Battery capacity grading method, electronic equipment and storage medium

Abstract

The invention discloses a battery capacity grading method, electronic equipment and a storage medium. The method comprises the following steps: obtaining the production line capacity grading capacity after capacity grading of a battery cell to be subjected to capacity grading and the battery cell temperature during capacity grading; based on a preset mapping relation between temperature and capacity, calculating a capacity compensation value of the battery cell to be subjected to capacity grading, the capacity compensation value being determined based on a capacity difference between a first capacity corresponding to a preset standard temperature in the mapping relation and a second capacity corresponding to the battery cell temperature in the mapping relation; and based on the capacity compensation value and the production line capacity grading capacity, determining the target capacity grading capacity of the battery cell to be subjected to capacity grading. The capacity grading capacity of the production line is compensated through the temperature of the battery cells, and the accuracy of capacity grading can be improved, so that the distribution range of the capacity grading capacity is reduced, and the matching rate of the battery cells is improved.

Description

Technical Field

[0001] This application relates to the field of battery capacity testing technology, specifically to a battery capacity testing method, electronic device, and storage medium. Background Technology

[0002] In battery production lines, batteries need to be capacity-tested. Only batteries whose measured capacity meets or exceeds the design capacity are considered qualified; batteries with a capacity less than the design capacity are considered unqualified. Capacity testing helps to screen out qualified batteries.

[0003] However, when batteries are currently being categorized by capacity, the capacity of different batteries varies greatly, and an overly wide distribution of capacity will lead to a decrease in the matching rate. Summary of the Invention

[0004] This application provides a battery capacity assessment method, electronic device, and storage medium. By using cell temperature to compensate for the capacity assessment on the production line, the accuracy of capacity assessment can be improved, thereby reducing the distribution difference of capacity assessment and improving the cell matching rate.

[0005] On one hand, embodiments of this application provide a battery capacity testing method, the method comprising: Obtain the capacity of the battery cell after capacity grading on the production line and the cell temperature during capacity grading; Based on a preset mapping relationship between temperature and capacity, the capacity compensation value of the cell to be rated is calculated. The capacity compensation value is determined based on the capacity difference between the first capacity corresponding to the preset standard temperature in the mapping relationship and the second capacity corresponding to the cell temperature in the mapping relationship. Based on the capacity compensation value and the capacity allocation capacity of the production line, the target capacity allocation capacity of the battery cell to be allocated is determined.

[0006] On the other hand, embodiments of this application provide an electronic device, which includes a processor and a memory. The memory stores a computer program, and the processor executes the battery capacity assessment method as described in any of the above embodiments by calling the computer program stored in the memory.

[0007] On the other hand, embodiments of this application provide a computer-readable storage medium storing a computer program adapted for loading by a processor to execute the battery capacity assessment method as described in any of the above embodiments.

[0008] The battery capacity testing method, electronic device, and storage medium provided in this application embodiment obtain the cell temperature during capacity testing when obtaining the production line capacity testing. Since the temperature of different cells during capacity testing may be different, the production line capacity testing obtained by the capacity testing may be different even if the actual capacity of two cells is the same. Therefore, to avoid the impact of temperature on capacity testing, one approach is to strictly control the temperature of each cell during capacity testing to ensure that the cell temperatures are basically consistent. However, this leads to reduced testing efficiency and higher costs. Since the effect of temperature on capacity follows a pattern, a pre-established mapping relationship between temperature and capacity can be used to determine the capacity at different temperatures. After obtaining the cell temperature of the cell to be tested, the required capacity compensation value (e.g., calculating the difference between the capacity at the standard temperature and the cell temperature) can be determined based on this mapping relationship. Finally, the target capacity is calculated using the capacity compensation value and the production line's capacity testing capacity. This ensures that each cell to be tested receives the corresponding capacity at the standard temperature, reducing the distribution variation in capacity testing and improving cell matching efficiency. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram of an example battery production system provided in an embodiment of this application.

[0011] Figure 2 This is a schematic diagram of the first process of the battery capacity testing method provided in the embodiments of this application.

[0012] Figure 3 This is a schematic diagram of the second process of the battery capacity testing method provided in the embodiments of this application.

[0013] Figure 4 This is a schematic diagram of the third process of the battery capacity testing method provided in the embodiments of this application.

[0014] Figure 5 This is a schematic diagram of the fourth process of the battery capacity testing method provided in the embodiments of this application.

[0015] Figure 6 This is a schematic diagram of the battery capacity testing device provided in an embodiment of this application.

[0016] Figure 7This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] This application provides a battery capacity testing method, apparatus, storage medium, device, and program product. Specifically, the battery capacity testing method of this application can be executed by an electronic device, which can be a terminal or server, etc.

[0019] The terminal can be a smartphone, tablet, laptop, smart TV, wearable smart device, smart vehicle terminal, etc. The terminal can also include a client, which can be a game client, browser client, instant messaging client, or mini-program, etc.

[0020] A server can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0021] It should be noted that in the embodiments of this application, the execution subject of the battery capacity grading method can be a terminal device or a server. The embodiments of this application do not limit the type of execution subject.

[0022] It is understood that in the specific implementation of this application, user object data, context data and other related data are involved. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0023] For example, in conjunction with the above description, Figure 1This application illustrates a battery production system 1000 for implementing a battery capacity grading method. The battery production system 1000 may include at least one terminal 1001, at least one server 1002, at least one database 1003, and a network. The terminal 1001 can connect to different servers via the network. The terminal can be any device with computing hardware capable of supporting and executing software applications corresponding to games.

[0024] For example, terminal 1001 can be a capacity testing cabinet. During capacity testing, the cabinet continuously collects the cell temperature of the cells to be tested and uploads it to server 1002 via the network, storing it in database 1003. Server 1002 can calculate the target capacity of the cells to be tested based on the collected cell temperatures.

[0025] Furthermore, when the battery production system 1000 includes multiple terminals, multiple servers, and multiple networks, different terminals can connect to each other through different networks and servers. The network can be a wireless network or a wired network; for example, wireless networks include Wi-Fi, LAN, cellular networks, 2G networks, 3G networks, 4G networks, and 5G networks. Additionally, different terminals can also connect to other terminals or servers using their own Bluetooth networks or hotspot networks. Furthermore, the system 100 can include multiple databases coupled to different servers, and can continuously store game-related information in the databases while different users are playing multiplayer games online.

[0026] It should be noted that, Figure 1 The schematic diagram of the battery production system shown is merely an example. The battery production system 1000 described in this application embodiment is intended to more clearly illustrate the technical solutions of this application embodiment and does not constitute a limitation on the technical solutions provided in this application embodiment. As those skilled in the art will know, with the evolution of battery production systems and the emergence of new business scenarios, the technical solutions provided in this application embodiment are also applicable to similar technical problems.

[0027] The technical solution of this application will be described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0028] Please see Figure 2 It should be noted that the steps shown may be performed in a logical order different from that shown in the flowchart. The battery capacity grading method of this application may include the following steps: Step 011: Obtain the capacity of the battery cell to be capacity-graded after capacity grading and the cell temperature during capacity grading.

[0029] Among them, the cells to be tested are those that have entered the testing cabinet but have not yet undergone testing.

[0030] Among them, capacity testing is the core capacity detection and grading process in battery production. Through standardized charge and discharge cycles, it accurately obtains key performance parameters such as actual cell capacity, internal resistance, and voltage, ultimately achieving the goal of "eliminating defective products and improving the assembly rate through grading". It is a key link to ensure the consistency and reliability of battery packs after assembly.

[0031] In one optional embodiment, the capacity grading test can be performed through multiple charge-discharge cycles. During each charge cycle, the battery can be activated by sequentially performing constant current and constant voltage charging, followed by a period of rest, and then constant current discharging at different discharge rates. After multiple charge-discharge cycles, constant current charging and constant voltage charging are performed again to complete the capacity grading test.

[0032] Among them, cell temperature is a core indicator affecting its performance, lifespan and safety. Especially in scenarios such as capacity testing and charging / discharging, temperature fluctuations will directly change the chemical activity of the cell, thereby affecting its capacity.

[0033] In one optional embodiment, cell temperature detection involves real-time acquisition of surface or internal temperature data of the cell using a dedicated sensor. For example, a temperature probe / thermometer (NTC / Positive Temperature Coefficient, PTC) can be used: directly attached to the cell surface (tab or casing). NTC probes are commonly used in capacity testing cabinets, offering fast response (≤1 second) and accuracy of ±0.5℃-±1℃, enabling real-time capture of temperature changes during charging and discharging.

[0034] In one optional embodiment, the cell temperature is determined based on the average of multiple temperature data collected by a corresponding temperature detection device (such as an NTC probe) in the capacity testing cabinet during the capacity testing process. This avoids temperature fluctuations affecting the accuracy of capacity testing compensation.

[0035] The production line capacity test refers to the capacity determined after the capacity test is conducted in the capacity testing cabinet. At this point, the capacity is affected by the cell temperature and fluctuates significantly.

[0036] Step 012: Based on the preset mapping relationship between temperature and capacity, calculate the capacity compensation value of the cell to be rated. The capacity compensation value is determined based on the capacity difference between the first capacity corresponding to the preset standard temperature in the mapping relationship and the second capacity corresponding to the cell temperature in the mapping relationship.

[0037] The preset mapping relationship between temperature and capacity refers to the nonlinear functional relationship between temperature and capacity, where temperature is the independent variable and capacity is the dependent variable.

[0038] This mapping relationship can be established by calibrating the capacity of the cells in advance at different cell temperatures to obtain an accurate calibrated capacity. Then, based on the calibrated capacity corresponding to different cell temperatures, the mapping relationship between cell temperature and capacity can be constructed.

[0039] The capacity compensation value refers to the capacity that needs to be compensated when the cell to be rated for capacity changes from its current cell temperature to the standard temperature.

[0040] Therefore, based on this mapping relationship, the first capacity corresponding to the standard temperature in the mapping relationship can be calculated first, then the second capacity corresponding to the cell temperature of the cell to be rated can be calculated in the mapping relationship, and then the capacity difference between the first capacity and the second capacity can be calculated to determine the capacity compensation value.

[0041] Step 013: Based on the capacity compensation value and the production line capacity allocation, determine the target capacity allocation for the cells to be allocated.

[0042] The target capacity is the capacity of the cell to be compensated for under standard temperature.

[0043] After obtaining the production line capacity allocation and the capacity compensation value, the capacity compensation value can be used to compensate the production line capacity allocation, thereby obtaining the target capacity allocation of the battery cells to be allocated.

[0044] In one alternative embodiment, the target capacity can be calculated using the following formula: C 目标 =C 产线 + (C1-C2), where C 目标 For the target capacity, C 产线 The production line is divided into different capacities. C1 is the first capacity at standard temperature, and C2 is the second capacity at cell temperature.

[0045] In this way, temperature compensation can be achieved for the capacity allocation on the production line, obtaining the target capacity allocation for each cell under standard temperature. The difference in target capacity allocation for each cell under the same standard temperature is small, which is beneficial to improving the grouping rate.

[0046] Please see Figure 3 In some embodiments, before performing capacity compensation on the cells to be rated, it is necessary to establish a mapping relationship between cell temperature and capacity. The battery rating method also includes: Step 014: Select cells from the same batch and of the same model as the cells to be tested; It is understandable that by using the controlled variable method and selecting cells from the same batch and model as the cells to be tested, the influence of different batches and / or models on the cell temperature and capacity can be avoided, which is beneficial to improving the accuracy of the mapping relationship.

[0047] Step 015: Under constant temperature conditions at different temperatures, the capacity of the cells under test is calibrated to obtain the calibrated capacity and cell temperature of each cell under test. The capacity calibration process differs from the aforementioned capacity testing process in that: (1) Differences in core objectives Capacity testing: The core is "screening + grading". It quickly identifies defective cells with insufficient capacity or abnormal internal resistance, while grouping qualified cells according to the consistency of capacity and internal resistance, providing a basis for subsequent grouping and prioritizing the efficiency of mass production and the grouping rate.

[0048] Capacity calibration: The core is "precise calibration". It determines the actual usable capacity of the battery cell in specific application scenarios (such as high-temperature conditions for electric vehicles and low-temperature scenarios for energy storage). The results must be consistent with actual usage requirements to provide accurate data for equipment range estimation and BMS strategy adjustment.

[0049] (2) Differences in key processes and parameters The charge / discharge rate, test temperature control, number of cycles, number of error corrections, and test duration are all different.

[0050] The capacity calibration generally has a smaller charge / discharge rate, more precise test temperature control, more cycles, more error corrections, and a longer test duration.

[0051] Therefore, capacity calibration can yield more accurate capacity and avoid the influence of other factors such as temperature.

[0052] It is understandable that in order to obtain the mapping relationship, it is necessary to obtain the capacity at different cell temperatures. Therefore, by setting constant temperature environments with different temperatures, the capacity of the cell under test can be calibrated at different cell temperatures. Moreover, the constant temperature environment can avoid the influence of ambient temperature on the capacity calibration, ensuring that the capacity is only affected by the cell temperature.

[0053] Therefore, by calibrating the capacity of the battery under test in a constant temperature environment at different temperatures, the calibrated capacity corresponding to different cell temperatures can be obtained, providing sufficient data support for the subsequent construction of mapping relationships.

[0054] In one optional embodiment, the preset temperature range can be divided into multiple test temperature ranges according to a preset range value; under the constant temperature environment corresponding to each test temperature range, the capacity of the cell under test is calibrated to obtain the calibrated capacity and cell temperature of each cell under test.

[0055] For example, the preset temperature range can be 25 degrees Celsius to 37 degrees Celsius, and the preset range value can be 3 degrees Celsius. This allows for the division of multiple test temperature ranges: [25, 28), [28, 31), [31, 34), and [34, 37]. Then, the constant temperature environment is controlled within the corresponding test temperature range to obtain the cell temperature of the battery under test at different cell temperatures.

[0056] It is understandable that the preset range value can be smaller or larger, depending on the accuracy requirements of the mapping relationship. The smaller the preset range value, the more test temperature ranges are divided, and the more sample data (i.e., cell temperature and corresponding calibrated capacity) are obtained, which is more conducive to building the mapping relationship.

[0057] In this way, by controlling the constant temperature environment within different temperature ranges and combining it with precise capacity calibration, the accurate calibrated capacity of each cell under test at different cell temperatures can be obtained, which can improve the accuracy of subsequent mapping relationship establishment.

[0058] Step 016: Construct a mapping relationship based on the rated capacity corresponding to different cell temperatures.

[0059] Once the calibrated capacity corresponding to different cell temperatures is accurately obtained, the mapping relationship can be constructed.

[0060] In one alternative embodiment, a polynomial regression analysis can be performed on the rated capacity corresponding to different cell temperatures to construct a polynomial regression equation.

[0061] The relationship between cell temperature and capacity is generally non-linear. Therefore, after obtaining the rated capacity corresponding to different cell temperatures, each cell temperature and its corresponding rated capacity can be used as a sample data point. Then, a polynomial regression analysis is performed on multiple sample data points to fit a polynomial regression equation. In the polynomial regression equation, the independent variable is cell temperature, and the dependent variable is capacity, thus obtaining the mapping relationship between cell temperature and capacity.

[0062] For example, a polynomial regression equation includes: C = a + bT - cT 2 Where C is the capacity, a, b and c are fitting constants, and T is the cell temperature.

[0063] For different battery models, the corresponding polynomial regression equations were calibrated. It was found that the only difference between the various polynomial regression equations was the fitting constant a, while the fitting parameters b and c were basically the same.

[0064] When calculating the capacity compensation value, the first capacity at standard temperature is subtracted from the second capacity at the cell temperature of the battery to be rated, which eliminates the fitting constant 'a'. Therefore, this polynomial regression is applicable to the calculation of capacity compensation values ​​for all types of cells.

[0065] Therefore, compared to establishing a mapping relationship for each model, this application only needs to build a mapping relationship once to be applicable to all models of batteries, which can significantly reduce the experimental cost required for capacity compensation.

[0066] Please see Figure 4 In some embodiments, the battery capacity grading method further includes: Step 0171: Calculate the significance test index and correlation index of the polynomial regression equation. The significance test index is determined based on each rated capacity, and the correlation index is determined based on each cell temperature and each rated capacity. Step 0172: Determine whether the polynomial regression equation is effective based on the significance test index and the correlation index; Step 0173: If the polynomial regression equation is invalid, reconstruct the polynomial regression equation.

[0067] The significance test index is determined based on each calibration capacity. Specifically, the total sum of squares, regression sum of squares, and residual sum of squares of the calibration capacity can be calculated first. Then, the F-statistic is determined based on the ratio of the average of the regression sum of squares to the average of the residual sum of squares. Finally, the probability that the F-statistic is greater than the current calculated value is obtained, thus yielding the significance test index.

[0068] The correlation index is determined based on the temperature and rated capacity of each cell. Specifically, the average value of the cell temperature and rated capacity can be calculated first, then the ratio of the square root of the product of the covariance of cell temperature and capacity and the product of the sum of temperature variance and the sum of capacity variance can be calculated, and finally the correlation index is obtained based on the square of the ratio.

[0069] It is understandable that after constructing the polynomial regression equation, in order to ensure the effectiveness of the polynomial regression equation, it is necessary to first perform mathematical verification on the polynomial regression equation.

[0070] By calculating the significance test index and correlation index of the polynomial regression equation, it is possible to quickly determine whether the polynomial regression equation is effective. If the polynomial regression equation is ineffective, it is necessary to reconstruct the polynomial regression equation (such as re-executing steps 014 to 016).

[0071] For example, if the significance test index is greater than the first preset index (e.g., 0.05) or the correlation index is less than the second preset index (e.g., 98%, 99%), the polynomial regression equation can be determined to be invalid. Conversely, if the significance test index is less than or equal to the first preset index and the correlation index is greater than or equal to the second preset index, the polynomial regression equation can be determined to be valid.

[0072] This avoids the inadequacy of verifying the accuracy of the polynomial regression equation through subsequent experiments, which would make it difficult to guarantee the required accuracy of the capacity compensation value calculation and reduce experimental costs.

[0073] Please see Figure 5 In some embodiments, the battery capacity grading method further includes: Step 0181: Perform capacity calibration on multiple cells to be calibrated to obtain the calibrated capacity of each cell. Step 0182: Calculate the capacity difference between the target capacity and the rated capacity of each cell to be allocated capacity; Step 0183: Based on the capacity difference corresponding to each cell to be allocated capacity, determine whether the target capacity allocation for each cell to be allocated capacity is accurate. Step 0184: If the proportion of cells to be allocated with accurate target capacity is greater than a preset proportion, the mapping relationship is determined to be accurate. Step 0185: If the proportion of cells to be allocated with accurate target capacity is less than a preset proportion, the mapping relationship is determined to be inaccurate, and the mapping relationship is reconstructed.

[0074] Specifically, in addition to using mathematical methods to verify the effectiveness of the polynomial regression equation, the accuracy of the polynomial regression equation can also be determined based on the difference between the target capacity after capacity compensation of the cell to be categorized and the calibrated capacity of the cell to be categorized.

[0075] It is understandable that the closer the target capacity of the cell to be compensated is to the rated capacity of the cell, the higher the accuracy of the polynomial regression equation.

[0076] Therefore, the capacity of each of the multiple cells to be allocated capacity can be calibrated first to obtain the calibrated capacity of each cell. Then, the capacity difference between the target capacity and the calibrated capacity of each cell is calculated. Based on the capacity difference of each cell, the accuracy of the target capacity of each cell is determined. If the capacity difference of the cell is greater than the preset capacity difference (which can be set according to the actual accuracy requirements; the higher the accuracy requirement, the lower this value), then the target capacity of the cell is determined to be accurate; otherwise, it is inaccurate.

[0077] After verifying the accuracy of the target capacity of a certain number of cells to be calibrated, the proportion of the number of cells to be calibrated to the total number (i.e., the number of cells to be calibrated for capacity) can be obtained. If this proportion is greater than or equal to a preset proportion (such as 98% or 99%), the mapping relationship (i.e., the polynomial regression equation) can be determined to be accurate. If this proportion is less than the preset proportion (such as 98% or 99%), the mapping relationship (i.e., the polynomial regression equation) can be determined to be inaccurate. In this case, the mapping relationship needs to be reconstructed (such as re-executing steps 014 to 016).

[0078] This not only ensures the effectiveness of the mapping relationship but also guarantees the accuracy of the polynomial regression equation, which is beneficial to improving the consistency of the target capacity and increasing the battery packing rate.

[0079] In some embodiments, a lifting door is provided in the passageway between the workshop where the capacity testing cabinet is located and the workshop where the adjacent process is located. The lifting door is opened when the battery cells enter or leave the space where the capacity testing cabinet is located.

[0080] It is understandable that the ambient temperature of the workshop where the capacity testing cabinet is located may be different from the ambient temperature of the adjacent workshops of other processes (such as the liquid injection process before capacity testing and the formation process after capacity testing). If the workshops are always interconnected, the temperature of the workshops of other processes may cause large fluctuations in the temperature of the workshop where the capacity testing cabinet is located, which will cause large fluctuations in the temperature of the cells to be tested during capacity testing, affecting the consistency of capacity testing.

[0081] Therefore, to ensure a relatively constant temperature environment in the workshop where the capacity testing cabinet is located, thus minimizing the temperature difference between the battery cells being tested and maximizing testing consistency, lifting doors are installed between the workshop containing the capacity testing cabinet and adjacent process workshops. These doors are normally closed and only open when battery cells enter or exit the capacity testing cabinet. This minimizes heat exchange between the workshop containing the capacity testing cabinet and other process workshops, maintaining a relatively constant temperature environment in the workshop containing the capacity testing cabinet.

[0082] In some embodiments, if the target capacity of the cell to be sized is less than a preset lower limit, the cell to be sized is sized again; if the target capacity obtained after the second sizing is still less than the lower limit, the cell to be sized is downgraded.

[0083] It is understandable that setting a reasonable lower limit for capacity can filter out "substandard cells" (such as those with substandard capacity, lithium plating, black spots, etc.), while also setting a minimum capacity standard for cells in the same group to avoid low-capacity cells dragging down the overall battery performance.

[0084] Therefore, if the target capacity is less than the preset lower limit, the cell to be capacity-compensated can be re-compensated (e.g., a new capacity-compensation test and capacity compensation can be performed) to obtain a new target capacity. If the new target capacity is still less than the lower limit, it can be determined that the cell to be capacity-compensated does not meet the actual capacity requirements, rather than due to factors such as test errors. In this case, the cell to be capacity-compensated can be downgraded, and it can be determined that the cell to be capacity-compensated is a defective cell.

[0085] In one alternative embodiment, the lower limit of the capacity limit is determined based on the maximum value of the first lower limit, the second lower limit, and the third lower limit; The first lower limit is determined based on the capacity distribution of each cell; for example, after allocating capacity to a batch of cells, the capacity distribution of this batch of cells can be viewed, and the average capacity of all cells can be calculated. And the standard deviation σ, and then determine the capacity range based on the average capacity and the standard deviation of the preset multiple, such as [ -6σ, +6σ], thus determining the first lower limit value is -6σ. This ensures that the required number of cells exceeding the lower capacity limit are met, preventing too many cells from being classified as defective.

[0086] The second lower limit is determined based on the minimum remaining capacity after discharge to the preset voltage. The preset voltage and the minimum remaining capacity are determined based on customer requirements. For example, if the customer requires the remaining capacity of the cell after discharge to the preset voltage to be greater than the minimum remaining capacity, the lower limit of capacity will be guaranteed to meet the customer's requirements.

[0087] The third lower limit is determined based on the lowest capacity of each cell without cell abnormalities. A batch with a determined capacity can be unpacked to identify cells with cell abnormalities (such as lithium plating or black spots) and cells without cell abnormalities. The lowest capacity among the cells without cell abnormalities is then determined as the third lower limit, thus ensuring that no cell abnormalities are present when the capacity lower limit is met.

[0088] Finally, the maximum value of the first, second, and third lower limits is determined as the capacity limit, thus ensuring that the capacity of the cells is greater than the capacity limit, which can simultaneously meet quantity requirements, customer needs, and prevent cell abnormalities.

[0089] In some embodiments, the capacity-dividing cabinet is equipped with a temperature acquisition device and a temperature detection device for detecting the temperature of each battery cell to be divided. The temperature acquisition device is connected to at least one temperature detection device to obtain the cell temperature collected by the connected temperature detection device. The temperature acquisition device uploads the collected temperature data to the host computer at preset intervals. The host computer determines abnormal temperature detection devices and temperature acquisition devices based on the temperature data uploaded by the temperature acquisition device.

[0090] It's understandable that capacity testing cabinets are typically equipped with temperature detection devices to monitor the temperature of each battery cell to be tested, as well as temperature acquisition devices to store and upload the collected temperature data. Each temperature acquisition device is connected to at least one temperature detection device to obtain the cell temperature data and upload it to a host computer at preset intervals. The host computer can maintain the temperature data collected by each detection device and, based on the trend of the temperature data collected by each device, determine whether the temperature detection device is malfunctioning or damaged. For example, since the temperature in the capacity testing cabinet generally does not fluctuate significantly, if the temperature data collected by the detection device shows large fluctuations (such as large range or variance), it can be determined that the temperature detection device or its connected temperature acquisition device may be malfunctioning. In this case, an alarm can be triggered promptly, allowing maintenance personnel to repair or replace the malfunctioning temperature detection device and its connected temperature acquisition device, ensuring that the cell temperature can be accurately detected.

[0091] All of the above technical solutions can be combined in any way to form optional embodiments of this application, and will not be described in detail here.

[0092] The battery capacity testing method of this application obtains the cell temperature during the capacity testing process when obtaining the capacity testing capacity of the production line. Since the temperature of different cells during capacity testing may be different, the capacity testing capacity obtained by the production line will be different even if the actual capacity of two cells is the same. Therefore, to avoid the impact of temperature on capacity testing, one approach is to strictly control the temperature of each cell during capacity testing to ensure that the cell temperatures are basically consistent. However, this leads to reduced testing efficiency and higher costs. Since the effect of temperature on capacity follows a pattern, a pre-established mapping relationship between temperature and capacity can be used to determine the capacity at different temperatures. After obtaining the cell temperature of the cell to be tested, the required capacity compensation value (e.g., calculating the difference between the capacity at the standard temperature and the cell temperature) can be determined based on this mapping relationship. Finally, the target capacity is calculated using the capacity compensation value and the production line's capacity testing capacity. This ensures that each cell to be tested receives the corresponding capacity at the standard temperature, reducing the distribution variation in capacity testing and improving cell matching efficiency.

[0093] To facilitate better implementation of the battery capacity testing method of this application embodiment, this application embodiment also provides a battery capacity testing device. Please refer to... Figure 6 , Figure 6 This is a schematic diagram of the battery capacity testing device provided in an embodiment of this application. The battery capacity testing device 200 can provide a graphical user interface through a terminal device. The graphical user interface includes at least a partial virtual scene and at least one virtual character. The battery capacity testing device 200 may include: The acquisition module 201 is used to acquire the capacity of the battery cell to be capacity-graded after capacity grading and the temperature of the battery cell during capacity grading. The calculation module 202 is used to calculate the capacity compensation value of the cell to be rated based on the preset temperature and capacity mapping relationship. The capacity compensation value is determined based on the capacity difference between the first capacity corresponding to the preset standard temperature in the mapping relationship and the second capacity corresponding to the cell temperature in the mapping relationship. The determination module 203 is used to determine the target capacity of the battery cell to be allocated based on the capacity compensation value and the capacity allocation capacity of the production line.

[0094] Each module or unit in the aforementioned battery capacity grading device can be implemented entirely or partially through software, hardware, or a combination thereof. Each unit can be embedded in or independent of the processor in the electronic device in hardware form, or stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of each unit.

[0095] The battery capacity balancing device 200 can be integrated into a terminal or server that has storage and a processor and thus computing power, or the battery capacity balancing device 200 can be the terminal or server.

[0096] Optionally, this application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0097] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may be a terminal or a server. Figure 7 As shown, the electronic device 300 includes a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, and a computer program stored in the memory 302 and executable on the processor. The processor 301 and the memory 302 are electrically connected. Those skilled in the art will understand that the electronic device structure shown in the figures does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0098] The processor 301 is the control center of the electronic device 300. It connects various parts of the electronic device 300 through various interfaces and lines. By running or loading software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device 300 and processes data, thereby performing overall processing of the electronic device 300.

[0099] Optional, such as Figure 7As shown, the electronic device 300 also includes: a display screen 303, a radio frequency circuit 304, an audio circuit 305, an input unit 306, and a power supply 307. The processor 301 is electrically connected to the display screen 303, the radio frequency circuit 304, the audio circuit 305, the input unit 306, and the power supply 307. Those skilled in the art will understand that... Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0100] The display screen 303 can be used to display a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. The display screen 303 may include a display panel and a touch panel. The display panel can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the electronic device. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. The touch panel can be used to collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel), generate corresponding operation commands, and execute the corresponding program. Optionally, the touch panel may include a touch detection device and a touch controller. The touch detection device detects the user's touch location and the signal generated by the touch operation, and transmits the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 301, and can receive and execute commands from the processor 301. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it transmits the information to the processor 301 to determine the type of touch event. Subsequently, the processor 301 provides corresponding visual output on the display panel according to the type of touch event. In this embodiment, the touch panel and the display panel can be integrated into the display screen 303 to achieve input and output functions. However, in some embodiments, the touch panel and the display screen 303 can be implemented as two independent components to achieve input and output functions. That is, the display screen 303 can also be used as part of the input unit 306 to achieve input functions.

[0101] The radio frequency circuit 304 can be used to transmit and receive radio frequency signals to establish wireless communication with network devices or other electronic devices, and to transmit and receive signals with network devices or other electronic devices.

[0102] Audio circuitry 305 can be used to provide an audio interface between a user and an electronic device via a speaker and a microphone. Audio circuitry 305 converts received audio data into electrical signals, transmits them to the speaker, and the speaker converts them into sound signals for output. Conversely, the microphone converts collected sound signals into electrical signals, which are then received by audio circuitry 305, converted back into audio data, and then processed by processor 301 before being transmitted via radio frequency circuitry 304 to, for example, another electronic device, or output to memory 302 for further processing. Audio circuitry 305 may also include an earphone jack to facilitate communication between peripheral headphones and electronic devices.

[0103] The input unit 306 can be used to receive input numbers, characters, or object feature information (such as fingerprints, irises, facial information, etc.), and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control.

[0104] Power supply 307 is used to supply power to various components of electronic device 300. Optionally, power supply 307 can be logically connected to processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. Power supply 307 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0105] although Figure 7 As not shown in the diagram, the electronic device 300 may also include a camera, sensor, wireless fidelity module, Bluetooth module, etc., which will not be described in detail here.

[0106] This application also provides a computer-readable storage medium for storing a computer program. This computer-readable storage medium can be applied to an electronic device, and the computer program causes the electronic device to execute the corresponding processes in the battery capacity testing method described in the embodiments of this application; for the sake of brevity, these will not be elaborated further here.

[0107] This application also provides a computer program product including computer instructions stored in a computer-readable storage medium. The processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the corresponding process in the battery capacity assessment method described in the embodiments of this application. For simplicity, further details are omitted here.

[0108] It should be understood that the processor in this application may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0109] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0110] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0111] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0112] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] In addition, the functional units in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0116] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer or a server) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0117] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A battery capacity testing method, characterized in that, include: Obtain the capacity of the battery cell after capacity grading on the production line and the cell temperature during capacity grading. Based on a preset mapping relationship between temperature and capacity, the capacity compensation value of the cell to be rated is calculated. The capacity compensation value is determined based on the capacity difference between the first capacity corresponding to the preset standard temperature in the mapping relationship and the second capacity corresponding to the cell temperature in the mapping relationship. Based on the capacity compensation value and the capacity allocation capacity of the production line, the target capacity allocation capacity of the battery cell to be allocated is determined.

2. The battery capacity assessment method according to claim 1, characterized in that, Also includes: Select cells from the same batch and of the same model as the cells to be tested; The capacity of the test cells is calibrated under constant temperature conditions at different temperatures to obtain the calibrated capacity and cell temperature of each test cell. The mapping relationship is constructed based on the rated capacity corresponding to different cell temperatures.

3. The battery capacity testing method according to claim 2, characterized in that, The process of calibrating the capacity of the battery cells under test in a constant temperature environment at different temperatures to obtain the calibrated capacity and temperature of each battery cell under test includes: The preset temperature range is divided into multiple test temperature ranges according to the preset range value; Under the constant temperature environment corresponding to each of the test temperature ranges, the capacity of the cell under test is calibrated to obtain the calibrated capacity and cell temperature of each cell under test.

4. The battery capacity testing method according to claim 2 or 3, characterized in that, The mapping relationship includes a polynomial regression equation. The construction of the mapping relationship based on the calibration capacity corresponding to different calibration temperatures includes: A polynomial regression analysis was performed on the rated capacity corresponding to different cell temperatures to construct the polynomial regression equation.

5. The battery capacity testing method according to claim 4, characterized in that, The polynomial regression equation includes: C = a + bT - c Where C is the capacity, a, b and c are fitting constants, and T is the cell temperature.

6. The battery capacity testing method according to claim 4 or 5, characterized in that, Also includes: The significance test index and correlation index of the polynomial regression equation are calculated. The significance test index is determined based on each of the calibration capacities, and the correlation index is determined based on each of the cell temperatures and each of the calibration capacities. The validity of the polynomial regression equation is determined based on the significance test index and the correlation index. If the polynomial regression equation is invalid, the polynomial regression equation is reconstructed.

7. The battery capacity testing method according to any one of claims 1-6, characterized in that, Also includes: The capacity of each of the multiple cells to be rated is calibrated to obtain the calibrated capacity of each of the multiple cells to be rated. Calculate the capacity difference between the target capacity and the rated capacity of each of the cells to be rated. Based on the capacity difference corresponding to each of the cells to be allocated capacity, determine whether the target capacity allocation for each of the cells to be allocated capacity is accurate. When the proportion of the target capacity-accepting cells to be allocated to the plurality of cells to be allocated is greater than a preset proportion, the mapping relationship is determined to be accurate. If the proportion of the target capacity-accounting cells to be allocated is less than a preset proportion, the mapping relationship is determined to be inaccurate, and the mapping relationship is reconstructed.

8. The battery capacity testing method according to any one of claims 1-7, characterized in that, A lifting door is installed in the passageway between the workshop where the capacity sorting cabinet is located and the workshop where the adjacent process is located. The lifting door opens when the battery cells enter or leave the space where the capacity sorting cabinet is located.

9. The battery capacity testing method according to any one of claims 1-8, characterized in that, Also includes: If the target capacity of the cell to be rated is less than the preset lower limit, the cell to be rated will be rerated. If the target capacity obtained after the second capacity allocation is still less than the lower limit of the capacity allocation, then the cell to be allocated capacity will be downgraded.

10. The battery capacity testing method according to claim 9, characterized in that, The lower limit of the production line capacity is determined based on the maximum value of the first lower limit, the second lower limit, and the third lower limit; The first lower limit is determined based on the capacity distribution of each cell; the second lower limit is determined based on the minimum remaining capacity after discharging to a preset voltage; and the third lower limit is determined based on the minimum capacity of each cell without cell abnormalities.

11. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing a computer program, and the processor executing the battery capacity grading method according to any one of claims 1-10 by calling the computer program stored in the memory.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted for loading by a processor to perform the battery capacity grading method as described in any one of claims 1-10.

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