Nondestructive testing method for black spots on lithium ion battery pole piece interface

Abstract

The invention discloses a lithium ion battery pole piece interface black spot nondestructive testing method, and belongs to the technical field of lithium ion battery manufacturing, and the method comprises the following steps: S1, sample testing; wherein the sample test comprises the following steps: S11, setting the moisture contents of sample pole pieces in groups according to gradients to obtain pole pieces with different moisture gradients; the method further comprises the steps of S2, data collection and feature extraction; s3, establishing a capacity difference conversion model, and determining a capacity value according to the minimum capacity difference interval; s4, determining the interval range of the black spot degree according to the capacity values of the samples with different moisture gradients; and S5, charging and discharging the to-be-detected battery, obtaining data, and predicting the black spot degree of the to-be-detected battery according to the data. The method has the advantages that node migration is detected, defect prediction is completed in the formation stage, and the production period is greatly advanced; the time consumption of battery cell detection is reduced, and the efficiency is greatly improved compared with that of a traditional disassembling method; and the cost is optimized, the cell disassembly loss is avoided, and the detection cost is reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of lithium ion battery manufacturing, and particularly relates to a lithium ion battery pole piece interface black spot nondestructive detection method. BACKGROUND

[0002] The pole piece interface black spot is a typical microscopic defect in the manufacturing process of the lithium ion battery, and its essence is an interface contact failure zone between an active material layer and a metal current collector. The black spot is mainly caused by solvent residue in the pole piece coating and drying process, microstructure damage in the rolling stage or poor local infiltration of electrolyte in the formation stage, which leads to abnormal interface impedance between the active material and the current collector, and causes local lithium deposition or side reactions. The traditional process can only avoid the black spot by adjusting the coating speed, compaction density and other macroscopic parameters, and lacks a real-time feedback mechanism.

[0003] The black spot area may cause local current density distortion due to poor interface contact. When charging, lithium ions are preferentially deposited in the low impedance area, which leads to accelerated growth rate of lithium dendrites around the black spot and increased probability of puncturing the separator. At the same time, the amount of gas produced by the side reaction increases, causing the swelling force of the battery to fluctuate. In addition, it will cause a series of problems such as the decrease of the effective active material utilization rate of the battery and the decrease of the capacity.

[0004] Currently, the industry mainly relies on the full charge disassembly detection method. The operation process is to charge the battery to 100% SOC, fix it with high-precision clamps, cut the shell, then manually peel off the pole piece in the dry room (dew point < -40℃), and observe the interface state of the pole piece. This test method needs to destroy the battery, and each test needs to scrap a battery with a value of more than 200 yuan, causing waste of cost. At the same time, the timeliness is lagging, and it takes 72-96 hours from the completion of the battery production to obtain the test results. The defective battery may have been integrated into a module, and the cost of repair is greatly increased.

[0005] Due to the inherent defects of the existing detection technology such as destructiveness, lagging and high cost, it has become a key obstacle to the high-quality development of the lithium battery industry. In view of the above industry pain points, it is urgent to develop an innovative scheme for nondestructive, real-time and predictive detection of the interface black spot during the production process of the battery, so as to reduce the quality cost and promote the closed-loop optimization of the manufacturing process. Based on the above reasons, the application designs a lithium ion battery pole piece interface black spot nondestructive detection method. SUMMARY

[0006] The purpose of the application is to solve the problems in the prior art and provide a lithium ion battery pole piece interface black spot nondestructive detection method.

[0007] In view of the above problems, the purpose of the application is to provide a lithium ion battery pole piece interface black spot nondestructive detection method.

[0008] A nondestructive testing method for black spot of lithium ion battery electrode interface, comprising the following steps:

[0009] S1: sample test;

[0010] Wherein the sample test comprises:

[0011] S11: grouping the moisture content of the sample electrode according to the gradient setting, obtaining electrode with different moisture gradient;

[0012] The method further comprises:

[0013] S2: data collection and feature extraction;

[0014] S3: establishing a capacity difference conversion model, and determining the capacity value according to the lowest capacity difference interval;

[0015] S4: determining the interval range of black spot degree according to the capacity value of the sample with different moisture gradient;

[0016] S5: charging and discharging the battery to be tested and obtaining data, and predicting the black spot degree of the battery to be tested according to the data.

[0017] In the above method, step S1 further comprises the following steps:

[0018] S12: make a battery and full charge test;

[0019] S13: wettability quantitative analysis.

[0020] In the above method, in step S11, the method of setting moisture content according to gradient comprises:

[0021] After coating, dry process is adopted and the temperature is set to 80-120℃, the time is set to 2-6h, the dew point is ≤-45℃, then online test is carried out using Swiss Wanhao Karl Fischer moisture meter, so as to achieve the target moisture content gradient of the electrode, wherein the electrode parameter setting is: surface density deviation ≤±1.5%, compacted density 2.4±0.05g / cm 3 .

[0022] In the above method, the step of full charge test comprises: making a plurality of electrode into a plurality of battery cells, then using charge-discharge test machine to reach 100% SOC, and then obtaining the plurality of electrode after test.

[0023] In the above method, in step S13, the wettability quantitative analysis method comprises: using contact angle measuring instrument Krytos DSA30, electrolyte is 1M LiPF6 / EC:DMC=3:7 in volume ratio, measuring droplet contact angle, and recording complete wetting time of each electrode.

[0024] In the above method, step S2 comprises the following parts:

[0025] S21: Formation parameters, the battery produced by different gradient moisture uses 0.1C current to charge 18min, rests 10min, and then uses 0.18C current to charge 80min to achieve the purpose of formation;

[0026] S22: dQ / dV processing is performed on the formation data;

[0027] S23: the characteristic signal peak is found, the relationship diagram is established, and the capacity difference interval of different moisture gradient samples is determined according to the area of the characteristic signal peak, and the interval range of the capacity difference where different black spot degrees are located is determined according to the capacity difference interval.

[0028] In the above method, in step S23, the area of the characteristic signal peak of dQ / dV can be converted into:

[0029] Delta Q = Q1-Q2

[0030] Wherein, Q1 and Q2 are two limit points of the characteristic signal peak respectively.

[0031] In step S5, the charge and discharge test is performed on the battery to be tested, and the steps of steps S21 and S22 are repeated to obtain the capacity difference of the battery to be tested, and the black spot condition of the battery to be tested is predicted according to the comparison between the capacity difference and the capacity difference interval obtained in step S23.

[0032] The beneficial effects of the present application are:

[0033] 1. The detection node migrates, and the defect prediction is completed in the formation stage, so that the production cycle is greatly advanced;

[0034] 2. Non-destructive and efficient, the time consumption of battery detection is reduced, and the efficiency is greatly improved compared with the traditional disassembly method;

[0035] 3. Cost optimization, avoiding battery disassembly loss and reducing detection cost. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is a flow chart of a non-destructive detection method for lithium ion battery pole piece interface black spot provided by the present application.

[0037] Figure 2 is a black spot result schematic diagram of sample detection in a non-destructive detection method for lithium ion battery pole piece interface black spot provided by the present application.

[0038] Figure 3 is a test diagram of the contact angle of the sample pole piece of different moisture gradients.

[0039] Figure 4 is a dq / dv curve comparison diagram of the sample pole piece of different moisture gradients. DETAILED DESCRIPTION

[0040] In order to facilitate the understanding of the present application, in order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below. In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, and the preferred embodiments of the present application are given in the accompanying drawings. However, the present application can be implemented in many different forms, and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive. The present application can be implemented in many different ways from those described herein, and those skilled in the art can make similar improvements without departing from the spirit of the present application, therefore the present application is not limited to the specific embodiments disclosed below. In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first", "second" can be explicitly or implicitly included at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise specifically limited. In the description of the present application, the meaning of "several" is at least one, such as one, two, etc., unless otherwise specifically limited. It should be noted that when an element is referred to as "fixed to" another element, it can be directly on the other element or there can be a middle element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there can be a middle element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for illustrative purposes and are not the only embodiments. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art of the technology to which the present application belongs. The terms used herein are only for the purpose of describing the specific embodiments and are not intended to limit the present application. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0041] Reference Figures 1 to 4 A nondestructive testing method for black spots on the interface of a lithium ion battery pole piece,

[0042] Step 1:

[0043] Moisture gradient pole piece preparation, black spot degree and corresponding wettability test

[0044] Experimental design

[0045] Sample grouping: taking lithium iron phosphate positive pole piece as an example, setting the moisture content gradient as 300ppm, 1000ppm, 1500ppm, 2000ppm;

[0046] Moisture control method: different drying processes (temperature 80-120℃, time 2-6h, dew point≤-45℃) were used after coating, and a Swiss Mettler Karl Fischer moisture meter was used for online testing to achieve the target moisture content gradient;

[0047] Pole piece parameters: surface density deviation≤±1.5%, compacted density 2.4±0.05g / cm 3 ;

[0048] Pole pieces with different moisture gradients were made into batteries and then disassembled after full charging

[0049] Test method: the pole pieces were made into 314Ah battery cells, and a charge-discharge tester was used to charge at 0.2C to 3.65V to achieve 100% SOC; then the electrode interface was disassembled and observed;

[0050] The test results are shown in Figure 2 .

[0051] Test method for wettability quantitative analysis: contact angle measuring instrument (Kruss DSA30), electrolyte: 1M LiPF6 / EC:DMC=3:7 (volume ratio);

[0052] The droplet contact angle was measured, and the time for complete wetting of the pole piece was recorded;

[0053] Data correlation: comparison of contact angle and wettability of pole pieces with different moisture gradients;

[0054] Table 1 Contact angle and wettability test data of pole pieces with different moisture gradients

[0055]

[0056] Reference can be made to Figure 3 Contact angle test of pole pieces with different moisture gradients, from the preparation of pole pieces with different moisture gradients, wettability test and black spot degree corresponding experiment, it can be seen that the higher the water content of the pole piece, the worse the wettability of the pole piece, and the higher the black spot degree of the battery cell made, showing a positive correlation, therefore the test results are quantitatively recorded through the above relationship;

[0057] Step 2: data extraction of formation and dQ / dV characteristics

[0058] 2.1 Formation parameters: 314Ah battery cells made at different levels were charged at 0.1C current for 18min, rested for 10min, and then charged at 0.18C current for 80min to achieve the purpose of formation;

[0059] 2.2 dQ / dV data processing: dQ / dV processing was performed on the formation data;

[0060] 2.3 dQ / dV characteristic peak extraction: find the characteristic peak, establish the relationship;

[0061] Referring to Figure 4 The dQ / dV curve comparison chart of the electrode sheet made into the battery cell under different moisture gradients, in the 314A battery cell formation data and dQ / dV characteristic extraction, it can be seen that as the moisture content of the electrode sheet increases, the dQ / dV peak at 2.0-2.2V is larger, indicating that due to the influence of moisture, a side reaction occurs at this voltage section.

[0062] Step 3: Capacity difference conversion model

[0063] According to Figure 4 It can be concluded that when the lithium iron phosphate positive electrode sheet is subjected to charge and discharge test, the interval section of the characteristic peak of the dQ / dV relationship diagram is 2.0-2.2V voltage section, then the dQ / dV peak area can be converted to:

[0064] Delta Q=Q 2.2V -Q 2.0V

[0065] Therefore, the capacity difference can be obtained by calculating Delta Q, and the capacity difference is corresponding to the black spot degree progress, and the following table is obtained:

[0066] Table 2: Capacity difference of battery cell under different moisture gradients and corresponding black spot degree

[0067]

[0068]

[0069] And after completing the corresponding relationship between the capacity difference and the black spot degree, the prediction of the subsequent battery can be realized, and the minimum tolerance value is obtained by full charging and disassembling the interface of the battery to be tested to obtain the prediction of the black spot degree.

[0070] From the technical common sense, the application can be realized by other embodiments without departing from the spirit or essential characteristics thereof. Therefore, the above disclosed embodiments are only examples, and are not the only ones. All changes within the scope of the application or within the scope equivalent to the application are included in the application.

Claims

1. A non-destructive testing method for black spot of lithium ion battery electrode sheet interface, characterized in that, The method comprises the following steps: S1: sample test; The sample test comprises: S11: grouping the samples according to the moisture content gradient to obtain samples with different moisture content gradients; The method further comprises: S2: data collection and feature extraction; S3: establishing a capacity difference conversion model and determining the capacity value according to the lowest capacity difference interval; S4: determining the interval range of the black spot degree according to the capacity value of the sample with different moisture content gradient; S5: performing charge and discharge on the battery to be tested and obtaining data, and predicting the black spot degree of the battery to be tested according to the data.

2. The method of claim 1, wherein the method further comprises: Step S1 further comprises the following steps: S12: making a battery and full charge test; S13: quantitative analysis of wettability.

3. The method of claim 1, wherein the method further comprises: In step S11, the method of setting the moisture content gradient comprises: After coating, dry process is adopted with temperature 80-120℃, time 2-6h, dew point≤-45℃, then online test is conducted by using Swiss Mettler Karl Fischer moisture meter to achieve the target moisture content gradient of the pole piece, wherein the pole piece parameter setting is: surface density deviation≤±1.5%, compacted density 2.4±0.05g / cm 3 .

4. The method of claim 2, wherein the method further comprises: In step S12, the full charge test comprises making a plurality of electrode plates into a plurality of battery cells, and then using a charge and discharge tester to reach 100% SOC, and then obtaining the plurality of electrode plates after the test.

5. The method of claim 2, wherein the method further comprises: In step S13, the quantitative analysis method of wettability comprises: using a contact angle measuring instrument, Krytos DSA30, and electrolyte is 1M LiPF6 / EC: DMC = 3:7 by volume ratio, measuring the contact angle of the droplet, and recording the complete wetting time of each electrode plate.

6. The method of claim 1, wherein the method further comprises: Step S2 comprises the following parts: S21: formation parameters, using 0.1C current to charge the battery cells made with different moisture content gradients for 18min, standing for 10min, and then using 0.18C current to charge for 80min to achieve the purpose of formation; S22: dQ / dV processing of the formation data; S23: finding the characteristic signal peak, establishing a relationship diagram, and determining the capacity difference interval of the sample with different moisture content gradient according to the area of the characteristic signal peak, and determining the interval range of the capacity difference of different black spot degrees according to the capacity difference interval.

7. The method of claim 6, wherein the method further comprises: In step S23, the area of the characteristic signal peak of dQ / dV can be converted to: ΔQ = Q1-Q2 Wherein, Q1 and Q2 are two limit points of the characteristic signal peak.

8. The method of claim 6, wherein the method further comprises: In step S5, the battery to be tested is subjected to charge and discharge test, and the steps of steps S21 and S22 are repeated to obtain the capacity difference of the battery to be tested, and the black spot condition of the battery to be tested is predicted by comparing the capacity difference with the capacity difference interval obtained in step S23.

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