Coating film roll quality evaluation method and system based on lithium battery manufacturing industry

Abstract

The invention discloses a coating film roll quality evaluation method and system based on the lithium battery manufacturing industry, and relates to the field of lithium battery manufacturing, and the method comprises the steps: collecting, transmitting and cleaning film roll multi-dimensional indexes, covering surface density transverse / longitudinal range, surface density transverse / longitudinal COV, process capability index and pole piece moisture; multi-dimensional index data such as foil leakage quantity are stored, a data intermediate table is constructed, each material area and each index data are stored, a grading scoring standard of film roll evaluation indexes is constructed based on the data intermediate table, item scores are calculated according to positive and negative index logic based on the data intermediate table and the grading scoring standard, a comprehensive score is obtained through accumulation, and a result table is generated. According to the invention, through structured data processing and differential scoring logic, the film roll evaluation efficiency and accuracy are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of lithium battery manufacturing, in particular to a quality evaluation method and system for coated film rolls based on lithium battery manufacturing. BACKGROUND

[0002] In the coating process of lithium ion battery electrode sheets, the number of dark marks, surface density, and electrode sheet moisture are controlled simultaneously, and any deviation directly affects the capacity, safety, and cycle life of the battery. The existing technology generally detects thickness, surface density, and defects separately, and each index is evaluated independently, lacking a unified quantitative model, resulting in fragmented quality determination, inability to output overall coating quality grades in real time, and difficulty in meeting the needs of high-speed online control and rapid business traceability. Therefore, there is an urgent need for a comprehensive evaluation method that can integrate multi-source detection data into a single observable index to achieve overall, real-time, and quantitative determination of electrode sheet coating quality. SUMMARY

[0003] The technical problem to be solved by the present application is how to solve the problems of scattered multi-source data and fuzzy scoring standards in existing quality evaluation methods.

[0004] The present application solves the above technical problems by the following technical means: a quality evaluation method for coated film rolls based on lithium battery manufacturing, comprising: S1, collecting, transmitting, cleaning, and warehousing processing of multi-dimensional index data involved in film roll evaluation; S2, based on the cleaned and warehoused index data, constructing a data intermediate table storing each material area and the multi-dimensional index data of each material area; S3, based on the index data stored in the data intermediate table constructed in S2, constructing a grading scoring standard for film roll evaluation indexes; S4, based on the actual values of each index stored in the data intermediate table in S2, combining the grading scoring standard constructed in S3, and calculating the sub-item scores of each index according to the preset calculation logic of positive and negative indexes; adding up the sub-item scores of all indexes to obtain the comprehensive score of the film roll, and then generating a result table storing the film roll evaluation results.

[0005] The present application overcomes the problems of low efficiency, strong subjectivity and limited coverage of traditional manual sampling detection in the quality evaluation of coated film rolls by establishing a full-process automated quality evaluation method covering data collection, intermediate table construction, score standard setting and score calculation. The method can automatically collect and process multi-dimensional indicators including face density transverse range, number of missing foils, peel strength, etc., and based on grading score standards and scoring logic designed for positive and negative indicators, realize objective and continuous sub-item scoring for each indicator, and finally obtain a comprehensive score through weighted aggregation. The method significantly improves the comprehensiveness, accuracy and consistency of quality evaluation, provides precise data support for the optimization of coating process, and directly helps to improve the performance consistency and production yield of lithium battery products, and reduces the quality cost.

[0006] Further, the multi-dimensional indicator data includes: face density transverse range, face density longitudinal range, face density transverse COV, face density longitudinal COV, face density transverse CPK, face density longitudinal CPK, number of missing foils, pole piece moisture, peel strength, number of thinning defects, number of material area defects, and number of dark marks.

[0007] Further, the grading score standard for constructing the film roll evaluation indicator is specifically: For different indicators, the scoring standard is constructed, and the score is divided into five levels A, B, C, D and E, and the score range of each level is as follows: A level: [90, 100]; B level: [80, 90); C level: [70, 80); D level: [60, 70); E level: [0, 60).

[0008] Further, the calculation of the sub-item score of each indicator is specifically: 1) Positive indicators B, C, D level score calculation formula:

[0009] E level score calculation formula: let

[0010]

[0011] A level score calculation formula: let

[0012]

[0013] 2) Negative indicators B, C, D level score calculation formula:

[0014] E-level rating calculation formula: Let

[0015]

[0016] Formula for calculating Grade A: Let

[0017]

[0018] in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator For the first i Scoring of each indicator.

[0019] Furthermore, the formula for calculating the overall score of the membrane roll is as follows:

[0020] in, n This refers to the number of indicators.

[0021] This invention also provides a quality evaluation system for coated film rolls based on lithium battery manufacturing, comprising: Data acquisition and cleaning module: used to collect, transmit, clean and store multi-dimensional indicator data involved in membrane roll evaluation; Intermediate table construction module: Used to build intermediate data tables that store multi-dimensional indicator data of each material area based on the cleaned and stored indicator data; Scoring Criteria Construction Module: Used to construct a graded scoring criteria for membrane roll evaluation indicators by storing various indicator data in the intermediate table built based on the intermediate table construction module; The scoring calculation and result generation module is used to calculate the sub-scores of each indicator based on the actual values ​​of each indicator stored in the intermediate table of the intermediate table construction module, combined with the graded scoring standards constructed in the scoring standard construction module, according to the preset calculation logic of positive and negative indicators; the sub-scores of all indicators are summed to obtain the comprehensive score of the membrane roll, and then a result table storing the evaluation results of the membrane roll is generated.

[0022] Furthermore, the multi-dimensional index data includes: lateral range of areal density, longitudinal range of areal density, lateral COV of areal density, longitudinal COV of areal density, lateral CPK of areal density, longitudinal CPK of areal density, number of missing foils, electrode moisture, peel strength, number of thinning defects, number of material area defects, and number of dark marks.

[0023] Furthermore, the specific grading and scoring criteria for the constructed membrane roll evaluation index are as follows: For different indicators, scoring criteria are constructed, and the scores are divided into 5 levels: A, B, C, D, and E. The scoring range for each level is as follows: Grade A: [90, 100]; Grade B: [80, 90); Grade C: [70, 80); Grade D: [60, 70); Grade E: [0, 60].

[0024] Furthermore, the calculation of the sub-scores for each indicator is specifically as follows: 1) Positive indicators Formulas for calculating B, C, and D grade scores:

[0025] E-level rating calculation formula: Let

[0026]

[0027] Formula for calculating Grade A: Let

[0028]

[0029] 2) Negative indicators Formulas for calculating B, C, and D grade scores:

[0030] E-level rating calculation formula: Let

[0031]

[0032] Formula for calculating Grade A: Let

[0033]

[0034] in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator For the first i Scoring of each indicator.

[0035] Furthermore, the formula for calculating the overall score of the membrane roll is as follows:

[0036] in, n This refers to the number of indicators.

[0037] The advantages of this invention are: (1) Based on comprehensive business scenarios and practical experience, an index system for evaluating coated film rolls was constructed. This index system covers mathematical indicators such as the range of areal density, COV, and CPK of coated film rolls, as well as production and manufacturing testing data such as the number of missing foils, peel strength, and electrode moisture content. At the same time, the indicators can be expanded or reduced according to business needs, and the scoring criteria of the index system can be refined.

[0038] (2) A mathematical method was constructed that integrates the above-mentioned index system and scoring criteria to comprehensively evaluate the membrane roll.

[0039] (3) In the process of constructing the scoring table, two layers of data tables are used, including the intermediate data table and the result table. This has two significances: first, when there is a problem with the data, it is easier to trace the problem through the intermediate table; second, by isolating the indicator table and the scoring table, the data source of the scoring table can be reduced, allowing us to focus on the scoring logic. At the same time, if the scoring logic needs to be reconstructed, historical data can be quickly reshaped. Attached Figure Description

[0040] Figure 1 This is a flowchart of a quality evaluation method for coated film rolls based on lithium battery manufacturing, according to Embodiment 1 of the present invention. Figure 2 This is a structural diagram of the coated film roll of Embodiment 1 of the present invention; Figure 3 This is a graph showing the B, C, and D grades of Embodiment 1 of the present invention – the larger the index value, the higher the score. Figure 4 This is a graph showing the E-level score of Embodiment 1 of the present invention – the larger the index value, the higher the score. Figure 5 This is a graph showing the A-level rating of Embodiment 1 of the present invention – the larger the indicator value, the higher the score. Figure 6 This is a graph showing the B, C, and D grades of Embodiment 1 of the present invention – the larger the index value, the lower the score. Figure 7 This is a graph showing the E-level score of Embodiment 1 of the present invention – the larger the index value, the lower the score. Figure 8 This is a graph showing the A-level score in Embodiment 1 of the present invention – the larger the index value, the lower the score. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Example 1 like Figure 1 As shown, a quality evaluation method for coated film rolls based on lithium battery manufacturing includes: S1. Collect, transmit, clean, and store the multi-dimensional index data involved in the membrane roll evaluation.

[0043] Specifically, such as Figure 2 The diagram shown is a structural diagram of the coated film roll. The multi-dimensional index data includes: the lateral range of areal density, the longitudinal range of areal density, the lateral COV of areal density, the longitudinal COV of areal density, the lateral CPK of areal density, the longitudinal CPK of areal density, the number of foil leaks, the moisture content of the electrode sheet, the peel strength, the number of thinning defects, the number of material area defects, and the number of dark marks.

[0044] Areal density transverse (longitudinal) range: determines the degree of deviation between upper and lower values ​​of coating values. The smaller the range, the better the coating effect.

[0045] Areal density transverse (longitudinal) COV: COV is used to determine the dispersion of coating values. The smaller the COV, the better the coating effect.

[0046] Areal density longitudinal CPK: CPK is a process capability based on comprehensive analysis of coating data, including upper and lower specification lines (usl, lsl), average value, variance, and other indicators. The larger the CPK, the better the coating effect.

[0047] Number of foils missing: The number of coating pastes missing from the film roll (electrode). The fewer the number of foils missing, the better the coating effect.

[0048] Electrode moisture content refers to the amount of moisture remaining on the coated film roll after drying. The lower the electrode moisture content, the better the coating effect.

[0049] Peel strength: refers to the bonding strength between the active material and the electrode on the membrane roll (electrode). The greater the peel strength, the better the coating effect.

[0050] Thinning defects: In the transition area of ​​the coating die roll area, the area is divided according to certain rules, and the number of abnormal areas is determined according to the coating standard. The fewer the thinning defects, the better the coating effect.

[0051] Defective quantity in the coating area: In the normal area of ​​the coating die roll, the area is divided according to certain rules, and the number of abnormal areas is determined according to the coating standard. The fewer the defective quantity in the coating area, the better the coating effect.

[0052] Number of dark marks: The number of scratches on the electrode (aluminum foil or copper foil). The fewer the number of dark marks, the better the coating effect.

[0053] S2. Based on the cleaned and stored indicator data, construct an intermediate data table to store the multi-dimensional indicator data of each material area. The intermediate data table is shown in Table 1.

[0054] Table 1: Intermediate Data Table

[0055] S3. Based on S2, the intermediate data table stores the data of each indicator, and constructs a graded scoring standard for the membrane roll evaluation indicators.

[0056] Specifically, as shown in Table 2, the data table is constructed according to the format and example in Table 2 (left-closed, right-open). Based on actual business scenarios and experience, scoring criteria are constructed for different indicators. Specifically, the scores are divided into five levels: A, B, C, D, and E, with the scoring range for each level as follows: Grade A: [90, 100].

[0057] Grade B: [80, 90].

[0058] Grade C: [70, 80].

[0059] Grade D: [60, 70].

[0060] Grade E: [0, 60].

[0061] Table 2. Rating Scale for Indicators

[0062] S4. Based on the actual values ​​of each indicator stored in the intermediate data table in S2, and combined with the graded scoring criteria constructed in S3, calculate the sub-scores of each indicator according to the preset calculation logic of positive and negative indicators; sum up the sub-scores of all indicators to obtain the comprehensive score of the membrane roll, and then generate a result table storing the evaluation results of the membrane roll.

[0063] Specifically, the sub-scores for each indicator are calculated as follows: 1) Positive indicators (the higher the indicator value, the higher the score), such as Figures 3-5 For example: the vertical CPK of surface A.

[0064] Formulas for calculating B, C, and D grade scores:

[0065] At this point, Level E only has the upper limit of indicators. utl E-level rating calculation formula: Let

[0066]

[0067] At this point, Level A only has the lower limit of the indicator. ltl The formula for calculating an A-level grade is: Let

[0068]

[0069] 2) Negative indicators (the smaller the indicator value, the higher the score), such as Figures 6-8 For example, the longitudinal COV of surface A.

[0070] Formulas for calculating B, C, and D grade scores:

[0071] At this point, Level E only has the lower limit of the indicator. ltl E-level rating calculation formula: Let

[0072]

[0073] At this point, Level A only has the upper limit of the indicator. utl The formula for calculating an A-level grade is: Let

[0074]

[0075] in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator For the first i Scoring of each indicator.

[0076] The general idea behind the membrane roll scoring formula is that for grades with upper and lower limits, it is natural to think of scoring in a linear manner, which is the most effective and fair scoring method.

[0077] For grades with only upper (lower) limits, linear scoring is impossible due to the lack of lower (upper) limit data. Furthermore, in practical scenarios, if a data indicator exceeds (falls below) a certain value, it can be judged as extremely excellent (extremely poor). In this case, the scores should not differ significantly. Therefore, the scoring function should exhibit a property of significantly increasing (decreasing) within a certain range, and then smoothing out after reaching a certain threshold. Thus, an exponential function satisfying this property was chosen. Regarding the base of the exponential function, through curve comparison, a base of 1.1 was chosen for grade E, and a base of 1.5 was chosen for grade A. Considering the need to control the score between LSL and USL, the above-described transformation and application of the exponential function were implemented.

[0078] The formula for calculating the overall score of the membrane roll is as follows:

[0079] in, n This refers to the number of indicators.

[0080] Based on the above method for calculating the comprehensive score of the membrane roll, the final evaluation results are shown in Table 3. The data structure and examples are as follows: Table 3 Results

[0081] During the demonstration, the scores from the material areas are summed to obtain the overall score for the film roll. As envisioned, the overall score integrates multiple data indicators and evaluation systems to obtain a unified and intuitively observable scoring result, enabling precise evaluation and monitoring of the quality of the coated film roll.

[0082] Example 2 Based on Example 1, Example 2 also provides a quality evaluation system for coated film rolls in the lithium battery manufacturing industry, including: Data acquisition and cleaning module: used to collect, transmit, clean and store multi-dimensional index data involved in membrane roll evaluation.

[0083] Specifically, the multi-dimensional indicator data includes: lateral range of areal density, longitudinal range of areal density, lateral COV of areal density, longitudinal COV of areal density, lateral CPK of areal density, longitudinal CPK of areal density, number of missing foils, electrode moisture, peel strength, number of thinning defects, number of material area defects, and number of dark marks.

[0084] Intermediate table construction module: Used to build intermediate data tables that store multi-dimensional indicator data for each material area based on the cleaned and stored indicator data.

[0085] Scoring Criteria Construction Module: This module stores the data of various indicators in the intermediate table built based on the intermediate table construction module, and constructs a graded scoring standard for membrane roll evaluation indicators.

[0086] The specific grading and scoring criteria for constructing membrane roll evaluation indicators are as follows: For different indicators, scoring criteria are constructed, and the scores are divided into 5 levels: A, B, C, D, and E. The scoring range for each level is as follows: Grade A: [90, 100].

[0087] Grade B: [80, 90].

[0088] Grade C: [70, 80].

[0089] Grade D: [60, 70].

[0090] Grade E: [0, 60].

[0091] The scoring calculation and result generation module is used to calculate the sub-scores of each indicator based on the actual values ​​of each indicator stored in the intermediate table of the intermediate table construction module, combined with the graded scoring standards constructed in the scoring standard construction module, according to the preset calculation logic of positive and negative indicators; the sub-scores of all indicators are summed to obtain the comprehensive score of the membrane roll, and then a result table storing the evaluation results of the membrane roll is generated.

[0092] Calculate the sub-scores for each indicator, specifically as follows: Positive indicators Formulas for calculating B, C, and D grade scores:

[0093] E-level rating calculation formula: Let

[0094]

[0095] Formula for calculating Grade A: Let

[0096]

[0097] negative indicators Formulas for calculating B, C, and D grade scores:

[0098] E-level rating calculation formula: Let

[0099]

[0100] Formula for calculating Grade A: Let

[0101]

[0102] in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator For the first i Scoring of each indicator.

[0103] The formula for calculating the overall score of the membrane roll is as follows:

[0104] in, n This refers to the number of indicators.

[0105] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such 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 quality evaluation method for coated film rolls based on lithium battery manufacturing, characterized in that, include: S1. Collect, transmit, clean, and store the multi-dimensional index data involved in the membrane roll evaluation. S2. Based on the cleaned and stored indicator data, construct an intermediate data table to store the multi-dimensional indicator data of each material area; S3. Based on the data intermediate table constructed in S2, store the data of each indicator and construct the graded scoring standard of the membrane roll evaluation indicator; S4. Based on the actual values ​​of each indicator stored in the intermediate data table in S2, and combined with the graded scoring criteria constructed in S3, calculate the sub-scores of each indicator according to the preset calculation logic of positive and negative indicators; sum up the sub-scores of all indicators to obtain the comprehensive score of the membrane roll, and then generate a result table storing the evaluation results of the membrane roll.

2. The quality evaluation method for coated film rolls based on lithium battery manufacturing according to claim 1, characterized in that, The multi-dimensional index data includes: lateral range of areal density, longitudinal range of areal density, lateral COV of areal density, longitudinal COV of areal density, lateral CPK of areal density, longitudinal CPK of areal density, number of missing foils, electrode moisture, peel strength, number of thinning defects, number of material area defects, and number of dark marks.

3. The quality evaluation method for coated film rolls based on lithium battery manufacturing according to claim 1, characterized in that, The specific grading and scoring criteria for the evaluation indicators of the constructed membrane roll are as follows: For different indicators, scoring criteria are constructed, and the scores are divided into 5 levels: A, B, C, D, and E. The scoring range for each level is as follows: Grade A: [90, 100]; Grade B: [80, 90); Grade C: [70, 80); Grade D: [60, 70); Grade E: [0, 60].

4. The quality evaluation method for coated film rolls based on lithium battery manufacturing according to claim 1, characterized in that, The calculation of the sub-scores for each indicator is as follows: 1) Positive indicators Formulas for calculating B, C, and D grade scores: E-level rating calculation formula: Let Formula for calculating Grade A: Let 2) Negative indicators Formulas for calculating B, C, and D grade scores: E-level rating calculation formula: Let Formula for calculating Grade A: Let in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator For the first i Scoring of each indicator.

5. The quality evaluation method for coated film rolls based on lithium battery manufacturing according to claim 1, characterized in that, The formula for calculating the overall score of the membrane roll is as follows: in, n This refers to the number of indicators.

6. A quality evaluation system for coated film rolls based on lithium battery manufacturing, characterized in that, include: Data acquisition and cleaning module: used to collect, transmit, clean and store multi-dimensional indicator data involved in membrane roll evaluation; Intermediate table construction module: Used to build intermediate data tables that store multi-dimensional indicator data of each material area based on the cleaned and stored indicator data; Scoring Criteria Construction Module: Used to construct a graded scoring criteria for membrane roll evaluation indicators by storing various indicator data in the intermediate table built based on the intermediate table construction module; The scoring calculation and result generation module is used to calculate the sub-scores of each indicator based on the actual values ​​of each indicator stored in the intermediate table of the intermediate table construction module, combined with the graded scoring standards constructed in the scoring standard construction module, according to the preset calculation logic of positive and negative indicators; the sub-scores of all indicators are summed to obtain the comprehensive score of the membrane roll, and then a result table storing the evaluation results of the membrane roll is generated.

7. A quality evaluation system for coated film rolls based on lithium battery manufacturing, as described in claim 6, is characterized in that... The multi-dimensional index data includes: lateral range of areal density, longitudinal range of areal density, lateral COV of areal density, longitudinal COV of areal density, lateral CPK of areal density, longitudinal CPK of areal density, number of missing foils, electrode moisture, peel strength, number of thinning defects, number of material area defects, and number of dark marks.

8. A quality evaluation system for coated film rolls based on lithium battery manufacturing, as described in claim 6, is characterized in that... The specific grading and scoring criteria for the evaluation indicators of the constructed membrane roll are as follows: For different indicators, scoring criteria are constructed, and the scores are divided into 5 levels: A, B, C, D, and E. The scoring range for each level is as follows: Grade A: [90, 100]; Grade B: [80, 90); Grade C: [70, 80); Grade D: [60, 70); Grade E: [0, 60].

9. A quality evaluation system for coated film rolls based on lithium battery manufacturing, as described in claim 6, is characterized in that, The calculation of the sub-scores for each indicator is as follows: 1) Positive indicators Formulas for calculating B, C, and D grade scores: E-level rating calculation formula: Let Formula for calculating Grade A: Let 2) Negative indicators Formulas for calculating B, C, and D grade scores: E-level rating calculation formula: Let Formula for calculating Grade A: Let in, This represents the upper limit of the rating level to which the indicator value belongs. This represents the lower limit of the rating level to which the indicator value belongs. This represents the upper limit of the rating level for the indicator value. This represents the lower limit of the rating level for the indicator value. For the first i The weight of each indicator in the score, For the first i The actual value of each indicator Let i be the score for the i-th indicator.

10. A quality evaluation system for coated film rolls based on lithium battery manufacturing, as described in claim 6, characterized in that, The formula for calculating the overall score of the membrane roll is as follows: in, n This refers to the number of indicators.

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