Method for screening defective moisture products of lithium iron phosphate cells

Abstract

The invention relates to a method for screening defective products of lithium iron phosphate cells, in particular to a method for screening moisture defective products of lithium iron phosphate cells, which comprises the following steps of: firstly, artificially manufacturing batteries with different gradients of moisture content, carrying out standard electrical property and safety performance test on samples of each gradient, and determining a moisture content reference curve according to a test result; and secondly, comparing the dynamic voltage data of the battery cell products with a reference value to select unqualified battery cell products. According to the invention, 100% product full inspection can be realized, the probability of outflow of bad battery cells can be further reduced, the consistency of the battery cells after selection is better, and the performance and the service life of the grouped battery cells are facilitated.

Description

Technical Field

[0001] The present invention relates to a method for screening defective products, and particularly to a method for screening defective products with moisture in lithium iron phosphate battery cells. Background Art

[0002] After lithium-ion batteries are manufactured, it is necessary to detect the moisture content in the battery cells for the following reasons: (1) To prevent the decomposition and corrosion of the electrolyte. Excessive moisture will cause hydrolysis reactions of lithium salts (such as LiPF6) in the electrolyte, generating corrosive substances such as hydrofluoric acid (HF), accelerating the corrosion of the metal current collector and the casing, and destroying the stability of the SEI film, ultimately leading to battery swelling, leakage, or even thermal runaway; (2) To avoid abnormal gas generation. A large amount of gas (such as H2, CO2) will be released during the reaction between moisture and the electrolyte, causing a sudden increase in the internal pressure of the battery and increasing the risk of explosion or fire.

[0003] Currently in the lithium battery industry, sampling is generally used to represent the moisture performance of the sampled battery cells. That is, a certain number of samples are selected from a small batch of products, and by detecting the moisture content of the samples, the moisture content representing this small batch is obtained. Since this method does not perform a full inspection of the products, it cannot be absolutely effective, and there are safety hazards when unqualified products flow into the market.

[0004] Based on this, a new method for screening defective products with moisture in lithium-ion battery cells needs to be designed. Summary of the Invention

[0005] In order to overcome the deficiencies in the prior art, the present invention provides a method for screening defective products with moisture in lithium iron phosphate battery cells.

[0006] To achieve the above object, a method for screening defective products with moisture in lithium iron phosphate battery cells disclosed by the present invention includes the following steps:

[0007] (S1) Artificially manufacture batteries with different gradients of moisture content, perform the first charging on the battery cells at a current of 0.01 - 0.05C at 40 - 60°C for 1 - 5 hours, then switch to 0.5C for continuous charging, and then complete the processing of subsequent processes. After all the battery cells are processed, perform standard electrical performance and safety performance tests on the samples of each gradient, and determine the moisture content reference curve according to the test results;

[0008] (S2) Extract at least one characteristic point from the reference curve to determine the acquisition time points of the dynamic voltage characteristic points and the voltage reference values at each acquisition time point;

[0009] (S3) For the preprocessed cell products, the cells are initially charged at a temperature of 40 - 60 °C with a current of 0.01 - 0.05C for 1 - 5 hours to obtain the dynamic voltage characteristic point data of the cell products. By comparing the dynamic voltage data of the cell products with the reference value, the cell products with voltages higher than the reference value are the cell products to be inspected, and the rest are unqualified cell products;

[0010] (S4) For the unqualified cell products, the subsequent charging process will be stopped. The cell products to be inspected are then charged at 0.5C until the initial charging is completed;

[0011] (S5) After the initial charging is completed, the OCV and IR of the cell products to be inspected in step (S4) are tested. The cell products to be inspected that are successfully charged are qualified products, and the rest are unqualified cell products.

[0012] During the process of screening cell products, data feedback can be formed to guide the improvement of cell manufacturing, which specifically includes the following steps:

[0013] (A1) Taking a certain time period as a unit, output the first pass rate of the dynamic voltage in each stage;

[0014] (A2) After obtaining the dynamic voltage characteristic point data of each cell, in the order of the cell serial number, with the acquisition time point as the classification basis, the dynamic voltages of the cells within each time period (the time range can be customized) at each acquisition time point are analyzed. All cells are judged according to the qualified range of voltage mean ± 3 times the standard deviation. According to the number of extracted characteristic points, the second pass rate of each charging dynamic voltage in different production segments under the current batch can be obtained.

[0015] The present invention has the following technical effects:

[0016] 1. Through the screening method disclosed in the present invention, 100% full inspection of products can be achieved, which can further reduce the probability of unqualified cells flowing out. After selection, the consistency of the cells is better, which is beneficial to the performance and life of the cells after grouping.

[0017] 2. The water content inside the cell will cause the curve of the initial charging to shift in the early stage of charging. By monitoring and extracting the voltage during the initial charging for analysis, and by comparing the reference and the data distribution of this batch, the water content of the cell is confirmed, the unqualified cells are marked / down-graded, and at the same time, the analysis results of the batch moisture are output to guide the improvement of the manufacturing process. Description of the Drawings

[0018] Figure 1 It is the reference curve of the moisture content of each gradient sample with different moisture contents. Detailed Embodiments

[0019] The principles and features of the present invention will be described below in conjunction with embodiments; the examples cited are only used to explain the present invention and are not intended to limit the scope of the present invention.

[0020] Traditional detection of the moisture content in battery cells mainly relies on spot checks of samples during the manufacturing process, and this sampling method has a certain possibility of failure. The applicant has found through research that dynamic voltage data can represent the internal state of the battery cell at low SOC. Therefore, the present invention provides a method for screening defective products with moisture in lithium iron phosphate battery cells, which can achieve 100% full inspection of products without increasing hardware costs. This method can further reduce the probability of defective battery cells flowing out. After selection, the battery cells have better consistency, which is beneficial to the performance and lifespan of the battery cells after being grouped.

[0021] Specifically, it includes the following steps:

[0022] (S1) Artificially manufacture batteries with different gradients of moisture content (from 100 ppm to 1000 ppm, with a gradient of 100 ppm for each interval, a total of 10 gradients). At 40 - 60 °C, use a current of 0.01 - 0.05C to perform the first charge on the battery cell for 1 - 5 hours, then switch to 0.5C to continue charging the battery cell, and then complete the processing of subsequent processes. After all the battery cells are processed, perform standard electrical performance and safety performance tests on the samples of each gradient, and determine the moisture content reference curve according to the test results.

[0023] (S2) Extract at least one characteristic point from the reference curve to determine the acquisition time point of the dynamic voltage characteristic point and the voltage reference value at each acquisition time point. In this embodiment, the acquisition time point of the dynamic voltage characteristic point is determined to be 10 minutes, and the reference value is 2400 mV.

[0024] (S3) Prepare 20000 PCS of battery cells to complete work such as welding, primary liquid injection, and aging in the previous process. All 20000 PCS of battery cells are sent into the charging device within 2 hours to complete pretreatment; at 45 °C, use a current of 0.05C to perform the first charge on the battery cells for 2 hours. Obtain the dynamic voltage data at 10 minutes of charging. By comparing the dynamic voltage data of the battery cells with the reference value of 2400 mV, the battery cells with a voltage higher than the reference value are qualified battery cells. For unqualified battery cells, the device will automatically stop the subsequent charging process, and the qualified battery cells will switch to 0.5C to continue charging until the first charge is completed.

[0025] (S4) For unqualified battery cell products, stop the subsequent charging process, and the battery cell products to be inspected will switch to 0.5C to continue charging until the first charge is completed.

[0026] (S5) After the first charge is completed, perform OCV and IR tests on the cell products to be inspected in step (S4). The cell products to be inspected that are successfully charged are qualified products, and the rest are unqualified cell products.

[0027] During the process of screening cell products, data feedback can be formed to guide the improvement of cell manufacturing. The specific data analysis and feedback methods are as follows:

[0028] (A1) Taking a certain time period as a unit, output the first pass rate of the dynamic voltage in each stage.

[0029] (A2) After obtaining the dynamic voltage characteristic point data of each cell, in the order of the cell serial number, with the acquisition time point as the classification basis, perform distribution analysis on the dynamic voltage of the cells within each time period (the time range can be customized) at each acquisition time point, and judge all cells according to the qualified range of voltage mean ± 3 times the standard deviation. According to the number of extracted characteristic points, the second pass rate of the dynamic voltage of each charge in different production sections under the current batch can be obtained.

[0030] The above are only the preferred embodiments of the present invention; they are not intended to limit the present invention; any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for screening defective lithium iron phosphate battery cells with excessive moisture, characterized in that, It includes the following steps: (S1) Artificially manufacture batteries with different gradients of water content. At 40 - 60 °C, use a current of 0.01 - 0.05C to perform the first charge on the battery cells for 1 - 5 hours. Then switch to 0.5C to continue charging the battery cells, and then complete the processing of subsequent processes. After all the battery cells are processed, perform standard electrical performance and safety performance tests on the samples of each gradient, and determine the moisture content reference curve according to the test results; (S2) Extract at least one characteristic point from the reference curve to determine the acquisition time points of the dynamic voltage characteristic points and the voltage reference values at each acquisition time point; (S3) At 40 - 60 °C, use a current of 0.01 - 0.05C to perform the first charge on the pre - processed battery cell products for 1 - 5 hours to obtain the dynamic voltage characteristic point data of the battery cell products. By comparing the dynamic voltage data of the battery cell products with the reference value, the battery cell products with voltage higher than the reference value are the battery cell products to be inspected, and the rest are unqualified battery cell products; (S4) For unqualified battery cell products, stop the subsequent charging process. The battery cell products to be inspected are switched to 0.5C to continue charging until the first charge is completed; (S5) After the first charge is completed, perform OCV and IR tests on the battery cell products to be inspected in step (S4). The battery cell products to be inspected that are successfully charged are qualified products, and the rest are unqualified battery cell products.

2. The method for screening defective lithium iron phosphate battery cells with excessive moisture according to claim 1, wherein, During the process of screening battery cell products, data feedback can be formed to guide the improvement of the battery cell manufacturing, which specifically includes the following steps: (A1) Output the first pass rate of the dynamic voltage at each stage in units of a certain time period; (A2) After obtaining the dynamic voltage characteristic point data of each battery cell, in the order of the battery cell serial number, with the acquisition time point as the classification basis, perform a distribution analysis on the dynamic voltage of the battery cells within each time period (the time range can be customized) at each acquisition time point. All battery cells are judged according to the qualified range of voltage mean ± 3 times the standard deviation. According to the number of extracted characteristic points, the second pass rate of each charging dynamic voltage in different production sections of the current batch can be obtained.

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