Method for predicting optimal aging time of battery

Abstract

The invention relates to the technical field of batteries, and provides a method for predicting the optimal aging time of batteries, which comprises the following steps: S100, selecting m batteries and dividing the batteries into a first group of batteries, a second group of batteries,..., and an nth group of batteries; s200, sequentially carrying out aging treatment, formation treatment, secondary liquid injection treatment, sealing treatment and charging treatment on each group of batteries in the S100; s300, disassembling each group of batteries in the step S200, detecting the area of purple spots on the interface of the negative plate, and determining the optimal aging time of the batteries according to the area of the purple spots; wherein m is greater than or equal to 2, and n is greater than or equal to 2; the m batteries are all batteries subjected to infiltration treatment; the aging times of the first group of batteries, the second group of batteries,..., and the nth group of batteries are different. By comprehensively simulating the production and storage processes of the batteries, disassembling the batteries and observing the purple spot area of the interface of the negative plate, the performance change of the batteries at different aging times can be intuitively reflected.

Description

Technical Field

[0001] The present invention relates to the technical field of batteries, and in particular, to a method for predicting the optimal aging time of a battery. Background Art

[0002] Secondary batteries have the advantages of high energy density, no memory effect, long cycle life, and environmental friendliness, and their applications have expanded from the field of consumer electronics to the fields of electric vehicles and new energy energy storage. However, as people's requirements for the mileage and energy storage of electric vehicles are getting higher and higher, high-energy density batteries are the future development direction. The use of positive and negative electrode sheets with high capacity and high tap density is a conventional way to improve the energy density of batteries at present. However, high-tap density electrode sheets will cause slow absorption of electrolyte during battery liquid injection, especially many problems such as uneven distribution of electrolyte inside the battery and poor electrode wettability.

[0003] The aging of the battery after liquid injection is a key process for the electrolyte to fully infiltrate and activate the battery. The quality of the electrolyte wettability after aging directly affects the contact situation between the various components inside the battery, and further affects the ion transport efficiency, battery safety, and cycle life. Aging determines the infiltration degree of the electrolyte, and thus also determines the first efficiency of its charge and discharge, constant current time ratio, etc. Therefore, developing an accurate and efficient method for predicting the optimal aging time of a battery is of great significance for promoting production line production. However, in the current related technologies, there is no method for predicting the optimal aging time of a battery.

[0004] Therefore, there is an urgent need to provide a prediction method that can accurately lock in the optimal aging time of a battery. Summary of the Invention

[0005] The present invention aims to solve at least one of the above technical problems.

[0006] The present invention provides a method for predicting the optimal aging time of a battery, including:

[0007] S100. Select m batteries and divide the batteries into the first group of batteries, the second group of batteries, ······, the nth group of batteries;

[0008] S200. Perform aging treatment, formation treatment, second liquid injection treatment, sealing treatment, and charging treatment on each group of batteries in S100 in sequence;

[0009] S300. Disassemble each battery in each group of batteries in S200, detect the area of the purple spots at the interface of the negative electrode sheet of each battery, and determine the optimal aging time of the battery according to the area of the purple spots;

[0010] Among them, m≥2, n≥2; all m batteries are batteries after one liquid injection treatment; the aging treatment times of the first group of batteries, the second group of batteries, ……, the nth group of batteries are different.

[0011] In any of the above technical features, in S200, the aging treatment times of the first group of batteries, the second group of batteries, ……, the nth group of batteries are t1, t2, ……, t n ;

[0012] t1, t2, ……, t n are each independently 18h - 50h respectively;

[0013] t1, t2, ……, t n gradually increase; and the absolute value of the difference in the aging treatment times of any two adjacent groups of batteries is 0.5h - 4h.

[0014] In any of the above technical features, in S200, the aging treatment temperature is 45 ± 5°C.

[0015] In any of the above technical features, in S200, the charge amount of each group of batteries after the supplementary charging treatment is 80% ± 2% SOC.

[0016] In any of the above technical features, the supplementary charging treatment includes: after the sealing treatment, charging at a rate of 0.1C - 1C to 80% ± 2% SOC.

[0017] In any of the above technical features, the supplementary charging treatment includes: after the sealing treatment, charging at a rate of 0.1C - 1C to 80% SOC.

[0018] In any of the above technical features, in S300, detecting the area of the purple spots at the negative electrode sheet interface includes: cutting X-fold electrode sheets from the negative electrode sheets of each battery in each group of batteries as sample electrode sheets, and measuring the area of the purple spots on the sample electrode sheets of each battery, where X is a positive integer greater than or equal to 1.

[0019] In any of the above technical features, determining the optimal aging time of the battery according to the area of the purple spots includes:

[0020] Calculating the average purple spot area S1 of the (n - 1)th group of batteries and calculating the average purple spot area S2 of the nth group of batteries; where:

[0021] S1 = A1 / (B1 * X), where A1 is the sum of the areas of the purple spots on the sample electrode sheets of all the batteries in the (n - 1)th group of batteries, and B1 is the number of batteries in the (n - 1)th group of batteries;

[0022] S2 = A2 / (B2 * X), where A is the sum of the areas of the purple spots on the sample electrode sheets of all the batteries in the nth group of batteries, and B2 is the number of batteries in the nth group of batteries;

[0023] When the absolute value of the difference between S1 and S2 is within the set threshold, the aging time corresponding to the (n - 1)th group is the optimal aging time.

[0024] In any of the above technical features, the set threshold is 0 - 3 cm 2 。

[0025] In any of the above technical features, the set threshold is 0 - 1 cm 2 。

[0026] After adopting the technical solution of the present invention, the following technical effects can be achieved:

[0027] 1. The present invention selects m batteries, groups the selected m batteries, and sequentially performs aging treatment, formation treatment, second liquid injection treatment, sealing treatment, and charging treatment on each group of batteries. This can comprehensively simulate the production and storage process of the batteries. By disassembling these batteries and observing the purple spot area at the negative electrode interface, the performance changes of the batteries at different aging times can be more intuitively reflected;

[0028] 2. The size of the purple spot area can be used as an indicator of the internal reaction of the battery, and then the optimal aging time of the battery can be inferred. It can effectively lock the aging duration to meet the infiltration and activation effects, while avoiding waste of process time caused by too long ineffective aging time, affecting production efficiency and production capacity; moreover, this analysis method can be further extended and applied to the analysis of other system batteries such as lithium iron phosphate soft-pack, cylindrical batteries, and ternary material system batteries;

[0029] 3. Different aging times are set for each group of batteries respectively, and then the batteries at different aging times are disassembled and the area of the purple spots on the negative electrode sheets is detected, so as to determine the optimal aging time of the batteries, making the electrolyte distribution inside the prepared batteries uniform, thus having better cycle life and battery capacity, and further improving the market competitiveness of the products. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is the infiltration mechanism diagram of the electrolyte of the embodiment of the present invention;

[0031] Figure 2 is the interface diagram of the negative electrode sheet with 80% SOC at different aging times in Embodiment 1 of the present invention;

[0032] Figure 3 is the interface diagram of the negative electrode sheet after full charge disassembly of the battery corresponding to the test example. DETAILED DESCRIPTION OF THE INVENTION

[0033] To make the above objects, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0034] In the related art, due to the advantages of high energy density, no memory effect, long cycle life, and environmental friendliness of lithium-ion batteries, their applications have been extended from the field of consumer electronics to the fields of electric vehicles and new energy energy storage. However, as people's requirements for the mileage and energy storage of electric vehicles are getting higher and higher, high-energy-density batteries are the future development direction. The use of positive and negative electrode sheets with high capacity and high tap density is a conventional way to improve the energy density of batteries at present. However, high-tap-density electrode sheets will cause problems such as slow liquid absorption of the electrolyte during battery filling, especially uneven distribution of the electrolyte inside the battery and poor electrode wettability.

[0035] In view of this, the present invention provides a method for predicting the optimal aging time of a battery. By aging the battery after the first liquid injection and then disassembling it to detect the area of the purple spots that appear on the negative electrode sheet, the optimal aging time of the battery is determined.

[0036] Specifically, an embodiment of the present invention provides a method for predicting the optimal aging time of a battery, including:

[0037] S100. Select m batteries and divide the batteries into the first group of batteries, the second group of batteries,..., the nth group of batteries;

[0038] S200. Sequentially perform aging treatment, formation treatment, second liquid injection treatment, sealing treatment, and charging treatment on each group of batteries in S100;

[0039] S300. Disassemble each battery in each group of batteries in S200, detect the area of the purple spots on the interface of the negative electrode sheet of each battery, and determine the optimal aging time of the battery according to the area of the purple spots;

[0040] Wherein, m≥2, n≥2; all m batteries are batteries after the first liquid injection treatment; the aging treatment times of the first group of batteries, the second group of batteries,..., the nth group of batteries are different.

[0041] Preferably, in the present invention, m batteries are first selected from the same batch of samples, and the selected m batteries are divided into n groups. Each group of batteries is successively subjected to aging treatment, formation treatment, second electrolyte injection treatment, sealing treatment, and charging treatment. This can comprehensively simulate the production and storage process of the batteries. By disassembling these batteries and observing the purple spot area at the negative electrode interface, the performance changes of the batteries at different aging times can be more intuitively reflected. During the production process of the batteries, after injecting the electrolyte, the electrolyte needs to fully infiltrate the separator and the electrode to ensure uniform distribution of the electrolyte inside the battery. Since it takes a certain amount of time for the electrolyte to completely penetrate into the pores of the electrode material and the separator structure, if the electrolyte is unevenly distributed, it will cause violent reactions during the subsequent charge and discharge processes of the batteries, thereby affecting the performance and lifespan of the batteries. Therefore, usually through aging treatment, the electrolyte is brought into full contact with the electrode to make the electrolyte evenly distributed inside the battery.

[0042] Preferably, the purple spot area at the negative electrode interface is one manifestation of the internal reaction of the battery and can reflect the infiltration degree inside the battery during the aging process. An appropriate purple spot area can prove that the aging process of the battery is appropriate. Therefore, the size of the purple spot area can be used as an indication of the internal reaction of the battery, and then the optimal aging time of the battery can be inferred. For example, when 80 batteries are sampled from the same batch of samples and divided into 10 groups, after obtaining the optimal aging time using the above method, the optimal aging time can be used for aging treatment during the actual production process to produce batteries with the best performance. Using the prediction method of the present invention can effectively lock the aging duration. While meeting the infiltration and activation effects, it can also avoid wasting process time caused by too long and ineffective aging time, affecting production efficiency and production capacity. Moreover, this analysis method can be further extended and applied to the analysis of other system batteries such as lithium iron phosphate soft-pack, cylindrical batteries, and ternary material system batteries.

[0043] Further, in S200, for the first group of batteries, the second group of batteries, ……, the nth group of batteries, the aging treatment times are t1, t2, ……, t n ;

[0044] t1, t2, ……, t n are each independently 18h - 50h;

[0045] t1, t2, ……, t n gradually increase; and the absolute value of the difference in the aging treatment times between any two adjacent groups of batteries is 0.5h - 4h.

[0046] Preferably, since the aging time of the battery is related to the performance of the battery, it is very important to determine the aging time of the battery; after grouping the batteries, different aging times are set for each group of batteries respectively. The aging treatment time is usually set between 18h and 50h, and the absolute value of the difference in the aging treatment time between adjacent two groups of batteries is usually set to 0.5h - 4h, for example, it can be 0.5h, 1h, 1.5h, 2h, 2.5h, 3h, 3.5h or 4h. It can be understood that the more the number of battery groups (i.e., the value of n) and the smaller the absolute value of the difference in the aging treatment time between any adjacent two groups of batteries, the more accurate the prediction of the optimal aging time of the battery. Since the batteries under different aging times are disassembled and the area of the purple spots on the negative electrode sheet is detected, the optimal aging time of the battery is determined. The electrolyte distribution inside the battery prepared according to the optimal aging time of the battery is uniform, so it has better cycle life and battery capacity, further improving the market competitiveness of the product.

[0047] Preferably, the temperature of the aging treatment is 45 ± 5°C. At a suitable temperature, the chemical reaction between the electrolyte and the electrode material will be more stable and uniform. Too high a temperature will accelerate the decomposition of the electrolyte, while too low a temperature may lead to incomplete reactions or too slow reaction rates. The temperature of 45 ± 5°C can not only effectively accelerate the reaction, but also prevent unnecessary side reactions inside the battery; and controlling the temperature at 45 ± 5°C helps the electrolyte to better penetrate and fully contact with the electrode material, accelerating the uniform infiltration of the electrolyte and promoting the electrochemical reaction inside the battery.

[0048] Preferably, in S200, the charge amount of each group of batteries after the charge replenishment treatment is 80% ± 2% SOC.

[0049] Preferably, during the charging process of the lithium-ion battery, as lithium ions are embedded, the negative electrode gradually changes from carbon to lithium hexacarbonide. As the charging SOC increases, the color of the negative electrode sheet gradually changes from black in the initial state to purple and then to golden yellow; since the wettability of the periphery of the battery electrode sheet is better than that of the middle region, the reaction is faster during the charging process, so the color change in the middle region lags behind that of the edge, thus forming purple scars as shown in Figure 2 The purple spots shown in the figure, that is, purple spots, can be seen by naked-eye observation; at the 80% SOC state, the degree of purple spots in the middle region is more obvious, and for the fully immersed battery, the purple spots tend to be stable.

[0050] Preferably, the charge replenishment treatment includes: after the sealing treatment, charging at a rate of 0.1C - 1C to 80% ± 2% SOC.

[0051] If the charge replenishment process does not replenish the battery to 78% SOC charge, the negative electrode sheet will be black at this time and there will be no purple spots. If the charge replenishment process is carried out to 100% SOC charge, the entire electrode sheet will turn golden yellow and there will be no purple spots either, thus making it impossible to evaluate the optimal aging time. At 80% ± 2% SOC charge, except for the dotted purple spots in the middle area of the electrode sheet, the overall electrode sheet will present a golden yellow interface. It is preferred to use 80% SOC charge. The 80% SOC interface effect has a strong correlation with the aging time, that is, when the aging time is short, the purple spot area in the middle interface of the electrode sheet is large. As the aging time increases, the purple spot area on the electrode sheet slowly decreases, and when the aging time increases to a certain critical point, the purple spot area on the electrode sheet remains stable and no longer changes. Therefore, replenishing the battery to 80% SOC is helpful for subsequent disassembly to observe the appearance of purple spots on the negative electrode sheet, thereby making it easier to determine the optimal aging time.

[0052] Preferably, in S300, detecting the area of the purple spots on the negative electrode sheet interface includes: cutting X-fold electrode sheets from the negative electrode sheets of each battery in each group of batteries as sample electrode sheets, and measuring the area of the purple spots on the sample electrode sheets of each battery, where X is a positive integer greater than or equal to 1. Usually, it is measured using an area measurement card. In this application, the X-fold electrode sheet of the purple spot area is used as the sample electrode sheet, and then the area of the purple spots on the sample electrode sheet is measured. By detecting the purple spot area of the battery at different aging times, the relationship between the purple spot area and the battery performance at different aging stages can be obtained. The size of the purple spot area can indicate whether the battery is in the best chemical reaction state, thereby reflecting whether the battery has the best capacity retention and cycle stability. By analyzing the change in the purple spot area of different groups of batteries at different aging times, it helps those skilled in the art to determine the optimal aging time of the battery. The change in the purple spot area can be used as a basis for optimizing the aging process to avoid too long or too short aging time.

[0053] It can be understood that usually, after the negative electrode sheet is disassembled from the battery, as Figure 2 shown, there will be obvious creases on the negative electrode sheet (the creases correspond to the arc R-angle position of the core). The area between two adjacent creases is one-fold electrode sheet.

[0054] Preferably, determining the optimal aging time of the battery according to the area of the purple spots includes:

[0055] Calculating the average purple spot area S1 of the (n - 1)th group of batteries and calculating the average purple spot area S2 of the nth group of batteries; where:

[0056] S1 = A1 / (B1 * X), where A1 is the sum of the purple spot areas on the sample electrode sheets of all batteries in the (n - 1)th group of batteries, and B1 is the number of batteries in the (n - 1)th group of batteries;

[0057] S2 = A2 / (B2*X), where A is the sum of the purple spot areas on the sample electrodes of all the batteries in the nth group of batteries, and B2 is the number of batteries in the nth group of batteries;

[0058] When the absolute value of the difference between S1 and S2 is within the set threshold, the aging time corresponding to the (n - 1)th group is the optimal aging time.

[0059] Preferably, the area of the purple spots changes with the progress of the aging process within a certain period of time. The difference in the purple spots on each battery within the same group is not significant, while the area of the purple spots varies among the batteries of different groups due to different aging times. As the aging time extends, the area of the purple spots tends to be stable, and even if the aging time is further extended, the area of the purple spots will not change significantly, indicating that the chemical reaction inside the battery has reached an equilibrium state and the battery performance has reached the best. The aging time adopted by the group of batteries that first reaches this stable area is the time point with the optimal battery performance; by identifying the group that first reaches the stable area of the purple spots, it can be ensured that the selected aging time point is the time with the optimal and most stable battery performance, that is, the optimal aging time, thus avoiding over-aging or under-aging and ensuring the best performance of the battery in actual use.

[0060] Further, the set threshold is 0 - 3 cm 2 , when the absolute value of the difference between S1 and S2 is within this range, it means that the area of the purple spots on the negative electrode sheet begins to tend to be stable at this time, and even if the aging time is continued to be extended, the area of the purple spots will not change anymore.

[0061] Further, the set threshold is 0 - 1 cm 2 .

[0062] Preferably, since the internal performance of the battery is closely related to the state of the internal electrolyte, especially in the initial liquid injection stage of the battery, that is, after the first liquid injection treatment of the battery, the electrode material contacts the electrolyte and the inside of the battery is gradually infiltrated by the electrolyte; a lithium-ion battery is a typical slit - pore structure (one of the double media); according to the mass transfer theory of porous media, the driving force for electrolyte infiltration is capillary force, which is a process of spontaneous imbibition; due to the barrier of the copper-aluminum foil current collector, whether the lithium-ion battery is a wound structure or a stacked structure, the electrolyte infiltrates into the battery interior from the battery end face through the separator, so the battery layer gap plays a role in guiding the flow, and the separator plays a role in shunting.

[0063] Preferably, as Figure 1As shown in the figure, the steps of electrolyte infiltration inside the battery are as follows: (1) Under the action of capillary force, the electrolyte is transported in the gap between the electrode and the separator; (2) The electrolyte preferentially seeps in the pores of the separator (the infiltration rate of the electrolyte in the separator is much greater than that in the porous coating of the electrode); (3) The electrolyte diffuses to the surfaces of the positive and negative electrodes on both sides through the separator and seeps into the pores inside the porous electrodes; Therefore, it takes a certain amount of time for the battery to be fully infiltrated. Through the first liquid injection treatment, the electrolyte is injected into the battery. To a large extent, the infiltration effect requires a certain amount of time. The middle position of the battery is finally infiltrated after a certain time, but the infiltration effect is always lower than that of the battery end face; After aging treatment for different aging times, the battery is subjected to formation treatment, second liquid injection treatment, sealing treatment, and charging compensation treatment, and then the battery disassembly interface is confirmed and analyzed. If the infiltration is sufficient, it can be found that only extremely slight dot-like purple spots appear at the interface of the negative electrode sheet during disassembly. The aging time corresponding to this purple spot can be used as the optimal time for the aging duration.

[0064] Example 1

[0065] This example provides a method for predicting the optimal aging time of a battery, including:

[0066] S100. Select 32 batteries after the first liquid injection and divide the batteries into the 1st group of batteries, the 2nd group of batteries, ······, the 8th group of batteries equally;

[0067] S200. For the 1st group of batteries, the 2nd group of batteries, ······, the 8th group of batteries in S100, perform aging treatment at 45 °C according to the aging time of 22h, 26h, ……, 50h, and then perform formation treatment, second liquid injection treatment, sealing treatment, and charging compensation treatment in sequence;

[0068] Among them, the steps of the formation treatment are: charge at 0.05C to 5% SOC, stand for 1 min, charge at 0.1C to 15% SOC, stand for 1 min, and charge at 0.2C to 25% SOC.

[0069] The mass ratio of the first liquid injection to the second liquid injection is 4:1;

[0070] The charging compensation treatment is: charge at a rate of 0.5C to 80% SOC.

[0071] S300. Disassemble each group of batteries in S200, cut 5-fold electrode sheets from the negative electrode sheets of each battery in each group of batteries as sample electrode sheets, and measure the area of the purple spots on the sample electrode sheets of each battery; Calculate the average purple spot area of each group of batteries. The test results of the purple spot area of each group of batteries are shown in Table 1:

[0072] Table 1

[0073]

[0074] From Table 1, it can be seen that the average purple spot area of the 6th to 8th groups almost remains at 2.8 cm 2 level, and the absolute values of the differences in the average purple spot areas between the 6th and 7th groups, and between the 7th and 8th groups are 0.3 and 0.4, respectively, and the differences are within the set threshold of 0 - 1 cm 2 range. Therefore, the aging duration of 42 h is the optimal aging time for this example.

[0075] Figure 2 Figures 2, 5, 6, and 7 are the negative electrode interface diagrams after disassembling the batteries of the 2nd, 5th, 6th, and 7th groups corresponding to Example 1. It can be seen from the figures that the purple spot areas on the batteries of the 6th and 7th groups are almost unchanged. Therefore, the aging duration of 42 h is the optimal aging time for this example.

[0076] Example Two

[0077] The difference between this example and Example 1 is only that the charge replenishment process is: charging at a rate of 0.5C to 78% SOC. In this example, the test results of the purple spot area of each group of batteries are shown in Table 2:

[0078] Table 2

[0079] From Table 2, it can be seen that the average purple spot area of the 6th to 8th groups also almost remains at 2.8 cm 2 level, and the absolute values of the differences in the average purple spot areas between the 6th and 7th groups, and between the 7th and 8th groups are 0.3 and 0.1, respectively, and the differences are within the set threshold of 0 - 1 cm 2 range. Therefore, the aging duration of 42 h is the optimal aging time for this example.

[0080] Example Three

[0081] The difference between this example and Example 1 is only that the charge replenishment process is: charging at a rate of 0.5C to 82% SOC. In this example, the test results of the purple spot area of each group of batteries are shown in Table 3:

[0082] Table 3

[0084] From Table 3, it can be seen that the average purple spot area of the 6th to 8th groups also almost remains at 2.4 cm 2 level, and the absolute values of the differences in the average purple spot areas between the 6th and 7th groups, and between the 7th and 8th groups are 0.1 and 0.2, respectively, and the differences are within the set threshold of 0 - 1 cm 2 range. Therefore, the aging duration of 42 h is the optimal aging time for this example.

[0085] Test Example:

[0086] Take 2 batteries and perform liquid injection and aging treatment on each of them (the aging times of the 2 batteries are 38 h and 42 h respectively), and then perform formation treatment, second liquid injection treatment, and sealing treatment in sequence;

[0087] Among them, the formation treatment, first liquid injection, second liquid injection treatment, and sealing treatment are exactly the same as those in Example 1; after the sealing treatment, a charging compensation treatment is performed, and the steps of the charging compensation treatment are: charging at a rate of 0.5C to 100% SOC.

[0088] After full charge, disassemble the battery and look at the negative electrode interface diagram of the battery, Figure 3 which is the negative electrode tab diagram of the battery corresponding to the test example. It can be seen from this diagram that after the battery cell with an aging time of 38 h ( Figure 3 left) is fully charged, due to insufficient infiltration at the battery cell interface, there will be a slight lithium precipitation phenomenon in the central area of the negative electrode tab after full charge, while for the battery cell with an aging time of 42 h ( Figure 3 right), after being fully charged, the whole negative electrode tab is golden yellow and there is no lithium precipitation phenomenon. Thus, it can be seen that the method involved in this application can accurately predict the aging time.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for predicting the optimal aging time of a battery, characterized in that, Including: S100. Select m batteries and divide the batteries into the first group of batteries, the second group of batteries, ……, the nth group of batteries; S200. Sequentially perform aging treatment, formation treatment, second liquid injection treatment, sealing treatment, and supplementary charging treatment on each group of the batteries in S100; S300. Disassemble each battery in each group of the batteries in S200, detect the area of the purple spots at the interface of the negative electrode sheet of each battery, and determine the optimal aging time of the battery according to the area of the purple spots; wherein, m≥2, n≥2; The m batteries are all batteries after one liquid injection treatment; The aging treatment times of the first group of batteries, the second group of batteries, ……, the nth group of batteries are different.

2. The prediction method according to claim 1, wherein In S200, The aging treatment times of the first group of batteries, the second group of batteries, ……, the nth group of batteries are t1, t2, ……, t respectively n ; t1, t2, ……, t n are each independently 18 h - 50 h respectively; t1, t2, ……, t n gradually increase; and the absolute value of the difference in the aging treatment time between any two adjacent groups of batteries is 0.5 h - 4 h.

3. The prediction method according to claim 1, wherein In S200, The temperature of the aging treatment is 45±5°C.

4. The prediction method according to claim 1, wherein In S200, After each group of the batteries undergoes the supplementary charging treatment, the charge amount is 80%±2%SOC.

5. The prediction method according to claim 4, wherein The supplementary charging treatment includes: After the sealing treatment, charge at a rate of 0.1C - 1C to 80%±2%SOC.

6. The prediction method according to claim 5, wherein The supplementary charging treatment includes: After the sealing treatment, charge at a rate of 0.1C - 1C to 80%SOC.

7. The prediction method according to claim 1, wherein In S300, the detecting the area of the purple spots at the interface of the negative electrode sheet includes: Cut X-fold electrode sheets from the negative electrode sheets of each battery in each group of batteries as sample electrode sheets, and measure the area of the purple spots on the sample electrode sheets of each battery, where X is a positive integer greater than or equal to 1.

8. The prediction method according to claim 7, characterized in that Determining the optimal aging time of the battery according to the area of the purple spots includes: Calculating the average purple spot area S1 of the (n - 1)th group of batteries, and calculating the average purple spot area S2 of the nth group of batteries; wherein: S1 = A1 / (B1*X), A1 is the sum of the areas of the purple spots on the sample electrode sheets of all the batteries in the (n - 1)th group of batteries, and B1 is the number of batteries in the (n - 1)th group of batteries; S2 = A2 / (B2*X), A is the sum of the areas of the purple spots on the sample electrode sheets of all the batteries in the nth group of batteries, and B2 is the number of batteries in the nth group of batteries; When the absolute value of the difference between S1 and S2 is within the set threshold, the aging time corresponding to the (n - 1)th group is the optimal aging time.

9. The prediction method according to claim 8, characterized in that The set threshold is 0 - 3 cm 2 .

10. The prediction method according to claim 9, characterized in that The set threshold is 0 - 1 cm 2 .

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