Lithium battery die cutting size adjusting method and system

Abstract

The invention provides a method and a system for adjusting the die cutting size of a lithium battery. The method comprises the following steps: acquiring parameter data in a die cutting process of the lithium battery; predicting current die cutting size data based on the parameter data; if the current die cutting size data is not in the preset data range, die cutting size error data are determined based on the parameter data; and adjusting the die cutting size of the lithium battery based on the die cutting size error data. According to the method, the parameter data in the lithium battery die cutting process is obtained to predict the current die cutting size data, if the current die cutting size data is not within the preset data range, the die cutting size error data can be determined based on the parameter data, and then the adjustment of the lithium battery die cutting size can be achieved. According to the method, human intervention is not needed, non-consistency changes in the die cutting process can be rapidly corrected, quality deviation occurring in the current die cutting process is remarkably reduced, it is ensured that the die cutting size is within the process requirement range, the stability of the die cutting process is improved, and the consistency of products is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium batteries, and in particular to a method and system for adjusting die-cutting size of lithium batteries. Background Art

[0002] As a new type of secondary battery with high energy density, many cycles and long service life, lithium-ion batteries have gradually become the main power source for new energy vehicles and energy storage. Die cutting is a key process in the manufacture of lithium-ion batteries. The accuracy of die cutting can have a direct impact on battery performance and stability. If the die cutting size is not accurate, it may lead to a decline in battery performance and the safety of the battery will inevitably be affected.

[0003] In the actual production process, the die-cutting dimensions are generally monitored through CCD, so as to obtain abnormal die-cutting dimensions and then adjust the corresponding parameters. The whole process is time-consuming and labor-intensive, increasing production time and cost. In addition, most existing parameter adjustment methods are based on preset data or post-adjustment, which cannot achieve real-time linkage adjustment and cannot meet the needs of high-precision and high-efficiency industrial manufacturing. What is important is that the traditional method of manually adjusting parameters to control the accuracy of dimensions has limitations and is prone to over-adjustment or under-adjustment. Summary of the invention

[0004] The present invention aims to provide a lithium battery die-cutting size adjustment method and system to solve the above technical problems, ensure that the die-cutting size is within the process requirements, improve the stability of the die-cutting process, and improve the consistency of the product.

[0005] In order to solve the above technical problems, the present invention provides a method for adjusting the die-cutting size of a lithium battery, which may include the following steps: obtaining parameter data in the die-cutting process of a lithium battery; predicting current die-cutting size data based on the parameter data; if the current die-cutting size data is not within a preset data range, determining die-cutting size error data based on the parameter data; and adjusting the die-cutting size of the lithium battery based on the die-cutting size error data.

[0006] In the above scheme, by obtaining the parameter data in the lithium battery die-cutting process to predict the current die-cutting size data, the size error in the die-cutting process can be discovered in time. If the current die-cutting size data is not within the preset data range, the die-cutting size error data can be determined based on the parameter data, and then the die-cutting size of the lithium battery can be adjusted. This method does not require human intervention, can quickly correct the inconsistency changes in the die-cutting process, significantly reduce the quality deviation of the current die-cutting process, ensure that the die-cutting size is within the process requirements, improve the stability of the die-cutting process, and improve the consistency of the product.

[0007] In the above scheme, the data range can be preset according to the actual die-cutting dimension accuracy requirements or historical die-cutting dimension data, and is used to determine whether the predicted current die-cutting dimension data has a dimension error.

[0008] Furthermore, predicting the die-cutting dimension data based on the parameter data may include: performing data analysis and deviation trend determination on the parameter data to associate the parameter data with historical die-cutting dimension data to obtain current die-cutting dimension data.

[0009] In the above scheme, by analyzing the parameter data, the offset error between the acquired parameter data and the ideal parameter data can be obtained, and then the offset trend of the parameter data can be determined by the offset error. According to the result of the offset trend determination, the parameter data can be associated with the historical die-cutting size data to predict the current die-cutting size data.

[0010] Furthermore, if the current die-cutting dimension data is not within the preset data range, determining the die-cutting dimension error data based on the parameter data may include: if the current die-cutting dimension data is not within the preset data range, comparing the parameter data with the preset parameter range to determine the die-cutting dimension error data.

[0011] In the above scheme, the parameter range can be set according to the parameter standard of the product with qualified die-cutting size, and is used to determine whether the parameter data meets the preset requirements. By comparing the parameter data with the preset parameter range, the die-cutting size error data can be determined.

[0012] It should be noted that the parameter data may include parameters such as substrate surface tension, die cutting speed, correction position error, etc. In determining the die cutting dimension error data, different parameters need to be compared with their corresponding parameter ranges.

[0013] Furthermore, the lithium battery die-cutting size adjustment method may also include: if the current die-cutting size data is within a preset data range, reacquiring parameter data and updating the current die-cutting size data based on the parameter data.

[0014] In the above scheme, if the current die-cutting dimension data is within the preset data range, it means that there is no dimensional error. At this time, the parameter data is re-acquired and predicted to update the current die-cutting dimension data, and real-time monitoring of the parameter data is achieved. The dimensional error can be predicted and adjusted in time, which effectively improves the stability of the die-cutting process and further ensures the consistency of the product.

[0015] Furthermore, before predicting the current die-cutting dimension data based on the parameter data, the method may also include: filtering outliers on the parameter data to remove interfering data and abnormal data.

[0016] In the above scheme, by filtering outliers in the parameter data, the accuracy of the parameter data can be improved, thereby ensuring the accuracy of the subsequent prediction of the current die-cutting size data.

[0017] Furthermore, adjusting the die-cutting size of the lithium battery based on the die-cutting size error data may include: determining the size anomaly type based on the die-cutting size error data; generating a corresponding machine adjustment amount according to the size anomaly type and the die-cutting size error data; and adjusting the die-cutting size of the lithium battery based on the machine adjustment amount.

[0018] In the above scheme, by analyzing the die-cutting dimension error data, the corresponding parameters with errors can be obtained, and then the dimension abnormality type can be determined. Different dimension abnormality types require different parameters to be adjusted, so according to the dimension abnormality type and the die-cutting dimension error data, the corresponding machine adjustment amount can be generated to adjust the parameters related to the dimension abnormality type, thereby realizing the adjustment of the lithium battery die-cutting dimension.

[0019] Further, generating a corresponding machine adjustment amount according to the size abnormality type and the die-cutting size error data may include: the preset data range is W R , whose upper limit is W up , whose lower limit is W low ; The best standard value for the preset size is W S , the current die-cutting size data is represented as W m ;

[0020] If W m Not in W R Inside, and W m >W up , then the corresponding adjustment amount T = W is generated according to the size abnormality type m -W up ; If W m Not in W R Inside, and W m <W low , then the corresponding adjustment amount T = W is generated according to the size abnormality type low -W m ; If W m Not in W R Inside, and W m >2W up or W m <2W low , then the corresponding adjustment amount T = W is generated according to the size abnormality type m -W S .

[0021] In the above scheme, the parameter type that needs to be adjusted can be confirmed based on the type of size anomaly, and then the adjustment amount corresponding to the parameter type that needs to be adjusted can be determined based on the data relationship between the current die-cutting size data and the data range. This scheme can ensure the accurate generation of the adjustment amount, further ensure the accuracy of subsequent adjustments to the lithium battery die-cutting size, and improve the stability of the die-cutting process.

[0022] Furthermore, obtaining parameter data in the lithium battery die-cutting process may include: obtaining several parameters in the lithium battery die-cutting process based on preset parameter acquisition weights to obtain parameter data.

[0023] In the above scheme, the parameter acquisition weight can be pre-set based on the actual die-cutting process requirements or historical die-cutting dimension abnormality data, so as to achieve the purpose of focusing on monitoring a specific parameter in the die-cutting process, which is conducive to quickly locking the problem when analyzing the parameter data.

[0024] Furthermore, obtaining parameter data in the lithium battery die-cutting process may also include: adjusting parameter acquisition weights based on die-cutting dimension error data.

[0025] In the above scheme, the die-cutting dimension error data can be used to determine the cause of the die-cutting dimension error in the current die-cutting process, thereby determining the corresponding parameter data. By adjusting the parameter acquisition weights based on the die-cutting dimension error data, it is possible to focus on monitoring the parameter data that causes the die-cutting dimension error, thereby effectively controlling the dimension fluctuations in the die-cutting process and ensuring the stability of the die-cutting process.

[0026] The present invention also provides a lithium battery die-cutting size adjustment system, which may include: a data acquisition module, used to acquire parameter data in the lithium battery die-cutting process; a data analysis module, used to predict the current die-cutting size data based on the parameter data; an error judgment module, used to determine whether the current die-cutting size data is within a preset data range, if the current die-cutting size data is not within the preset data range, then determine the die-cutting size error data based on the parameter data; size adjustment module, used to adjust the lithium battery die-cutting size based on the die-cutting size error data.

[0027] The lithium battery die-cutting size adjustment system provided by the above scheme has a simple structure, is easy to build and promote, and can effectively implement a lithium battery die-cutting size adjustment method, which can automatically obtain parameter data and predict the current die-cutting size data. If the current die-cutting size data is not within the preset data range, it can automatically determine the die-cutting size error data and adjust the lithium battery die-cutting size in advance. The system does not require human intervention, can quickly correct the inconsistency changes in the die-cutting process, significantly reduce the quality deviation of the current die-cutting process, ensure that the die-cutting size is within the process requirements, improve the stability of the die-cutting process, and improve the consistency of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic flow chart of a lithium battery die-cutting size adjustment method provided in one embodiment of the present invention;

[0029] Figure 2 A practical schematic diagram of die-cutting size defects provided by an embodiment of the present invention;

[0030] Figure 3 A schematic diagram of a lithium battery production process provided by one embodiment of the present invention;

[0031] Figure 4 An architecture diagram of a lithium battery die-cutting size adjustment system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0034] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0035] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0036] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0037] In the die-cutting process of lithium battery manufacturing, the battery pole piece size is often unevenly cut, which easily leads to the waste of raw materials, prolonged production time and increased labor costs. Therefore, a pole piece size adjustment control method is urgently needed to improve product consistency, improve production efficiency and ensure product quality. For details, please refer to Figure 1The present embodiment provides a method for adjusting the die-cutting size of a lithium battery, which may include the following steps: Step S1: acquiring parameter data in the die-cutting process of the lithium battery; Step S2: predicting the current die-cutting size data based on the parameter data; Step S3: if the current die-cutting size data is not within the preset data range, determining the die-cutting size error data based on the parameter data; Step S4: adjusting the die-cutting size of the lithium battery based on the die-cutting size error data.

[0038] In this embodiment, by obtaining parameter data in the die-cutting process of lithium batteries to predict the current die-cutting size data, the size error in the die-cutting process can be discovered in a timely manner. If the current die-cutting size data is not within the preset data range, the die-cutting size error data can be determined based on the parameter data, and then the die-cutting size of the lithium battery can be adjusted. This method does not require human intervention, can quickly correct the inconsistency changes in the die-cutting process, significantly reduce the quality deviation of the current die-cutting process, ensure that the die-cutting size is within the process requirements, improve the stability of the die-cutting process, and improve the consistency of the product.

[0039] It should be noted that the parameter data may include parameters such as substrate surface tension, die cutting speed, correction position error, etc. The data range can be preset according to the actual die cutting dimension accuracy requirements or historical die cutting dimension data to determine whether the predicted current die cutting dimension data has a dimension error.

[0040] In one embodiment, by analyzing the obtained parameter data in the lithium battery die-cutting process, the die-cutting size error data can be accurately determined, thereby obtaining an intelligent control strategy. The intelligent control strategy can guide the adjustment of the lithium battery die-cutting size. After the lithium battery die-cutting size is adjusted by the intelligent control strategy, a new round of parameter data can be re-acquired, and steps S1 to S4 can be repeated to obtain new die-cutting size error data to update the intelligent control strategy in real time, and adjust the lithium battery die-cutting size in real time.

[0041] In one embodiment, predicting die-cutting dimension data based on parameter data may include: performing data analysis and deviation trend determination on the parameter data to associate the parameter data with historical die-cutting dimension data to obtain current die-cutting dimension data.

[0042] In this embodiment, by analyzing the parameter data, the offset error between the acquired parameter data and the ideal parameter data can be obtained, and then the offset trend of the parameter data can be determined by the offset error. According to the result of the offset trend determination, the parameter data can be associated with the historical die-cutting size data to predict the current die-cutting size data.

[0043] It should be noted that the ideal parameter data may be the corresponding parameter data when no die-cutting dimension error occurs, that is, the lithium battery die-cutting result obtained by performing the die-cutting process using the ideal parameter data is qualified.

[0044] Furthermore, the deviation trend determination process can be: Taking the deviation correction position error as an example, the SPC statistical process control principle can be used to set the deviation judgment rules. If the deviation correction position error shows a trend of 6 points continuously deviating from the center, it is necessary to focus on whether the size of the segment fluctuates, and then intervene and adjust in advance to control the die-cutting size data to float around the center value. The same applies to the determination rules of the remaining parameters such as substrate surface tension and die-cutting speed.

[0045] Furthermore, the offset error may be too small or too large. For example, when the surface tension of the substrate is too small or too large, it is easy to cause wrinkles in the current electrode, folding of the pole ear, etc., which affect the fluctuation of the die-cutting width; if the die-cutting speed is too high, the battery electrode is prone to breakage, the pole ear is prone to adhesion, and the re-taping operation is prone to uneven left and right positions, and the die-cutting width of the electrode is prone to change and fluctuate; if the deviation correction position error exists, it is easy to cause the battery electrode to deviate from the belt, resulting in deviations during laser cutting, thereby causing fluctuations in the die-cutting width of the electrode. By determining the offset trend of different parameters, the historical die-cutting dimension data can be associated with the parameter data, that is, the die-cutting dimension data that will be obtained by judging the corresponding parameters can be used to predict the current die-cutting dimension data.

[0046] It should be noted that the historical die-cutting dimension data may include abnormal die-cutting dimension data and normal die-cutting dimension data, as well as corresponding parameter data under abnormal die-cutting dimension data and corresponding parameter data under normal die-cutting dimension data. The historical die-cutting dimension data may form a database according to whether the die-cutting dimension data is normal or not and the parameters related to the abnormal situation. This embodiment can quickly locate the corresponding data area in the historical die-cutting dimension data through the determination of the offset trend, and then quickly and accurately obtain the die-cutting dimension data that can be obtained under the parameter, so as to realize the prediction of the current die-cutting dimension data.

[0047] In one embodiment, if the current die-cutting dimension data is not within the preset data range, the die-cutting dimension error data is determined based on the parameter data, which may include: if the current die-cutting dimension data is not within the preset data range, the parameter data is compared with the preset parameter range to determine the die-cutting dimension error data.

[0048] In this embodiment, the parameter range can be set according to the parameter standard of the product with qualified die-cutting size, which is used to judge whether the parameter data meets the preset requirements, and then accurately determine the relevant parameters that cause the die-cutting size error. In determining the die-cutting size error data, different parameters need to be compared with their corresponding parameter ranges. By comparing the parameter data with the preset parameter range, the die-cutting size error data can be determined.

[0049] In one embodiment, the lithium battery die-cutting size adjustment method may further include: if the current die-cutting size data is within a preset data range, reacquiring parameter data and updating the current die-cutting size data based on the parameter data.

[0050] In this embodiment, if the current die-cutting dimension data is within the preset data range, it means that there is no dimensional error. At this time, the parameter data is re-acquired and predicted to update the current die-cutting dimension data, thereby realizing real-time monitoring of the parameter data. The dimensional error can be predicted and adjusted in time, thereby effectively improving the stability of the die-cutting process and further ensuring the consistency of the product.

[0051] It should be noted that through real-time monitoring of parameter data, the corresponding parameters can be analyzed in real time. For example, by comprehensively considering several factors that affect the die-cutting size, such as substrate surface tension, die-cutting speed, and deviation correction position error, the regularity in the die-cutting process and the regularity problems can be found, and the regularity problems can be uniformly adjusted, thereby effectively avoiding repeated adjustments due to regularity problems during real-time adjustment and improving product consistency. If the problem with the hardware itself leads to the inevitable deviation after a period of operation, the corresponding parameters can be adjusted and corrected at intervals according to the pre-set time, thereby avoiding regularity problems.

[0052] In one embodiment, before predicting the current die-cutting dimension data based on the parameter data, it may also include: filtering outliers on the parameter data to remove interfering data and abnormal data.

[0053] In this embodiment, by filtering outliers on the parameter data, the accuracy of the parameter data can be improved, thereby ensuring the accuracy of subsequent predictions of the current die-cutting dimension data.

[0054] It should be noted that in the die-cutting process, after the machine is turned on, the equipment and process parameters may not be completely stable, so the parameter data produced may have large fluctuations or deviations. In order to ensure the accuracy and reliability of the parameter data, this embodiment filters the data obtained in the initial production to exclude those parameter data that obviously do not meet the quality standards or have abnormalities, so as to avoid the current parameter data from interfering with the subsequent data analysis.

[0055] In one embodiment, adjusting the die-cutting size of a lithium battery based on die-cutting size error data may include: determining a size anomaly type based on the die-cutting size error data; generating a corresponding machine adjustment amount based on the size anomaly type and the die-cutting size error data; and adjusting the die-cutting size of a lithium battery based on the machine adjustment amount.

[0056] In this embodiment, by analyzing the die-cutting dimension error data, the corresponding parameters with errors can be obtained, and then the dimension abnormality type can be determined. Different dimension abnormality types require different parameters to be adjusted, so according to the dimension abnormality type and the die-cutting dimension error data, the corresponding machine adjustment amount can be generated to adjust the parameters related to the dimension abnormality type, thereby achieving the adjustment of the lithium battery die-cutting dimension.

[0057] More specifically, the die-cutting dimension error data can intuitively feedback the reasons for the fluctuations in the die-cutting dimensions, and then determine the corresponding parameters and dimensional anomaly types that cause the fluctuations. The corresponding machine adjustment amount can be generated to adjust the corresponding execution equipment, thereby achieving the adjustment of the die-cutting dimensions of lithium batteries.

[0058] It should be noted that the adjustment amount can be calculated based on the obtained parameter data, or it can be the recommended adjustment amount obtained based on the analysis. The recommended adjustment amount is the adjustment amount obtained based on historical data. The adjustment amount can be used to adjust the parameters of the corresponding execution equipment, thereby correcting the problem of uneven cutting of the die-cutting size of the stage film and ensuring that the quality of the die-cutting size meets the specified standards.

[0059] In one embodiment, the adjustment amount is generated to correct the trend of the corresponding dimensional abnormality type, which may specifically include: determining the direction type required for adjustment of the current lithium battery plate area based on the acquired parameter data and the preset data range: if the size value of the parameter data is greater than the upper limit of the preset data range, then the adjustment type is outward adjustment to the target value; if the weight value of the current pole plate area is less than the lower limit of the preset data range, then the adjustment type of the pole plate area is inward adjustment to the target value.

[0060] It should be noted that, since parameter data types include multiple types, the adjustment strategies for different types of parameters are different, so this embodiment only describes one strategy for generating the adjustment amount, and cannot exhaust possible implementation methods of all strategies.

[0061] In one embodiment, if Figure 2 A schematic diagram of die-cutting size defects is shown, which can be the current die-cutting size data obtained by prediction, or can be obtained by measurement. In the figure, the lithium battery pole piece 1 is not in the center area, so the larger area 2 and the smaller area 3 need to be adjusted. At this time, the machine adjustment amount can be generated and adjusted through this embodiment.

[0062] Specifically, the corresponding machine adjustment amount is generated according to the size abnormality type and the die-cutting size error data, which may include: the preset data range is W R , whose upper limit is W up , whose lower limit is W low ; The best standard value for the preset size is W S , the current die-cutting size data is represented as W m ; W m With W R In comparison, the sizes of the two ends of the electrode will restrain each other. When adjusting the machine, one end will become larger while the other side will become smaller. In addition, due to the limitations of the coating material in the previous step, the electrode is prone to misalignment problems. These problems will cause the width of the die-cutting side to be unable to be adjusted to the optimal state. Therefore, when the die-cutting width is detected and needs to be adjusted, it needs to be adjusted according to the actual width of the incoming material.

[0063] If W m In W R If the value is within the range, the corresponding adjustment amount T=0 is generated, that is, no adjustment is required.

[0064] If W m Not in W R Inside, and W m >W up , then the corresponding adjustment amount T = W is generated according to the size abnormality type m -W up ; If W m Not in W R Inside, and W m <W low , then the corresponding adjustment amount T = W is generated according to the size abnormality type low -W m It should be noted that W up and W low It can be set according to the specific process parameter requirements. This embodiment only calibrates the range within the upper and lower limits, which can reduce the risk of overshoot caused by the misalignment of the incoming materials to a certain extent. The specific production can be adjusted according to actual needs. The adjustment method of this embodiment is different from the previous one-to-two adjustment strategy. The previous adjustment method is prone to overshoot risks and does not take into account the double-sided situation of the incoming materials. The amount of adjustment can be better applied to handle various incoming material situations.

[0065] If W m Not in W R Inside, and W m >2W up or W m <2W lowAt this time, the incoming material width is not enough to ensure that the incoming materials on both sides are adjusted to the target range. The generation of the intelligent control strategy can only give priority to ensuring the width of one side. At this time, the corresponding adjustment amount T=W can be generated according to the size abnormality type. m -W S .

[0066] It should be noted that, since the data range is fixed, when the real-time data of the electrode falls within the preset data range, the current data is judged to be qualified data. When the real-time data of the electrode is greater than twice the upper limit of the data range or less than twice the lower limit of the data range, the real-time data is judged to be bad data and is measurement data that needs to be adjusted.

[0067] In this embodiment, the parameter type that needs to be adjusted can be confirmed based on the size anomaly type, and then the adjustment amount corresponding to the parameter type that needs to be adjusted can be determined based on the data relationship between the current die-cutting size data and the data range (die-cutting size error data). This embodiment can ensure the accurate generation of the adjustment amount, further ensure the accuracy of subsequent adjustment of the lithium battery die-cutting size, and improve the stability of the die-cutting process.

[0068] In one embodiment, obtaining parameter data in the lithium battery die-cutting process may include: obtaining several parameters in the lithium battery die-cutting process based on preset parameter acquisition weights to obtain parameter data.

[0069] In this embodiment, parameter acquisition weights can be pre-set based on actual die-cutting process requirements or historical die-cutting dimension abnormality data, so as to achieve the purpose of focusing on monitoring a specific parameter in the die-cutting process, which is conducive to quickly locking in problems when analyzing parameter data.

[0070] In one embodiment, obtaining parameter data in the lithium battery die-cutting process may further include: adjusting parameter acquisition weights based on die-cutting dimension error data.

[0071] In this embodiment, the die-cutting dimension error data can be used to determine the cause of the die-cutting dimension error in the current die-cutting process, thereby determining the corresponding parameter data. By adjusting the parameter acquisition weights based on the die-cutting dimension error data, it is possible to focus on monitoring the parameter data that causes the die-cutting dimension error, thereby effectively controlling the dimension fluctuations in the die-cutting process and ensuring the stability of the die-cutting process.

[0072] Specifically, the importance of each parameter can be analyzed based on the actual production situation, and different weights can be assigned to each parameter during the data analysis of the parameter data. The importance of each parameter can be reflected in the commonness of the problem. For example, when the surface tension of the substrate changes frequently in the actual production process, the dimensional data will fluctuate immediately. In this case, a higher monitoring weight can be set for the substrate surface tension, and the monitoring of the die-cutting speed and the deviation correction position error can be adjusted to a smaller weight. This setting is conducive to quickly locking the problem during data analysis.

[0073] In one embodiment, the parameters such as substrate surface tension, die-cutting speed, and deviation correction position error can be used to predict the current die-cutting size data at the front end of lithium battery pole piece production, and the machine adjustment quantity can be generated through the predicted die-cutting size data. This embodiment can effectively control the size fluctuation of die-cutting by monitoring the parameter data before the die-cutting size data has an error, and can adjust the relevant parameters in advance, intelligently generate new control strategies, and improve the immediacy of die-cutting size adjustment.

[0074] In one embodiment, in the actual die-cutting process, the parameter data may also include various die-cutting dimension data obtained by measurement. At the back end of lithium battery pole piece production, various die-cutting dimension data of lithium battery pole pieces can be obtained in real time using CCD and other measuring equipment. By analyzing various die-cutting dimension data, corresponding machine adjustment quantities can be generated to adjust the subsequent die-cutting dimensions, thereby avoiding the situation where the current die-cutting dimension data is inaccurately predicted and causes die-cutting dimension errors, further ensuring the stability of the die-cutting process, and realizing real-time monitoring of pole piece quality.

[0075] It should be noted that there will be a certain interval between the adjustment of parameters and the feedback of CCD monitoring data, that is, there is an interval between the process of obtaining the parameters after a round of adjustment, so it is necessary to do a good job of data hysteresis processing, such as setting a data delay acquisition strategy, to ensure the accuracy of data acquisition. The CCD monitoring data fed back can also be used to determine whether the current intelligent control strategy is effectively implemented.

[0076] In order to further illustrate the technical points of the present invention and highlight its technical advantages, this embodiment provides a production process using the above-mentioned lithium battery die-cutting size adjustment method. Figure 3. The lithium battery die-cutting size adjustment method provided in this embodiment is a method that can automatically feedback parameter data and closed-loop control. Parameter data collection can be performed when stable production begins, and data analysis can be performed on the collected parameter data to determine whether parameter adjustment is required. If not, production continues and waits for the next judgment. If parameter adjustment is required, the corresponding machine adjustment amount is generated, and adjustment control and feedback are achieved through the machine adjustment amount. This process can effectively avoid the problem that the uneven width of the battery pole piece cut in the die process may have a direct impact on battery performance and product quality, effectively improve the stability of the die-cutting process, ensure that the die-cutting width is within the process requirements, reduce human operation errors, improve production efficiency and accuracy, and ensure product quality.

[0077] In one embodiment, see Figure 4 This embodiment aims to improve the instability and performance problems existing in the current die-cutting process, bring significant improvements and reliability to the lithium battery manufacturing industry, and propose a lithium battery die-cutting size adjustment system, which may include: a data acquisition module, used to acquire parameter data in the lithium battery die-cutting process; a data analysis module, used to predict the current die-cutting size data based on the parameter data; an error determination module, used to determine whether the current die-cutting size data is within a preset data range, if the current die-cutting size data is not within the preset data range, then determine the die-cutting size error data based on the parameter data; a size adjustment module, used to adjust the lithium battery die-cutting size based on the die-cutting size error data.

[0078] It should be noted that the lithium battery die-cutting size adjustment system exists independently of the existing die-cutting system, and it can implement the above-mentioned lithium battery die-cutting size adjustment method, which is used to obtain parameter data of the existing die-cutting system, obtain die-cutting size error data through data analysis, and then generate corresponding intelligent control strategies to obtain corresponding machine adjustment quantities and act back on the die-cutting system, thereby forming a closed-loop control process.

[0079] The lithium battery die-cutting size adjustment system provided in this embodiment has low cost, high system execution efficiency and reliability, is easy to implement and promote, and has a short detection time, which can greatly improve detection efficiency and effectively reduce production costs. The system can automatically obtain parameter data and predict the current die-cutting size data. If the current die-cutting size data is not within the preset data range, it can automatically determine the die-cutting size error data and adjust the lithium battery die-cutting size in advance. The system does not require human intervention and can quickly correct inconsistent changes in the die-cutting process, significantly reduce the quality deviation of the current die-cutting process, ensure that the die-cutting size is within the process requirements, improve the stability of the die-cutting process, and improve the consistency of the product.

[0080] Furthermore, the system can use several existing acquisition devices as data acquisition modules to acquire various parameters of the die-cutting system, such as substrate surface tension parameters, die-cutting speed parameters, deviation correction position error parameters, and various die-cutting size data. The acquisition process of the relevant parameters is not the focus of protection of this embodiment, so it will not be elaborated in this embodiment.

[0081] Furthermore, the system can filter outliers on parameter data through the data analysis module to remove obviously outlier data, making the analyzed data more valuable and making the subsequent intelligent control strategy more in line with actual production conditions. The data analysis module can also be used to analyze the parameter data. When there is no error in the die-cutting dimension data, the offset trend of the parameter data is determined to predict the occurrence of die-cutting dimension data errors; and when there is an error in the die-cutting dimension data, the data of each parameter in the parameter data is compared and analyzed with its preset data range to obtain the die-cutting dimension error data.

[0082] It should be noted that this system and the existing die-cutting system can form a closed-loop control system, which controls the die-cutting dimensional data and automatically adjusts the parameters through the closed-loop system to achieve the purpose of automatic machine adjustment, reduce human intervention, and can quickly correct inconsistent changes in the die-cutting process, significantly reducing the quality deviation in the current die-cutting production, improving product consistency, thereby achieving significant quality improvements, avoiding the flow of defective products into the next process, and improving product quality rates.

[0083] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0084] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0085] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

Claims

1. A lithium battery die-cutting size adjustment method, characterized in that: The following steps are involved: Obtain parameter data in the lithium battery die-cutting process; Predicting current die-cutting dimension data based on the parameter data; If the current die-cutting dimension data is not within the preset data range, determining die-cutting dimension error data based on the parameter data; The die-cutting size of the lithium battery is adjusted based on the die-cutting size error data.

2. A lithium battery die-cutting size adjustment method according to claim 1, characterized in that: The method of predicting die-cutting dimension data based on the parameter data comprises: Data analysis and deviation trend determination are performed on the parameter data to associate the parameter data with historical die-cutting dimension data to obtain current die-cutting dimension data.

3. A lithium battery die-cutting size adjustment method according to claim 1, characterized in that: If the current die-cutting dimension data is not within the preset data range, determining the die-cutting dimension error data based on the parameter data includes: If the current die-cutting dimension data is not within the preset data range, the parameter data is compared with the preset parameter range to determine the die-cutting dimension error data.

4. A lithium battery die-cutting size adjustment method according to claim 1, characterized in that: Also includes: If the current die-cutting dimension data is within the preset data range, the parameter data is re-acquired and the current die-cutting dimension data is updated based on the parameter data.

5. A lithium battery die-cutting size adjustment method according to claim 1, characterized in that: Before predicting the current die-cutting dimension data based on the parameter data, the method further includes: filtering outliers on the parameter data.

6. A lithium battery die-cutting size adjustment method according to claim 1, characterized in that: The step of adjusting the die-cutting size of the lithium battery based on the die-cutting size error data includes: Determining the type of dimensional anomaly based on the die-cutting dimensional error data; Generate a corresponding machine adjustment amount according to the dimension abnormality type and the die-cutting dimension error data; The die-cutting size of the lithium battery is adjusted based on the adjustment amount.

7. A lithium battery die-cutting size adjustment method according to claim 6, characterized in that: The generating corresponding machine adjustment amount according to the dimension abnormality type and the die-cutting dimension error data includes: The default data range is W R , whose upper limit is W up , whose lower limit is W low ; The best standard value for the preset size is W S , the current die-cutting size data is represented as W m ; If W m Not in W R Inside, and W m >W up , then generate the corresponding adjustment amount T=W according to the size anomaly type m -W up ; If W m Not in W R Inside, and W m <W low , then generate the corresponding adjustment amount T=W according to the size anomaly type low -W m ; If W m Not in W R Inside, and W m >2W up or W m <2W low , then generate the corresponding adjustment amount T=W according to the size anomaly type m -W S .

8. A lithium battery die-cutting size adjustment method according to any one of claims 1 to 7, characterized in that: The step of obtaining parameter data in the lithium battery die-cutting process includes: Based on the preset parameter acquisition weights, several parameters in the lithium battery die-cutting process are acquired to obtain parameter data.

9. A lithium battery die-cutting size adjustment method according to claim 8, characterized in that: The method of obtaining parameter data in the lithium battery die-cutting process also includes: adjusting the parameter acquisition weight based on the die-cutting dimension error data.

10. A lithium battery die-cutting size adjustment system, characterized in that: include: Data acquisition module, used to obtain parameter data in the lithium battery die-cutting process; A data analysis module, used for predicting current die-cutting dimension data based on the parameter data; An error determination module is used to determine whether the current die-cutting dimension data is within a preset data range, and if the current die-cutting dimension data is not within the preset data range, determine the die-cutting dimension error data based on the parameter data; The size adjustment module is used to adjust the die-cutting size of the lithium battery based on the die-cutting size error data.

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