Apparatus and method for controlling distribution of battery cells

Abstract

The present disclosure relates to a battery cell classification control device and a method thereof. The technical problem to be solved is to provide a mechanism for classifying battery cells according to thickness in order to control the compression force of a battery module or battery pack. To this end, the present disclosure provides a configuration comprising a processor that predicts the thickness of a packaged battery cell based on the thickness of the battery cell measured during the process, sets a grade to the battery cell according to the predicted thickness, and controls the battery cell to be classified according to the grade.

Description

Technology Field

[0001] The present disclosure relates to a battery cell classification control device and a method for classifying battery cells according to thickness. Background Technology

[0002] In the manufacturing process of secondary batteries, battery cells are loaded and packaged according to the order in which they are produced. Since these packaged battery cells are moved in the same order as they are loaded, they are assembled into battery modules or battery packs according to the production sequence.

[0003] At this time, the thickness of the battery cell is influenced by the electrode plate or the assembly process, and differences in battery cell thickness occur depending on the electrode plate or the assembly process. Due to the characteristics of the battery manufacturing process, battery cells produced on the same reel are continuously fed, so the battery cells tend to have the same thickness on a reel-by-reel basis.

[0004] Accordingly, during the assembly process of a battery module or battery pack, battery cells are assembled according to the order in which they are loaded, resulting in a phenomenon where battery cells with a tendency toward the same thickness are concentrated in a specific module or pack.

[0005] The thickness of the battery cells is not randomly distributed; instead, thick battery cells or thin battery cells may be continuously fed into a specific battery module or battery pack.

[0006] In this case, the battery module or battery pack will have a difference in final thickness after assembly is complete, and this difference affects the compression force.

[0007] Compression force is a critical factor that requires management in battery modules or battery packs, but the current problem is that there is no way to control it during the assembly process.

[0008] The information described above disclosed in the background technology of this invention is intended only to enhance understanding of the background of the present invention and may therefore include information that does not constitute prior art. The problem to be solved

[0009] The object of the present invention is to provide a battery cell classification control device and a method thereof for classifying battery cells according to thickness in order to control the compression force of a battery module or battery pack.

[0010] However, the technical problems that the present invention aims to solve are not limited to those described above, and other unmentioned problems can be clearly understood by those skilled in the art from the description of the invention below. means of solving the problem

[0011] A battery cell classification control device according to an embodiment of the present invention for solving the above technical problem comprises: a communication unit that receives thickness data from a measuring device that measures the thickness of a battery cell; and a processor that calculates a predicted thickness by predicting the final thickness of the battery cell packaged based on the thickness data, sets a grade for each battery cell based on the predicted thickness, and controls the battery cell to be classified according to the grade when it is packaged.

[0012] In the present invention, the processor is characterized by calculating the predicted thickness based on the thickness data measured in the stack process in which the separator, the cathode sheet, and the anode sheet are loaded.

[0013] The present invention is characterized by predicting the thickness of a primary packaged cell package based on the thickness data, and predicting the thickness of a final packaged cell package based on the predicted value to calculate the predicted thickness.

[0014] In the present invention, the processor analyzes data regarding the thickness in the stacking process of the battery cell, the thickness of the primary packaged cell package, and the thickness of the final packaged cell package to calculate a correlation equation, and calculates the predicted thickness according to the correlation equation.

[0015] In the present invention, the processor is characterized by performing a simulation of a battery module or battery pack assembly by combining a plurality of battery cells of different thicknesses, and setting the combination of the plurality of battery cells as a battery cell group according to the result of the simulation.

[0016] In the present invention, the processor is characterized by enabling battery cells to be assembled according to group data for the battery cell group in the assembly process of a battery module or battery pack.

[0017] In the present invention, the processor is characterized by setting a battery cell expected to be defective as a defective cell during the simulation and controlling it to be separated before packaging.

[0018] In the present invention, the processor is characterized by determining the battery cell as a defective cell and controlling it to be separated before packaging when the predicted thickness deviates from a set range.

[0019] A battery cell classification system according to another embodiment of the present invention is characterized by comprising: a battery manufacturing device that performs a stacking process, a cell packaging process, a final cell packaging process, a classification process, and a module pack assembly process; and a classification control device that predicts the thickness of the battery cell after the final cell packaging process is completed based on the thickness of the battery cell measured in the stacking process, sets a grade for the battery cell according to the predicted thickness, and controls the battery cell to be classified according to the grade in the classification process.

[0020] In the present invention, the classification control device is characterized by predicting the thickness of the battery cell after the cell packaging process is completed based on the thickness of the battery cell measured in the stacking process, and predicting the thickness of the battery cell after the final cell packaging process is completed based on the predicted value to calculate the predicted thickness.

[0021] In the present invention, the classification control device is characterized by separating the battery cell as a defective cell when the predicted thickness of the battery cell deviates from a set range.

[0022] In the present invention, the classification control device is characterized by forming a battery cell group by combining a plurality of battery cells with different thicknesses based on the predicted thickness, and controlling the assembly of the battery cells according to group data for the battery cell group during the assembly process of the battery module or battery pack.

[0023] A battery cell classification control method according to another embodiment of the present invention comprises: a step in which a processor receives thickness data from a measuring device that measures the thickness of a battery cell through a communication unit; a step in which the processor predicts the final thickness of the battery cell packaged based on the thickness data and calculates the predicted thickness; a step in which the processor sets a grade to the battery cell based on the predicted thickness; and a step in which the processor controls the battery cell to be classified according to the grade when the final packaging of the battery cell is completed.

[0024] In the present invention, the step of calculating the predicted thickness comprises: a step in which the processor predicts the thickness of a primary packaged cell package based on the thickness data; and a step in which the processor predicts the thickness of a final packaged cell package based on the predicted value and calculates the predicted thickness.

[0025] The present invention is characterized by further including, after the step of calculating the predicted thickness, the step of the processor performing a simulation of assembling a battery module or battery pack by combining a plurality of battery cells of different thicknesses based on the predicted thickness.

[0026] In the step of performing the simulation of the present invention, the processor performs the simulation by combining a plurality of battery cells with different thicknesses so that the thickness of the battery module or the battery pack is equalized.

[0027] After the step of performing the simulation of the present invention, the processor sets a battery cell expected to be defective during the simulation as a defective cell;

[0028] The step of the processor setting a battery cell that falls outside the set range according to the predicted thickness as a defective cell; and

[0029] The method further comprises the step of controlling the processor to separate the defective cell before packaging.

[0030] In the step of receiving the thickness data of the present invention, the processor calculates the predicted thickness for the final packaged battery cell based on the thickness data measured in the stack process in which the separator, the negative electrode sheet, and the positive electrode sheet are loaded. Effects of the invention

[0031] According to the present invention, the thickness of a final cell package is predicted, battery cells are classified according to the predicted thickness, and the classified battery cells are combined to assemble a battery module, thereby allowing the thickness of the battery module or battery pack to be equalized.

[0032] According to the present invention, the compression force of a battery module or battery pack composed of a plurality of battery cells can be effectively controlled.

[0033] According to the present invention, by performing a simulation based on the predicted thickness of a battery cell, defective cells can be removed in advance, and the defect rate of the battery cell can be reduced.

[0034] According to the present invention, the quality of the battery module and battery pack can be improved by controlling the defects of the battery cell and the compression force of the battery module.

[0035] However, the effects obtainable through the present invention are not limited to those described above, and other unmentioned technical effects will be clearly understood by those skilled in the art from the description of the invention below. Brief explanation of the drawing

[0036] The following drawings attached to this specification illustrate preferred embodiments of the present invention and serve to further enhance understanding of the technical concept of the present invention together with the detailed description of the invention provided below; therefore, the present invention should not be interpreted as being limited only to the matters described in such drawings. FIG. 1 is a diagram illustrating the configuration of a battery cell classification system according to one embodiment of the present invention. FIG. 2 is a block diagram briefly illustrating the control configuration of a classification control device according to one embodiment of the present invention. FIG. 3 is a drawing referenced to explain the compressive force of a battery module according to one embodiment of the present invention. FIG. 4 is a drawing showing the grades of battery cells by thickness according to one embodiment of the present invention. FIGS. 5A, FIGS. 5B, and FIGS. 5C are drawings showing the predicted thickness of a battery cell according to one embodiment of the present invention. FIG. 6 is an exemplary diagram showing the thickness and predicted values ​​of the manufacturing steps of a battery cell according to one embodiment of the present invention. FIGS. 7a, FIGS. 7b, and FIGS. 7c are exemplary diagrams illustrating the predicted thickness of a battery cell at each drafting step according to an embodiment of the present invention. FIG. 8 is a flowchart illustrating a battery cell classification control method according to one embodiment of the present invention. Specific details for implementing the invention

[0037] Preferred embodiments of the present invention will be described in detail below with reference to the attached drawings. Prior to this, terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings. Instead, based on the principle that the inventor may appropriately define the concepts of terms to best describe his invention, they should be interpreted in a meaning and concept consistent with the technical spirit of the present invention. Therefore, it should be understood that the embodiments described in this specification and the configurations illustrated in the drawings are merely some of the most preferred embodiments of the present invention and do not represent all of the technical spirit of the present invention; thus, various equivalents and modifications that can replace them may exist at the time of filing this application. Furthermore, as used in this specification, "comprise" or "include" and / or "comprising" or "including" specify the presence of the mentioned features, numbers, steps, actions, parts, elements, and / or groups thereof, and do not exclude the presence or addition of one or more other features, numbers, actions, parts, elements, and / or groups. In addition, when describing embodiments of the present invention, "may" and "may be" may include "one or more embodiments of the present invention."

[0038] Additionally, to aid in understanding the invention, the attached drawings are not drawn to actual scale, and the dimensions of some components may be exaggerated. Furthermore, the same reference numerals may be assigned to identical components in different embodiments.

[0039] The statement that two subjects of comparison are 'identical' means that they are 'substantially identical.' Therefore, substantial identity may include deviations considered low in the industry, for example, deviations within 5%. Additionally, the statement that a parameter is uniform in a given area may mean that it is uniform from an average perspective.

[0040] Although terms such as "first," "second," etc., are used to describe various components, it goes without saying that these components are not limited by these terms. These terms are used merely to distinguish one component from another, and unless specifically stated otherwise, the first component may also be the second component.

[0041] Throughout the specification, unless specifically stated otherwise, each component may be singular or plural.

[0042] The fact that any configuration is placed on the "upper (or lower)" of a component or on the "upper (or lower)" of a component may mean not only that any configuration is placed in contact with the upper (or lower) surface of said component, but also that another configuration may be interposed between said component and any configuration placed on (or below) said component.

[0043] Furthermore, where it is stated that one component is "connected," "coupled," or "connected" to another component, it should be understood that while said components may be directly connected or connected to each other, another component may be "interposed" between each component, or that each component may be "connected," "coupled," or "connected" through another component. Additionally, when it is stated that a part is electrically coupled with another part, this includes not only cases where they are directly connected but also cases where they are connected with another component in between.

[0044] Throughout the specification, "A and / or B" means A, B, or A and B unless specifically stated otherwise. That is, "and / or" includes any combination or any combination of the enumerated items. "C to D" means C or more and D or less, unless specifically stated otherwise.

[0045] FIG. 1 is a diagram showing the configuration of a battery cell classification control system according to one embodiment of the present invention.

[0046] Referring to FIG. 1, a battery cell classification control system according to one embodiment of the present invention may include a classification control device (100) and a battery manufacturing device (1).

[0047] The classification control device (100) classifies battery cells by calculating a predicted thickness based on the thickness of the battery cells measured during the battery cell manufacturing process of the battery manufacturing device (1), and controls the assembly of battery modules and battery packs based on the classified battery cells.

[0048] The battery manufacturing device (1) can perform a stacking process (10), an assembly process (20), a cell packaging process (30), a final cell packaging process (40), a sorting process (50), and a module and pack assembly process (60). At this time, the sorting process (50) and the module and pack assembly process (60) are described as being performed in a single manufacturing device, but may be performed by separate devices as needed.

[0049] The stacking process (10) involves sequentially stacking a separator, a negative electrode sheet, and a positive electrode sheet to manufacture a battery cell, and can create a jelly roll by stacking sheets and separators in the order of separator-negative electrode sheet-separator-positive electrode sheet. At this time, the jelly roll is an electrode assembly formed by joining a positive electrode sheet or a negative electrode sheet with a separator and winding it into a roll shape to create a cell, which is the basic unit of a battery.

[0050] The assembly process (20) is a step of assembling parts into a stack, the cell packaging process (30) is a step of performing packaging for the battery cell, and the final packaging process (40) is a step of completing the battery cell packaging and performing a final inspection. At this time, a cell package refers to the state in which the battery cell is primarily packaged through stack assembly. A final cell package refers to the state in which the final package is performed after a final inspection of the cell package. For example, the battery cell may be packaged as a prismatic battery cell.

[0051] At this time, the battery manufacturing device (1) may include a plurality of measuring devices (71, 72, 73) to measure the thickness of the battery cell at each process stage. The first measuring device (71) is installed in the stacking process (10) to measure the stack thickness of the battery cell. The second measuring device (72) is installed in the cell packaging process (30) to measure the thickness of the packaged battery cell, i.e., the thickness of the cell package. The third measuring device (73) is installed in the final cell packaging process (40) to measure the thickness of the final cell package.

[0052] The classification control device (100) can receive measured thickness data from a plurality of measuring devices (71, 72, 73) at each stage. The classification control device (100) can predict the final thickness based on the thickness data received from the measuring device (70) and set the grade so that the battery cells are classified according to thickness.

[0053] The classification control device (100) can predict the thickness of the final cell package based on the stack thickness measured in the stack process (10), and classify the battery cells based on the predicted thickness at the time when the final cell package process (40) is completed. At this time, the classification control device (100) can predict the thickness of the cell package based on the stack thickness and predict the thickness of the final cell package based on the predicted thickness of the cell package.

[0054] Additionally, the classification control device (100) can perform a simulation corresponding to the thickness of the final cell package predicted based on the stack thickness, i.e., the predicted thickness of the final cell package, and detect defective cells according to the simulation results. The classification control device (100) can determine the possibility of defects occurring through the simulation and separate battery cells that are expected to be defective.

[0055] The classification control device (100) applies the grade of the battery cell, which is set based on the predicted thickness for the final cell package, to the battery manufacturing device (1). When the grade (grade) for the battery cell is set by thickness, the battery manufacturing device (1) can classify the battery cell based on the grade.

[0056] Accordingly, the battery manufacturing device (1) can classify battery cells according to the grade of the final cell package and load the classified battery cells into a plurality of classification buffers. The battery cells loaded into the classification buffers in this manner can be moved to a module and pack assembly process (60) and assembled by combining them according to their thickness.

[0057] The battery manufacturing device (1) transfers battery cells classified by grade to a module and pack assembly process (60), and in the assembly process (60), groups are formed according to the thickness of the battery cells to assemble a battery module or battery pack.

[0058] The classification control device (100) can set a group of battery cells to be included in a module or pack based on the thickness of the battery cells and apply it to the assembly process (60). The classification control device (100) can set a group of battery cells such that a thick battery cell and a thin battery cell are included in one group. The classification control device (100) can set a group of battery cells such that the thickness of the battery module or battery pack is maintained constant.

[0059] Accordingly, the battery manufacturing device (1) can assemble a battery module or battery pack by combining battery cells of various thicknesses based on a battery cell group. Hereinafter, the assembly process represents a module and pack assembly process (60).

[0060] Accordingly, the classification control device (100) of the present invention classifies battery cells by predicting the thickness of the battery cells based on the stack thickness, and can equalize the thickness of the battery module or battery pack within a certain range by combining a plurality of battery cells to form a battery module or battery pack, and can adjust the compression force of the battery module or battery pack accordingly.

[0061] FIG. 2 is a block diagram briefly illustrating the control configuration of a classification control device according to one embodiment of the present invention.

[0062] Referring to FIG. 2, the classification control device (100) of the present invention may include a memory (120), a communication unit (130), an input unit (170), an output unit (180), and a processor (110).

[0063] The memory (120) can store thickness data input from the measuring device (70), prediction data calculated based on the thickness data, the final thickness of the battery cell (predicted thickness of the final cell package), and group data for a battery cell group set based on the thickness of the battery cell. Additionally, the memory (120) can store simulation data for the battery cell, simulation result data, and defective cell data.

[0064] The memory (120) can store data regarding at least one of a thickness prediction algorithm, a simulation algorithm, a group setting algorithm, a compression force control algorithm, and a cell classification algorithm.

[0065] For example, memory (120) may include non-volatile memory such as RAM (Random Access Memory), ROM (ROM), EEPROM (Electrically Erased Programmable ROM), flash memory, HDD, SSD, SDS, etc.

[0066] In some cases, the classification control device (100) may include a database (DB) (not shown) and store large amounts of data, such as simulation data and result data, in the database (DB).

[0067] The communication unit (130) transmits and receives data from each unit. The communication unit (130) is connected to the battery manufacturing device (1) and the measuring device (70) to receive data regarding the manufacturing status of the battery cell and to receive thickness data regarding the battery cell. In addition, the communication unit (130) can apply a control signal to a classification buffer in response to a control command from the processor (110) and transmit data regarding the battery cell group to the module and pack assembly process (60).

[0068] For example, the communication unit (130) can communicate via wireless communication methods such as Wi-Fi, Bluetooth, Zigbee, and mobile communication (LTE, 5G), and can also communicate via wired communication methods such as serial communication, Ethernet, and power line communication.

[0069] The input unit (170) includes at least one input means among a button, a switch, and a touchpad, and can receive user data. The input unit (170) can receive user commands for thickness prediction and defect data detection for a battery cell.

[0070] The output unit (180) may include at least one of a speaker, an operation lamp, and a display. The output unit (180) may output data of the battery manufacturing device (1) received through the communication unit (130). Additionally, the output unit (180) may output measurement data and prediction data for the battery cell, and output data regarding a battery cell group set based on the thickness of the battery cell.

[0071] The output unit (180) can output a warning message through a display or a warning sound through a speaker when an abnormality occurs or a defective battery cell is detected. Additionally, the output unit (180) can output at least one of a sound effect, a warning sound, and a voice guide during the process.

[0072] The processor (110) may include at least one microprocessor and may operate based on data and algorithms stored in memory (120).

[0073] The processor (110) can manage data transmitted and received through the communication unit (130), data input through the input unit (170), data output through the output unit (180), and data in the memory (120).

[0074] When the processor (110) receives thickness data from the measuring device (70), it stores the received thickness data in the memory (120) and can predict the thickness of the battery cell. The processor (110) can calculate the predicted thickness by applying different mathematical formulas depending on the type, model, and characteristics of the battery cell. The processor (110) may also correct the mathematical formula for thickness prediction by comparing the predicted thickness with the measured thickness.

[0075] The processor (110) predicts the thickness of the final cell package based on thickness data measured in the stack process (10), namely the stack thickness. In the process of calculating the predicted thickness of the final cell package, the processor (110) may predict the thickness of the cell package based on the predicted thickness of the cell package after predicting the thickness of the cell package from the stack thickness, rather than calculating the predicted thickness of the final cell package from the stack thickness in order to increase accuracy.

[0076] The processor (110) can set the grade of the battery cell based on the predicted thickness of the final cell package.

[0077] Since the process is delayed because it takes time to classify the actual battery cells using the thickness measured in the cell packaging process (30) or the final cell packaging process (40), the processor (110) predicts the thickness of the final cell package based on the thickness measured in the stacking process (10), sets a grade for each battery cell, and classifies the battery cells immediately when the final cell packaging process (40) is completed.

[0078] The processor (110) can simulate the possibility of defects occurring when creating a battery module or battery pack based on stack thickness. The processor (110) diagnoses the possibility of defects based on a specified simulation and classifies battery cells expected to be defective in advance based on the simulation results. The processor (110) can apply a signal to the battery manufacturing device (1) to exclude battery cells expected to be defective from the process.

[0079] The processor (110) can set up battery cell groups by combining battery cells based on the predicted thickness of the final cell package, i.e., the predicted thickness of the final cell package or the grade of each battery cell, so that the thickness can be uniform when assembling a battery module or battery pack. The processor (110) can set up battery cell groups by combining battery cells by grade through simulation.

[0080] At this time, the processor (110) can set a reference thickness according to the manufacturing model and combine multiple battery cells through simulation so that the thickness of the battery module or battery pack is determined within a certain error range based on the reference thickness.

[0081] The processor (110) can set up a battery cell group by combining multiple battery cells of different thicknesses and apply group data for the battery cell group to the battery manufacturing device (1).

[0082] Therefore, the processor (110) can control the battery manufacturing process to classify the battery cells by setting a grade according to the thickness of the battery cells without delay, and to assemble the battery module or battery group.

[0083] FIG. 3 is a drawing referenced to explain the compressive force of a battery module according to one embodiment of the present invention.

[0084] Referring to FIG. 3, the final thickness of the battery cell (81, 82, 83) may vary depending on the thickness of the electrode plate.

[0085] The first battery cell (81) has a first thickness, the second battery cell (82) has a second thickness that is thicker than the first thickness, and the third battery cell (83) has a third thickness that is thinner than the first thickness (third thickness < first thickness < second thickness).

[0086] In this case, when simply stacked according to the manufacturing order, the first battery module (91) may be assembled with battery cells of a first thickness, the second battery module (92) may be assembled with battery cells of a second thickness, and the third battery module (93) may be assembled with battery cells of a third thickness. In this case, the compression force of the second battery module (92) may increase, causing defects, and the compression force of the third battery module (93) may decrease, causing the package to shrink.

[0087] Accordingly, the classification control device (100) of the present invention can classify battery cells by predicting the thickness of the battery cells and setting a grade according to the thickness of the battery cells so that battery cells with a specific thickness tendency are not introduced into a specific battery module, and can control the assembly of a battery module or battery pack by combining battery cells having multiple thicknesses according to the grade.

[0088] The classification control device (100) can control the compression force of the battery module or battery pack and reduce the defect rate of the product because the thickness of the battery module or battery pack is equalized within an error range even if the thickness of the battery cell is different.

[0089] FIG. 4 is a drawing showing the grades of battery cells by thickness according to one embodiment of the present invention.

[0090] Referring to FIG. 4, the classification control device (100) can classify the thickness of the battery cell into five grades. At this time, the number of grades and the reference value for classifying each grade may be changed according to the settings.

[0091] The classification control device (100) can determine the distribution of battery cells manufactured according to the model of the battery cell and set the grade.

[0092] The classification control device (100) sets the grade for the battery cell using the final cell package predicted thickness calculated based on the stack thickness among the thicknesses of the battery cell. The classification control device (100) can set the grade from A to E.

[0093] The classification control device (100) can set the grade of the battery cell based on the thickness value for each grade. Grade A means the thinnest thickness and Grade E means the thickest thickness.

[0094] The classification control device (100) can simulate grouping battery cells according to a grade set based on a predicted thickness, reflecting the quantity of battery cells accommodated in a battery module and a battery pack. The classification control device (100) can set battery cell groups by combining multiple battery cells so that the thickness of the battery module is included within a certain range. For example, the classification control device (100) can set battery cell groups by combining Grade A and Grade E or combining Grade B and Grade D, with Grade C as the center.

[0095] The classification control device (100) can perform a simulation based on the placement of battery cells and the unit in which the battery cells are placed within the process, and can also perform a simulation on a daily basis or on a specific work time basis.

[0096] Additionally, the classification control device (100) may determine that a cell is defective if the predicted thickness of the final cell package falls outside the set range. For example, the classification control device (100) may determine that a battery cell is defective if the predicted thickness of the final cell package is thicker than Grade E, or if the predicted thickness of the final cell package is thinner than Grade A.

[0097] FIGS. 5A, FIGS. 5B, and FIGS. 5C are drawings showing the predicted thickness of a battery cell according to one embodiment of the present invention.

[0098] The processor (110) receives the stack thickness (measured thickness) from the measuring device (70) in the stack process (10), and receives the thickness (measured thickness) of the cell package and the thickness (measured thickness) of the final cell package in the cell package process (30) and the final cell package process (40), respectively.

[0099] When classifying battery cells by setting grades based on thickness, using the thickness of the cell package (measured thickness) or the thickness of the final cell package (measured thickness) can be the most accurate standard, but this presents a problem of process delay.

[0100] Accordingly, the processor (110) predicts the thickness of the final cell package in which the battery cell packaging is completed based on the stack thickness, and sets a grade for each battery cell according to the predicted thickness. When the final cell package process (40) is completed, the processor (110) controls the classification of the battery cells according to the grade.

[0101] At this time, the processor (110) needs to accurately predict the thickness of the final cell package based on the stack thickness. The processor (110) can calculate a predicted value based on the thickness of the battery cell for each process to accurately predict the thickness of the final cell package based on the stack thickness.

[0102] Referring to FIG. 5a, the processor (110) can predict the thickness of the final cell package from the stack measurement thickness. Referring to FIG. 5b, the processor (110) can predict the thickness of the final cell package based on the cell package measurement thickness. In this case, the measurement thickness is the actual thickness of the battery cell measured by the measuring device (70), and the predicted thickness is the thickness predicted using a mathematical formula calculated based on the correlation between the thicknesses of the battery cells by process.

[0103] Additionally, the processor (110) can predict the thickness of the final cell package based on the predicted cell package thickness as shown in FIG. 5c. At this time, the predicted cell package thickness is a predicted value based on the stack measurement thickness.

[0104] It can be seen that the final cell package predicted thickness calculated based on the stack measurement thickness differs from the final cell package predicted thickness calculated based on the cell package measurement thickness. On the other hand, the final cell package predicted thickness calculated based on the cell package measurement thickness is similar to the final cell package predicted thickness calculated based on the cell package predicted thickness.

[0105] Accordingly, the processor (110) can calculate the predicted thickness of the cell package based on the stack thickness rather than predicting the thickness of the final cell package from the stack thickness, and calculate the predicted thickness of the final cell package based on the predicted thickness of the cell package.

[0106] When the stack thickness is measured in the stack process (10), the processor (110) calculates the final cell package predicted thickness based on this and sets the grade of the battery cell according to the predicted thickness of the battery cell.

[0107] The processor (110) can classify the battery cells according to the set grade when the final cell packaging process (40) is completed.

[0108] FIG. 6 is an exemplary diagram showing the thickness and predicted values ​​of the manufacturing steps of a battery cell according to one embodiment of the present invention.

[0109] Referring to Fig. 6, the thickness of the battery cell can be compared according to the number of samples (count), median, and average value (Avg, Average).

[0110] When comparing the final cell package measured thickness, the final cell package predicted thickness based on stack measured thickness, the final cell package predicted thickness based on cell package measured thickness, and the final cell package predicted thickness based on cell package predicted thickness, it can be seen that the final cell package predicted thickness based on cell package predicted thickness has a similar average value to the final cell package measured thickness.

[0111] At this time, the processor (110) can calculate the predicted thickness of the cell package based on the stack measurement thickness, and then predict the final cell package based on the predicted thickness of the cell package to calculate the predicted thickness of the final cell package based on the predicted thickness of the cell package.

[0112] Accordingly, when the stack thickness is measured in the stack process (10), the classification control device (100) of the present invention can predict the thickness of the cell package based on the measured stack thickness, predict the thickness of the final cell package based on the predicted cell package thickness, and set the grade of the battery cell based on the predicted thickness.

[0113] The processor (110) can calculate the predicted thickness of the battery cell based on the following mathematical formula 1. In this case, mathematical formula 1 is derived by analyzing the correlation between the stack thickness, the thickness of the cell package, and the thickness of the final cell package based on actual measured thickness data.

[0114]

[0115] At this time, X is the stack measurement thickness, Y1 is the predicted thickness of the cell package, and Y2 is the predicted thickness of the final cell package. a0 and b0 are constants, and a1, a2, a3, and b1 are coefficients of X and Y, which may change depending on the battery cell model. Each constant and coefficient is calculated as an average value for the 0.01 mm thickness interval of the battery cell and can be calculated based on data with a correlation coefficient of 0.99 or higher. The calculated constants and coefficients can be stored in memory (120) in advance for each model and used for thickness prediction.

[0116] FIGS. 7a, FIGS. 7b, and FIGS. 7c are exemplary diagrams illustrating the predicted thickness of a battery cell at each drafting step according to an embodiment of the present invention.

[0117] Referring to FIG. 7a, the processor (110) can calculate the cell package predicted thickness (average) based on the stack measurement thickness. Referring to FIG. 7b, the processor (110) can calculate the final cell package predicted thickness (average) based on the cell package predicted thickness.

[0118] Referring to Fig. 7c, it can be seen that the predicted thickness of the final cell package is similar to the measured thickness of the final cell package.

[0119] Accordingly, the processor (110) can predict the thickness of the battery cell step by step according to the process, set a grade for the battery cell based on the predicted thickness before the final cell packaging process (40) is completed, and classify the battery cell according to the grade once the final cell packaging process (40) is completed.

[0120] FIG. 8 is a flowchart illustrating a battery cell classification control method according to one embodiment of the present invention.

[0121] Referring to FIG. 8, the classification control device (100) is connected to the battery manufacturing device (1) to receive thickness data, and can predict the thickness of the battery cell based on the received thickness data to set a grade for the battery cell.

[0122] The battery manufacturing device (1) first measures the stack thickness in the stack process (10) (S310). The processor (110) can receive the stack thickness from the first measuring device (71).

[0123] The processor (110) predicts the thickness of the cell package (Y1) and the thickness of the final cell package (Y2) according to the previously described mathematical formula 1 based on the received stack thickness (S320). At this time, the processor (110) can predict the thickness of the cell package based on the stack thickness and predict the thickness of the final cell package based on the predicted thickness of the cell package (predicted thickness of the cell package). The processor (110) can predict the thickness of the battery cell by changing the coefficients and constants according to the battery cell model based on mathematical formula 1.

[0124] The processor (110) can simulate the case of assembling an actual battery module or battery pack based on the predicted thickness of the final cell package (S330). The processor (110) can simulate a combination of battery cells for assembling the battery module or battery pack based on the number of battery cells included in the battery module or battery pack and the thickness (predicted thickness) of each battery cell. Additionally, the processor (110) can simulate a compression force after assembling the battery module or battery pack.

[0125] The processor (110) can determine that a battery cell predicted to be defective during the simulation process is a defective cell (S340). The processor (110) can determine that a battery cell is defective if it cannot be combined with the next battery cell, or if the predicted thickness of the battery cell is outside a specified range. If the processor (110) determines that a battery cell is defective, it separates the battery cell and ensures that the battery cell is disposed of (S350).

[0126] The processor (110) sets a grade for each battery cell based on the thickness (predicted thickness) of the battery cell (S360). For example, the processor (110) may set it to Grade B when the predicted thickness is 32.2 as described in FIG. 4 above, and set it to Grade C when the predicted thickness is 32.3. The processor (110) stores the grades of the battery cells by thickness in memory (120). At this time, the processor (110) may also set the grade for the battery cell before the simulation.

[0127] Meanwhile, the battery manufacturing device (1) measures the thickness of the cell package a second time in the cell package process (30) after going through the stack process (10) and the assembly process (20) (S370). In addition, the battery manufacturing device (1) performs an inspection of the cell package and completes the cell package to measure the thickness of the final cell package (S380).

[0128] The processor (110) receives thickness data from the second measuring device (72) and the third measuring device (73). The processor (110) can correct the constants and coefficients of Equation 1 by comparing the predicted thickness with the measured thickness.

[0129] The processor (110) can control the battery manufacturing device (1) by transmitting grade data set for the battery cell so that the battery cell is classified according to the grade. Accordingly, after the final cell packaging process (40), the battery manufacturing device (1) classifies the battery cell according to the grade in the classification process (50) and loads it into a buffer (S390).

[0130] At this time, the processor (110) sets up a battery cell group based on the simulation results (S400). The group data for the battery cell group is used in the module and pack assembly process (60).

[0131] The battery manufacturing device (1) ships and moves battery cells classified according to grade and assembles a battery module or battery pack (S410). Based on group data received from the classification control device (100), the battery manufacturing device (1) can assemble a battery module or battery pack by combining multiple battery cells.

[0132] According to the present invention, the thickness of the final cell package can be predicted and the battery cells classified according to the thickness so that the assembly process proceeds, thereby equalizing the thickness of the battery module or battery pack.

[0133] According to the present invention, the compression force of a battery module or battery pack composed of battery cells can be controlled, defective cells can be classified in advance to reduce the defect rate of battery cells, and the quality of the product can be improved.

[0134] As used herein, the term “part” may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. The “part” may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, the “part” may be implemented in the form of an Application-Specific Integrated Circuit (ASIC).

[0135] The implementations described herein may be implemented, for example, as methods or processes, devices, software programs, data streams, or signals. Even if discussed only in the context of a single form of implementation (e.g., discussed only as a method), the implementation of the discussed features may also be implemented in other forms (e.g., devices or programs). Devices may be implemented in appropriate hardware, software, and firmware, etc. Methods may be implemented in devices such as processors, which generally refer to processing devices including, for example, computers, microprocessors, integrated circuits, or programmable logic devices. Processors also include communication devices such as computers, cell phones, portable / personal digital assistants ("PDAs"), and other devices that facilitate the communication of information between end-users.

[0136] Although the present invention has been described above by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs. Explanation of the symbols

[0137] 1: Battery manufacturing device 10: Stack Process 20: Assembly Process 30: Cell packaging process 40: Final cell packaging process 50: Classification process 60: Module and Pack Assembly Process 70, 71, 72, 73: Measuring device 100: Classification control device 110 : Processor 120 : Memory 130 : Communications Department 170 : Input section 180 : Output section

Claims

Claim 1 A battery cell classification control device characterized by comprising: a communication unit that receives thickness data from a measuring device that measures the thickness of a battery cell; and a processor that calculates a predicted thickness by predicting the final thickness of the battery cell packaged based on the thickness data, sets a grade for each battery cell based on the predicted thickness, and controls the battery cell to be classified according to the grade when it is packaged. Claim 2 A battery cell classification control device according to claim 1, wherein the processor calculates the predicted thickness based on the thickness data measured in the stack process in which the separator, cathode sheet, and anode sheet are loaded. Claim 3 A battery cell classification control device according to claim 2, characterized in that the processor predicts the thickness of a primary packaged cell package based on the thickness data, and predicts the thickness of a final packaged cell package based on the predicted value to calculate the predicted thickness. Claim 4 A battery cell classification control device according to claim 2, wherein the processor analyzes data regarding the thickness in the stacking process of the battery cell, the thickness of the primary packaged cell package, and the thickness of the final packaged cell package to calculate a correlation equation, and calculates the predicted thickness according to the correlation equation. Claim 5 A battery cell classification control device according to claim 1, wherein the processor performs a simulation for assembling a battery module or battery pack by combining a plurality of battery cells of different thicknesses, and sets the combination of the plurality of battery cells as a battery cell group according to the result of the simulation. Claim 6 A battery cell classification control device according to claim 5, characterized in that the processor performs the simulation by combining a plurality of battery cells of different thicknesses so that the thickness of the battery module or the battery pack is equalized. Claim 7 A battery cell classification control device according to claim 5, wherein the processor enables battery cells to be assembled according to group data for the battery cell group in the assembly process of a battery module or battery pack. Claim 8 A battery cell classification control device according to claim 5, characterized in that the processor controls a battery cell expected to be defective during the simulation to be separated before packaging by setting it as a defective cell. Claim 9 A battery cell classification control device according to claim 1, characterized in that the processor determines the battery cell as a defective cell and controls it to be separated before packaging when the predicted thickness deviates from a set range. Claim 10 A battery cell classification control system characterized by comprising: a battery manufacturing device that performs a stacking process, a cell packaging process, a final cell packaging process, a classification process, and a module pack assembly process; and a classification control device that predicts the thickness of the battery cell after the final cell packaging process is completed based on the thickness of the battery cell measured in the stacking process, sets a grade for the battery cell according to the predicted thickness, and controls the battery cell to be classified according to the grade in the classification process. Claim 11 A battery cell classification control system according to claim 10, wherein the classification control device predicts the thickness of the battery cell after the cell packaging process is completed based on the thickness of the battery cell measured in the stacking process, and predicts the thickness of the battery cell after the final cell packaging process is completed based on the predicted value to calculate the predicted thickness. Claim 12 A battery cell classification control system according to claim 10, wherein the classification control device separates the battery cell as a defective cell when the predicted thickness of the battery cell deviates from a set range. Claim 13 A battery cell classification control system according to claim 10, wherein the classification control device sets a battery cell group by combining a plurality of battery cells with different thicknesses based on the predicted thickness, and controls the assembly of the battery cells according to group data for the battery cell group during the assembly process of the battery module or battery pack. Claim 14 A battery cell classification control method characterized by comprising: a step in which a processor receives thickness data from a measuring device that measures the thickness of a battery cell through a communication unit; a step in which the processor predicts the final thickness of the battery cell packaged based on the thickness data and calculates the predicted thickness; a step in which the processor sets a grade to the battery cell based on the predicted thickness; and a step in which the processor controls the battery cell to be classified according to the grade when the final packaging of the battery cell is completed. Claim 15 A battery cell classification control method according to claim 14, wherein the step of calculating the predicted thickness comprises: a step in which the processor predicts the thickness of a primary packaged cell package based on the thickness data; and a step in which the processor predicts the thickness of a final packaged cell package based on the predicted value and calculates the predicted thickness. Claim 16 A battery cell classification control method according to claim 14, further comprising: a step of, after the step of calculating the predicted thickness, the step of the processor performing a simulation of assembling a battery module or battery pack by combining a plurality of battery cells of different thicknesses based on the predicted thickness. Claim 17 A battery cell classification control method according to claim 16, characterized in that, in the step of performing the simulation, the processor performs the simulation by combining a plurality of battery cells of different thicknesses so that the thickness of the battery module or the battery pack is equalized. Claim 18 A battery cell classification control method according to the 16th, further comprising: a step of, after the step of performing the simulation, a step of the processor setting a battery cell expected to be defective during the simulation as a defective cell; a step of the processor setting a battery cell that falls outside a set range according to the predicted thickness as a defective cell; and a step of the processor controlling the separation of the defective cell before packaging. Claim 19 A battery cell classification control method according to claim 14, wherein, in the step of receiving the thickness data, the processor calculates the predicted thickness for the final packaged battery cell based on the thickness data measured in the stack process in which the separator, the cathode sheet, and the anode sheet are loaded.

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