency of the expansion force.

[0127] In a specific implementation, the computer device can introduce a certain amount of gas at a certain frequency, so that the weld seam is subjected to a certain pressure, even enabling the weld seam to reach a certain fatigue strength. Specifically, take a semi-finished battery without electrolyte, connect a hose to the liquid injection hole of the battery, and then use AB glue to seal the contact position between the hose and the liquid injection hole to ensure the tightness of the battery; in order to ensure that other weak areas of the battery during the experiment will not crack prior to the weld seam and affect the experimental results, AB glue can be applied to other weak areas of the battery, such as the explosion-proof valve; then clamp the battery, connect the hose to the gas supply device, and the gas supply device is connected to the gas source. Here, the gas supply device can automatically control the amount of gas introduced into the battery and the gas supply frequency, and this gas supply frequency is consistent with the change frequency of the expansion force in the above 4 stages; when the weld seam of the battery cracks, the battery will leak air, and at this time, the gas supply device cannot raise the air pressure in the battery to the set value within the set time, and the gas supply device will stop supplying gas and record its weld seam fatigue life.

[0128] Schematically, as Figure 11 shown, Figure 11 is a schematic structural diagram of an S-N curve provided by an embodiment of the present application; Figure 11 in this case, the fatigue strengths S used in the experiment are 0.3 MPa, 0.25 MPa, 0.2 MPa, and 0.15 Mpa respectively, and then gas is introduced into the battery in a cycle according to the preset change frequency of the expansion force to obtain the weld seam fatigue life N corresponding to each dynamic fatigue strength S, and then an S-N curve is plotted and generated: N*S^3.289 = 5.864, where = 0.993, indicating a good fitting degree.

[0129] Therefore, through the S-N curve, the computer device can directly determine the weld seam fatigue life corresponding to the dynamic fatigue strength. For example, according to Figure 10 , when the dynamic fatigue strength S obtained by averaging the dynamic fatigue strength of the target service cycle of the target lithium battery is 0.132 MPa, according to the S-N curve, its corresponding weld seam fatigue life N = 13771. In addition, since the target lithium battery is charged and discharged once a day, when its target service cycle is 10 years, the target lithium battery needs to be charged and discharged 3650 times, that is, the number of weld seam fatigue times = 3650.

[0130] In one embodiment, the expression of the dynamic remaining strength model in step S130 may include:

[0131]

[0132] In the formula, represents the dynamic remaining burst strength output by the dynamic remaining strength model; represents the initial burst strength; represents the dynamic fatigue strength; Indicates the fatigue ratio.

[0133] In a specific implementation, the dynamic fatigue strength of the target lithium battery is determined according to the target service cycle = 0.132 MPa, and then the weld fatigue life N = 13771 is determined according to the S-N curve, and the weld fatigue times = 3650, that is, the fatigue ratio = / N = 3650 / 13771 = 0.265. The computer device inputs these data into the dynamic remaining strength model, and then the dynamic remaining burst strength of the target lithium battery at the target service cycle can be obtained = 1.179 MPa.

[0134] In one embodiment, the process of evaluating the weld reliability of the target lithium battery based on the final remaining burst strength in step S140 may include:

[0135] S141: Determine whether the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength.

[0136] S142: If so, confirm that the weld of the target lithium battery is reliable within the target service cycle.

[0137] S143: If not, confirm that the weld of the target lithium battery is unreliable within the target service cycle.

[0138] In this embodiment, when the computer device evaluates the weld reliability of the standard lithium battery, it can determine whether the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength. If so, the computer device can confirm that the weld of the target lithium battery is reliable within the target service cycle; if not, the computer device can confirm that the weld of the target lithium battery is unreliable within the target service cycle.

[0139] It can be understood that if the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength, it indicates that the lithium battery weld can withstand the stress loads under static and dynamic conditions within the target service cycle and has not reached the failure state. Therefore, the computer device can confirm that the weld of the target lithium battery is reliable and can meet the design requirements and safe operation needs. On the contrary, if the final remaining burst strength is less than the static fatigue strength or the dynamic fatigue strength, it means that the lithium battery weld has withstood stresses beyond its capacity, and there may be phenomena such as crack propagation, material degradation, or other damage accumulations, and it cannot ensure normal operation within the target service cycle. Therefore, the computer device can confirm that the weld of the target lithium battery is unreliable, and at this time, repair or replacement measures need to be taken to ensure the safety of the target lithium battery.

[0140] The weld reliability device provided by the embodiments of the present application will be described below. The weld reliability device described below can be correspondingly referred to the weld reliability method described above.

[0141] In one embodiment, as Figure 12 shown, Figure 12 is a schematic structural diagram of a weld reliability evaluation device provided by an embodiment of the present application; the present application also provides a weld reliability evaluation device, including a fatigue strength determination module 210, a strength degradation prediction module 220, a remaining strength prediction module 230, and a reliability evaluation module 240, specifically including the following:

[0142] The fatigue strength determination module 210 is configured to obtain a target lithium battery, and determine the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery during the target service cycle based on the expansion force data and the battery housing area.

[0143] The strength degradation prediction module 220 is configured to input the static fatigue strength and the target service cycle into a preset static fatigue damage model to obtain the amount of burst strength degradation output by the static fatigue damage model.

[0144] The remaining strength prediction module 230 is configured to determine the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength, so as to obtain the dynamic remaining burst strength of the target lithium battery.

[0145] The reliability evaluation module 240 is configured to determine the final remaining burst strength of the target lithium battery according to the amount of burst strength degradation and the dynamic remaining burst strength, and evaluate the weld reliability of the target lithium battery based on the final remaining burst strength.

[0146] In the above embodiments, when evaluating the weld reliability of the target lithium battery, the expansion force data, the battery housing area, and the initial burst strength of the target lithium battery can be determined first, so as to determine the static fatigue strength and the dynamic fatigue strength of the target lithium battery according to the expansion force data and the battery housing area, as the basic data for predicting the dynamic and static fatigue strength damage. Then, the static fatigue strength and the target service life cycle can be input into a preset static fatigue damage model to obtain the amount of burst strength decrease output by the static fatigue damage model, so as to predict in advance the static fatigue damage of the weld of the target lithium battery within the target service life cycle. At the same time, the present application can also determine the fatigue ratio of the target lithium battery based on the target service life cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength to obtain the dynamic remaining burst strength, so as to realize the advance prediction of the dynamic fatigue damage of the weld of the target lithium battery within the target service life cycle. Finally, the final remaining burst strength can be determined according to the amount of burst strength decrease and the dynamic remaining burst strength, and the weld reliability of the target lithium battery can be evaluated based on the final remaining burst strength. Through this method, the present application can predict in advance the dynamic and static fatigue damage of the target lithium battery within the target service life cycle through the static fatigue damage model and the dynamic remaining strength model, and use it to evaluate the reliability of the battery weld, thereby significantly improving the accuracy of the evaluation results.

[0147] In one embodiment, the expansion force data in the fatigue strength determination module 210 includes the full charge expansion force, the storage expansion force, and the full discharge expansion force; the fatigue strength determination module 210 may further include:

[0148] A static fatigue damage calculation sub-module, configured to determine the pre-tightening force of the target lithium battery, and calculate the full charge expansion force, the storage expansion force, the pre-tightening force, and the battery housing area by using a static fatigue strength algorithm, so as to obtain the static fatigue strength of the target lithium battery within the target service life cycle.

[0149] A dynamic fatigue damage calculation sub-module, configured to calculate the full charge expansion force, the full discharge expansion force, and the battery housing area by using a dynamic fatigue strength algorithm, so as to obtain the dynamic fatigue strength of the target lithium battery within the target service life cycle.

[0150] In one embodiment, the static fatigue strength algorithm adopted in the static fatigue damage calculation sub-module may include:

[0151]

[0152] In the formula, represents the static fatigue strength; represents the full charge expansion force; represents the storage expansion force; represents the pre-tightening force; Represents the battery housing area.

[0153] In one embodiment, the dynamic fatigue strength algorithm adopted in the dynamic fatigue damage calculation sub-module may include:

[0154]

[0155] In the formula, Represents the full charge expansion force; Represents the full discharge expansion force; Represents the battery housing area.

[0156] In one embodiment, the expression of the static fatigue damage model adopted in the strength degradation prediction module 220 may include:

[0157]

[0158] In the formula, Represents the amount of burst strength degradation output by the static fatigue damage model; Represents the ambient temperature; Pt represents the static fatigue strength, characterizing the pressure holding pressure; t represents the pressure holding time of the target lithium battery during the target service cycle.

[0159] In one embodiment, the remaining strength prediction module 230 may include:

[0160] A data determination sub-module, configured to determine the weld fatigue life corresponding to the dynamic fatigue strength according to a preset S-N curve, and determine the weld fatigue times of the target lithium battery according to the target service cycle.

[0161] A fatigue ratio calculation sub-module, configured to calculate the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

[0162] In one embodiment, the expression of the dynamic remaining strength model adopted in the remaining strength prediction module 230 may include:

[0163]

[0164] In the formula, Represents the dynamic remaining burst strength output by the dynamic remaining strength model; Represents the initial burst strength; Represents the dynamic fatigue strength; Represents the fatigue ratio.

[0165] In one embodiment, the process of evaluating the weld reliability of the target lithium battery based on the final remaining burst strength in step S140 may include:

[0166] The strength judgment sub-module is used to judge whether the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength.

[0167] The first result confirmation sub-module is used to confirm the reliability of the weld of the target lithium battery within the target service cycle when it is judged that the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength.

[0168] The second result confirmation sub-module is used to confirm the unreliability of the weld of the target lithium battery within the target service cycle when it is judged that the final remaining burst strength is not greater than the static fatigue strength and the dynamic fatigue strength.

[0169] In one embodiment, the present application further provides a computer device. Computer-readable instructions are stored in the computer device. When the computer-readable instructions are executed by one or more processors, the one or more processors are caused to execute the steps of the weld reliability evaluation method as described in any one of the above embodiments.

[0170] Schematically, as Figure 13 shown, Figure 13 is an internal structural schematic diagram of a computer device provided by an embodiment of the present application. The computer device 300 can be provided as a server. Referring to Figure 13 , the computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by a memory 301 for storing instructions executable by the processing component 302, such as application programs. The application programs stored in the memory 301 can include one or more modules each corresponding to a set of instructions. In addition, the processing component 302 is configured to execute instructions to perform the weld reliability evaluation method of any of the above embodiments.

[0171] The computer device 300 may further include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 can operate based on an operating system stored in the memory 301, such as WindowsServer TM, Mac OS XTM, Unix TM, Linux TM, Free BSDTM or the like.

[0172] Those skilled in the art can understand that Figure 13 the structure shown in

[0173] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0174] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0175] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the reliability of a weld, characterized in that, The method includes: Obtain a target lithium battery, and determine the expansion force data, battery housing area, and initial burst strength of the target lithium battery, so as to determine the static fatigue strength and dynamic fatigue strength of the target lithium battery during a target service life based on the expansion force data and the battery housing area; Input the static fatigue strength and the target service life into a preset static fatigue damage model to obtain the amount of decrease in burst strength output by the static fatigue damage model; Determine the fatigue ratio of the target lithium battery based on the target service life and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio, and the initial burst strength to obtain the dynamic remaining burst strength of the target lithium battery; Determine the final remaining burst strength of the target lithium battery according to the amount of decrease in burst strength and the dynamic remaining burst strength, and evaluate the weld reliability of the target lithium battery based on the final remaining burst strength; Among them, determining the fatigue ratio of the target lithium battery based on the target service life and the dynamic fatigue strength includes: Determine the weld fatigue life corresponding to the dynamic fatigue strength according to a preset S-N curve, and determine the weld fatigue times of the target lithium battery according to the target service life; Calculate the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

2. The weld reliability evaluation method according to claim 1, characterized in that, The expansion force data includes full charge expansion force, storage expansion force, and full discharge expansion force; Determining the static fatigue strength and dynamic fatigue strength of the target lithium battery during a target service life based on the expansion force data and the battery housing area includes: Determine the pre-tightening force of the target lithium battery, and calculate the static fatigue strength of the target lithium battery during the target service life based on the full charge expansion force, the storage expansion force, the pre-tightening force, and the battery housing area using a static fatigue strength algorithm; Calculate the dynamic fatigue strength of the target lithium battery during the target service life based on the full charge expansion force, the full discharge expansion force, and the battery housing area using a dynamic fatigue strength algorithm.

3. The weld reliability evaluation method according to claim 2, wherein The static fatigue strength algorithm includes: ； In the formula, represents the static fatigue strength; represents the full charge expansion force; represents the storage expansion force; represents the pre-tightening force; represents the battery case area.

4. The weld reliability evaluation method according to claim 2, wherein The dynamic fatigue strength algorithm includes: ； Wherein, represents the full charge expansion force; represents the full discharge expansion force; represents the battery housing area.

5. The weld reliability evaluation method according to claim 1, characterized in that The expression of the static fatigue damage model includes: ； In the formula, represents the decrease in burst strength output by the static fatigue damage model; represents the ambient temperature; Pt represents the static fatigue strength, which characterizes the pressure holding pressure; t represents the pressure holding time of the target lithium battery during the target service cycle.

6. The weld reliability evaluation method according to claim 1, characterized in that, The expression of the dynamic remaining strength model includes: ； In the formula, represents the dynamic residual burst strength output by the dynamic residual strength model; represents the initial burst strength; represents the dynamic fatigue strength; represents the fatigue ratio.

7. The weld reliability evaluation method according to claim 1, wherein Evaluating the weld reliability of the target lithium battery based on the final remaining burst strength includes: Judge whether the final remaining burst strength is greater than the static fatigue strength and the dynamic fatigue strength; If so, confirm that the weld of the target lithium battery is reliable during the target service life; If not, confirm that the weld of the target lithium battery is unreliable during the target service life.

8. A weld reliability evaluation device, characterized in that, Include: A fatigue strength determination module, configured to obtain a target lithium battery, and determine the expansion force data, battery housing area, and initial burst strength of the target lithium battery, so as to determine the static fatigue strength and dynamic fatigue strength of the target lithium battery during a target service life based on the expansion force data and the battery housing area; The strength degradation prediction module is configured to input the static fatigue strength and the target service cycle into a preset static fatigue damage model, and obtain the amount of burst strength degradation output by the static fatigue damage model; The remaining strength prediction module is configured to determine the fatigue ratio of the target lithium battery based on the target service cycle and the dynamic fatigue strength, and use a preset dynamic remaining strength model to estimate the remaining strength of the dynamic fatigue strength, the fatigue ratio and the initial burst strength, so as to obtain the dynamic remaining burst strength of the target lithium battery; The reliability evaluation module is configured to determine the final remaining burst strength of the target lithium battery according to the amount of burst strength degradation and the dynamic remaining burst strength, and evaluate the weld reliability of the target lithium battery based on the final remaining burst strength; Among them, the remaining strength prediction module includes: Determine the weld fatigue life corresponding to the dynamic fatigue strength according to a preset S-N curve, and determine the weld fatigue times of the target lithium battery according to the target service cycle; Calculate the ratio of the weld fatigue times to the weld fatigue life to obtain the fatigue ratio of the target lithium battery.

9. A computer device, characterized in that, Include: One or more processors, and a memory; Computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the one or more processors, the steps of the weld reliability evaluation method according to any one of claims 1 to 7 are executed.

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