Pole piece stripping detection method, system and equipment in battery aging process and medium

Abstract

The invention provides a pole piece stripping detection method, system and equipment in a battery aging process and a medium, and relates to the technical field of battery detection, and the method comprises the following steps: obtaining battery cell experiment data of battery aging; calculating a first charging capacity change rate and a second charging capacity change rate according to the battery cell experiment data, and determining a first capacity attenuation range caused by battery lithium precipitation, a second capacity attenuation range caused by battery aging and stripping, and a characteristic peak area change range; according to the first charging capacity change rate and the second charging capacity change rate, determining a capacity attenuation range of pure stripping of the battery cell pole piece, and obtaining a third capacity attenuation range; and acquiring cell capacity data and cell voltage data of the to-be-detected cell, calculating to obtain an actual capacity attenuation rate and a target characteristic peak area variation, and determining a pole piece stripping result of the to-be-detected cell in combination with the second capacity attenuation range and the characteristic peak area variation range. According to the invention, the battery cell of which the pole piece is stripped during battery aging can be accurately identified.

Description

Technical Field

[0001] This invention relates to the field of battery testing technology, specifically to a method, system, equipment, and medium for detecting electrode stripping during battery aging. Background Technology

[0002] As batteries enter the aging stage, the active material shedding from battery electrodes exhibits significantly different characteristics and mechanisms due to the combined effects of multiple factors, including uneven local stress distribution, cumulative temperature effects, and electrochemical performance degradation. This phenomenon mainly occurs inside the battery, and its evolution typically begins in localized areas at the microscale, gradually intensifying with increasing cycle count.

[0003] Currently, the development of detection technologies for electrode shedding during battery aging faces several key challenges: First, there is the issue of signal detection sensitivity, as the physical signal amplitude generated by early shedding is typically extremely weak and easily interfered with by signals from other aging mechanisms; second, there is the challenge of decoupling multiple mechanisms, as shedding often occurs simultaneously with aging processes such as lithium plating and SEI film growth, making it significantly difficult to accurately distinguish the contributions of different mechanisms. Therefore, effectively addressing the insufficient detection accuracy of electrode shedding caused by the coupling effect of multiple mechanisms during battery aging has become a critical technological bottleneck that urgently needs to be overcome in this field. Summary of the Invention

[0004] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method, system, equipment and medium for detecting electrode stripping during battery aging, which effectively solves the problem of insufficient detection accuracy of electrode stripping caused by the coupling effect of multiple mechanisms during battery aging.

[0005] In a first aspect, the present invention provides a method for detecting electrode stripping during battery aging, the method comprising: Obtain battery cell test data for battery aging, including normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data; Calculate the first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and determine the first capacity decay range caused by lithium plating based on the first charging capacity change rate. The second charging capacity change rate is calculated based on the data of the aged and de-materialized battery cells, and a capacity increment curve is constructed. The range of the second capacity decay caused by battery aging and de-materialization is determined based on the second charging capacity change rate, and the range of characteristic peak area change is determined based on the capacity increment curve. Based on the first charging capacity change rate and the second charging capacity change rate, the capacity decay range of the cell electrode sheet under simple stripping is determined, and a third capacity decay range is obtained. Acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct a target capacity increment curve based on the cell capacity data and the cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve; The electrode stripping result of the cell under test is determined based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range.

[0006] In an optional implementation, obtaining the battery cell experimental data during battery aging includes: Selected battery cells during the battery aging process: normally aged cells, aged lithium-plated cells, and aged cells that have been stripped of material. Two consecutive constant current charge-discharge tests were performed on the normal aging cell, the aging lithium-plated cell, and the aging dematerialized cell, respectively. Capacity and voltage data of the normally aged battery cell, the aged lithium-plated battery cell, and the aged dematerialized battery cell were collected from two consecutive charging cycles to obtain data of the normally aged battery cell, the aged lithium-plated battery cell, and the aged dematerialized battery cell.

[0007] In an optional implementation, the step of calculating a first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and determining a first capacity decay range caused by lithium plating based on the first charging capacity change rate, includes: Obtain the capacity data from the normal aging cell data and the aging lithium-plated cell data, calculate the capacity change rate of the normal aging cell and the aging lithium-plated cell, and obtain the first charging capacity change rate; A first capacity increment curve is constructed based on the normal aging cell data and the aging lithium-plated cell data obtained from the first charge, and a second capacity increment curve is constructed based on the normal aging cell data and the aging lithium-plated cell data obtained from the second charge. The amount of lithium deposited during the first charge is calculated based on the lithium deposit peak of the first capacity increment curve, and the amount of lithium deposited during the second charge is calculated based on the lithium deposit peak of the second capacity increment curve. The first capacity decay range is obtained by calculating the range of the first charging capacity change rate based on the lithium deposition amount during the first charge and the lithium deposition amount during the second charge.

[0008] In an optional implementation, the step of calculating the second charging capacity change rate and constructing a capacity increment curve based on the data of the aged and de-discharged battery cells, determining the second capacity decay range caused by battery aging and de-discharge based on the second charging capacity change rate, and determining the characteristic peak area change range based on the capacity increment curve includes: Obtain the capacity data from the aged and de-materialized battery cell data, calculate the capacity change rate of the aged and de-materialized battery cell and statistically analyze the numerical range to obtain the second capacity decay range; A third capacity increment curve is constructed based on the aging and stripping cell data obtained from the first charge, and a fourth capacity increment curve is constructed based on the aging and stripping cell data obtained from the second charge. The area of ​​the first charging desiccation peak is calculated based on the desiccation peak of the third capacity increment curve, and the area of ​​the second charging desiccation peak is calculated based on the desiccation peak of the fourth capacity increment curve. The range of variation of the characteristic peak area is determined based on the peak area of ​​the first charging and the peak area of ​​the second charging.

[0009] In an optional implementation, determining the capacity decay range of the cell electrode stripping based on the first charging capacity change rate and the second charging capacity change rate, and obtaining the third capacity decay range, includes: Calculate the difference between the second charging capacity change rate and the first charging capacity change rate to obtain the third charging capacity change rate, which represents the capacity change rate of the cell electrode sheet simply after deslagging. The third charging capacity change rate is statistically analyzed to obtain the third capacity decay range.

[0010] In an optional implementation, the steps of acquiring the cell capacity data and cell voltage data of the cell to be tested, calculating the actual capacity decay rate based on the cell capacity data, constructing a target capacity increment curve based on the cell capacity data and the cell voltage data, and calculating the target characteristic peak area change based on the target capacity increment curve include: The cell under test is subjected to two consecutive constant current charge-discharge tests to obtain the capacity data and voltage data of the first cell during the first charge, and the capacity data and voltage data of the second cell during the second charge. The actual capacity decay rate is obtained by calculating based on the first cell capacity data and the second cell capacity data; A first target capacity increment curve is constructed based on the first cell capacity data and the first cell voltage data, and a second target capacity increment curve is constructed based on the second cell capacity data and the second cell voltage data. The area of ​​the first target desizing peak is calculated based on the desizing peak of the first target capacity increment curve, and the area of ​​the second target desizing peak is calculated based on the desizing peak of the second target capacity increment curve. The change in the area of ​​the target characteristic peak is calculated based on the area of ​​the first target deslagging peak and the area of ​​the second target deslagging peak.

[0011] In an optional implementation, determining the electrode stripping result of the cell under test based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range, includes: If the actual capacity decay rate of the cell under test is greater than or equal to the minimum value of the second capacity decay range, and the change in the target characteristic peak area is greater than or equal to the minimum value of the characteristic peak area change range, then the cell under test is a cell with electrode stripping; otherwise, it is a cell with electrode non-stripping.

[0012] Secondly, the present invention provides a battery electrode stripping detection system during battery aging, the system comprising: The data acquisition module is used to acquire battery cell test data during battery aging. The battery cell test data includes normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data. The first calculation module is used to calculate the first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and to determine the first capacity decay range caused by battery lithium plating based on the first charging capacity change rate. The second calculation module is used to calculate the second charging capacity change rate and construct the capacity increment curve based on the aging and descaling cell data, determine the second capacity decay range caused by battery aging and descaling based on the second charging capacity change rate, and determine the characteristic peak area change range based on the capacity increment curve. The third calculation module is used to determine the capacity decay range of the cell electrode sheet simply being removed from the material based on the first charging capacity change rate and the second charging capacity change rate, and to obtain the third capacity decay range. The cell detection module is used to acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct a target capacity increment curve based on the cell capacity data and the cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve. The stripping detection module is used to determine the electrode stripping result of the cell under test based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range.

[0013] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the electrode stripping detection method during battery aging as described in the first aspect of the present invention.

[0014] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the electrode stripping detection method during battery aging as described in the first aspect of the present invention.

[0015] This invention provides a method, system, equipment, and medium for detecting electrode shedding during battery aging. By constructing a quantitative relationship model between lithium plating and capacity decay, and eliminating the influence of lithium plating, it accurately analyzes the correspondence between electrode shedding and capacity decay. Combined with the characteristic peak area changes of the capacity increment curve, it effectively distinguishes multiple mechanisms in the battery aging process, accurately identifying battery cells experiencing electrode shedding. It can achieve early identification of aging cells with highly concealed and slow-developing shedding, avoiding misjudgments. Simultaneously, it provides a new approach to solving the complex coupling problem of battery aging, promoting the development of battery testing technology towards greater accuracy and depth. Furthermore, it eliminates the need for complex and expensive equipment and destructive disassembly, simplifying operation, reducing the complexity and cost of the testing process, and can be easily integrated into existing battery management systems or testing processes, enhancing its engineering application and promotion value. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a first schematic diagram of the battery aging process electrode stripping detection method provided in the embodiments of the present invention; Figure 2 This is a second schematic diagram of the battery aging process electrode stripping detection method provided in the embodiments of the present invention; Figure 3 This is a third schematic diagram of the battery aging process electrode stripping detection method provided in the embodiments of the present invention; Figure 4 This is a schematic diagram of a capacity increment curve in an embodiment of the present invention; Figure 5 This is the fourth schematic diagram of the battery aging process electrode stripping detection method provided in the embodiments of the present invention; Figure 6 This is the fifth schematic diagram of the battery aging process electrode stripping detection method provided in the embodiments of the present invention; Figure 7 This is the sixth schematic diagram of the battery aging process electrode stripping detection method provided in the embodiment of the present invention; Figure 8This is a schematic diagram illustrating the accuracy of battery cell electrode stripping identification under different conditions in an embodiment of the present invention; Figure 9 This is a schematic diagram of the electrode stripping detection system provided in an embodiment of the present invention during battery aging. Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0018] Explanation of key component symbols: 200. Electrode stripping detection system during battery aging; 210. Data acquisition module; 220. First calculation module; 230. Second calculation module; 240. Third calculation module; 250. Cell detection module; 260. Stripping detection module; 300. Electronic equipment; 310. Processor; 320. Communication interface; 330. Memory; 340. Communication bus. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be further described clearly and completely below with reference to the accompanying drawings of the embodiments of this invention. It should be noted that the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0022] During battery aging, repeated charge-discharge cycles cause the active materials to undergo repeated volume expansion and contraction, gradually weakening the bonds between active material particles and between the active material and the current collector. Temperature exacerbates this process; the battery generates heat during operation, and uneven temperature distribution leads to differences in expansion across different areas of the electrodes, inducing thermal stress. Electrochemical factors also work synergistically with stress and temperature, causing the electrolyte to gradually seep into microcracks and react with the highly active, fresh surface, forming an unstable interfacial phase. This process not only consumes active lithium but also produces gaseous byproducts, creating additional internal pressure and further accelerating the shedding of active material.

[0023] Therefore, under the coupled effects of chemical, temperature, and mechanical fields, electrode stripping during battery aging exhibits gradual and localized characteristics. Initially, it only affects small areas, but over time, these micro-regions gradually coalesce, leading to accelerated battery performance degradation. Simultaneously, electrode stripping during battery aging often coexists with other aging modes such as lithium plating and SEI film thickening, and these modes mutually reinforce each other, forming a complex positive feedback loop. Accurately distinguishing the contributions of different mechanisms is significantly difficult. Therefore, effectively addressing the insufficient detection accuracy of electrode stripping caused by the multi-mechanism coupling effect during battery aging has become a key technological bottleneck that urgently needs to be overcome in this field.

[0024] Example 1 This invention provides a method for detecting electrode stripping during battery aging, effectively solving the problem of insufficient detection accuracy of electrode stripping caused by the coupling effect of multiple mechanisms during battery aging. Figure 1 This is a first schematic diagram of the battery aging process electrode stripping detection method provided in this embodiment of the invention, as shown below. Figure 1 As shown, the method includes the following steps: S100. Obtain battery cell test data during battery aging. The battery cell test data includes data of normally aged cells, data of aged lithium-plated cells, and data of aged cells that have been stripped of material.

[0025] Figure 2 This is a second schematic diagram of the electrode stripping detection method during battery aging provided in this embodiment of the invention, as shown in the figure. Figure 2 As shown, the acquisition of cell experimental data specifically includes the following steps: S110. Select normal aging cells, lithium-plated aging cells, and dematerialized aging cells during the battery aging process.

[0026] In this embodiment of the invention, cells of the same model can be selected from the same batch of aged batteries, including normally aged cells, aged lithium-plated cells, and aged cells with electrode stripping. Normally aged cells are those without lithium plating or electrode stripping; aged lithium-plated cells are those with lithium plating during normal aging but without electrode stripping; and aged cells with electrode stripping are those with electrode stripping during normal aging, regardless of whether lithium plating or other factors are present.

[0027] S120. Two consecutive constant current charge-discharge tests were performed on the normal aging cell, the aging lithium-plated cell, and the aging dematerialized cell, respectively.

[0028] In this embodiment of the invention, under the same testing environment, two consecutive constant current charge-discharge tests are performed on normal aging cells, aged lithium-plated cells, and aged dematerialized cells using arbitrary currents, i.e., constant current charge-discharge-charge-discharge tests are conducted. Continuous constant current charge-discharge tests can minimize interference from other factors. If two discontinuous charging data are compared, other factors may cause capacity changes in between.

[0029] S130: Collect capacity and voltage data from two consecutive charges of normal aging cells, aging lithium-plated cells, and aging dematerialized cells, respectively, to obtain data for normal aging cells, aging lithium-plated cells, and aging dematerialized cells.

[0030] In this embodiment of the invention, capacity and voltage data of normally aged cells, aged lithium-plated cells, and aged dematerialized cells are collected from two consecutive charges during a constant current charge-discharge-charge-discharge test, respectively, to obtain data for normally aged cells, aged lithium-plated cells, and aged dematerialized cells. The data for normally aged cells, aged lithium-plated cells, and aged dematerialized cells all include the capacity and voltage data obtained from the first charge and the second charge.

[0031] S200: Calculate the first charging capacity change rate based on normal aging cell data and aging lithium-plated cell data, and determine the first capacity decay range caused by lithium plating based on the first charging capacity change rate.

[0032] Figure 3 This is a third schematic diagram of the battery aging process electrode stripping detection method provided in this embodiment of the invention, as shown in the diagram. Figure 3 As shown, determining the first capacity decay range specifically includes the following steps: S210. Obtain capacity data from normal aging cell data and aging lithium-plated cell data, calculate the capacity change rate of normal aging cell and aging lithium-plated cell, and obtain the first charging capacity change rate.

[0033] In this embodiment of the invention, the capacity data obtained from the first charge and the capacity data obtained from the second charge of normal aging cells and aged lithium-plated cells are obtained respectively. The capacity change rate of each normal aging cell and aged lithium-plated cell is calculated to obtain the first charging capacity change rate. The calculation formula is as follows:

[0034] In the above formula, a This represents the first rate of change in charging capacity. Q 1 indicates the capacity data of the first charge of a normal aging cell or an aged lithium-plated cell. Q 2 indicates the capacity data of a normal aging cell or an aging lithium-plated cell during the second charge.

[0035] S220. Construct a first capacity increment curve based on the normal aging cell data and the aging lithium-plated cell data obtained from the first charge, and construct a second capacity increment curve based on the normal aging cell data and the aging lithium-plated cell data obtained from the second charge.

[0036] In this embodiment of the invention, for each normal aging cell and aged lithium-plated cell, the capacity and voltage data obtained from the first charge in the normal aging cell data and aged lithium-plated cell data are differentiated to obtain... dQ / dV Data, with voltage data as the x-axis value, dQ / dV The data is used to construct the first capacity increment curve based on the ordinate values. Figure 4 This is a schematic diagram of a capacity increment curve in an embodiment of the present invention. Similarly, for each normally aged cell and aged lithium-plated cell, the capacity and voltage data obtained from the second charge can be differentiated and a second capacity increment curve can be constructed.

[0037] S230. Calculate the amount of lithium deposited during the first charge based on the lithium deposit peak of the first capacity increment curve, and calculate the amount of lithium deposited during the second charge based on the lithium deposit peak of the second capacity increment curve.

[0038] The last peak of the capacity increment curve is the phase transition peak caused by lithium plating, i.e., the lithium plating amount peak. Therefore, by integrating the peak area within the voltage range corresponding to the lowest point between the penultimate peak of the capacity increment curve and the lithium plating amount peak, and ending at the voltage corresponding to the end of the capacity increment curve, the specific value of the lithium plating amount for each charge can be obtained. The integral calculation formula is as follows:

[0039] In the above formula, L Indicates the amount of lithium deposited. This represents the derivative of capacitance with respect to voltage. V1 represents the voltage value at the lowest point between the penultimate peak of the capacity increment curve and the lithium deposition peak. V 2 indicates the voltage value corresponding to the end of the capacity increment curve.

[0040] By integrating the lithium deposition peaks of each first capacity increment curve, multiple amounts of lithium deposition during the first charge can be obtained. L 1. By integrating the lithium deposition peaks of each second capacity increment curve, multiple amounts of lithium deposition during the second charge can be obtained. L 2.

[0041] S240. Based on the lithium plating amount during the first charge and the lithium plating amount during the second charge, calculate the numerical range of the first charge capacity change rate to obtain the first capacity decay range.

[0042] In this embodiment of the invention, if the calculated amount of lithium plating during the first charge is... L 1 and the amount of lithium deposited during the second charge L If both 2 equal 0, it indicates that the corresponding battery cell does not exhibit lithium plating. This suggests the cell is a normally aging cell, without lithium plating or material loss. The range of values ​​corresponding to the first charging capacity change rate at this point is then calculated to obtain the corresponding range of the first charging capacity change rate. If the calculated amount of lithium plating during the first charge is... L If 1 is greater than 0, it indicates that the corresponding cell has lithium plating. The cell can be considered as an aged lithium plating cell. The range of the first charging capacity change rate is statistically analyzed to obtain the corresponding range of the second charging capacity change rate.

[0043] In this embodiment of the invention, the first capacity decay range is the range of cell capacity changes caused by normal aging and lithium plating, i.e., the union of the first charging capacity change rate range and the second charging capacity change rate range. This range can be used to eliminate capacity changes caused by normal aging and lithium plating, and to quantitatively calculate the capacity changes mainly caused by electrode stripping. For example, if the first charging capacity change rate range is 0 ≤ a ≤ A 1. The range of the second charging capacity change rate is: A 2≤ a ≤ A 3, then the first capacity decay range is 0 ≤ a ≤ A 1 and A 2≤ a ≤ A 3.

[0044] S300: Calculate the second charging capacity change rate based on the data of the aged and de-materialized battery cells and construct the capacity increment curve. Determine the range of the second capacity decay caused by battery aging and de-materialization based on the second charging capacity change rate, and determine the range of characteristic peak area change based on the capacity increment curve.

[0045] Figure 5 This is the fourth schematic diagram of the battery aging process electrode stripping detection method provided in this embodiment of the invention, as shown in the following figure. Figure 5 As shown, determining the second capacity decay range and the characteristic peak area variation range specifically includes the following steps: S310. Obtain the capacity data from the aged and de-materialized battery cell data, calculate the capacity change rate of the aged and de-materialized battery cell and statistically analyze the numerical range to obtain the second capacity decay range.

[0046] In this embodiment of the invention, the capacity data obtained from the first charge and the capacity data obtained from the second charge of the aged and de-discharged battery cells are acquired respectively. The capacity change rate of each aged and de-discharged battery cell is calculated to obtain the second charge capacity change rate. The calculation formula is as follows:

[0047] In the above formula, b This indicates the rate of change of the second charging capacity. Q 3 indicates the capacity data of the first charge of a certain aged and stripped battery cell. Q 4 indicates the capacity data of a certain aged and stripped battery cell during its second charge.

[0048] By statistically analyzing the range of the second charging capacity change rate for all aged, degraded battery cells, the second capacity decay range can be obtained. If a battery cell has a charging capacity change rate greater than or equal to the minimum value of the second capacity decay range after two consecutive charges, it is determined that the cell's electrodes have degraded. For example, if the second capacity decay range is... B 1 ≤ b≤B 2. If the rate of change of charging capacity of a certain battery cell during two consecutive charging cycles is greater than or equal to... B 1. This indicates that the electrode plates of the battery cell are experiencing material loss.

[0049] S320. Construct a third capacity increment curve based on the aging and stripping cell data obtained from the first charge, and construct a fourth capacity increment curve based on the aging and stripping cell data obtained from the second charge.

[0050] In this embodiment of the invention, for each aged and stripped battery cell, the capacity and voltage data obtained from the first charge in the aged and stripped battery cell data are differentiated to obtain... dQ / dV Data, with voltage data as the x-axis value, dQ / dV The data is used as the vertical axis to construct a third capacity increment curve. Similarly, for each aged and stripped cell, the capacity and voltage data obtained from the second charge can be differentiated to construct a fourth capacity increment curve.

[0051] S330. Calculate the area of ​​the first charging desiccation peak based on the desiccation peak of the third capacity increment curve, and calculate the area of ​​the second charging desiccation peak based on the desiccation peak of the fourth capacity increment curve.

[0052] Electrode stripping in battery cells leads to the permanent loss of active material, which is directly reflected in the attenuation of the peak area of ​​the incremental capacity curve, representing the phase transition characteristics of this active material. In the capacity increment curves obtained from two consecutive charge-discharge tests, the changes in the area of ​​the first two peaks are strongly correlated with electrode stripping; therefore, the first two peaks in the capacity increment curve are considered as stripping peaks. Using the voltage value corresponding to the start of the capacity increment curve as the starting point and the voltage value corresponding to the lowest point between the second and third peaks as the ending point, the peak area within this voltage range is integrated to obtain the stripping peak area. The formula for calculating the stripping peak area is as follows:

[0053] In the above formula, S This indicates the area of ​​the discharge peak. This represents the derivative of capacitance with respect to voltage. V 3 indicates the voltage value corresponding to the start of the capacity increment curve. V 4 represents the voltage value corresponding to the lowest point between the second and third peaks of the capacity increment curve.

[0054] By integrating the shedding peaks of the first capacity increment curve corresponding to each aged and shedding cell, the areas of multiple shedding peaks during the first charge can be obtained. S 1. By integrating the shedding peaks of the second capacity increment curves corresponding to each aged and shedding cell, the areas of multiple shedding peaks during the second charge can be obtained. S 2.

[0055] S340. Determine the range of characteristic peak area variation based on the peak area of ​​the first charge and the peak area of ​​the second charge.

[0056] In this embodiment of the invention, the change in characteristic peak area is calculated based on the peak areas of the first and second charging cycles corresponding to each aged and shed battery cell. The calculation formula is as follows:

[0057] In the above formula, This indicates the change in the area of ​​the characteristic peak. S 1 represents the peak area of ​​the first charge desiccation. S 2 indicates the peak area of ​​the second charge stripping.

[0058] By statistically analyzing the numerical range of the change in the area of ​​the characteristic peak, the range of change in the area of ​​the characteristic peak can be obtained.

[0059] S400: Determine the capacity decay range of the cell electrode sheet under simple stripping based on the first and second charging capacity change rates, and obtain the third capacity decay range.

[0060] Figure 6 This is the fifth schematic diagram of the battery aging process electrode stripping detection method provided in this embodiment of the invention, as shown in the figure. Figure 6 As shown, determining the third capacity attenuation range specifically includes the following steps: S410. Calculate the difference between the second charging capacity change rate and the first charging capacity change rate to obtain the third charging capacity change rate, which represents the capacity change rate of the cell electrode sheet after simple stripping.

[0061] In this embodiment of the invention, aging and material loss in the battery cell will inevitably be accompanied by lithium plating. Therefore, the second charging capacity change rate is usually greater than or equal to the first charging capacity change rate. Subtracting the first charging capacity change rate from the second charging capacity change rate yields the third charging capacity change rate. c=ba ,in c This represents the third charging capacity change rate. This third charging capacity change rate excludes capacity changes caused by normal aging and lithium plating, and represents the capacity change rate due to simple stripping of the cell electrode sheets.

[0062] S420: Perform numerical statistics on the third charging capacity change rate to obtain the third capacity decay range.

[0063] In this embodiment of the invention, each second charging capacity change rate is subtracted from each first charging capacity change rate to obtain a third charging capacity change rate, and numerical statistics are performed to obtain a third capacity decay range, which is used to quantify the impact range of simple cell electrode stripping on capacity change.

[0064] S500: Acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct the target capacity increment curve based on the cell capacity data and cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve.

[0065] Figure 7 This is the sixth schematic diagram of the battery aging process electrode stripping detection method provided in this embodiment of the invention, as shown in Figure 6. Figure 7 As shown, the calculation of the actual capacity decay rate and the change in the target characteristic peak area specifically includes the following steps: S510. Perform two consecutive constant current charge-discharge tests on the cell to be tested to obtain the capacity and voltage data of the first cell during the first charge, and the capacity and voltage data of the second cell during the second charge.

[0066] In this embodiment of the invention, the battery cell to be tested is subjected to two consecutive constant current charge-discharge tests. The current used is the same as the current used to obtain the battery cell experimental data. The first battery cell capacity data and the first battery cell voltage data are obtained during the first charge, and the second battery cell capacity data and the second battery cell voltage data are obtained during the second charge.

[0067] S520: Calculate the actual capacity decay rate based on the capacity data of the first and second cells.

[0068] In this embodiment of the invention, the formula for calculating the actual capacity decay rate is as follows:

[0069] In the above formula, q Indicates the actual capacity decay rate. Q 5 indicates the capacity data of the first cell during the first charge of the battery cell under test. Q 6 indicates the capacity data of the second cell during the second charge of the cell under test.

[0070] S530. Construct a first target capacity increment curve based on the first cell capacity data and the first cell voltage data, and construct a second target capacity increment curve based on the second cell capacity data and the second cell voltage data.

[0071] In this embodiment of the invention, for the battery cell to be tested, differential processing is performed based on the first battery cell capacity data and the first battery cell voltage data to obtain... dQ / dV Data, with the voltage data of the first cell as the x-axis value, dQ / dV The data is used as the ordinate to construct the first target capacity increment curve. Similarly, the second target capacity increment curve is constructed by differentiating the second cell capacity data and the second cell voltage data.

[0072] S540. Calculate the area of ​​the first target desiccant peak based on the desiccant peak of the first target capacity increment curve, and calculate the area of ​​the second target desiccant peak based on the desiccant peak of the second target capacity increment curve.

[0073] In this embodiment of the invention, the area of ​​the first target deslagging peak can be obtained by integrating the deslagging peak of the first target capacity increment curve corresponding to the cell under test. D 1. By integrating the desizing peak of the second target capacity increment curve corresponding to the cell under test, the area of ​​the second target desizing peak can be obtained. D 2.

[0074] S550. Calculate the change in the area of ​​the target characteristic peak based on the area of ​​the first target desizing peak and the area of ​​the second target desizing peak.

[0075] In this embodiment of the invention, the formula for calculating the change in the area of ​​the target characteristic peak is as follows:

[0076] In the above formula, This represents the change in the area of ​​the target characteristic peak. D 1 represents the area of ​​the first target stripping peak. D 2 represents the area of ​​the second target material removal peak.

[0077] S600. Based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range, determine the electrode stripping result of the cell to be tested.

[0078] In this embodiment of the invention, if the actual capacity decay rate of the cell under test is greater than or equal to the minimum value of the second capacity decay range, and the change in the target characteristic peak area is greater than or equal to the minimum value of the characteristic peak area change range, then the cell under test is a cell with de-electrode electrode; otherwise, it is a cell with un-electrode electrode. For example, the second capacity decay range is... B 1≤ b ≤ B 2. The range of characteristic peak area variation is: If the actual capacity decay rate of the cell to be tested q Greater than or equal to B 1, and the change in the area of ​​the target characteristic peak. Greater than or equal to U If so, the cell to be tested is determined to be a cell with de-electrode electrode.

[0079] As a further embodiment of the present invention, to verify the accuracy of the electrode stripping detection method during battery aging provided by the present invention, multiple battery cells in actual application are selected as a verification set. Constant current charging-discharging-charging-discharging tests of arbitrary current are performed on each battery cell to obtain a cell verification dataset. Based on this cell verification dataset, the actual capacity decay rate and the target characteristic peak area change are calculated according to each step of step S500. These are then compared with the second capacity decay range and characteristic peak area change range obtained through prior experimental testing for judgment under different conditions. First, only the actual capacity decay rate and the second capacity decay range are used for judgment. Then, only the target characteristic peak area change and the characteristic peak area change range are used for judgment. Finally, the actual capacity decay rate and the target characteristic peak area change are combined with the second capacity decay range and the characteristic peak area change range for comprehensive judgment. The accuracy of electrode stripping identification under different conditions is calculated using the following formula:

[0080] In the above formula, P This indicates the accuracy of the identification of battery cell electrode stripping.n 1 indicates the number of cells identified as having undergone electrode stripping in the verification process. n 2 indicates the number of battery cells with de-electrode material actually present in the verification set.

[0081] Figure 8 This is a schematic diagram illustrating the accuracy of battery cell electrode stripping identification under different conditions in an embodiment of the present invention, such as... Figure 8 As shown, the accuracy rate for identifying electrode stripping in battery cells using only the second capacity decay range as the judgment condition is 73%, the accuracy rate using only the characteristic peak area change range as the judgment condition is 76%, and the accuracy rate using a combination of the second capacity decay range and the characteristic peak area change range as the judgment condition is 89%. Therefore, combining the two judgment conditions can greatly improve the accuracy of identifying electrode stripping in battery cells.

[0082] The electrode shedding detection method provided in this invention, during battery aging, accurately analyzes the correspondence between electrode shedding and capacity decay by constructing a quantitative relationship model between lithium plating and capacity decay, eliminating the influence of lithium plating. Combined with the characteristic peak area changes of the capacity increment curve, it effectively distinguishes multiple mechanisms in the battery aging process, accurately identifying battery cells experiencing electrode shedding. This allows for early identification of aging cells with highly concealed and slow-developing shedding, avoiding misjudgments. Simultaneously, it provides a new approach to solving the complex coupling problem of battery aging, promoting the development of battery detection technology towards greater precision and depth.

[0083] Example 2 Based on the same technical concept as Embodiment 1 above, this embodiment of the invention provides an electrode stripping detection system during battery aging. Figure 9 This is a schematic diagram of the electrode stripping detection system during battery aging provided in an embodiment of the present invention, as shown below. Figure 9 As shown, the electrode stripping detection system 200 during the battery aging process includes: The data acquisition module 210 is used to acquire battery cell test data during battery aging. The battery cell test data includes normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data.

[0084] The first calculation module 220 is used to calculate the first charging capacity change rate based on normal aging cell data and aging lithium-plated cell data, and to determine the first capacity decay range caused by lithium plating based on the first charging capacity change rate.

[0085] The second calculation module 230 is used to calculate the second charging capacity change rate and construct the capacity increment curve based on the data of the aged and de-materialized battery cells, determine the second capacity decay range caused by battery aging and de-materialization based on the second charging capacity change rate, and determine the characteristic peak area change range based on the capacity increment curve.

[0086] The third calculation module 240 is used to determine the capacity decay range of the cell electrode sheet simply stripping based on the first charging capacity change rate and the second charging capacity change rate, and to obtain the third capacity decay range.

[0087] The cell detection module 250 is used to acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct the target capacity increment curve based on the cell capacity data and cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve.

[0088] The stripping detection module 260 is used to determine the stripping result of the electrode of the cell under test based on the actual capacity decay rate and the change in the target characteristic peak area, combined with the second capacity decay range and the change range of the characteristic peak area.

[0089] The electrode stripping detection system provided in this invention for battery aging processes does not require complex and expensive equipment or destructive disassembly. It is easy to operate, reduces the complexity and cost of the detection process, and can be easily integrated into existing battery management systems or detection processes, thereby enhancing its engineering application and promotion value.

[0090] It is understood that the implementation method of the electrode stripping detection method in the battery aging process described in Embodiment 1 above is also applicable to this embodiment and can achieve the same technical effect, so it will not be described again here.

[0091] Example 3 Based on the same concept, embodiments of the present invention also provide an electronic device. Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 10 As shown, the electronic device 300 may include a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute the steps of the electrode stripping detection method during battery aging as described in the above embodiments. For example, this includes: S100. Obtain battery cell test data for battery aging. The battery cell test data includes normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data. S200: Calculate the first charging capacity change rate based on normal aging cell data and aging lithium-plated cell data, and determine the first capacity decay range caused by battery lithium plating based on the first charging capacity change rate. S300: Calculate the second charging capacity change rate and construct the capacity increment curve based on the data of the aged and de-materialized battery cells; determine the range of the second capacity decay caused by battery aging and de-materialization based on the second charging capacity change rate; and determine the range of characteristic peak area change based on the capacity increment curve. S400: Determine the capacity decay range of simple deslagging of the cell electrode based on the first charging capacity change rate and the second charging capacity change rate, and obtain the third capacity decay range. S500: Acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct the target capacity increment curve based on the cell capacity data and cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve. S600. Based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range, determine the electrode stripping result of the cell to be tested.

[0092] The processor 310 can be a central processing unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0093] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] The memory 330 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0095] Example 4 Based on the same concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program containing at least one piece of code executable by a master control device to control the master control device to implement the steps of the electrode stripping detection method during battery aging as described in the above embodiments. For example, it includes: S100. Obtain battery cell test data for battery aging. The battery cell test data includes normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data. S200: Calculate the first charging capacity change rate based on normal aging cell data and aging lithium-plated cell data, and determine the first capacity decay range caused by battery lithium plating based on the first charging capacity change rate. S300: Calculate the second charging capacity change rate and construct the capacity increment curve based on the data of the aged and de-materialized battery cells; determine the range of the second capacity decay caused by battery aging and de-materialization based on the second charging capacity change rate; and determine the range of characteristic peak area change based on the capacity increment curve. S400: Determine the capacity decay range of simple deslagging of the cell electrode based on the first charging capacity change rate and the second charging capacity change rate, and obtain the third capacity decay range. S500: Acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct the target capacity increment curve based on the cell capacity data and cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve. S600. Based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range, determine the electrode stripping result of the cell to be tested.

[0096] Based on the same technical concept, this embodiment of the invention also provides a computer program, which, when executed by a master control device, is used to implement the above-described method embodiments.

[0097] The computer program may be stored, in whole or in part, on a computer-readable storage medium packaged with the processor, or in part or in whole on a memory not packaged with the processor.

[0098] Based on the same technical concept, embodiments of the present invention also provide a processor for implementing the above-described method embodiments. The processor may be a chip.

[0099] In summary, the electrode shedding detection method, system, equipment, and medium provided by this invention, during battery aging, accurately analyzes the correspondence between electrode shedding and capacity decay by constructing a quantitative relationship model between lithium plating and capacity decay, eliminating the influence of lithium plating. Combined with the characteristic peak area changes of the capacity increment curve, it effectively distinguishes multiple mechanisms in the battery aging process, accurately identifying battery cells experiencing electrode shedding. This enables early identification of aging cells with highly concealed and slow-developing shedding, avoiding misjudgments. Simultaneously, it provides a new approach to solving the complex coupling problem of battery aging, promoting the development of battery testing technology towards greater accuracy and depth. Furthermore, it eliminates the need for complex and expensive equipment and destructive disassembly, simplifying operation, reducing the complexity and cost of the testing process, and can be easily integrated into existing battery management systems or testing processes, enhancing its engineering application and promotion value.

[0100] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0101] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting electrode stripping during battery aging, characterized in that, The method includes: Obtain battery cell test data for battery aging, including normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data; Calculate the first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and determine the first capacity decay range caused by lithium plating based on the first charging capacity change rate. Calculate the second charging capacity change rate and construct the capacity increment curve based on the data of the aged and de-materialized battery cells. Determine the range of the second capacity decay caused by battery aging and de-materialization based on the second charging capacity change rate. Determine the range of characteristic peak area change based on the capacity increment curve. Based on the first charging capacity change rate and the second charging capacity change rate, the capacity decay range of the cell electrode sheet under simple stripping is determined, and a third capacity decay range is obtained. Acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct a target capacity increment curve based on the cell capacity data and the cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve; The electrode stripping result of the cell under test is determined based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range.

2. The method for detecting electrode stripping during battery aging according to claim 1, characterized in that, The acquisition of battery cell experimental data during battery aging includes: Selected battery cells during the battery aging process: normally aged cells, aged lithium-plated cells, and aged cells that have been stripped of material. Two consecutive constant current charge-discharge tests were performed on the normal aging cell, the aging lithium-plated cell, and the aging dematerialized cell, respectively. Capacity and voltage data of the normally aged battery cell, the aged lithium-plated battery cell, and the aged dematerialized battery cell were collected from two consecutive charging cycles to obtain data of the normally aged battery cell, the aged lithium-plated battery cell, and the aged dematerialized battery cell.

3. The method for detecting electrode stripping during battery aging according to claim 2, characterized in that, The step of calculating the first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and determining the first capacity decay range caused by lithium plating based on the first charging capacity change rate, includes: Obtain the capacity data from the normal aging cell data and the aging lithium-plated cell data, calculate the capacity change rate of the normal aging cell and the aging lithium-plated cell, and obtain the first charging capacity change rate; A first capacity increment curve is constructed based on the normal aging cell data and the aging lithium-plated cell data obtained from the first charge, and a second capacity increment curve is constructed based on the normal aging cell data and the aging lithium-plated cell data obtained from the second charge. The amount of lithium deposited during the first charge is calculated based on the lithium deposit peak of the first capacity increment curve, and the amount of lithium deposited during the second charge is calculated based on the lithium deposit peak of the second capacity increment curve. The first capacity decay range is obtained by calculating the range of the first charging capacity change rate based on the lithium deposition amount during the first charge and the lithium deposition amount during the second charge.

4. The method for detecting electrode stripping during battery aging according to claim 3, characterized in that, The step of calculating the second charging capacity change rate and constructing a capacity increment curve based on the data of the aged and de-discharged battery cells, determining the second capacity decay range caused by battery aging and de-discharge based on the second charging capacity change rate, and determining the characteristic peak area change range based on the capacity increment curve includes: Obtain the capacity data from the aged and de-materialized battery cell data, calculate the capacity change rate of the aged and de-materialized battery cell and statistically analyze the numerical range to obtain the second capacity decay range; A third capacity increment curve is constructed based on the aging and stripping cell data obtained from the first charge, and a fourth capacity increment curve is constructed based on the aging and stripping cell data obtained from the second charge. The area of ​​the first charging desiccation peak is calculated based on the desiccation peak of the third capacity increment curve, and the area of ​​the second charging desiccation peak is calculated based on the desiccation peak of the fourth capacity increment curve. The range of variation of the characteristic peak area is determined based on the peak area of ​​the first charging and the peak area of ​​the second charging.

5. The method for detecting electrode stripping during battery aging according to claim 4, characterized in that, The step of determining the capacity decay range of the cell electrode stripping based on the first charging capacity change rate and the second charging capacity change rate, and obtaining the third capacity decay range, includes: Calculate the difference between the second charging capacity change rate and the first charging capacity change rate to obtain the third charging capacity change rate, which represents the capacity change rate of the cell electrode sheet simply after deslagging. The third charging capacity change rate is statistically analyzed to obtain the third capacity decay range.

6. The method for detecting electrode stripping during battery aging according to claim 1, characterized in that, The process of acquiring the cell capacity data and cell voltage data of the cell to be tested, calculating the actual capacity decay rate based on the cell capacity data, constructing a target capacity increment curve based on the cell capacity data and cell voltage data, and calculating the target characteristic peak area change based on the target capacity increment curve includes: The cell under test is subjected to two consecutive constant current charge-discharge tests to obtain the capacity data and voltage data of the first cell during the first charge, and the capacity data and voltage data of the second cell during the second charge. The actual capacity decay rate is obtained by calculating based on the first cell capacity data and the second cell capacity data; A first target capacity increment curve is constructed based on the first cell capacity data and the first cell voltage data, and a second target capacity increment curve is constructed based on the second cell capacity data and the second cell voltage data. The area of ​​the first target desizing peak is calculated based on the desizing peak of the first target capacity increment curve, and the area of ​​the second target desizing peak is calculated based on the desizing peak of the second target capacity increment curve. The change in the area of ​​the target characteristic peak is calculated based on the area of ​​the first target deslagging peak and the area of ​​the second target deslagging peak.

7. The method for detecting electrode stripping during battery aging according to claim 6, characterized in that, The step of determining the electrode stripping result of the cell under test based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range, includes: If the actual capacity decay rate of the cell under test is greater than or equal to the minimum value of the second capacity decay range, and the change in the target characteristic peak area is greater than or equal to the minimum value of the characteristic peak area change range, then the cell under test is a cell with electrode stripping; otherwise, it is a cell with electrode non-stripping.

8. A battery aging process electrode stripping detection system, characterized in that, The system includes: The data acquisition module is used to acquire battery cell test data during battery aging. The battery cell test data includes normal aging cell data, aging lithium-plated cell data, and aging dematerialized cell data. The first calculation module is used to calculate the first charging capacity change rate based on the normal aging cell data and the aging lithium-plated cell data, and to determine the first capacity decay range caused by battery lithium plating based on the first charging capacity change rate. The second calculation module is used to calculate the second charging capacity change rate and construct the capacity increment curve based on the aging and descaling cell data, determine the second capacity decay range caused by battery aging and descaling based on the second charging capacity change rate, and determine the characteristic peak area change range based on the capacity increment curve. The third calculation module is used to determine the capacity decay range of the cell electrode sheet simply being removed from the material based on the first charging capacity change rate and the second charging capacity change rate, and to obtain the third capacity decay range. The cell detection module is used to acquire the cell capacity data and cell voltage data of the cell to be tested, calculate the actual capacity decay rate based on the cell capacity data, construct a target capacity increment curve based on the cell capacity data and the cell voltage data, and calculate the target characteristic peak area change based on the target capacity increment curve. The stripping detection module is used to determine the electrode stripping result of the cell under test based on the actual capacity decay rate and the target characteristic peak area change, combined with the second capacity decay range and the characteristic peak area change range.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the electrode stripping detection method during battery aging as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the electrode stripping detection method during battery aging as described in any one of claims 1 to 7.

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