Method and device for manufacturing battery pole piece and electronic equipment

Abstract

The application discloses a battery pole piece manufacturing method and device and electronic equipment. The method comprises the following steps: obtaining a to-be-coated metal foil; determining a coating parameter corresponding to the to-be-coated metal foil, determining a plurality of coating index items corresponding to the coating parameter, determining coating index data corresponding to the plurality of coating index items in the process of coating electrode core slurry on the to-be-coated metal foil according to initial coating process data, updating the initial coating process data according to the coating index data corresponding to the plurality of coating index items, obtaining target coating process parameters, and obtaining a target battery pole piece until the to-be-coated metal foil is coated. The application solves the technical problem that in the related art, when the battery pole piece is manufactured, the coating parameters are adjusted by relying on real-time data obtained by image processing, and it is difficult to ensure the quality of the manufactured battery pole piece.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a battery pole piece manufacturing method and device and electronic equipment. BACKGROUND

[0002] As a key pre-step of battery pole piece production, the quality control of the coating process directly affects the final quality of the whole batch of battery pole pieces. However, the processing method of most data of the coating process still relies on traditional manual analysis. For example, the face density measurement method, the CCD detection method, and the image processing method are used to analyze the data of the coating process in real time. However, the face density measurement method and the CCD detection method are not only inefficient, but also difficult to ensure the accuracy and comprehensive representativeness of the data, which undoubtedly limits the accurate control of the coating quality. When the unqualified coating products enter the subsequent production process, unnecessary waste of manpower and resources will be caused. In the process of analyzing the coating data, the image processing method relies on real-time data obtained by image processing to adjust the coating parameters, and it is also difficult to ensure the quality of the manufactured battery pole pieces.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present application provide a battery pole piece manufacturing method and device and electronic equipment to at least solve the technical problem that in related technologies, the quality of the manufactured battery pole pieces is difficult to ensure when the coating parameters are adjusted by relying on real-time data obtained by image processing during the manufacturing of the battery pole pieces.

[0005] According to an aspect of an embodiment of the present application, a battery pole piece manufacturing method is provided, including: obtaining a metal foil to be coated; determining coating parameters corresponding to the metal foil to be coated, wherein the coating parameters include electrode core slurry and initial coating process data used in the coating process; determining a plurality of coating index items corresponding to the coating parameters, wherein the coating index items are used to evaluate the quality of the coating, the coating index items include index items conforming to a normal distribution, each coating index item corresponds to a plurality of subgroups, and each subgroup of the plurality of subgroups includes a plurality of consecutive observation points; determining coating index data corresponding to the plurality of coating index items during the coating of the electrode core slurry on the metal foil to be coated according to the initial coating process data, wherein the coating index data includes first coating index data and second coating index data, the first coating index data is index data corresponding to all observation points, and the second coating index data is index data corresponding to the plurality of subgroups; updating the initial coating process data according to the coating index data corresponding to the plurality of coating index items to obtain target coating process parameters until the coating of the metal foil to be coated is completed to obtain a target battery pole piece.

[0006] Optionally, in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the plurality of coating index items respectively is determined, including: in the case that the plurality of coating index items include the process capability ratio item, and the corresponding coating index data includes the corresponding process capability ratio value, determining the target limit specification corresponding to the target coating index item, wherein the target limit specification includes the upper limit specification and the lower limit specification, and the target coating index item is any one of the plurality of coating index items; determining the specification difference between the upper limit specification and the lower limit specification; and determining the process capability ratio value corresponding to the target coating index item according to the specification difference and the combined standard deviation corresponding to the target coating index item, wherein the process capability ratio value represents the deviation degree of the observation points included in the plurality of subgroups from the target limit specification in the coating process, and the combined standard deviation is the standard deviation corresponding to the plurality of subgroups.

[0007] Optionally, in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the plurality of coating index items respectively is determined, and the method further includes: in the case that the plurality of coating index items include the process capability item, and the corresponding coating index data includes the corresponding process capability index, determining the upper limit specification, the lower limit specification and the process average value corresponding to the target coating index item, wherein the process average value represents the average value of the total observation points corresponding to the coating index item; determining the first difference value between the upper limit specification and the process average value, and determining the second difference value between the process average value and the lower limit specification; and determining the process capability index corresponding to the target coating index item according to the first difference value, the second difference value and the combined standard deviation corresponding to the target coating index item, wherein the process capability index represents the coating fluctuation degree of the observation points included in the plurality of subgroups in the coating process.

[0008] Optionally, in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the plurality of coating index items respectively is determined, including: in the case that the plurality of coating index items include the process performance item, and the corresponding coating index data includes the corresponding process performance index, determining the target limit specification corresponding to the target coating index item, wherein the target limit specification includes the upper limit specification and the lower limit specification; determining the specification difference between the upper limit specification and the lower limit specification; and determining the process performance index corresponding to the target coating index item according to the specification difference and the overall standard deviation corresponding to the target coating index item, wherein the process performance index represents the deviation degree of the total observation points from the target limit specification in the coating process, and the overall standard deviation is the standard deviation of the total observation points corresponding to the target coating index item.

[0009] Optionally, in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the plurality of coating index items is determined, including: in the case that the plurality of coating index items include the determination process index item, and the corresponding coating index data includes the corresponding process index data, determining the upper limit specification, the lower limit specification and the process average value corresponding to the target coating index item; determining the first difference value between the upper limit specification and the process average value, and the second difference value between the process average value and the lower limit specification; determining the process index index corresponding to the target coating index item according to the first difference value, the second difference value and the overall standard deviation corresponding to the target coating index item, wherein the process index index represents the coating fluctuation degree of the full observation point in the coating process.

[0010] Optionally, the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameter until the coating of the metal foil to be coated is completed to obtain the target battery pole piece, including: determining a linear regression model, wherein the linear regression model includes a plurality of independent variables, and the plurality of independent variables are variables corresponding to the plurality of coating index items; inputting the coating index data corresponding to the plurality of coating index items into the linear regression model to determine the performance score of the current battery; updating the initial coating process data according to the performance score to obtain the target coating process parameter.

[0011] Optionally, the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameter until the coating of the metal foil to be coated is completed to obtain the target battery pole piece, including: determining a first-order continuous system model, wherein the first-order continuous system model includes a coating process parameter item to perform coating according to the data in the coating process parameter item; inputting the target coating process parameter into the first-order continuous system model to update the data in the coating process parameter item to the target coating process parameter to control and adjust the coating process until the coating of the metal foil to be coated is completed to obtain the target battery pole piece.

[0012] According to an aspect of some embodiments of the present application, there is provided a device for manufacturing a coated layer of a battery, comprising: an obtaining module configured to obtain a metal foil to be coated; a first determining module configured to determine a coating parameter corresponding to the metal foil to be coated, wherein the coating parameter comprises electrode core paste and initial coating process data used in a coating process; a second determining module configured to determine a plurality of coating index items corresponding to the coating parameter, wherein the coating index items are used to evaluate the quality of the coating, the coating index items comprise index items conforming to a normal distribution, each coating index item corresponds to a plurality of subgroups, and each subgroup of the plurality of subgroups comprises a plurality of consecutive observation points; a third determining module configured to determine coating index data corresponding to the plurality of coating index items during a process of coating the electrode core paste on the metal foil to be coated according to the initial coating process data, wherein the coating index data comprises first coating index data and second coating index data, the first coating index data is index data corresponding to all observation points, and the second coating index data is index data corresponding to the plurality of subgroups; and a fourth determining module configured to update the initial coating process data according to the coating index data corresponding to the plurality of coating index items to obtain target coating process parameters, until the coating of the metal foil to be coated is completed, and a target battery pole piece is obtained.

[0013] According to an aspect of some embodiments of the present application, there is provided an electronic device, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method for manufacturing a battery pole piece of any of the above.

[0014] According to an aspect of some embodiments of the present application, there is provided a computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method for manufacturing a battery pole piece of any of the above.

[0015] In this embodiment of the invention, a metal foil to be coated is obtained; coating parameters corresponding to the metal foil to be coated are determined, wherein the coating parameters include electrode cell paste and initial coating process data used in the coating process; multiple coating index items corresponding to the coating parameters are determined, wherein the coating index items are used to evaluate the coating quality, and the coating index items include index items that conform to a normal distribution, each coating index item corresponds to multiple subgroups, and each subgroup includes multiple consecutive observation points; during the process of coating the metal foil to be coated with electrode cell paste based on the initial coating process data, coating index data corresponding to the multiple coating index items are determined, wherein the coating index data includes first coating index data and second coating index data, the first coating index data is the index data corresponding to all observation points, and the second coating index data is the index data corresponding to multiple subgroups; based on the coating index data corresponding to the multiple coating index items, the initial coating process data is updated to obtain the target coating process parameters, until the coating of the metal foil to be coated is completed, and the target battery electrode is obtained. As can be seen, the embodiments of the present invention update the coating process data based on the coating index data corresponding to multiple coating index items, so as to achieve the purpose of producing electrode sheets that meet quality standards. Since the establishment of multiple coating index items can comprehensively measure the coating quality, and the coating index data can evaluate the coating process capability in real time, multiple observation points corresponding to multiple coating index items are collected in real time during the coating process, and the corresponding coating index data are calculated respectively. The coating process capability is evaluated using the coating index data, and real-time control is performed based on the evaluation results to ensure that the produced electrode sheets meet the quality requirements. This solves the technical problem in related technologies where, when producing battery electrode sheets, relying on image processing to obtain real-time data to adjust coating parameters makes it difficult to ensure the quality of the manufactured battery electrode sheets. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of a method for manufacturing battery electrodes according to an embodiment of the present invention;

[0018] Figure 2 This is a normal distribution diagram of an embodiment provided by an optional implementation of the present invention;

[0019] Figure 3 This is a curve fitting graph generated by the process capability algorithm model provided in an optional embodiment of the present invention;

[0020] Figure 4 This is another curve fitting graph generated by the process capability algorithm model provided in the optional embodiment of the present invention;

[0021] Figure 5 is another curve fitting diagram generated by the process capability algorithm model provided by the optional embodiment of the present application;

[0022] Figure 6 is another curve fitting diagram generated by the process capability algorithm model provided by the optional embodiment of the present application;

[0023] Figure 7 is a coating surface density time sequence diagram provided by the optional embodiment of the present application;

[0024] Figure 8 is a structural block diagram of a battery pole piece manufacturing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] First, some of the nouns or terms that appear in the description of the embodiments of the present application are applicable to the following explanations:

[0028] CCD detection method: a non-contact, non-invasive automatic detection technology, mainly using optical principles, focusing the measured object on the charge coupled device chip through the lens, the charge coupled device chip converts the optical signal into an electrical signal, and then obtains a digital image after processing. According to different application scenarios and detection requirements, different charge coupled device detection equipment and technology can be selected.

[0029] Python: a dynamic, object-oriented computer programming language.

[0030] sklearn library: a free software machine learning library for the Python programming language.

[0031] Embodiment 1

[0032] According to the embodiments of the present application, an embodiment of a battery coating layer manufacturing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0033] Figure 1 is a flowchart of a battery pole piece manufacturing method according to an embodiment of the present application, as shown in Figure 1 , the method comprises the following steps:

[0034] Step S102, obtaining a metal foil to be coated.

[0035] In the present application, the metal foil to be coated is obtained in step S102.

[0036] Among them, the metal foil to be coated refers to the battery pole piece on the battery production line which has not yet undergone the coating process, waiting for the electrode core paste to be coated on its surface to form the electrode pole piece.

[0037] In this step, the metal foil to be coated is obtained, that is, the battery pole piece which has not yet been coated with electrode core paste is selected for use in the next coating process, which is a basic step in manufacturing the battery pole piece.

[0038] Step S104, determining the coating parameters corresponding to the metal foil to be coated, wherein the coating parameters include the electrode core paste and the initial coating process data used in the coating process.

[0039] In the present application, the coating parameters corresponding to the metal foil to be coated are determined in step S104.

[0040] Among them, the coating parameters refer to a series of control parameters that need to be set in the lithium battery coating process in order to ensure the coating quality, these parameters affect the uniformity, thickness, width and other important characteristics of the coating. For example, coating speed, coating pressure, paste viscosity, paste flow, etc.

[0041] The electrode core slurry refers to a viscous liquid formed by mixing electrode active material, binder, solvent, and possibly added thickening agent, conductive agent, etc. It is an important raw material for making battery core components, and is formed into an electrode of a battery through coating, drying, and other processes.

[0042] The initial coating process data refers to a set of parameters set before coating begins, which are determined comprehensively according to factors such as battery design requirements and electrode core slurry composition, and are used to guide the coating machine to perform coating.

[0043] In this step, the coating parameters corresponding to the metal foil to be coated are determined, that is, before the coating process begins, the coating process parameters need to be determined according to the specific type of the metal foil to be coated. These parameters will serve as the basis for the operation of the coating machine to ensure that the coating process can proceed according to the predetermined target.

[0044] The determination of the corresponding coating parameters helps to complete the battery coating process.

[0045] In step S106, a plurality of coating index items corresponding to the coating parameters are determined, wherein the plurality of coating index items are used to evaluate the quality of coating, the plurality of coating index items include index items conforming to a normal distribution, each coating index item corresponds to a plurality of subgroups, and each subgroup in the plurality of subgroups includes a plurality of consecutive observation points.

[0046] In step S106 provided in the present application, a plurality of coating index items corresponding to the coating parameters are determined.

[0047] The coating index item refers to a plurality of specific indicators for measuring the quality of coating, such as area density, alignment, margin width, coating width, slurry distribution uniformity, and coating thickness. These indicators reflect the key quality attributes in the coating process.

[0048] The index item conforming to a normal distribution refers to the fact that the index item data is concentrated around the mean value, gradually decreases on both sides, and presents a bell-shaped curve. When the distribution of the observed values of the coating index item presents a normal distribution characteristic, it means that the fluctuation of the data is within a certain range, and such fluctuation is random and can be predicted and controlled.

[0049] In this step, a plurality of coating index items corresponding to the coating parameters are determined, that is, in order to ensure the quality of the coating process, a series of coating index items for measuring the quality of coating need to be determined according to the set coating parameters.

[0050] By determining the multiple coating index items corresponding to the coating parameters, the observation values of the specific indexes measuring the coating quality can be collected in real time during the coating process. Through statistical analysis, such as calculating the average value, standard deviation, process capability ratio, etc., the fluctuation law of the indexes in the coating process can be deeply understood, and data support can be provided for the optimization of the coating parameters, thereby improving the quality of the obtained electrode plate.

[0051] In step S108, coating index data corresponding to the multiple coating index items is determined during the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data. The coating index data includes first coating index data and second coating index data. The first coating index data is the index data corresponding to all observation points, and the second coating index data is the index data corresponding to multiple subgroups.

[0052] In step S108 provided in the present application, the coating index data corresponding to the multiple coating index items is determined.

[0053] The coating index data refers to the data values corresponding to the coating index items, such as process capability ratio values, process capability indexes, process performance indexes, and process index data, which are calculated based on the multiple observation values corresponding to the multiple coating index items collected during the coating process, and are used for real-time evaluation of the coating process capability.

[0054] The first coating index data refers to the data values corresponding to the coating index items, such as process performance indexes and process index data, which are calculated for all observation points corresponding to each coating index item during the coating process.

[0055] The second coating index data refers to the data values of multiple subgroups corresponding to the coating index items, such as process capability ratio values and process capability indexes, which are calculated by grouping the observation points corresponding to each coating index item during the coating process.

[0056] The observation point is a single data point collected during the coating process, which is the measurement value of a single coating index item such as area density, alignment, and margin width. The full-quantity observation point refers to all observation points collected corresponding to the coating index item.

[0057] In this step, the coating index data corresponding to the multiple coating index items is determined. Since multiple coating index items can comprehensively measure the coating quality, multiple observation values corresponding to multiple coating index items are collected and processed in real time during the coating process, the corresponding coating index data is obtained, the coating process capability can be monitored and evaluated in real time, and the coating process data can be adjusted subsequently to produce a better coating layer.

[0058] Step S110, according to the coating index data corresponding to a plurality of coating index items respectively, update the initial coating process data, get the target coating process parameters, until the coating of the to-be-coated metal foil is completed, and the target battery pole piece is obtained.

[0059] In the step S110 provided in the present application, the initial coating process data is updated according to the coating index data corresponding to a plurality of coating index items respectively, and the target coating process parameters are obtained.

[0060] Among them, the target coating process parameters refer to the new coating process parameters obtained by optimizing and adjusting the feedback of the coating index data, which meet the coating process parameter conditions for making the coating layer of the to-be-coated metal foil.

[0061] In this step, by real-time calculation and analysis of the coating index data, the initial set coating process data is optimized and adjusted to obtain new coating process parameters, which can optimize the coating process quality and make the coated electrode pole piece meet the standard.

[0062] It should be noted that the target coating process parameters are obtained by real-time adjustment, so as to determine more accurate parameters in the whole coating process, which can make the coating layer with better quality.

[0063] By the above steps S102-S110, the to-be-coated metal foil is obtained. The coating parameters corresponding to the to-be-coated metal foil are determined, wherein the coating parameters include initial coating process data used in the coating process. A plurality of coating index items corresponding to the coating parameters are determined, wherein the plurality of coating index items are used to evaluate the quality of the coating, the plurality of coating index items include index items conforming to a normal distribution, each of the plurality of subgroups includes a plurality of consecutive observation points, and each coating index item corresponds to a plurality of subgroups. In the process of coating the electrode core slurry on the to-be-coated metal foil according to the initial coating process data, coating index data corresponding to the plurality of coating index items is determined, wherein the coating index data includes first coating index data and second coating index data, the first coating index data is index data corresponding to all observation points, and the second coating index data is index data corresponding to the plurality of subgroups. According to the coating index data corresponding to the plurality of coating index items, the initial coating process data is updated to obtain target coating process parameters, until the to-be-coated metal foil is coated to obtain a target battery pole piece. It can be known that, according to the coating index data corresponding to the plurality of coating index items, the coating process data is updated to achieve the purpose of manufacturing an electrode pole piece meeting the quality standard. Since the plurality of coating index items can comprehensively measure the coating quality, and the coating index data can evaluate the coating process capability in real time, the plurality of observation points corresponding to the plurality of coating index items are collected in real time during the coating process, the corresponding coating index data is calculated respectively, the coating process capability is evaluated by using the coating index data, real-time closed-loop control is performed according to the evaluation result, and it is ensured that the manufactured electrode pole piece meets the quality requirement, thereby solving the technical problem in the related art that it is difficult to ensure the quality of the manufactured battery pole piece by relying on image processing to obtain real-time data to adjust the coating parameters when the battery pole piece is manufactured.

[0064] As an optional embodiment, in the process of coating the electrode core slurry on the to-be-coated metal foil according to the initial coating process data, determining the coating index data corresponding to the plurality of coating index items includes: in the case that the plurality of coating index items include a process capability ratio item, and the corresponding coating index data includes a corresponding process capability ratio value, determining a target limit specification corresponding to a target coating index item, wherein the target limit specification includes an upper limit specification and a lower limit specification, the target coating index item is any one of the plurality of coating index items; determining a specification difference value of the upper limit specification and the lower limit specification; determining a process capability ratio value corresponding to the target coating index item according to the specification difference value and a combined standard deviation corresponding to the target coating index item, wherein the process capability ratio value represents the deviation degree of the observation points included in the plurality of subgroups from the target limit specification in the coating process, and the combined standard deviation is a standard deviation corresponding to the plurality of subgroups.

[0065] In the embodiment, the specific steps of determining the process capability ratio value corresponding to the target coating index item in the process of determining the coating index data corresponding to the plurality of coating index items in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data are illustrated.

[0066] The process capability ratio item refers to a statistical index that reflects the deviation of the observation points included in the plurality of subgroups from the target limit specification in the coating process when the process is not affected by external factors, that is, the deviation of the observation points of the plurality of subgroups corresponding to the target coating index item from the target limit specification in the coating process.

[0067] The process capability ratio value refers to the specific value of the process capability ratio item. The larger the process capability ratio value, the higher the proportion of the observation values of the plurality of subgroups corresponding to the target coating index item within the target limit specification in the coating process.

[0068] The target coating index item refers to any one of the plurality of coating index items.

[0069] The target limit specification refers to the expected specification range corresponding to the plurality of coating index items in the coating process, including the upper limit specification and the lower limit specification, and is used to define the qualified standard of the coating quality. The target limit specification can be obtained by referring to the coating production process document.

[0070] The specification difference refers to the difference between the upper limit specification and the lower limit specification, which is a measure of the specification width and reflects the acceptable range of the coating index item.

[0071] The combined standard deviation refers to the within-group standard deviation obtained by combining the standard deviations of the plurality of subgroups in the data grouping analysis of the target coating index item, which reflects the overall variability of the index item in the coating process.

[0072] In the steps involved in the embodiment, the target limit specification corresponding to the target coating index item is first determined, which sets a clear qualified range for the coating index item. Then, the specification difference is calculated, which is a basic step for process capability evaluation. Finally, the process capability ratio value corresponding to the target coating index item is determined according to the specification difference and the combined standard deviation corresponding to the target coating index item.

[0073] Taking the areal density as an example, the process capability ratio is used to evaluate whether the distribution of the areal density data can completely cover the set specification limit without exceeding the limit under the normal operating conditions of the coating process.

[0074] The meaning of the process capability ratio is as follows:

[0075] If the process capability ratio is greater than one, it means that the natural variability of the process is completely within the specification limits, indicating that the process has sufficient capability to produce products that meet the specifications.

[0076] If the process capability ratio is equal to one, the natural variability of the process exactly matches the specification limits, with no additional buffer space, and the process is in a borderline state.

[0077] If the process capability ratio is less than one, the natural variability of the process exceeds the specification limits, which means that a portion of the products may not meet the quality standards, and the process capability is insufficient.

[0078] In this way, the process capability ratio value of the target coating index item can be obtained, and the process capability ratio value serves as an index for coating process quality monitoring, reflecting the natural variability of the target coating index item, i.e., the relationship between the observed values in the corresponding subgroups of the target coating index item and the target limit specification. When the value is less than a predetermined value, it indicates that the observed values in the corresponding subgroups of the target coating index item have excessive variability in the coating process, and some observed points are not within the target limit specification, requiring measures to be taken for optimization in order to adjust the corresponding process parameters according to the index, such as adjusting the coating head movement amount, coating speed, pressure, and other parameters of the coating machine.

[0079] As an optional embodiment, in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the plurality of coating index items is determined, and in the case that the plurality of coating index items includes the process capability item and the corresponding coating index data includes the corresponding process capability index, the upper limit specification corresponding to the target coating index item, the lower limit specification, and the process average value are determined, wherein the process average value represents the average value of all observed points corresponding to the coating index item; the first difference between the upper limit specification and the process average value is determined, and the second difference between the process average value and the lower limit specification is determined; the process capability index corresponding to the target coating index item is determined according to the first difference, the second difference, and the combined standard deviation corresponding to the target coating index item, wherein the process capability index represents the coating fluctuation degree of the observed points included in the plurality of subgroups in the coating process of the target coating index item.

[0080] In this embodiment, the specific steps of determining the process capability index corresponding to the target coating index item when determining the coating index data corresponding to the plurality of coating index items in the process of coating the electrode cell slurry on the metal foil to be coated according to the initial coating process data are described.

[0081] The process capability index is a specific value of the process capability item. The greater the process capability ratio value, the higher the proportion of the observation values of the multiple subgroups corresponding to the target coating index item within the target limit specification in the coating process, and the closer the center of the target coating index item to the midpoint of the specification limit.

[0082] The process capability index is a specific value of the process capability item. The greater the process capability ratio value, the higher the proportion of the observation values of the multiple subgroups corresponding to the target coating index item within the target limit specification in the coating process, and the closer the center of the target coating index item to the midpoint of the specification limit.

[0083] The process average is the center of the target coating index item, i.e., the average value of the total observation points corresponding to the target coating index item, which can reflect the average level of the target coating index item in the coating process and is one of the key parameters required for calculating the process capability index.

[0084] The first difference is the difference between the upper limit specification corresponding to the target coating index item and the process average, and the second difference is the difference between the process average corresponding to the target coating index item and the lower limit specification.

[0085] In the steps involved in this embodiment, first, the upper limit specification, the lower limit specification, and the process average corresponding to the target coating index item are determined to determine the qualified range of the target coating index item and the average level of the target coating index item in the coating process. Secondly, the first difference and the second difference are determined, which can reflect the relationship between the center of the target coating index item in the coating process and the specification limit. Finally, the process capability index corresponding to the target coating index item is determined according to the first difference, the second difference, and the combined standard deviation of the target coating index item.

[0086] Taking the areal density as an example, the process capability index can indicate whether the areal density value produced by the coating process is within the specified upper specification limit (USL) and lower specification limit (LSL) range, and whether the output of the process deviates or aligns with the target areal density value.

[0087] If the process capability index is greater than one, it indicates that most of the outputs of the process (at least 99.73%) fall within the specification limit, and the center of the process is close to the midpoint of the specification limit, and the process has good capability.

[0088] If the process capability index is equal to one, the output of the process just covers the specification limit, and the process is in a boundary state, which may have certain quality risks.

[0089] If the process capability index is less than one, it means that the natural variability or center position of the process has deviated, resulting in a portion of the output exceeding the specification limit, the process capability is insufficient, and improvement is needed.

[0090] A high process capability index value means that the fluctuation of the area density is small, the output of the process is concentrated around the target value, and few products will exceed the specification limit, which directly reflects the superiority of the area density quality.

[0091] In this way, the process capability index of the target coating index item can be obtained. The process capability index, as an index for monitoring the quality of the coating process, can measure the fluctuation degree of the observation points included in the multiple subgroups of the target coating index item and determine the relationship between the center of the target coating index item and the specification limit. When the value is less than a predetermined value, it indicates that the observation values in the multiple subgroups corresponding to the target coating index item fluctuate greatly in the coating process, the center of the target coating index item deviates from the specification center, and measures need to be taken to optimize it. In order to adjust the corresponding process parameters, such as coating probe movement, coating speed, pressure, etc.

[0092] As an optional embodiment, in the process of coating the electrode cell slurry of the metal foil to be coated according to the initial coating process data, the coating index data corresponding to the multiple coating index items is determined, including: in the case that the multiple coating index items include the process performance item, and the corresponding coating index data includes the corresponding process performance index, determining the target limit specification corresponding to the target coating index item, wherein the target limit specification includes the upper limit specification and the lower limit specification; determining the specification difference between the upper limit specification and the lower limit specification; determining the process performance index corresponding to the target coating index item according to the specification difference and the overall standard deviation corresponding to the target coating index item, wherein the process performance index represents the deviation degree of the overall observation points of the target coating index item from the target limit specification in the coating process, and the overall standard deviation is the standard deviation of the overall observation points corresponding to the target coating index item.

[0093] In this embodiment, the specific steps of determining the process performance index corresponding to the target coating index item when determining the coating index data corresponding to the multiple coating index items in the process of coating the electrode cell slurry of the metal foil to be coated according to the initial coating process data are illustrated.

[0094] Among them, the process performance item refers to the proportion of the overall observation points within the target limit specification in the coating process.

[0095] Among them, the process performance index refers to the specific value of the process performance item. The larger the process performance index value, the higher the proportion of the overall observation values corresponding to the target coating index item within the target limit specification in the coating process.

[0096] In the embodiment, the overall standard deviation refers to the standard deviation of the full amount of observation points corresponding to the target coating index item in the coating process, and is used to measure the dispersion degree of the data distribution in the entire coating process.

[0097] In the steps involved in the embodiment, firstly, the target limit specification corresponding to the target coating index item is determined, thereby setting a clear qualified range for the coating index item; secondly, the target limit specification corresponding to the target coating index item is determined; and finally, the process performance index corresponding to the target coating index item is determined according to the specification difference and the overall standard deviation corresponding to the target coating index item.

[0098] In this way, the process performance index of the target coating index item is determined. As an index for monitoring the quality of the coating process, the process performance index can measure whether the target coating index item is controllable in a long-time coating process, that is, the relationship between the full amount of observation values of the target coating index item and the target limit specification. A high process performance index value means that the distribution width of the areal density of the coating process is moderate, and will not cause the product to exceed the USL or LSL due to excessive variability, which directly reflects the stability of the areal density quality. However, when the value is less than a predetermined value, it indicates that the full amount of observation values corresponding to the target coating index item has excessive variability in the coating process, and part of the observation points are not within the target limit specification, and measures need to be taken for optimization.

[0099] As an optional embodiment, in the process of coating the electrode cell slurry of the metal foil to be coated according to the initial coating process data, the coating index data corresponding to a plurality of coating index items is determined, including: in the case where the plurality of coating index items include a determination process index item, and the corresponding coating index data includes corresponding process index data, determining the upper limit specification, the lower limit specification and the process average value corresponding to the target coating index item; determining a first difference between the upper limit specification and the process average value, and a second difference between the process average value and the lower limit specification; and determining a process index index corresponding to the target coating index item according to the first difference, the second difference and the overall standard deviation corresponding to the target coating index item, wherein the process index index represents the coating fluctuation degree of the full amount of observation points of the target coating index item in the coating process.

[0100] In the embodiment, the specific steps of determining the process index index corresponding to the target coating index item when determining the coating index data corresponding to a plurality of coating index items in the process of coating the electrode cell slurry of the metal foil to be coated according to the initial coating process data are described.

[0101] In the embodiment, the process index item refers to the fluctuation degree of the full amount of observation points corresponding to the target coating index item in a long-time coating process, and the positional relationship between the center of the target coating index item and the specification limit.

[0102] The process index data is a specific value of the process index item, and the greater the process index data value, the higher the proportion of the total observation value of the target coating index item within the target limit specification, and the closer the center of the target coating index item to the midpoint of the specification limit.

[0103] In the steps involved in this embodiment, first, the upper limit specification, the lower limit specification and the process average value corresponding to the target coating index item are determined to determine the qualified range of the target coating index item and the average level of the target coating index item in the coating process. Second, the first difference and the second difference are determined, which can reflect the relationship between the center of the target coating index item and the specification limit. Finally, the process index data corresponding to the target coating index item is determined according to the first difference, the second difference and the overall standard deviation corresponding to the target coating index item.

[0104] In this way, the process index data of the target coating index item can be obtained. As an index for monitoring the quality of the coating process, the process index data can measure the fluctuation degree of the total observation point corresponding to the target coating index item and determine the relationship between the center of the target coating index item and the specification limit. When the value is less than a predetermined value, it indicates that the total observation value corresponding to the target coating index item fluctuates greatly in the coating process, and the center of the target coating index item deviates from the specification center, and measures need to be taken to optimize.

[0105] As an optional embodiment, the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameters until the coating of the to-be-coated metal foil is completed to obtain the coating layer corresponding to the to-be-coated metal foil, comprising: determining a linear regression model, wherein the linear regression model includes a plurality of independent variables, and the plurality of independent variables are variables corresponding to the plurality of coating index items; inputting the coating index data corresponding to the plurality of coating index items into the linear regression model to determine the performance score of the current battery; updating the initial coating process data according to the performance score to obtain the target coating process parameters.

[0106] In this embodiment, the steps of determining a linear regression model, updating the initial coating process data to obtain the target coating process parameters when the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameters until the coating of the to-be-coated metal foil is completed to obtain the coating layer corresponding to the to-be-coated metal foil are explained.

[0107] The linear regression model is a model for evaluating the linear relationship between the plurality of coating index items and the battery performance score by using a statistical method. The linear regression model describes the relationship between the coating index items and the battery performance score by finding a best fitting line.

[0108] The independent variable refers to a variable used to predict the dependent variable in the linear regression model. In this optional embodiment, the independent variable refers to the plurality of coating index items determined in the coating process.

[0109] The performance score refers to a score calculated by the linear regression model and reflecting the performance level of the current electrode sheet.

[0110] In the steps involved in this embodiment, the plurality of coating index items are first determined as independent variables to determine the linear regression model. The addition of the plurality of coating index items can identify the different influence degrees of different coating index items on the electrode sheet performance score, such as the size of the influence. Second, the corresponding coating index data is input into the linear regression model to determine the performance score of the current battery, quantify the quality of the electrode sheet, and finally update the initial coating process data according to the performance score to obtain the target coating process parameters.

[0111] In this way, coating index data can be received in real time to determine the electrode sheet performance score, determine the influence of the plurality of coating index items on the electrode sheet performance score, predict the future electrode sheet performance score based on the current coating index item observation point data, dynamically adjust according to the prediction result in the coating process, update the initial coating process data, obtain the target coating process parameters, and realize closed-loop control.

[0112] As an optional embodiment, the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameters until the coating of the to-be-coated metal foil is completed to obtain a coating layer corresponding to the to-be-coated metal foil, comprising: determining a first-order continuous system model, wherein the first-order continuous system model includes a coating process parameter item to perform coating according to the data in the coating process parameter item; inputting the target coating process parameters into the first-order continuous system model to update the data in the coating process parameter item to the target coating process parameters to control and adjust the coating process until the coating of the to-be-coated metal foil is completed to obtain a target battery electrode sheet.

[0113] In this embodiment, the specific steps of determining a first-order continuous system model, and updating the data in the coating process parameter item to the target coating process parameters by using the first-order continuous system model when the initial coating process data is updated according to the coating index data corresponding to the plurality of coating index items to obtain the target coating process parameters until the coating of the to-be-coated metal foil is completed to obtain the target battery electrode sheet are explained.

[0114] In the above embodiment, the first-order continuous system model is related to a first-order continuous system model, which is a mathematical model used to describe dynamic processes, especially linear dynamic systems, in control theory and system engineering. It is usually represented as a first-order differential equation and can capture the characteristics of the process over time.

[0115] In the above embodiment, the coating process parameter item is related to various process parameter items involved in the coating process, such as coating speed, slurry flow, etc.

[0116] In the steps involved in the above embodiment, first, a first-order continuous system model is determined based on the coating process parameter item and the coating index data, and the dynamic relationship between the coating process parameter item and the coating index data is determined. Second, the target coating process parameter is input into the first-order continuous system model, and the first-order continuous system model is adjusted according to the target coating process parameter. Finally, the data in the coating process parameter item is updated to the target coating process parameter until the coating of the metal foil to be coated is completed, and the target battery electrode sheet is obtained.

[0117] In this way, the data in the coating process parameter item can be controlled in a closed loop by the first-order continuous system model, so that the data in the coating process parameter item is the target coating process parameter, and the coating process of the electrode sheet is monitored and adjusted in real time.

[0118] Based on the above embodiment and optional embodiments, an optional implementation is provided, which is described in detail below.

[0119] The manufacturing method of the battery electrode sheet provided in the optional embodiment of the present application can also be referred to as an intelligent coating closed-loop control method based on lithium battery coating process data, which fully utilizes an intelligent diagnostic algorithm model library to analyze real-time data collected, compares the corresponding parameter standard range in the control plan to make a result judgment and mark the problem area, and returns the parameters to the coating equipment to control the manufacturing process quality in a closed loop.

[0120] The optional embodiment of the present application focuses on the quality control of the coating production process, and designs an intelligent diagnostic algorithm model for the diversified quality risk factors existing in the current production. This model can quickly locate and mark the problem points in the coating process by analyzing the production data in real time, and feedback to the equipment to form a closed loop control, thereby reducing the manufacturing process quality risk. The intelligent diagnostic algorithm model has the following core functions:

[0121] Intelligent analysis and positioning: the model can receive various data in the coating production process in real time, and use advanced algorithms for rapid analysis to accurately identify potential quality problem points such as uneven coating, bubbles, impurities, etc.

[0122] Automatic data processing: The system not only automatically collects data, but also automatically cleans the data to remove noise and error values, ensuring the accuracy of the analysis results. In addition, the system can automatically generate charts to visually display production data and analysis results.

[0123] Automatic push of analysis results: Once a problem is found, the system can automatically push the analysis results to relevant personnel in a timely manner so that they can take corrective measures to reduce production losses.

[0124] Linkage with subsequent process equipment: In order to realize the automation and intelligence of the production process, the invention also designs a linkage mechanism with subsequent process equipment. When detecting problem materials, the system can automatically trigger the rejection mechanism to reject problem products from the production line to avoid entering subsequent processes, thereby further improving product quality.

[0125] Continuous optimization and improvement: With the continuous accumulation of production data, the intelligent diagnostic algorithm model of the invention can also be continuously optimized and improved through advanced technologies such as machine learning, continuously improving its diagnostic accuracy and efficiency.

[0126] The optional embodiment of the invention generally includes the following steps:

[0127] Confirm the key process parameters of coating, such as area density, alignment, margin width, coating width, etc.; create device types and corresponding data models using the Internet of Things platform, configure collection parameters and collection frequency; use communication methods such as network communication protocol (TCP / IP), message queue telemetry transmission (MQTT), and open platform communication unified architecture (OPC UA) to realize automatic data collection, use high-performance storage platforms for big data storage; use big data platforms to obtain process data for data cleaning; configure process standards and set parameter upper and lower thresholds; establish a diagnostic algorithm model library service layer to classify, label, and index the models, quickly find the most matching model with the current data, generate graphics and charts in combination with process standards; use big data and PC data analysis report platforms to implement data anomaly marking and early warning notification of super-threshold points in graphics through algorithm model operation; obtain the ratio between historical defect variation and normal coating variation to determine the parameter variation, and real-time feedback the variation to the device host computer system for control and adjustment.

[0128] The specific steps involved in the optional embodiment of the invention are introduced as follows.

[0129] S1, obtain the metal foil to be coated. The metal foil to be coated refers to the battery pole piece on the battery production line that has not yet undergone the coating process, waiting to coat the electrode core paste on its surface to form the electrode pole piece.

[0130] S2, determine the coating parameters corresponding to the metal foil to be coated, wherein the coating parameters include initial coating process data used in the coating process.

[0131] The coating parameters refer to a series of control parameters that need to be set in the lithium battery coating process to ensure coating quality. These parameters affect important characteristics such as uniformity, thickness, and width of the coating. For example, coating speed, coating pressure, slurry viscosity, slurry flow, etc. The initial coating process data refers to a set of parameters set before the coating starts. They are determined according to factors such as battery design requirements, electrode core slurry composition, etc. to guide the coating machine to coat.

[0132] S3, determine a plurality of coating index items corresponding to the coating parameters. The plurality of coating index items are used to evaluate the quality of the coating, and the plurality of coating index items include index items conforming to a normal distribution.

[0133] It should be noted that the coating index items are determined according to historical coating process data, and key process parameters affecting quality are confirmed, such as area density, alignment, margin width, coating width, slurry distribution uniformity, and coating thickness. These indicators reflect the key quality attributes in the coating process.

[0134] S4, collect observation point data of the plurality of coating index items.

[0135] Specifically, the following steps can be included:

[0136] S402, create a coating process device type and a corresponding data model for the metal foil to be coated using an Internet of Things platform, configure collection parameters and collection frequency according to the device type and data model, and the parameters include the data type, data format, and data unit that need to be collected. To ensure real-time data, the collection frequency uses the mode of changing and collecting immediately.

[0137] S404, configure communication methods such as network communication protocol (TCP / IP), message queue telemetry transmission (MQTT), and open platform communication unified architecture (OPC UA) to realize automatic data collection, send device data to a central server or cloud platform, and use high-performance storage platforms such as distributed file systems or relational databases (MYSQL databases) to store big data.

[0138] S406, use a big data platform to obtain process data for data cleaning, identify and correct errors, remove duplicates, fill in missing values, convert data types and formats, and obtain accurate, consistent, and easy-to-analyze data sets.

[0139] S408, according to the coating production process file, configure process standards using a manufacturing system, and set parameter upper and lower thresholds.

[0140] S5, a diagnostic algorithm model library service layer is established, including: a process capability algorithm model library and a process control algorithm model library. The models are classified, labeled and indexed, so that the most matched model can be quickly found according to current data, and a graph and a chart are automatically generated in combination with a process standard.

[0141] Specifically, the following steps can be included:

[0142] S502, a process capability algorithm model library is constructed: in the process of coating electrode cell slurry of the metal foil to be coated according to the initial coating process data, coating index data corresponding to a plurality of coating index items is determined, wherein the coating index data includes first coating index data and second coating index data, the first coating index data is index data corresponding to full observation points, the second coating index data is index data corresponding to a plurality of subgroups, each subgroup in the plurality of subgroups includes a plurality of continuous observation points, and each coating index item corresponds to a plurality of subgroups.

[0143] It should be noted that the normal distribution graph in the process capability algorithm model library is applied, refined by collecting data, and big data model analysis is realized. If the process parameter X obeys a normal distribution with a mathematical expectation μ and a variance δ, it is denoted as N(μ, δ). The probability density function is the expected value μ of the normal distribution, which determines its position, and the standard deviation δ determines the amplitude of the distribution. When μ = 0 and δ = 1, the normal distribution is a standard normal distribution.

[0144] The specific steps of constructing the process capability algorithm model library are as follows:

[0145] A1, calculate the combined standard deviation:

[0146] In the optional embodiment of the application, the normal capability analysis estimates the group standard deviation, and the method for estimating the group standard deviation δ in the subgroup depends on the size of the subgroup.

[0147] When the size of the subgroup is greater than 1, one of the following methods is used to estimate the group standard deviation:

[0148] The combined standard deviation (δ within ):

[0149]

[0150] Wherein:

[0151]

[0152] If the default method is changed and the unbiased constant is not selected, δ will be estimated according to SP.

[0153] Wherein, d represents the degrees of freedom of SP, which is calculated by ∑(ni-1); x ij represents the jth observation value in the ith subgroup. represents the mean of the ith subgroup, x i represents each observation value; n i represents the number of observations in the ith subgroup; C4(D+1) is an unbiased constant, and Γ(·) is the Euler second integral (Gamma) function.

[0154] When the subgroup size = 1, one of the following methods will be used to estimate the within-group standard deviation:

[0155] moving range average (δ xbar ):

[0156]

[0157] where:

[0158] R i = Max[x i ..., x i-w+1 ]- Min[x i ..., x i-w+1 ], i = w

[0159]

[0160] Ri represents the ith moving range; w represents the number of observations used in the moving range, and by default, w = 2; d2(w) is an unbiased constant read from the table, and d2(w) is the expected value of the total number of observations (N) in a normal population distribution (standard deviation = 1).

[0161] Therefore, if r is the range (E(r)) of a sample of the total number of observations (N) in a normal distribution (standard deviation = δ), then:

[0162] E(r) = d2(N) δ

[0163] The within-group standard deviation thus obtained is the combined standard deviation.

[0164] A2, In the alternative embodiment of the present application, the normal capacity analysis estimates the overall standard deviation δ overall :

[0165]

[0166] where:

[0167]

[0168] By default, no unbiased constant is used in estimating δoverall, and the overall standard deviation is estimated by the sample standard deviation S; represents the process mean; C4(N) is an unbiased constant (defined for the combined standard deviation); N (or ∑n i) represents the total number of observations.

[0169] A3, analyze the potential capacity of the coating index item in the coating process:

[0170] Method and formula for potential capacity measurement in normal capacity analysis:

[0171] Process capability ratio CP:

[0172]

[0173] Where USL is the upper specification limit, LSL is the lower specification limit, and δ within is the subgroup standard deviation. The higher the CP value, the smaller the variability of the process, and the stronger the process capability.

[0174] According to the process standard, set the target area density value 90 g / m 2 , the USL of the area density is set to 100 g / m 2 , and the LSL is set to 80 g / m 2 , 50 samples are automatically collected, and the area density data is distributed between 80-100 g / m 2 , assuming that the calculated CP value deviates greatly from the target value 90 g / m 2 , improvement measures need to be taken to adjust the coating head movement amount, coating speed, pressure and other parameters of the coating machine.

[0175] Process capability index CPK:

[0176]

[0177] Process average u:

[0178]

[0179] Where USL is the upper specification limit, LSL is the lower specification limit, and δ within is the subgroup standard deviation. The larger the CPK value, the stronger the process capability, i.e. the smaller the variability of the process, and the closer the process average to the specification center.

[0180] According to the process standard, set the USL of the area density to 100 g / m 2 , and the LSL to 80 g / m 2 , 50 samples are automatically collected, and the area density data is distributed between 80-100 g / m 2 . If the calculated result CPK=1.2 indicates that the process capability is good, but there is still room for improvement, if the calculated result CPK=1.33, improvement measures need to be taken to adjust the coating head movement amount, coating speed, pressure and other parameters.

[0181] A4, analyze the overall capability of the coating index item in the coating process:

[0182] In a more specific technical solution, the method and formula for measuring overall capability in normal capability analysis:

[0183] Process performance Pp:

[0184]

[0185] Where USL is the upper specification limit, LSL is the lower specification limit, and δ overall is the overall standard deviation. Pp indicates the proportion of process performance within the specification limit range. The larger the Pp value, the smaller the variability of the process within the specification range, and the stronger the capability.

[0186] According to the process standard, the upper limit of the coating area density of lithium batteries USL is 100 g / m 2 , the lower limit of the specification LSL is 80 g / m 2 , the overall standard deviation of automatic acquisition parameters is 2 g / m 2 , and Pp=(100-80) / (6*2)=10 / 12=0.83. In the alternative embodiment of the present application, the Pp value is 0.83, indicating that the variability of the process within the specification range is relatively large, and improvement measures need to be taken.

[0187] Process indicator Ppk:

[0188]

[0189] Process average u:

[0190]

[0191] Where USL is the upper specification limit, LSL is the lower specification limit, and δ overall is the overall standard deviation.

[0192] According to the process standard, the upper limit of the coating area density of lithium batteries USL is 100 g / m 2 , the lower limit of the specification LSL is 80 g / m 2 , the number of automatic acquisition samples n is 90 g / m 2 , the overall standard deviation is 2 g / m 2 . Ppk=min(100-90, 90-80) / (3*2)=min(10, 10) / 6=10 / 6≈1.67, and the Ppk value is 1.67, indicating that the process performs well in meeting the specification requirements.

[0193] A5、In a more specific embodiment, Pz represents the proportion of process outputs that exceed a special specified value (e.g. an engineering specification limit) that is z standard deviation units away from the mean of the process. When z is -2.17, it means that the specified limit is 2.17 standard deviation units below the mean of the process. In a normal distribution, this region (i.e. 2.17 standard deviation units below the mean) contains approximately 1.5% of the data points.

[0194] Figure 2 is a normal distribution chart provided by an optional embodiment of the present application, as shown in Figure 2 , the areal density mean (μ) of the lithium battery coating process is 90 g / m 2 , and the standard deviation is 2 g / m 2 . A lower limit is set so that only 1.5% of the product areal density is below this limit. According to the normal distribution, the region below 2.17 standard deviation units from the mean contains approximately 1.5% of the data points. Therefore, the lower limit (LSL) can be calculated by the following formula: LSL = u - 2.17 * δ, and the given values are inserted: LSL = 90 - 2.17 * 2 = 85.66 g / m 2 , USL = u + 2.17 * δ, and the given values are inserted: USL = 90 + 2.17 * 2 = 94.34 g / m 2 .

[0195] A6、Using the normal distribution chart, the process capability algorithm model is applied, and graphics and charts are generated in combination with process standards. The overall solid curve is compared with the group virtual curve to determine how closely they are aligned. If the curves are similar, Figure 3 is a curve fitting chart generated by the process capability algorithm model of an optional embodiment of the present application, as shown in Figure 3 , it indicates that the coating process is stable. If there is a large difference between the curves, Figure 4 is another curve fitting chart generated by the process capability algorithm model of an optional embodiment of the present application, as shown in Figure 4 , it indicates that the process may not be stable, or there may be significant variation between subgroups.

[0196] The overall solid curve is compared with the bars of the histogram to evaluate whether the data is approximately normal. If the bars and the curve are well fitted, Figure 5 is still another curve fitting chart generated by the process capability algorithm model of an optional embodiment of the present application, as shown in Figure 5 , the data is normally distributed; if there is a large difference between the bars and the curve, and the fitting degree is low, Figure 6 is still another curve fitting chart generated by the process capability algorithm model of an optional embodiment of the present application, as shown in Figure 6 , the data may not be normal, and the process capability estimate may not be reliable.

[0197] S504, construct a process control algorithm model library.

[0198] It should be noted that in the process control algorithm model library, data is collected for refinement, big data model analysis is realized, and the library contains linear regression algorithm, time series analysis, continuous and discrete system model, etc.

[0199] The specific types of constructing the process control algorithm model library are as follows:

[0200] B1, using linear regression algorithm to predict coating quality.

[0201] According to the stored historical data, including coating key quality parameters (areal density, alignment, margin width, coating width) and one or more target variables (such as battery performance score), a linear regression model is trained.

[0202] The coating index data corresponding to each coating index item is input into the linear regression model to determine the performance score of the current battery.

[0203] It should be noted that the Linear Regression class in the sklearn library of Python can be used to train the model. The parameters (intercept and slope) of the model are obtained, and the predicted battery performance score based on new data points is obtained. Table 1 is a table of historical data of the coating process, as shown in Table 1 (the data is fictitious and only for example):

[0204] Table 1

[0205] Uniformity (0-10) Margin width (mm) Coating width (mm) Battery performance score (0-100) 8.5 2 1000 85 9.0 1.5 1010 90 7.8 2.2 990 80 … … … …

[0206] The general form of the linear regression model is:

[0207] y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \beta_4 x_4

[0208] Where y is the target variable (battery performance score), (x_1, x_2, x_3, x_4) are areal density, alignment, margin width, and coating width, respectively, and (\beta_0, \beta_1, \beta_2, \beta_3, \beta_4) are the parameters (intercept and slope) of the model.

[0209] B2, using time series analysis to analyze data arranged in chronological order to discover its patterns and trends.

[0210] In the coating process, time series analysis is used to monitor and predict the trend of key quality parameters (such as area density, alignment, margin width, coating width), and a moving average model is used for time series analysis to smooth short-term fluctuations and highlight long-term trends or cycles.

[0211] The formula of the moving average model is:

[0212] [MA_t = \frac{1}{n} \sum_{i=0}^{n-1} Y_{t-i}],

[0213] where (MA_t) is the moving average at time (t), (Y_{t-i}) is the observation at time (t-i), and (n) is the window size of the moving average.

[0214] Figure 7 is the coating area density time series chart provided by the optional embodiment of the present application, wherein the horizontal coordinate of the curve in the sequence chart is the scanning time, and the vertical coordinate is the positive electrode coating AB surface area density net coating partition data, the blue curve represents the AB surface area density net coating partition data 1 mean value, the red curve represents the AB surface area density net coating partition data 2 mean value, the green curve represents the AB surface area density net coating partition data 3 mean value, the purple curve represents the AB surface area density net coating partition data 4 mean value, the orange curve represents the AB surface area density net coating partition data 5 mean value, and the cyan curve represents the AB surface area density net coating partition data 6 mean value, and the mean value range of the partition data is 406.5 to 415.5, as shown in Figure 7 The coating area density time series chart shows the original area density time series data and the prediction number based on the simple exponential smoothing model, so as to timely adjust the process parameters and ensure product quality.

[0215] B3, determine a first-order continuous system model to close-loop control the coating index item.

[0216] Determine a first-order continuous system model, wherein the first-order continuous system model includes the coating process parameter item.

[0217] In the optional embodiment of the present application, the continuous system model controls the coating area density, which is a continuous variable, by adjusting the coating speed, coating pressure and coating flow.

[0218] A simple first-order continuous system model is used to describe the change of the coating area density. The model can be expressed as:

[0219] [\frac{dD}{dt} = k_1 \cdot (F - D)]

[0220] where: D represents the coating area density (unit: g / cm 2); t represents time (unit: s); F represents target area density (unit: g / cm 2 ); k_1 represents system gain, reflecting the response speed of the system to the control input (unit: 1 / s).

[0221] The model describes the relationship between the rate of change of the coating area density with time and the difference between the current area density and the target area density. By adjusting parameters such as coating flow, coating speed, etc., the system gain (k_1) can be changed, thereby controlling the coating area density to reach the target value.

[0222] S6, according to S5, S6 steps, using big data and PC data analysis report platform, through algorithm model operation, automatically generate normal distribution, discrete, etc. Graph, calculate coating index items, generate diagnosis report, etc., and mark and warn the data abnormality of the super threshold point in the graph.

[0223] S7, according to the coating index data corresponding to the plurality of coating index items, update the initial coating process data, obtain the target coating process parameters, until the coating of the to-be-coated metal foil is completed, and obtain the target battery pole piece.

[0224] According to S6, S7 steps, through the process capability algorithm model library and the process control algorithm model library, the key process parameter data processing is realized, the ratio between the historical defect change quantity and the normal coating change quantity is obtained, the parameter change quantity is determined, and the change quantity is fed back to the equipment host computer system in real time for control and adjustment.

[0225] Among them, the process capability algorithm model library and the process control algorithm model library classify, label and index the models, quickly find the model that best matches the current data, automatically generate graphics and charts in combination with process standards. Using the intelligent diagnosis algorithm model library, the collected real-time data is analyzed, the standard range of the corresponding parameters in the control plan is compared for result judgment and problem area marking, and the parameters are returned to the coating equipment for closed-loop control of the manufacturing process quality.

[0226] Through the above optional implementation, at least the following beneficial effects can be achieved:

[0227] (1) Determining a plurality of coating index items corresponding to the coating parameters can collect observation values of a plurality of specific indicators measuring coating quality in real time during the coating process. Through statistical analysis such as calculating the average value, standard deviation, and process capability ratio, the fluctuation rule of the indicators in the coating process can be deeply understood, data support for optimization of the coating parameters is provided, and the quality of the obtained electrode pole piece is improved;

[0228] (2) Establish a process capability algorithm model, which can determine the process capability ratio value, process capability index, process performance index, process index data, etc. of the coating index data according to the collected coating index observation value, determine the fluctuation of the coating index observation value within the specification limit in the coating process, and the positional relationship between the coating index center and the specification center, real-time evaluate the coating process capability, and facilitate subsequent adjustment of the coating process data;

[0229] (3) Establish a process capability algorithm model, use linear regression algorithm, time series analysis, continuous and discrete system model, etc. to control the coating process in a closed loop according to the coating index and coating index data, update the initial coating process data, obtain the target coating process parameters, and produce a coating layer of the battery that meets the standard.

[0230] (4) The optional embodiment of the present application aims at the quality control of the lithium battery coating process, and constructs an intelligent diagnostic algorithm model, which can accurately cope with various quality risk factors. Through automatic data acquisition, cleaning, chart generation and result pushing, the model can quickly locate and mark the problem points in the coating process, realize real-time feedback and closed loop control, thereby greatly improving the efficiency of coating area density and CCD detection data analysis, significantly improving the CPK consistency, and realizing significant improvement of product quality.

[0231] It should be noted that for the above-mentioned method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0232] From the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above-mentioned embodiments can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), includes a plurality of instructions to make a terminal device (which can be a mobile phone, computer, server, or network device, etc.) execute the method of each embodiment of the present application.

[0233] Example 2

[0234] According to an embodiment of the present invention, an apparatus for implementing the above-described method for manufacturing battery electrodes is also provided. Figure 8 This is a structural block diagram of a battery electrode fabrication apparatus according to an embodiment of the present invention, such as... Figure 8 As shown, the device includes: an acquisition module 802, a first determination module 804, a second determination module 806, a third determination module 808, and a fourth determination module 810. The device will be described in detail below.

[0235] The acquisition module 802 is used to acquire the metal foil to be coated; the first determination module 804, connected to the acquisition module 802, is used to determine the coating parameters corresponding to the metal foil to be coated, wherein the coating parameters include initial coating process data used in the coating process; the second determination module 806, connected to the first determination module 804, is used to determine multiple coating index items corresponding to the coating parameters, wherein the multiple coating index items are used to evaluate the coating quality, the multiple coating index items include index items that conform to a normal distribution, each subgroup in the multiple subgroups includes multiple consecutive observation points, and each coating index item corresponds to multiple subgroups; the third determination module 808, connected to the second determination module 806, is used to determine multiple coating index items corresponding to the coating parameters. The determining module 806 is used to determine coating index data corresponding to multiple coating index items during the coating of electrode cell slurry on the metal foil to be coated based on the initial coating process data. The coating index data includes first coating index data and second coating index data. The first coating index data is the index data corresponding to the full observation point, and the second coating index data is the index data corresponding to multiple subgroups. The fourth determining module 810 is connected to the third determining module 808 and is used to update the initial coating process data based on the coating index data corresponding to the multiple coating index items to obtain the target coating process parameters until the coating of the metal foil to be coated is completed and the target battery electrode is obtained.

[0236] It should be noted that the above-mentioned acquisition module 802, first determination module 804, second determination module 806, third determination module 808 and fourth determination module 810 correspond to steps S102 to S110 in the method of manufacturing battery electrode sheets. The multiple modules and the corresponding steps are the same in terms of implementation examples and application scenarios, but are not limited to the content disclosed in the above embodiment 1.

[0237] Example 3

[0238] According to another aspect of the present invention, an electronic device is also provided, comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the method for manufacturing a battery electrode according to any of the above embodiments.

[0239] Example 4

[0240] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided. When instructions in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the above-mentioned any one of the battery tab manufacturing method.

[0241] The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0242] In the above-mentioned embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0243] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other manners. Among them, the above-mentioned apparatus embodiment is only schematic, for example, the division of the unit can be a logical function division, and in actual implementation, there can be another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0244] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment scheme.

[0245] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0246] The integrated unit, if in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such an understanding, the technical solutions of the present application, essentially or in the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

Claims

1. A method of manufacturing a battery electrode sheet, characterized by, The method comprises the following steps: obtaining a metal foil to be coated; determining coating parameters corresponding to the metal foil to be coated, wherein the coating parameters include electrode core slurry and initial coating process data used in the coating process; determining a plurality of coating index items corresponding to the coating parameters, wherein the coating index items are used to evaluate the quality of coating, the coating index items include index items conforming to a normal distribution, each coating index item corresponds to a plurality of subgroups, and each subgroup includes a plurality of continuous observation points; during the coating of the electrode core slurry on the metal foil to be coated according to the initial coating process data, determining coating index data corresponding to the plurality of coating index items respectively, wherein the coating index data includes first coating index data and second coating index data, the first coating index data is index data corresponding to all observation points, and the second coating index data is index data corresponding to a plurality of subgroups; updating the initial coating process data according to the coating index data corresponding to the plurality of coating index items respectively to obtain target coating process parameters until the coating of the metal foil to be coated is completed to obtain a target battery pole piece; wherein, according to the coating index data corresponding to the plurality of coating index items respectively, the initial coating process data is updated to obtain the target coating process parameters until the coating of the metal foil to be coated is completed to obtain the target battery pole piece, comprising: determining a linear regression model, wherein the linear regression model includes a plurality of independent variables, and the plurality of independent variables are variables corresponding to the plurality of coating index items respectively; inputting the coating index data corresponding to the plurality of coating index items respectively into the linear regression model to determine a performance score of the current battery; and updating the initial coating process data according to the performance score to obtain the target coating process parameters.

2. The method of claim 1, wherein, during the coating of the electrode core slurry on the metal foil to be coated according to the initial coating process data, determining coating index data corresponding to the plurality of coating index items respectively, comprising: in the case that the plurality of coating index items include a process capability ratio item and the corresponding coating index data include a corresponding process capability ratio value, determining a target limit specification corresponding to a target coating index item, wherein the target limit specification includes an upper limit specification and a lower limit specification; determining a specification difference between the upper limit specification and the lower limit specification; determining a process capability ratio value corresponding to the target coating index item according to the specification difference and a combined standard deviation corresponding to the target coating index item, wherein the process capability ratio value represents the deviation degree of a plurality of observation points included in a plurality of subgroups in the coating process from the target limit specification, and the combined standard deviation is a standard deviation when a plurality of subgroups are combined.

3. The method of claim 1, wherein, during the coating of the electrode core slurry on the metal foil to be coated according to the initial coating process data, determining coating index data corresponding to the plurality of coating index items respectively, further comprising: In the case that the plurality of coating index items include process capability items, and the corresponding coating index data include corresponding process capability indexes, an upper limit limit specification, a lower limit limit specification, and a process average value corresponding to the target coating index item are determined, wherein the process average value represents an average value of all observation points corresponding to the coating index item; a first difference value between the upper limit limit specification and the process average value is determined, and a second difference value between the process average value and the lower limit limit specification is determined; a process capability index corresponding to the target coating index item is determined according to the first difference value and the second difference value, wherein the process capability index represents a coating fluctuation degree of a plurality of observation points in a sub-group in the coating process of the target coating index item.

4. The method of claim 1, wherein, In the process of coating the electrode core slurry on the to-be-coated metal foil according to the initial coating process data, coating index data corresponding to the plurality of coating index items are determined, including: In the case that the plurality of coating index items include process performance items, and the corresponding coating index data include corresponding process performance indexes, an upper limit limit specification and a lower limit limit specification corresponding to the target coating index item are determined; a specification difference value between the upper limit limit specification and the lower limit limit specification is determined; a process performance index corresponding to the target coating index item is determined according to the specification difference value and a whole standard deviation corresponding to the target coating index item, wherein the process performance index represents a deviation degree of all observation points from the target limit specification in the coating process of the target coating index item, and the whole standard deviation is a standard deviation of all observation points corresponding to the target coating index item.

5. The method of claim 1, wherein, In the process of coating the electrode core slurry on the to-be-coated metal foil according to the initial coating process data, coating index data corresponding to the plurality of coating index items are determined, including: In the case that the plurality of coating index items include process index items, and the corresponding coating index data include corresponding process index indexes, an upper limit limit specification, a lower limit limit specification, and a process average value corresponding to the target coating index item are determined; a first difference value between the upper limit limit specification and the process average value is determined, and a second difference value between the process average value and the lower limit limit specification is determined; a process index index corresponding to the target coating index item is determined according to the first difference value and the second difference value, wherein the process index index represents a coating fluctuation degree of corresponding all observation points in the coating process of the target coating index item.

6. The method according to any one of claims 1 to 5, characterized in that, According to the coating index data corresponding to the plurality of coating index items, the initial coating process data is updated to obtain a target coating process parameter, until the to-be-coated metal foil is coated to obtain a target battery pole piece, including: a first-order continuous system model is determined, wherein the first-order continuous system model includes a coating process parameter item, and coating is performed according to data in the coating process parameter item; input the target coating process parameters into the first-order continuous system model, update data in the coating process parameter item to the target coating process parameters, to control the coating process until the coating of the metal foil to be coated is completed, to obtain a target battery pole piece.

7. An apparatus for manufacturing battery electrode sheets, characterized in that, The method comprises the following steps: an acquisition module, configured to acquire a metal foil to be coated; a first determination module, configured to determine coating parameters corresponding to the metal foil to be coated, wherein the coating parameters comprise electrode core slurry and initial coating process data used in a coating process; a second determination module, configured to determine a plurality of coating index items corresponding to the coating parameters, wherein the coating index items are used to evaluate the quality of coating, the coating index items comprise index items conforming to a normal distribution, each coating index item corresponds to a plurality of subgroups, and each subgroup of the plurality of subgroups comprises a plurality of continuous observation points; a third determination module, configured to determine coating index data corresponding to the plurality of coating index items respectively during coating of the electrode core slurry on the metal foil to be coated according to the initial coating process data, wherein the coating index data comprises first coating index data and second coating index data, the first coating index data is index data corresponding to all observation points, and the second coating index data is index data corresponding to a plurality of subgroups; a fourth determination module, configured to update the initial coating process data according to the coating index data corresponding to the plurality of coating index items respectively, to obtain target coating process parameters, until the coating of the metal foil to be coated is completed, to obtain a target battery pole piece; wherein the fourth determination module is further configured to determine a linear regression model, wherein the linear regression model comprises a plurality of independent variables, and the plurality of independent variables are variables corresponding to the plurality of coating index items respectively; input the coating index data corresponding to the plurality of coating index items respectively into the linear regression model, to determine a performance score of a current battery; and update the initial coating process data according to the performance score, to obtain the target coating process parameters.

8. An electronic device, comprising: The method comprises the following steps: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the method for manufacturing a battery pole piece according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device can perform the method for manufacturing a battery pole piece according to any one of claims 1 to 6.

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