Battery life model acquisition method and device, computer equipment and storage medium

Abstract

The invention relates to a battery life model acquisition method and device, computer equipment and a storage medium. The method comprises the following steps: based on a first test condition, carrying out a short-cycle test on a first sample battery pack to obtain relative irreversible capacity data; the first sample battery pack comprises at least two first sample batteries with different specifications; based on a second test condition, carrying out life cycle test on the second sample battery pack to obtain life inflection point data; the second sample battery pack comprises second sample batteries with the same specification as the first sample batteries; and performing fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relation model. The method can improve the service life detection efficiency.

Description

Technical Field

[0001] The present application relates to the field of measurement technologies, and particularly to a method, apparatus, computer device, and storage medium for obtaining a battery life model. Background Art

[0002] Nowadays, after a battery is produced, there is usually a link for detecting the performance of the battery to screen out qualified batteries. However, the current battery cycle life test takes a long time, and there is a problem of low life detection efficiency. Summary of the Invention

[0003] Based on this, in view of the above technical problems, it is necessary to provide a method, apparatus, computer device, and storage medium for obtaining a battery life model that can improve the life detection efficiency.

[0004] In a first aspect, the present application provides a method for obtaining a battery life model. The method for obtaining a battery life model includes:

[0005] Performing a short cycle test on a first sample battery group based on a first test condition to obtain relative irreversible capacity data; the first sample battery group includes at least two first sample batteries of different specifications;

[0006] Performing a life cycle test on a second sample battery group based on a second test condition to obtain life inflection point data; the second sample battery group includes second sample batteries of the same specifications as each of the first sample batteries;

[0007] Performing fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0008] In one embodiment, the relative irreversible capacity data includes an average irreversible capacity per cycle. Performing a short cycle test on a first sample battery group based on a first test condition to obtain the relative irreversible capacity data of the first sample battery group includes the following steps:

[0009] Performing multiple short cycle tests on the current first sample battery group based on the first test condition to obtain the irreversible capacity of each first sample battery in each cycle;

[0010] Determining the relative irreversible capacity of each first sample battery in each cycle based on the irreversible capacity of each first sample battery in each cycle;

[0011] Calculating the average value of the multiple relative irreversible capacities of a single first sample battery to obtain the average irreversible capacity per cycle of each first sample battery.

[0012] In one embodiment, based on the second test conditions, performing a life cycle test on the second sample battery pack, and obtaining life inflection point data includes the following steps:

[0013] Based on the second test conditions, performing a life cycle test on the second sample battery pack to obtain life cycle data for each second sample battery; the life cycle data includes data on the variation of life estimation with the number of cycles;

[0014] Based on the life cycle data of each second sample battery, determining the life inflection point of each second sample battery;

[0015] Based on the life inflection points of each second sample battery, obtaining life inflection point data.

[0016] In one embodiment, the at least two first sample batteries of different specifications are first sample batteries with different electrolyte components or first sample batteries with different anode material components.

[0017] In one embodiment, based on the relative irreversible capacity data and the life inflection point data for fitting, obtaining a capacity-life inflection point relationship model includes the following steps:

[0018] Based on the relative irreversible capacity data and life inflection point data respectively obtained from the first sample batteries and the second sample batteries of the same specification, determining a capacity-life inflection point data set, and obtaining at least two capacity-life inflection point data sets;

[0019] Based on the at least two capacity-life inflection point data sets for fitting, obtaining the capacity-life inflection point relationship model.

[0020] In one embodiment, based on the relative irreversible capacity data and the life inflection point data for fitting, obtaining a capacity-life inflection point relationship model includes the following steps:

[0021] Based on the reciprocal of the relative irreversible capacity data and the life inflection point data for linear fitting, obtaining the capacity-life inflection point relationship model.

[0022] In a second aspect, the present application provides a battery life prediction method, and the battery life prediction method includes:

[0023] Obtaining the above-mentioned capacity-life inflection point relationship model matching the battery to be tested, and the first test conditions corresponding to the capacity-life inflection point relationship model;

[0024] Based on the first test conditions, performing a short cycle test on the battery to be tested to obtain the relative irreversible capacity of the battery to be tested;

[0025] Based on the relative irreversible capacity and the capacity-life inflection point relationship model, determine the life inflection point of the battery to be tested.

[0026] In one embodiment, the first sample battery corresponding to the capacity-life inflection point relationship model and the battery to be tested are batteries of the same system.

[0027] In one embodiment, the battery life prediction method further includes the following steps:

[0028] Obtain the life inflection point range corresponding to the capacity-life inflection point relationship model;

[0029] Based on the life inflection point range, determine whether the battery to be tested is qualified.

[0030] In a third aspect, the present application provides a device for obtaining a battery life model, and the device for obtaining a battery life model includes:

[0031] A short cycle test module, configured to perform a short cycle test on a first sample battery group based on a first test condition to obtain relative irreversible capacity data; the first sample battery group includes at least two first sample batteries of different specifications;

[0032] A life cycle test module, configured to perform a life cycle test on a second sample battery group based on a second test condition to obtain life inflection point data; the second sample battery group includes second sample batteries of the same specification as each of the first sample batteries;

[0033] A model fitting module, configured to perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0034] In a fourth aspect, the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the method described above is implemented.

[0035] In a fifth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described above is implemented.

[0036] The above battery life model acquisition method, device, computer device, and storage medium obtain relative irreversible capacity data by performing short-cycle tests on a first sample battery pack based on a first test condition. The first sample battery pack includes at least two first sample batteries of different specifications; based on a second test condition, perform life cycle tests on a second sample battery pack to obtain life inflection point data. The second sample battery pack includes second sample batteries with the same specifications as each of the first sample batteries; perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model. The obtained capacity-life inflection point relationship model can accurately represent the mapping relationship between the relative irreversible capacity of the battery under short cycles and the life inflection point of the battery. Therefore, only a short-cycle test with relatively short time consumption needs to be performed on the battery to be tested, and the life inflection point prediction result of the battery to be tested can be obtained, thereby achieving the effect of improving the life detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 FIG. is an application environment diagram of the battery life model acquisition method in an embodiment;

[0038] Figure 2 FIG. is a flowchart of the battery life model acquisition method in an embodiment;

[0039] Figure 3 FIG. is a flowchart of the battery life prediction method in an embodiment;

[0040] Figure 4 FIG. is a schematic diagram of the relationship between relative irreversible capacity and number of cycles in an embodiment;

[0041] Figure 5 FIG. is a schematic diagram of the relationship between capacity retention rate and number of cycles in an embodiment;

[0042] Figure 6 FIG. is a structural block diagram of the battery life model acquisition method in an embodiment;

[0043] Figure 7 FIG. is an internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] The battery life model acquisition method provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the terminal 102 can be connected to the test device 106, and the test device 106 is used to test the battery under test or the sample battery according to specific test rules and test conditions. The terminal 102 and the test device 106 can be integrally arranged or separately arranged. Based on the first test condition, the terminal 102 controls the test device 106 to perform a short cycle test on the first sample battery group to obtain relative irreversible capacity data. The first sample battery group includes at least two first sample batteries of different specifications; based on the second test condition, the terminal 102 controls the test device 106 to perform a life cycle test on the second sample battery group to obtain life inflection point data. The second sample battery group includes second sample batteries of the same specification as each of the first sample batteries; based on the relative irreversible capacity data and the life inflection point data, fitting is performed to obtain a capacity-life inflection point relationship model. Among them, the terminal 102 can be but is not limited to various personal computers, laptop computers, smart phones, tablet computers, etc.

[0046] In one embodiment, as Figure 2 shown, a method for obtaining a battery life model is provided. Taking the terminal 102 in Figure 1 as an example, the method includes the following steps:

[0047] Step S110, based on the first test condition, perform a short cycle test on the first sample battery group to obtain relative irreversible capacity data.

[0048] Among them, the first sample battery group may include at least two first sample batteries of different specifications.

[0049] Batteries of different specifications refer to the differences between the batteries in the same sample battery group. This difference can be: for the same battery, due to factors such as different suppliers of the same material, different production equipment used by the same supplier, or different production batches, etc., differences between the batteries result in different specifications; it can also be different specifications of batteries caused by experimental design.

[0050] Exemplarily, the first sample battery in this embodiment can be a battery with a life inflection point such as a lithium-ion battery or a semi-solid battery.

[0051] The short cycle test can be compared with the traditional long-cycle test. It can complete a preset number of charge and discharge cycles in a shorter time, so as to quickly obtain relevant data on battery performance. The short cycle test can perform a certain number of charge and discharge cycles according to the first test condition, and record parameters such as the battery capacity at the end of each cycle, and quickly obtain the performance change trend of the battery in the initial use stage.

[0052] The first test condition is a preset test condition, which may include test rules, test environment, etc. The test rules may be, for example, charge-discharge rate, charge-discharge sequence, depth of discharge, etc. The test environment may be, for example, temperature, humidity, voltage range, etc. The first test condition can be set according to the characteristics of the battery system and simulate the actual usage scenario as much as possible to ensure the accuracy of the test results.

[0053] The irreversible capacity may be the part that, during the use of the battery, due to reasons such as loss of active material, structural change, decomposition of the electrolyte, etc., causes the battery to not be able to fully recover to the initial capacity and cannot be reused during subsequent use. Further, the relative irreversible capacity may be the relative magnitude between the irreversible capacity exhibited by the battery within a preset cycle range and the initial capacity or theoretical capacity, which can reflect the cycle stability and performance degradation of the battery within the preset cycle range, etc.

[0054] Performing a short-cycle test on the first sample battery pack to obtain relative irreversible capacity data may be to obtain, through the short-cycle test, the relative irreversible capacity data corresponding to each first sample battery. The relative irreversible capacity data may include the relative irreversible capacity data of the first sample battery within a preset cycle range under the short-cycle test.

[0055] Step S120, based on the second test condition, perform a life cycle test on the second sample battery pack to obtain life inflection point data.

[0056] Among them, performing a life cycle test on the second sample battery pack to obtain life inflection point data may be to obtain the life inflection point data corresponding to each second sample battery.

[0057] The second sample battery pack includes second sample batteries with the same specifications as each of the first sample batteries. The life cycle test is used to test the life change of the second sample battery. The life cycle test may be a long-term charge-discharge cycle until the battery capacity drops to a preset threshold. Exemplarily, it may be a test with more cycle numbers compared to the short-cycle test, and record the life change of the second sample battery in each cycle, and then determine the life inflection point data based on the life change.

[0058] The life inflection point can be a node at which the battery capacity significantly decreases, marking the entry of the battery into the rapid aging stage. During the use of some batteries, their performance, such as capacity and energy density, will gradually decrease over time and finally reach an inflection point, which is the life inflection point. Exemplarily, the life inflection point can be the number of cycles corresponding to when the battery capacity begins to significantly decrease. Therefore, based on the life change of each second sample battery, the life inflection point of each second sample battery can be determined. Further, methods such as the linear regression method, the difference method, and the threshold method can be used to calibrate the life inflection point of the second sample battery. Among them, the linear regression method can be to perform curve fitting on the life change data to determine the point where the curve slope changes significantly; the difference method can be to calculate the change rate of the life estimation between adjacent cycles. If the change rate exceeds the preset threshold, it is considered that the life inflection point has been reached; the threshold method can be that when the life estimation reaches the preset threshold, it is considered that the life inflection point has been reached.

[0059] Step S130, perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0060] Among them, the capacity-life inflection point relationship model can be a mathematical model determined by fitting based on the relative irreversible capacity data and the life inflection point data, and is used to describe the relationship between the capacity data of the battery and the life inflection point.

[0061] Performing fitting on the relative irreversible capacity data and the life inflection point data can be to determine the corresponding relationship between the relative irreversible capacity and the life inflection point according to a mathematical algorithm, so that the corresponding life inflection point can be deduced based on the relative irreversible capacity.

[0062] Further, after obtaining the capacity-life inflection point relationship model, the first test condition, the second test condition, and the battery system of the first sample battery group can also be saved.

[0063] A method for obtaining a battery life model provided by this embodiment obtains relative irreversible capacity data by performing a short-cycle test on a first sample battery pack based on a first test condition. The first sample battery pack includes at least two first sample batteries of different specifications; based on a second test condition, a life cycle test is performed on a second sample battery pack to obtain life inflection point data. The second sample battery pack includes second sample batteries with the same specifications as each of the first sample batteries; based on the relative irreversible capacity data and the life inflection point data, a capacity-life inflection point relationship model is obtained. The obtained capacity-life inflection point relationship model can accurately characterize the mapping relationship between the relative irreversible capacity of the battery under short cycles and the life inflection point of the battery. Therefore, only a short-cycle test with relatively short time consumption needs to be performed on the battery to be tested, and the life inflection point prediction result of the battery to be tested can be obtained, thereby achieving the effect of improving the life detection efficiency.

[0064] In one of the embodiments, the relative irreversible capacity data includes the average irreversible capacity per cycle. Based on the first test condition, performing a short-cycle test on the first sample battery pack to obtain the relative irreversible capacity data of the first sample battery pack includes the following steps:

[0065] Based on the first test condition, perform multiple short-cycle tests on the current first sample battery pack to obtain the irreversible capacity of each first sample battery in each cycle;

[0066] Based on the irreversible capacity of each first sample battery in each cycle, determine the relative irreversible capacity of the first sample battery in each cycle;

[0067] Calculate the average value of the multiple relative irreversible capacities of a single first sample battery to obtain the average irreversible capacity per cycle of each first sample battery.

[0068] Among them, based on the first test condition, performing multiple short-cycle tests on the current first sample battery pack to obtain the irreversible capacity of each first sample battery in each cycle may be to calculate the charging capacity and discharging capacity of the first sample battery in a single cycle, and determine the irreversible capacity in this cycle according to the charging capacity and discharging capacity.

[0069] Based on the irreversible capacity of each first sample battery in each cycle, determining the relative irreversible capacity of the first sample battery in each cycle may be to use the initial capacity of the battery before the short-cycle test as the reference capacity, and according to the irreversible capacity and the initial capacity of the battery in each cycle, obtain the relative irreversible capacity of the current first sample battery in each cycle.

[0070] Further, based on the relative irreversible capacity, the relative irreversible capacity data of the current first sample battery can be determined, which can be calculating the average value of multiple relative irreversible capacities of a single first sample battery, that is, the average value of the relative irreversible capacities corresponding to multiple cycles, to obtain the average relative irreversible capacity per cycle of each first sample battery.

[0071] A method for obtaining a battery life model provided in this embodiment obtains the irreversible capacity of the current first sample battery in each cycle, and then obtains the relative irreversible capacity of the current first sample battery in each cycle, so as to determine the relative irreversible capacity data of the current first sample battery by calculating the average value. It can achieve a detailed record of the irreversible capacity parameters of the battery in each cycle, reduce the influence caused by single measurement errors, and simplify the data processing process, thereby improving the accuracy of the data and enhancing the prediction ability of the model, so as to achieve the effect of improving the life detection efficiency.

[0072] In one embodiment, based on the second test condition, performing a life cycle test on the second sample battery group, and obtaining the life inflection point data includes the following steps:

[0073] Based on the second test condition, performing a life cycle test on the second sample battery group to obtain the life cycle data of each second sample battery; the life cycle data includes the change data of the life estimation with the number of cycles.

[0074] Based on the life cycle data of each second sample battery, determine the life inflection point of each second sample battery.

[0075] Based on the life inflection points of each second sample battery, obtain the life inflection point data.

[0076] Among them, the second test condition can be used to simulate the battery working conditions. The second test condition and the first test condition can be the same. In a specific embodiment, the first test condition and the second test condition can both be 25°C, 1C. The second test condition and the first test condition can also be different. In a specific embodiment, the first test condition is -10°C to 60°C, 2C, and the second test condition is 25°C, 1C.

[0077] Based on the second test condition, a life cycle test is performed on the second sample battery pack to obtain life inflection point data. It can be that under the second test condition, through the life cycle test, the number of cycles when each battery reaches the life inflection point is recorded, so as to form the life inflection point data. Further, the cycle number corresponding to the life inflection point can be obtained by recording the life change data of the second sample battery in each cycle during the life cycle test and analyzing the life change data. The life change data includes the change data of the life estimation with the number of cycles. Further, the life estimation can be obtained according to the ratio of the battery capacity to the initial capacity to reflect the remaining life of the battery. The number of cycles represents the serial number of each charge and discharge cycle.

[0078] Further, based on the relative irreversible capacity data and the life inflection point data for fitting, the capacity-life inflection point relationship model is obtained. It can be to fit the relationship between the relative irreversible capacity data of each first sample battery and the number of cycles corresponding to the life inflection point, so as to obtain the capacity-life inflection point relationship model.

[0079] Through the life cycle test, the data of the change of the capacity situation of each battery with the increase of the number of cycles can be determined. Based on the global analysis, the node when the battery capacity shows a rapid decay can be used as the life inflection point of the current battery.

[0080] A method for obtaining a battery life model provided in this embodiment obtains life inflection point data through a life cycle test based on the second test condition and obtains the capacity-life inflection point relationship model, so that the change law of battery performance can be more comprehensively captured by combining short-term and long-term test data, thereby improving the accuracy of battery life prediction. And only through short cycle tests, battery performance data can be quickly obtained, significantly shortening the test time, so as to achieve the effect of improving the life detection efficiency.

[0081] In one embodiment, the at least two first sample batteries of different specifications are first sample batteries with different electrolyte components or first sample batteries with different negative electrode material components.

[0082] Exemplarily, for two batteries A and B of different specifications, only different main materials, conductive agents or binders, etc. are used in the negative electrode material, and the others are the same; or only the content of a certain component in the negative electrode material is different, and the others are the same; or only the content of the additive in the electrolyte is different, and the others are the same; it can also be that only the content of a certain component in the electrolyte is different, and the others are the same; it can also be that only the types of additives in the electrolyte are different, and the others are the same. This embodiment does not make a limitation here.

[0083] Among them, different examples of the main negative electrode material can be that the main negative electrode materials of the battery under test and the first sample battery are both selected from artificial graphite, and the difference is that the main materials of the two are respectively selected from mesocarbon microbead artificial graphite and needle coke artificial graphite in artificial graphite; or, for example, the main negative electrode materials of the battery under test and the first sample battery are both selected from natural graphite, and the difference is that the main materials of the two are respectively selected from flake graphite and earthy graphite in natural graphite; or, for example, the main negative electrode materials of the battery under test and the first sample battery are both selected from soft carbon, and the difference is that the main materials of the two are respectively selected from petroleum coke-based soft carbon and needle coke-based soft carbon in soft carbon. Therefore, the selection of the negative electrode material (including the main material and its additive materials) follows the above principles. Similarly, the selection of the types of additives in the electrolyte is also the same, which will not be elaborated below.

[0084] Furthermore, when there are only differences in the content of a certain component of the negative electrode material, a certain electrolyte additive, or a certain component of the electrolyte between batteries of different specifications, the content difference can be controlled within 5 wt.%. There may be deviations in the difference range of the content of a specific material in the negative electrode or electrolyte, or it may be greater than 5 wt.%, which can also be understood to be within the protection scope of the present invention.

[0085] In one of the embodiments, based on the relative irreversible capacity data and the life inflection point data for fitting, obtaining the capacity-life inflection point relationship model includes the following steps:

[0086] Based on the relative irreversible capacity data and the life inflection point data respectively obtained from the first sample battery and the second sample battery under the same specifications, determining the capacity-life inflection point data groups, and obtaining at least two capacity-life inflection point data groups;

[0087] Based on the at least two capacity-life inflection point data groups for fitting, obtaining the capacity-life inflection point relationship model.

[0088] Among them, it can be understood that the relative irreversible capacity data and the life inflection point data are obtained by separately testing sample batteries of the same specifications. When it is necessary to fit the capacity-life inflection point relationship model, the relative irreversible capacity data and the life inflection point data under the same specifications should also be used as a set of corresponding relationships for fitting.

[0089] In this embodiment, based on the relative irreversible capacity data and the life inflection point data respectively obtained from the first sample battery and the second sample battery under the same specifications, determining the capacity-life inflection point data groups can be based on the relative irreversible capacity data obtained from the first sample battery and the life inflection point data obtained from the second sample battery of the same specifications as the first sample battery, as a set of capacity-life inflection point data groups, forming a set of mapping relationships. In the case where the first sample battery group includes N first sample batteries, N sets of mapping relationships can be formed, and N is a positive integer.

[0090] Fitting is performed based on the at least two capacity-life inflection point data sets to obtain the capacity-life inflection point relationship model. It can be to analyze the corresponding relationship between each set of relatively irreversible capacity data and the life inflection point data to obtain the capacity-life inflection point relationship model that best suits the current sample battery system.

[0091] A method for obtaining a battery life model provided in this embodiment can ensure the accuracy and reliability of the mapping relationship of the capacity-life inflection point by grouping and fitting the relatively irreversible capacity data and the life inflection point data obtained from the first sample battery and the second sample battery respectively, forming a more accurate capacity-life inflection point relationship model, so as to achieve the effect of improving the life detection efficiency.

[0092] In one embodiment, fitting is performed based on the relatively irreversible capacity data and the life inflection point data to obtain the capacity-life inflection point relationship model, including the following steps:

[0093] Perform linear fitting based on the reciprocal of the relatively irreversible capacity data and the life inflection point data to obtain the capacity-life inflection point relationship model.

[0094] In this embodiment, there is a linear relationship between the reciprocal of the relatively irreversible capacity data and the life inflection point data. Therefore, the linear fitting can be in the form of the least squares method, and the best fitting parameters are determined by minimizing the sum of the squared residuals, thereby constructing the capacity-life inflection point relationship model.

[0095] A method for obtaining a battery life model provided in this embodiment can improve the accuracy of battery life prediction and simplify the model construction process by performing linear fitting based on the reciprocal of the relatively irreversible capacity data and the life inflection point data, so as to achieve the effect of improving the life detection efficiency.

[0096] In one embodiment, as Figure 3 shown, a battery life prediction method is provided, and the battery life prediction method includes:

[0097] Step S210, obtain the capacity-life inflection point relationship model as described above that matches the battery to be tested, and the first test conditions corresponding to the capacity-life inflection point relationship model.

[0098] Among them, obtaining the capacity-life inflection point relationship model as described above that matches the battery under test can be to select a capacity-life inflection point relationship model that matches the battery characteristics according to the battery characteristics of the battery under test. Exemplarily, it can be to obtain a capacity-life inflection point relationship model under the same system as the battery under test according to the battery system of the battery under test. The same system means that the battery under test and a certain first sample battery can be the same battery; or: the negative electrode component or electrolyte component design of the battery under test and the first sample battery is different, and the others are the same batteries. It should be noted that the difference in the negative electrode component can be that the others of the battery under test are the same as the first sample battery, only the ratio of the negative electrode component is different, or the type of negative electrode material (including the main negative electrode material and its additive materials) is different; the difference in the electrolyte component can be that the others of the battery under test are the same as the first sample battery, only the ratio of the electrolyte component is different, or the type of electrolyte additive is different. It should be noted that when there is only a difference in the ratio of the negative electrode component and the ratio of a certain electrolyte component between the battery under test and the first sample battery, the ratio difference can be controlled within 5 wt.%. There may be deviations in the ratio difference range of a specific material in the negative electrode or electrolyte, or it may be greater than 5 wt.%, which can also be understood to be within the protection scope of the present invention. The first test condition can be the test condition required for life prediction using this capacity-life inflection point relationship model.

[0099] By obtaining the first test condition corresponding to the capacity-life inflection point relationship model, it can be ensured that the variables in the short-cycle test of the battery under test are consistent with those in the short-cycle test during the establishment of the capacity-life inflection point relationship model, thereby improving the accuracy of the life inflection point prediction result.

[0100] Step S220, based on the first test condition, perform a short-cycle test on the battery under test to obtain the relative irreversible capacity of the battery under test.

[0101] Among them, the short-cycle test can complete a preset number of charge and discharge cycles in a shorter time compared to the traditional long-cycle test, so as to quickly obtain relevant data on battery performance, which will not be elaborated in this embodiment.

[0102] Performing a short-cycle test on the battery under test to obtain relative irreversible capacity data can be to obtain relative irreversible capacity data of the battery under test through a short-cycle test. The relative irreversible capacity data can include the relative irreversible capacity data of the battery under test within a preset cycle range under the short-cycle test.

[0103] Step S230, based on the relative irreversible capacity and the capacity-life inflection point relationship model, determine the life inflection point of the battery under test.

[0104] The capacity-life inflection point relationship model characterizes the mapping relationship between the relative irreversible capacity and the life inflection point. Therefore, by means of mapping calculation, comparison query, etc. through the relative irreversible capacity and the capacity-life inflection point relationship model, the life inflection point corresponding to the relative irreversible capacity can be determined, which is the life inflection point of the battery to be tested.

[0105] A battery life prediction method provided in this embodiment, by obtaining the capacity-life inflection point relationship model as described above that matches the battery to be tested, and the first test condition corresponding to the capacity-life inflection point relationship model, based on the first test condition, performing a short cycle test on the battery to be tested to obtain the relative irreversible capacity of the battery to be tested, and based on the relative irreversible capacity and the capacity-life inflection point relationship model, determining the life inflection point of the battery to be tested, can achieve the prediction of the life inflection point of the battery to be tested when only a short cycle test needs to be performed on the battery to be tested, so as to achieve the effect of improving the life detection efficiency.

[0106] In one embodiment, the first sample battery corresponding to the capacity-life inflection point relationship model and the battery to be tested are batteries of the same system.

[0107] In one embodiment, the battery life prediction method further includes the following steps:

[0108] Obtain the life inflection point range corresponding to the capacity-life inflection point relationship model;

[0109] Based on the life inflection point range, determine whether the battery to be tested is qualified.

[0110] Among them, the life inflection point range can be the life inflection point range set according to the capacity-life inflection point relationship model. This range can be the determined allowable life inflection point range according to historical data and prior standards, or the result of determining the allowable predicted number of cycles.

[0111] Based on the life inflection point range, determining whether the battery to be tested is qualified can be to predict the number of cycles at the life inflection point of the battery to be tested according to the capacity-life inflection point relationship model and determine whether the number of cycles is within the preset allowable range. Further, it can be to determine whether the minimum number of cycle thresholds is met, so as to determine whether the battery to be tested is qualified.

[0112] A battery life prediction method provided in this embodiment, by determining whether the battery to be tested is qualified based on the life inflection point range corresponding to the capacity-life inflection point relationship model, can effectively evaluate the expected life of the battery to be tested, strengthen quality control, and achieve the effect of improving the reliability of battery products.

[0113] To more clearly illustrate the technical solution of the present application, the present application also provides a detailed embodiment.

[0114] In one embodiment, a method for obtaining a battery life model is provided, which can be used for predicting batteries that theoretically have a life inflection point, including the following steps:

[0115] Step S1: Subject the first sample battery group a 1 , a 2 , a 3 ,...., a n to a short cycle test to obtain the relative irreversible capacity per average single cycle which are respectively:

[0116] Step S2: Use batteries b 1 identical to a 1 in step S1, batteries b 2 identical to a 2 , batteries b 3 identical to a 3 ...., and batteries b n identical to a n as the second sample battery group, conduct a life cycle test, and measure the number of cycles C when the life inflection point appears, which are respectively: C 1 , C 2 , C 3 ,...., C n ;

[0117] Step S3: Perform data fitting on C n ) to obtain a relationship model between and the number of cycles C;

[0118] Furthermore, this embodiment can use the obtained relationship model to predict the life inflection point of the battery to be tested.

[0119] Step S4: Conduct a short cycle test on the battery to be tested. The conditions of the short cycle test are the same as those in step S1, and measure the irreversible capacity per average single cycle of the battery to be tested Substitute into the relationship model in step S3 to predict the number of cycles C` when the life inflection point of the battery to be tested appears.

[0120] Furthermore, obtaining the relative irreversible capacity per average single cycle in step S1 includes the following steps:

[0121] Subject the first sample battery a 1 , a 2 , a3 ,..., a n Perform a cycle test under certain conditions such as temperature and charge-discharge mechanism, and record the charging capacity of the nth cycle as Q CHn , and record the discharge capacity as Q DCHn , and the irreversible capacity is Q IRn = Q CHn - Q DCHn .

[0122] The initial capacity of the battery is recorded as Q 0 , and the relative irreversible capacity of the nth cycle of the battery cycle test is Q RE,IRn = Q IRn / Q 0 , and similarly, the relative irreversible capacity of the first cycle can be obtained as Q RE,IR1 , the relative irreversible capacity of the second cycle is Q RE,IR2 ,..., the relative irreversible capacity of the (n - 1)th cycle is Q RE,IRn-1 .

[0123] Calculate the average value of the irreversible capacity per cycle for the first n cycles:

[0124] Among them, the test conditions of the short cycle test and the life cycle test can be the same or different. In a specific embodiment, the conditions of the short cycle test are -10°C - 60°C, 2C, and the test conditions of the short cycle are adjusted according to the characteristics of the battery system; the cycle life test conditions are 25°C, 1C, and are used to simulate the battery working conditions.

[0125] In a specific embodiment, has a linear relationship with the number of cycles C. As Figure 4 shows the schematic diagram of the relationship between the relative irreversible capacity and the number of cycles. For a battery of a specific system, such as a battery designed with a preset material as an experimental factor in the battery evaluation or some mass-produced batteries, select the average irreversible capacity of different experimental groups or batches of samples for the first n cycles and the number of cycles CycleEOL at which the capacity decreases to the end of life due to non-linear attenuation in the later stage of life. CycleEOL and are significantly positively correlated, and establish a coordinate system to determine the trend relationship between the two.

[0126] Furthermore, the sample battery a in step S1 1 , a 2 , a 3 ,..., a n are batteries of different specifications, that is, a 1 - a nThe positive and negative electrode materials of the batteries can be the same while the electrolyte components are different, or the positive electrode material and the electrolyte components can be the same while the negative electrode material is different.

[0127] Furthermore, the battery life inflection point in step S2 can be determined by methods such as taking the derivative and calculating the average.

[0128] Furthermore, the battery under test in step S4 and the a 1 -a n battery in step S1 are batteries of the same system.

[0129] In a specific embodiment, as Figure 5 shown in the schematic diagram of the relationship between the capacity retention rate and the number of cycles, the three groups of sample batteries are sample batteries produced by a single-factor experiment with the same design system and using a preset key material as the experimental factor. In the later stage of the cycle test, all three groups of samples show non-linear attenuation, and CycleEOL is positively correlated with . Therefore, in subsequent experiments, the number of cycles at which non-linear attenuation occurs can be predicted in advance based on the relationship between CycleEOL and

[0130] In an embodiment, a method for predicting the battery life inflection point is also provided for qualified detection of mass-produced batteries, including:

[0131] Obtain multiple batteries of the same system as the mass-produced battery, divide them into a first sample battery group and a second sample battery group, and use a short cycle test to measure the relative irreversible capacity of each first sample battery for an average single cycle Perform a life cycle test on the second sample battery, measure the number of cycles at which the life inflection point appears, establish a relationship model with the number of cycles C, and set the range of the number of cycles of qualified batteries to obtain the range.

[0132] Use the test conditions of the short cycle to perform a short cycle test on the mass-produced battery. After 10 - 100 cycles, the relative irreversible capacity of the mass-produced battery for an average single cycle can be obtained. If this value is within the range of the qualified value, it is qualified. It can be understood that the 10 to 100 cycles in this embodiment are only used as an example for scheme description, and the number of cycles can also be other than 10 to 100 cycles. This embodiment does not make any limitations in this regard.

[0133] Furthermore, it can also be to measure the number of cycles at which the life inflection point appears, compare the value of the number of cycles with the range required for the life cycle inflection point of qualified batteries, and then determine whether the battery is qualified.

[0134] It can be understood that the appearance of an inflection point in the battery during the cycle life test means that the battery will enter a period of rapid decay. If the time when the inflection point of the battery cycle life appears is advanced, it indicates that the battery life is shortened. That is, the larger the number of cycles when the inflection point of the battery cycle life appears, the longer the battery life; the smaller the number of cycles when the inflection point appears, the shorter the battery life.

[0135] A method for obtaining a battery life model provided in this embodiment predicts the number of cycles when the battery appears at the life inflection point through a relatively short number of cycles, effectively shortening the prediction time for the battery cycle to appear at the life inflection point, improving the prediction efficiency of the diving or life, increasing the screening speed of defective batteries on the production line, and achieving the effect of improving the reliability of battery products.

[0136] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0137] Based on the same inventive concept, the embodiment of the present application also provides a battery life model acquisition device for implementing the above-mentioned battery life model acquisition method. The implementation solution provided by this device to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the battery life model acquisition device provided below can refer to the limitations on the battery life model acquisition method in the above text, and will not be repeated here.

[0138] In one embodiment, as Figure 6 shown, a battery life model acquisition device is provided. The battery life model acquisition device includes:

[0139] A short cycle test module for performing a short cycle test on the first sample battery group based on the first test condition to obtain relatively irreversible capacity data; the first sample battery group includes at least two first sample batteries of different specifications;

[0140] A life cycle test module for performing a life cycle test on the second sample battery group based on the second test condition to obtain life inflection point data; the second sample battery group includes second sample batteries of the same specification as each of the first sample batteries;

[0141] A model fitting module, configured to perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0142] In one embodiment, the relative irreversible capacity data includes the average irreversible capacity per cycle. Based on the first test condition, performing a short cycle test on the first sample battery pack to obtain the relative irreversible capacity data of the first sample battery pack includes the following steps:

[0143] Based on the first test condition, performing multiple short cycle tests on the current first sample battery pack to obtain the irreversible capacity of each first sample battery in each cycle;

[0144] Based on the irreversible capacity of each first sample battery in each cycle, determining the relative irreversible capacity of each first sample battery in each cycle;

[0145] Calculating the average value of the multiple relative irreversible capacities of a single first sample battery to obtain the average irreversible capacity per cycle of each first sample battery.

[0146] In one embodiment, based on the second test condition, performing a life cycle test on the second sample battery pack to obtain the life inflection point data includes the following steps:

[0147] Based on the second test condition, performing a life cycle test on the second sample battery pack to obtain the life cycle data of each second sample battery; the life cycle data includes the variation data of the life estimation with the number of cycles;

[0148] Based on the life cycle data of each second sample battery, determining the life inflection point of each second sample battery;

[0149] Based on the life inflection points of each second sample battery, obtaining the life inflection point data.

[0150] In one embodiment, the at least two first sample batteries of different specifications are first sample batteries with different electrolyte components or first sample batteries with different anode material components.

[0151] In one embodiment, performing fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model includes the following steps:

[0152] Based on the relative irreversible capacity data and the life inflection point data respectively obtained from the first sample battery and the second sample battery under the same specification, determining a capacity-life inflection point data group, and obtaining at least two capacity-life inflection point data groups;

[0153] Fitting is performed based on the at least two capacity-life inflection point data sets to obtain the capacity-life inflection point relationship model.

[0154] In one embodiment, fitting is performed based on the relative irreversible capacity data and the life inflection point data to obtain the capacity-life inflection point relationship model, including the following steps:

[0155] Performing linear fitting based on the reciprocal of the relative irreversible capacity data and the life inflection point data to obtain the capacity-life inflection point relationship model.

[0156] Each module in the above battery life model acquisition device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0157] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 7 shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, 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. The wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a battery life model acquisition method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0158] Those skilled in the art can understand that Figure 7 the structure shown in

[0159] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the battery life model acquisition method of any of the above embodiments is implemented:

[0160] Based on a first test condition, perform a short cycle test on a first sample battery pack to obtain relative irreversible capacity data; the first sample battery pack includes at least two first sample batteries of different specifications;

[0161] Based on a second test condition, perform a life cycle test on a second sample battery pack to obtain life inflection point data; the second sample battery pack includes second sample batteries of the same specifications as each of the first sample batteries;

[0162] Perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0163] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the battery life model acquisition method of any of the above embodiments is implemented:

[0164] Based on a first test condition, perform a short cycle test on a first sample battery pack to obtain relative irreversible capacity data; the first sample battery pack includes at least two first sample batteries of different specifications;

[0165] Based on a second test condition, perform a life cycle test on a second sample battery pack to obtain life inflection point data; the second sample battery pack includes second sample batteries of the same specifications as each of the first sample batteries;

[0166] Perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

[0167] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0168] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0169] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0170] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for obtaining a battery life model, characterized in that: The battery life model acquisition method comprises: Based on the first test condition, a short cycle test is performed on the first sample battery group to obtain relative irreversible capacity data; the first sample battery group includes at least two first sample batteries of different specifications; Based on the second test condition, a life cycle test is performed on the second sample battery group to obtain life inflection point data; the second sample battery group includes second sample batteries with the same specifications as each of the first sample batteries; Based on the relative irreversible capacity data and the life inflection point data, fitting is performed to obtain a capacity-life inflection point relationship model.

2. The method for obtaining a battery life model according to claim 1, characterized in that: The relative irreversible capacity data includes an average single-cycle irreversible capacity. Based on the first test condition, a short cycle test is performed on the first sample battery pack to obtain the relative irreversible capacity data of the first sample battery pack, including the following steps: Based on the first test condition, performing multiple short cycle tests on the current first sample battery pack to obtain the irreversible capacity of each of the first sample batteries in each cycle; Determining the relative irreversible capacity of the first sample battery at each cycle based on the irreversible capacity of each of the first sample batteries at each cycle; The average value of the plurality of relative irreversible capacities of a single first sample battery is calculated to obtain the average single-cycle relative irreversible capacity of each first sample battery.

3. The method for obtaining a battery life model according to claim 1, characterized in that: Based on the second test condition, performing a life cycle test on the second sample battery pack to obtain life inflection point data includes the following steps: Based on the second test condition, a life cycle test is performed on the second sample battery pack to obtain life cycle data of each second sample battery; the life cycle data includes data on changes in life estimation with the number of cycles; Determine a life inflection point of each second sample battery based on the life cycle data of each second sample battery; Based on the life inflection point of each second sample battery, life inflection point data is obtained.

4. The method for obtaining a battery life model according to claim 1, characterized in that: The at least two first sample batteries of different specifications are first sample batteries of different electrolyte components, or first sample batteries of different negative electrode material components.

5. The method for obtaining a battery life model according to claim 1, characterized in that: Fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model comprises the following steps: Based on the relative irreversible capacity data and life inflection point data respectively obtained from the first sample battery and the second sample battery under the same specifications, determine the capacity-life inflection point data group to obtain at least two capacity-life inflection point data groups; The capacity-life inflection point relationship model is obtained by fitting based on the at least two capacity-life inflection point data groups.

6. The method for obtaining a battery life model according to claim 1, characterized in that: Fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model comprises the following steps: The capacity-life inflection point relationship model is obtained by performing linear fitting based on the inverse of the relative irreversible capacity data and the life inflection point data.

7. A battery life prediction method, characterized in that: The battery life prediction method comprises: Acquire a capacity-life inflection point relationship model according to any one of claims 1 to 6 that matches the battery to be tested, and a first test condition corresponding to the capacity-life inflection point relationship model; Based on the first test condition, performing a short cycle test on the battery to be tested to obtain a relative irreversible capacity of the battery to be tested; Based on the relative irreversible capacity and the capacity-life inflection point relationship model, the life inflection point of the battery to be tested is determined.

8. The battery life prediction method according to claim 7, characterized in that: The first sample battery corresponding to the capacity-life inflection point relationship model and the battery to be tested are batteries of the same system.

9. The battery life prediction method according to claim 7, characterized in that: The battery life prediction method further comprises the following steps: Obtaining a life inflection point range corresponding to the capacity-life inflection point relationship model; Based on the life inflection point range, it is determined whether the battery to be tested is qualified.

10. A battery life model acquisition device, characterized in that: The battery life model acquisition device comprises: A short cycle test module, used to perform a short cycle test on a first sample battery pack based on a first test condition to obtain relative irreversible capacity data; the first sample battery pack includes at least two first sample batteries of different specifications; A life cycle test module, used to perform a life cycle test on a second sample battery pack based on a second test condition to obtain life inflection point data; the second sample battery pack includes a second sample battery with the same specification as each of the first sample batteries; A model fitting module is used to perform fitting based on the relative irreversible capacity data and the life inflection point data to obtain a capacity-life inflection point relationship model.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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