Battery cell grading method and system based on OCV detection

Abstract

The invention provides a battery cell grading method and system based on OCV detection, and relates to the technical field of battery cell grading, and the method comprises the following steps: adjusting the spatial position of a battery cell tray, and carrying out battery cell feeding; performing code scanning on the battery cell of the operation platform, and reading capacity information; synchronously triggering a voltage internal resistance tester to execute a battery cell test; a grading rule is set, programmed configuration is carried out, a cell flow direction judgment unit is constructed, and MES data and test data are compared; and a grading execution instruction is generated based on the battery cell grading mark number, the mechanical arm is responded, the battery cells are transferred to a multi-stage grading channel, and the graded battery cells are subjected to conveying management and control. According to the invention, the technical problem in the prior art that the processing speed of a production line is limited due to the fact that the battery cells are carried and operated for many times in the feeding, detecting and grading transfer processes can be solved, and the technical goal of improving the grading efficiency and the classification accuracy of the battery cells is achieved; the technical effects of reducing frequent operation of the manipulator and improving the processing speed of a production line are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of battery cell binning, and in particular to a method and system for battery cell binning based on OCV detection. Background Art

[0002] During the battery cell production process, cell grading is a key step to ensure product quality and consistency, and is usually completed through automated equipment.

[0003] At present, the efficiency of existing battery cell binning technology is low. The process of battery cell loading, testing and binning transfer involves multiple handling and operations. The robot needs to frequently perform battery cell grabbing and moving operations, which limits the processing speed of the overall production line. For example, the processing of each battery cell may take a few seconds, and for mass production scenarios, this processing speed is difficult to meet the requirements of efficient production. In addition, the sensitivity and accuracy of the detection equipment may fluctuate in actual production, resulting in inaccurate classification of some battery cells, especially when the battery cell performance indicators are close to the binning critical value, the probability of misclassification will increase, which in turn affects the quality consistency of the finished product.

[0004] In summary, the prior art has technical problems in that, due to the multiple handling and operations involved in the process of loading, testing and grading transfer of battery cells, the robot frequently grasps and moves, which limits the processing speed of the overall production line, further affecting the production efficiency and the accuracy of battery cell classification in mass production scenarios, and ultimately affecting the quality consistency of the finished products. Summary of the invention

[0005] The purpose of the present application is to provide a method and system for cell grading based on OCV detection, so as to solve the technical problem in the prior art that due to the multiple handling and operations involved in the process of loading, testing and grading transfer of battery cells, the robot frequently grasps and moves the cells, the overall production line processing speed is limited, and the production efficiency and accuracy of battery cell classification in mass production scenarios are further affected, which ultimately affects the quality consistency of the finished products.

[0006] In view of the above problems, the present application provides a method and system for cell grading based on OCV detection.

[0007] In the first aspect, the present application provides a method for cell grading based on OCV detection, which is implemented through a system for cell grading based on OCV detection, including: controlling an electric lift, adjusting the spatial position of a cell tray and loading cells, wherein the loading position is an operating platform; scanning the cells on the operating platform through a cell grading machine, and reading capacity information based on MES as MES data; synchronously triggering a voltage internal resistance tester to perform cell testing and determine test data, wherein the test indicators at least include voltage, internal resistance and shell pressure; setting grading rules and performing programmatic configuration, constructing a cell flow direction judgment unit, comparing the MES data with the test data, and generating cell grading labels, wherein the grading rules are set based on an indicator interval; generating grading execution instructions based on the cell grading labels, and in response to a robot, transferring the cells to a multi-level grading channel to control the conveying of the grading cells.

[0008] In the second aspect, the present application also provides a system for cell grading based on OCV detection, which is used to execute a method for cell grading based on OCV detection as described in the first aspect, including: a cell loading module, the cell loading module is used to control the electric lift, adjust the spatial position of the cell tray and load the cells, wherein the loading position is the operating platform; a cell scanning module, the cell scanning module is used to scan the cells on the operating platform through the cell grading machine, and read the capacity information based on MES as MES data; a cell testing module, the cell testing module is used to synchronously trigger The voltage internal resistance tester performs battery cell testing and determines test data, wherein the test indicators at least include voltage, internal resistance and shell pressure; a battery cell grading module, wherein the battery cell grading module is used to set grading rules and perform programmatic configuration, construct a battery cell flow direction judgment unit, compare the MES data with the test data, and generate battery cell grading labels, wherein the grading rules are set based on the indicator interval; a battery cell transfer module, wherein the battery cell transfer module is used to generate grading execution instructions based on the battery cell grading labels, and in response to the robot arm, transfer the battery cells to the multi-level grading channels to control the transportation of the grading battery cells.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages: By controlling the electric lift, the spatial position of the battery tray is adjusted and the battery cells are loaded, wherein the loading position is the operating platform; the battery cells on the operating platform are scanned by the battery cell grading machine, and the capacity information is read based on the MES as the MES data; the voltage internal resistance tester is synchronously triggered to perform the battery cell test and determine the test data, wherein the test indicators at least include voltage, internal resistance and shell pressure; the grading rules are set and programmed configuration is performed, a battery cell flow direction judgment unit is constructed, the MES data and the test data are compared, and the battery cell grading label is generated, wherein the grading rules are set based on the indicator interval; a grading execution instruction is generated based on the battery cell grading label, and in response to the robot, the battery cells are transferred to the multi-level grading channel, and the grading battery cells are transported and controlled, so as to achieve the technical goal of improving the efficiency of battery cell grading and the accuracy of classification, and achieve the technical effect of reducing the frequent operation of the robot, improving the processing speed of the production line, and ensuring that the battery cell classification is more accurate, thereby improving the consistency of the quality of the finished product.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 A schematic diagram of a flow chart of a method for cell grading based on OCV detection in this application; Figure 2 This is a structural schematic diagram of a system for cell grading based on OCV detection in the present application.

[0013] Description of reference numerals: Battery cell loading module 11, battery cell scanning module 12, battery cell testing module 13, battery cell grading module 14, battery cell transfer module 15. DETAILED DESCRIPTION

[0014] This application provides a method and system for cell grading based on OCV detection, which solves the technical problem in the prior art that due to the multiple handling and operations involved in the process of loading, testing and grading transfer of cells, the robot frequently grabs and moves, which limits the processing speed of the overall production line, further affecting the production efficiency and accuracy of cell classification in mass production scenarios, and ultimately affecting the quality consistency of the finished product. The technical goal of improving the efficiency and accuracy of cell grading is achieved, and the technical effect of reducing the frequent operation of the robot, increasing the processing speed of the production line, and ensuring more accurate cell classification, thereby improving the quality consistency of the finished product, is achieved.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] For example, please refer to the attached Figure 1 The present application provides a method for cell grading based on OCV detection, which is applied to a system for cell grading based on OCV detection, and specifically includes: Step 1: Control the electric lift, adjust the spatial position of the battery tray and load the battery cells, where the loading position is the operating platform.

[0017] Specifically, OCV refers to the voltage across the battery cell when no external current flows through it, and is usually used to measure the charge and discharge state of the battery cell. An electric lift is used to control the position of the battery cell tray, and its height is adjusted by moving the tray up and down to facilitate subsequent loading. Loading refers to the process of transferring the battery cell from a storage location to an operating platform, where the operating platform is the working area for actual sorting operations. For example, an electric lift can raise the tray from an initial position of 50 cm from the ground to 1 meter, making it easier to place the battery cells on the tray and sort the battery cells into different grades according to the open circuit voltage value.

[0018] Step 2: Scan the battery cells on the operating platform through the battery cell classifier, and read the capacity information based on MES as MES data.

[0019] Specifically, the battery cell grading machine first scans the battery cells on the operating platform. Scanning is to identify the unique identification information of the battery cell by reading the barcode or QR code affixed to the surface of the battery cell. For example, the barcode may contain a 12-digit serial number to track the production and performance records of the battery cell. Subsequently, the capacity information of the battery cell is read based on the manufacturing execution system (MES) as MES data. MES is a system for managing and tracking the production process. The capacity information refers to the amount of electricity that the battery cell can store, usually in ampere-hours. For example, the capacity of the battery cell can be 2.5 ampere-hours. This capacity information is stored in the system as part of the MES data for subsequent analysis and traceability to ensure that the performance and quality of the battery cell meet the requirements.

[0020] Step 3: Synchronously trigger the voltage internal resistance tester to perform the battery cell test and determine the test data, wherein the test indicators at least include voltage, internal resistance and case pressure.

[0021] Specifically, the synchronous trigger voltage internal resistance tester is used to perform battery cell testing. The test process starts multiple test items at the same time through a trigger signal to determine the test data. The purpose of battery cell testing is to evaluate the key performance indicators of the battery cell. The test data is the result obtained by measuring different parameters, including voltage, internal resistance and shell pressure. Voltage refers to the potential difference between the two ends of the battery cell, internal resistance refers to the resistance to the flow of current inside the battery cell, and shell pressure refers to the physical pressure or force of the battery cell shell.

[0022] Step 4: Set the grading rules and perform programmatic configuration, build a cell flow direction judgment unit, compare the MES data with the test data, and generate cell grading labels, wherein the grading rules are set based on the indicator interval.

[0023] Specifically, setting the grading rules means formulating classification standards according to the different performance of the battery cells, and dividing the performance indicators of the battery cells into multiple intervals. For example, the voltage of the battery cell can be set between 3.6 volts and 3.7 volts as one level, and between 3.7 volts and 3.8 volts as another level. After the grading rules are set, the classification process is automatically executed through programmed configuration. Constructing a battery cell flow direction judgment unit means establishing a module for analyzing battery cell data and determining its classification. The battery cell flow direction judgment unit compares the capacity data in the MES system with the voltage, internal resistance and other test data obtained by the test instrument to generate the grading label of the battery cell. For example, if the battery cell voltage is 3.65 volts, the internal resistance is 40 milliohms, and the capacity is 2.6 ampere hours, the battery cell is marked as the third level. Finally, the grading label is generated according to the set indicator interval to identify the classification to which the battery cell belongs.

[0024] Step 5: Generate a binning execution instruction based on the cell binning label, transfer the cell to a multi-level binning channel in response to the robot, and perform transportation control on the binned cell.

[0025] Specifically, a binning execution instruction is generated based on the cell binning label, and a command for executing the classification action is automatically generated according to the result of the cell being classified. For example, if a cell is marked as the third bin, an instruction is generated to send the cell to the storage location of the third bin. Subsequently, in response to the action of the manipulator, which is an automated device for grabbing and moving cells, the cell will be transferred from the operating platform to the designated multi-level binning channel according to the binning execution instruction. The multi-level binning channel is a channel system for receiving and guiding cells of different grades, and each channel corresponds to a specific cell grade. For example, cells of the first bin may be sent to the first channel, and cells of the third bin may be sent to the third channel. Finally, the transportation control of binned cells refers to ensuring the smooth movement and management of cells in the binning channels by controlling the conveying equipment.

[0026] The method for cell grading based on OCV detection is applied to a system for cell grading based on OCV detection, which can achieve the technical goal of improving cell grading efficiency and classification accuracy, and achieve the technical effect of reducing frequent operation of the robot, increasing the processing speed of the production line, and ensuring more accurate cell classification, thereby improving the consistency of finished product quality.

[0027] Furthermore, the present application also includes: Based on the ejection cylinder, the graded battery cells are pushed out to the graded docking wires; the graded battery cell numbers are identified, and the graded docking wires connect the graded battery cells to the multi-level graded channels, wherein the multi-level graded channels correspond one to one to the battery cell graded numbers.

[0028] Specifically, a push-out cylinder device is used to push the sorted cells from their current position and onto the graded conveyor line. A cylinder is a mechanical device that pushes a piston rod out or back out through air pressure. For example, a cylinder may push cells from the operating platform to the graded docking line at a speed of 5 cm per second.

[0029] Identifying the cell binning number refers to automatic identification based on the binning number attached to the cell, which indicates which category the cell belongs to. For example, the cell may be labeled as the third bin, indicating that it needs to be directed to a specific channel. The binning docking wire connects the binned cells to the multi-level binning channels, which means that the binning docking wire is used as a transmission path to send the cells to the corresponding channels according to their labels. The multi-level binning channel is a shunt path for processing cells of different grades, and each channel corresponds to a specific cell number, for example, the first channel corresponds to the first-level cell, and the third channel corresponds to the third-level cell.

[0030] The sorted battery cells are pushed from the operating platform to the transmission line through mechanical force. After the battery cell's grading number is identified, the grading docking line will send the battery cells into the corresponding multi-level grading channels according to the number. Each channel corresponds to a specific grade one by one to achieve accurate classification.

[0031] Furthermore, the present application also includes: Receive real-time group matching information, monitor the grading channel cache in real time, and make group matching gear determination, wherein the real-time group matching information is determined based on the needs of the battery assembly end; if it does not belong to the group matching gear, it is marked as a redundant gear battery cell.

[0032] Specifically, receiving real-time matching information means obtaining the latest demand information from the battery assembly end, and the matching information is used to determine the classification requirements and quantity requirements of the battery cells. For example, the battery assembly end may need 100 battery cells with a capacity of 2.5 ampere hours as real-time matching information. Subsequently, the grading channel cache is monitored in real time based on the information. Monitoring the cache means checking the number and status of the battery cells currently stored in each grading channel to ensure that the matching requirements are met. For example, if there are already 90 battery cells in a channel, continue to monitor to replenish the required 10.

[0033] The determination of the grouping position refers to judging whether there are cells that meet the assembly requirements in the current channel based on the grouping information and the status of the cells in the binned channel. For example, if the requirement is a 2.5 ampere-hour cell, it is determined whether a channel contains cells that meet the requirement. The grouping position is the cell level that directly corresponds to the battery assembly requirement, and only cells that meet the requirement will be assigned to the corresponding assembly task.

[0034] If it does not belong to the matching position, it is marked as redundant position cells. When some cells do not meet the current matching requirements, they are marked as redundant position cells. Excess position cells are those that do not meet the current assembly requirements but still exist in the binning channel. For example, if a 2.5Ah cell is currently required, and there is a 2.7Ah cell in a certain channel, the 2.7Ah cell will be marked as a redundant position cell for subsequent processing.

[0035] By receiving real-time matching information from the battery assembly end and monitoring the number of cells in the binning channel in real time, the matching position is determined by comparing the matching information and the cell status in the channel to determine which cells meet the assembly requirements. If some cells do not meet the current matching position requirements, they will be marked as redundant cells for subsequent processing or adjustment.

[0036] Furthermore, the present application also includes: If it belongs to the grouping gear, a channel transfer instruction is generated based on the real-time grouping information, wherein the channel transfer instruction is the execution information of the cell transfer from the grading channel to the straight conveying channel, and there are grading levels and cell quantity marks; based on the channel transfer instruction, the manipulator is controlled to transfer the cached cells in the grading channel to the branch conveying channel, one end of the branch conveying channel is connected to the grading channel, and the other end is connected to the battery assembly end.

[0037] Specifically, when the cell's position meets the requirements of battery assembly, an instruction is generated based on the latest assembly information to instruct the cell to be transferred from the current binning channel to the linear conveying channel. For example, the cells in the third bin (capacity of 2.5 ampere hours) are transferred from the binning channel to the linear conveying channel, including the binning level and cell quantity markings of the cells, and 50 cells in the third bin are transferred.

[0038] The channel transfer instruction not only contains the path of the cell transfer, but also records in detail the cell classification level and the number of cells to be transferred. For example, the transfer instruction can include "transfer 50 cells of the third batch from the binning channel 1 to the straight conveying channel" to ensure the accuracy of the execution process.

[0039] After receiving the transfer instruction, the robot is activated to perform the work of moving the battery cells. The robot is an automated device that can grab the battery cells and move them from one location to another. For example, the robot will grab 50 battery cells and move them from the grading channel to the branch conveying channel.

[0040] According to the transfer instruction, the manipulator moves the cells in the binning channel to the branch conveying channel. One end of the branch conveying channel is connected to the binning channel, and the other end is connected to the battery assembly end, indicating that the cells will eventually be transported to the battery assembly area after passing through the branch conveying channel. For example, the branch conveying channel can transport cells from the binning area to the battery assembly end at a speed of 10 cm per second to ensure timely supply of assembly needs.

[0041] By generating channel transfer instructions, the cell classification level and quantity are clarified, and the cells are instructed to be transferred from the classification channel to the linear conveying channel. Then, the robot is controlled to transfer the cells from the classification channel to the branch conveying channel, and the cells are transferred to the battery assembly end through the branch conveying channel to ensure that the cells that meet the requirements can be used for assembly in a timely manner.

[0042] Furthermore, the present application also includes: A grading channel cache threshold is set, wherein the multi-level grading channel includes multi-level good product grading channels and defective product grading channels, and the grading channel cache threshold is used to determine whether the number of battery cells on the grading channel has reached an upper limit; if the number of battery cells in the grading channel is less than the grading channel cache threshold, the grading battery cells are cached to the grading channel; if the number of battery cells in the grading channel is greater than the grading channel cache threshold, the offline battery cells are located and transferred to the unloading position for offline processing, wherein the offline battery cells are battery cells whose number exceeds the limit constrained by the grading channel cache threshold.

[0043] Specifically, a maximum upper limit on the number of cells that can be stored is set for each binning channel, called a cache threshold, which is used to determine whether the number of cells on the binning channel has reached or exceeded the upper limit. For example, the cache threshold of a multi-level binning channel can be set to 100 cells, and when this number is exceeded, offline processing will be triggered. The binning channels include multi-level good binning channels and defective binning channels. The good channels are used to store cells that meet quality requirements, and the defective channels are used to store cells that have not passed the inspection.

[0044] If the number of cells in a binning channel is less than the binning channel cache threshold, and the number of cells stored in the binning channel has not reached the upper limit, the classified cells will continue to be cached in the channel. For example, if the cache threshold of a good binning channel is 100 cells, and 80 cells are currently stored, then the newly binned cells will continue to be stored in the channel until the upper limit of 100 is reached.

[0045] If the number of cells in the binning channel is greater than the buffer threshold of the binning channel, offline processing is started, that is, the cells that exceed the buffer upper limit are located and transferred to the unloading position for processing. The unloading position is an area dedicated to processing excess cells. Offline cells refer to excess cells that exceed the buffer threshold of the binning channel. For example, when the threshold of the binning channel is 100 cells, but there are now 120 cells, the extra 20 cells will be located as offline cells and transferred to the unloading position for processing.

[0046] By setting a buffer threshold for each bin channel, the maximum number of cells that can be stored is controlled. If the number of cells in a channel is lower than the threshold, the cells will continue to be buffered in the channel; if the number of cells exceeds the threshold, the excess cells will be marked as offline cells and transferred to the unloading position for processing by mechanical equipment.

[0047] Furthermore, the present application also includes: If the cached cells of the defective binning channel meet the buffer threshold of the binning channel, a material unloading warning message is generated.

[0048] Specifically, if the cached cells of the defective binning channel meet the cache threshold of the binning channel, this state will be detected when the number of cells in the defective binning channel reaches the previously set maximum cache value. For example, assuming that the cache threshold of the defective binning channel is set to 50 cells, when 50 defective cells have been stored in the channel, it will be judged that the cache is full, and then the unloading warning information will be generated, that is, a warning signal will be issued to remind the operator or the automatic system to unload the material. The unloading warning information contains the details of the reminder, such as the defective binning channel is full and unloading operations are required, etc., to help deal with defective products in a timely manner and avoid channel overload.

[0049] By automatically generating unloading warning information, the operator or system is reminded to handle defective battery cells, ensuring that defective products are promptly transferred out of the channel for subsequent processing.

[0050] Furthermore, the present application also includes: The calculation formula for the bin channel buffer threshold is as follows: ;in, The total time (in seconds) to complete one loading, inspection, and transfer to the buffer of the binning channel. is the number of cells in each string in a module, is the production line efficiency, that is, the time required to process each battery cell (unit: seconds / cell), Used for each string of cells in a module The number of gears, 1.5 is the buffer coefficient, wherein one module is the real-time matching information at a preset time interval.

[0051] Specifically, in order to ensure that the binned channels can operate efficiently when caching cells, general rules for calculating the cache threshold are formulated to ensure that different factors are taken into consideration, thereby providing a reasonable upper limit setting for the channel's cell cache.

[0052] in, Indicates the total time to complete a loading, testing, and transfer to the binning channel cache, measured in seconds. For example, if the entire process from cell loading to binning into the cache channel takes 60 seconds, then This is equal to 60 seconds, including the running time of all automated processes to ensure the smooth connection of the entire production process.

[0053] Indicates the number of cells in each string in a module, that is, the number of cells a module contains. For example, a module may contain 12 cells, then Equal to 12. A module refers to a batch processing unit that runs based on the group information within a certain time interval.

[0054] Indicates the production line efficiency in seconds per cell, which refers to the time required to process each cell. For example, if it takes 3 seconds to process each cell, then This is equal to 3 seconds per battery cell, including the inspection and grading process, which is a key factor affecting the overall efficiency of the production line.

[0055] Indicates that a module is used The number of cells in the gear, The gear refers to the specific classification of the battery cells. For example, in a module with 12 batteries, suppose 4 of them are classified as gear position, then Equal to 4, reflecting the distribution of battery cells in different bins.

[0056] 1.5 is the buffer factor, which means that when calculating the buffer threshold, a 50% buffer is added to cope with uncertainty or production fluctuations. For example, if the calculated battery cell buffer is 100, the final buffer threshold will be multiplied by 1.5, resulting in 150.

[0057] One module processes the battery cell grouping requirements according to the real-time grouping information at the preset time interval. The grouping information includes the number of battery cells in each batch on the production line and their classification requirements, which will affect the calculation of the cache threshold.

[0058] The total time of loading, testing and transportation, the number of cells in a module, the efficiency of handling cells and the The distribution of gears, plus a buffer coefficient of 1.5, ensures the smooth operation of the production process.

[0059] In summary, the method for cell grading based on OCV detection provided by the present application has the following technical effects: By controlling the electric lift, the spatial position of the battery tray is adjusted and the battery cells are loaded, wherein the loading position is the operating platform; the battery cells on the operating platform are scanned by the battery cell grading machine, and the capacity information is read based on the MES as the MES data; the voltage internal resistance tester is synchronously triggered to perform the battery cell test and determine the test data, wherein the test indicators at least include voltage, internal resistance and shell pressure; the grading rules are set and programmed configuration is performed, a battery cell flow direction judgment unit is constructed, the MES data and the test data are compared, and the battery cell grading label is generated, wherein the grading rules are set based on the indicator interval; a grading execution instruction is generated based on the battery cell grading label, and in response to the robot, the battery cells are transferred to the multi-level grading channel, and the grading battery cells are transported and controlled, so as to achieve the technical goal of improving the efficiency of battery cell grading and the accuracy of classification, and achieve the technical effect of reducing the frequent operation of the robot, improving the processing speed of the production line, and ensuring that the battery cell classification is more accurate, thereby improving the consistency of the quality of the finished product.

[0060] Embodiment 2: Based on the method of cell grading based on OCV detection in the above embodiment, and with the same inventive concept, the present application also provides a system for cell grading based on OCV detection, as shown in the attached Figure 2 ,include: A cell loading module 11, the cell loading module 11 is used to control the electric lift, adjust the spatial position of the cell tray and load the cells, wherein the loading position is the operating platform; a cell code scanning module 12, the cell code scanning module 12 is used to scan the cells on the operating platform through the cell classifier, and read the capacity information based on the MES as the MES data; a cell testing module 13, the cell testing module 13 is used to synchronously trigger the voltage internal resistance tester to perform the cell test and determine the test data, wherein the test index is up to At least including voltage, internal resistance and shell pressure; a battery cell grading module 14, the battery cell grading module 14 is used to set grading rules and perform programmatic configuration, build a battery cell flow direction judgment unit, compare the MES data with the test data, and generate battery cell grading labels, wherein the grading rules are set based on the indicator interval; a battery cell transfer module 15, the battery cell transfer module 15 is used to generate grading execution instructions based on the battery cell grading labels, and transfer the battery cells to the multi-level grading channels in response to the manipulator, so as to control the transportation of the grading battery cells.

[0061] Furthermore, the system for cell grading based on OCV detection is also used for: Based on the ejection cylinder, the graded battery cells are pushed out to the graded docking wires; the graded battery cell numbers are identified, and the graded docking wires connect the graded battery cells to the multi-level graded channels, wherein the multi-level graded channels correspond one to one to the battery cell graded numbers.

[0062] Furthermore, the system for cell grading based on OCV detection is also used for: Receive real-time group matching information, monitor the grading channel cache in real time, and make group matching gear determination, wherein the real-time group matching information is determined based on the needs of the battery assembly end; if it does not belong to the group matching gear, it is marked as a redundant gear battery cell.

[0063] Furthermore, the system for cell grading based on OCV detection is also used for: If it belongs to the grouping gear, a channel transfer instruction is generated based on the real-time grouping information, wherein the channel transfer instruction is the execution information of the cell transfer from the grading channel to the straight conveying channel, and there are grading levels and cell quantity marks; based on the channel transfer instruction, the manipulator is controlled to transfer the cached cells in the grading channel to the branch conveying channel, one end of the branch conveying channel is connected to the grading channel, and the other end is connected to the battery assembly end.

[0064] Furthermore, the system for cell grading based on OCV detection is also used for: A grading channel cache threshold is set, wherein the multi-level grading channel includes multi-level good product grading channels and defective product grading channels, and the grading channel cache threshold is used to determine whether the number of battery cells on the grading channel has reached an upper limit; if the number of battery cells in the grading channel is less than the grading channel cache threshold, the grading battery cells are cached to the grading channel; if the number of battery cells in the grading channel is greater than the grading channel cache threshold, the offline battery cells are located and transferred to the unloading position for offline processing, wherein the offline battery cells are battery cells whose number exceeds the limit constrained by the grading channel cache threshold.

[0065] Furthermore, the system for cell grading based on OCV detection is also used for: If the cached cells of the defective binning channel meet the buffer threshold of the binning channel, a material unloading warning message is generated.

[0066] Furthermore, the system for cell grading based on OCV detection is also used for: The calculation formula for the bin channel buffer threshold is as follows: ;in, The total time (in seconds) to complete one loading, inspection, and transfer to the buffer of the binning channel. is the number of cells in each string in a module, is the production line efficiency, that is, the time required to process each battery cell (unit: seconds / cell), Used for each string of cells in a module The number of gears, 1.5 is the buffer coefficient, wherein one module is the real-time matching information at a preset time interval.

[0067] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The method for cell grading based on OCV detection and the specific examples in the aforementioned embodiment 1 are also applicable to the system for cell grading based on OCV detection in this embodiment. Through the aforementioned detailed description of the method for cell grading based on OCV detection, those skilled in the art can clearly understand the system for cell grading based on OCV detection in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0068] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0069] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A method for cell grading based on OCV detection, characterized in that the method include: Control the electric lift, adjust the space position of the battery tray and load the battery, where the loading position is the operating platform; Scan the battery cells on the operating platform through the battery cell classifier, and read the capacity information based on MES as MES data; The voltage internal resistance tester is synchronously triggered to perform a cell test to determine test data, wherein the test index at least includes voltage, internal resistance and case pressure; Setting the binning rules and performing programmatic configuration, constructing a cell flow direction judgment unit, comparing the MES data with the test data, and generating cell binning labels, wherein the binning rules are set based on the indicator interval; A binning execution instruction is generated based on the battery cell binning label, and in response to the robot arm, the battery cells are transferred to the multi-level binning channels to perform transportation control on the binned battery cells.

2. A method for cell grading based on OCV detection as claimed in claim 1, characterized in that: Transfer cells to multi-level binning channels, including: Based on the push-out cylinder, the graded battery cells are pushed out to the graded docking lines; The cell binning numbers are identified, and the binning docking wires connect the binned cells to the multi-level binning channels, wherein the multi-level binning channels correspond to the cell binning numbers one by one.

3. A method for cell grading based on OCV detection as claimed in claim 1, characterized in that: Control the transportation of graded cells, including: Receive real-time group matching information, monitor the grading channel cache in real time, and make group matching gear position determination, wherein the real-time group matching information is determined based on the needs of the battery assembly end; If it does not belong to the matching position, it is marked as a redundant position battery cell.

4. A method for cell grading based on OCV detection as claimed in claim 3, characterized in that: The method also includes: If it belongs to the grouping gear, a channel transfer instruction is generated based on the real-time grouping information, wherein the channel transfer instruction is the execution information of the cell transfer from the grading channel to the straight conveying channel, and there are grading levels and cell quantity marks; Based on the channel transfer instruction, the robot is controlled to transfer the cache cells in the grading channel to the branch conveying channel, one end of the branch conveying channel is connected to the grading channel, and the other end is connected to the battery assembly end.

5. A method for cell grading based on OCV detection as claimed in claim 3, characterized in that: Real-time monitoring of the binned channel cache includes: Setting a binning channel cache threshold, wherein the multi-level binning channel includes a multi-level good product binning channel and a defective product binning channel, and the binning channel cache threshold is used to determine whether the number of cells on the binning channel has reached an upper limit; If the number of cells in the binning channel is less than the binning channel cache threshold, the binning cells are cached to the binning channel; If the number of battery cells in the binning channel is greater than the binning channel cache threshold, the offline battery cells are located and transferred to the unloading position for offline processing, wherein the offline battery cells are battery cells whose number exceeds the limit constrained by the binning channel cache threshold.

6. A method for cell grading based on OCV detection as claimed in claim 5, characterized in that: If the cached cells of the defective binning channel meet the buffer threshold of the binning channel, a material unloading warning message is generated.

7. A method for cell grading based on OCV detection as claimed in claim 5, characterized in that: The step of setting the buffer threshold of the binned channel includes: The calculation formula for the bin channel buffer threshold is as follows: ; in, The total time (in seconds) to complete one loading, inspection, and transfer to the grading channel cache. is the number of cells in each string in a module, is the production line efficiency, that is, the time required to process each battery cell (unit: seconds / cell), Used for each string of cells in a module The number of gears, 1.5 is the buffer coefficient, wherein one module is the real-time matching information at a preset time interval.

8. A system for cell grading based on OCV detection, characterized in that: The steps for implementing the method for cell grading based on OCV detection as described in any one of claims 1 to 7 include: A cell loading module, which is used to control the electric lift, adjust the spatial position of the cell tray and load the cells, wherein the loading position is an operating platform; A battery cell scanning module, which is used to scan the battery cells of the operating platform through a battery cell classifier, and read the capacity information based on MES as MES data; A cell test module, the cell test module is used to synchronously trigger the voltage internal resistance tester to perform cell testing and determine test data, wherein the test indicators at least include voltage, internal resistance and shell pressure; A cell binning module, the cell binning module is used to set binning rules and perform program configuration, construct a cell flow direction judgment unit, compare the MES data with the test data, and generate cell binning labels, wherein the binning rules are set based on the index interval; A cell transfer module is used to generate a binning execution instruction based on the cell binning label, transfer the cell to a multi-level binning channel in response to the manipulator, and perform transportation control on the binned cell.

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