Method, device and electronic equipment for predicting discharge capacity of battery cell

Abstract

The present invention discloses a method, device and electronic device for predicting the capacity of a battery cell. The method for predicting the capacity of a battery cell is applied to a device for predicting the capacity of a battery cell, and includes: providing a plurality of first sampled battery cells, wherein the plurality of first sampled battery cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; obtaining the divided capacity discharge capacity of each first sampled battery cell; establishing a first functional relationship between the divided capacity discharge capacity and the formation charging capacity according to the plurality of first formation charging capacities and the divided capacity discharge capacity of the plurality of first sampled battery cells; providing a target battery cell, obtaining a second formation charging capacity, and calculating the battery capacity of the target battery cell according to the second formation charging capacity and the first functional relationship. Compared with the prior art, the method, device and electronic device for predicting the capacity of a battery cell provided by the embodiments of the present invention have the advantages of reducing the production time and production cost of the battery cell and improving the production efficiency of the battery cell.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a method and device for predicting the discharge capacity of a battery cell by capacity, and electronic equipment. Background Art

[0002] Lithium-ion batteries have the advantages of high voltage platform, high energy density, long life, low self-discharge rate and green environmental protection, and are widely used in electric vehicles, consumer electronics, energy storage and other fields. Capacity is an important performance indicator of the battery cell, which can directly reflect the quality of the battery cell. Therefore, in production, there is often a capacity inspection test process before the battery cell is off the line to obtain the capacity of the battery cell as the basis for screening and grading the battery cell.

[0003] At present, the common capacity division process is to perform at least one complete charge and discharge at room temperature or high temperature with a low rate current after the battery cell is formed, and take the discharge capacity of the complete discharge as the battery cell capacity. This process is time-consuming, requires a large number of charging and discharging cabinets, and consumes a lot of electricity, so it has the disadvantages of high production cost and low efficiency. Summary of the invention

[0004] The present invention provides a method, device and electronic equipment for predicting battery cell capacity, so as to reduce the production time and production cost of battery cells and improve the production efficiency of battery cells.

[0005] According to one aspect of the present invention, a cell capacity prediction method is provided, which is applied to a cell capacity prediction device, and includes: providing a plurality of first sample cells, wherein the plurality of first sample cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; obtaining the fractional discharge capacity of each of the first sample cells; establishing a first functional relationship between the fractional discharge capacity and the formation charging capacity according to the plurality of first formation charging capacities and the fractional discharge capacity of the plurality of first sample cells; providing a target cell, obtaining the second formation charging capacity, and calculating the cell capacity of the target cell according to the second formation charging capacity and the first functional relationship.

[0006] According to another aspect of the present invention, a cell capacity prediction device is provided, comprising: a sampling cell data acquisition module, used to acquire a plurality of first formation charging capacities and fractional discharge capacities, wherein the plurality of first sampling cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; a function acquisition module, used to establish a first functional relationship between fractional discharge capacity and formation charging capacity according to the plurality of first formation charging capacities and fractional discharge capacities of the plurality of first sampling cells; a target cell data acquisition module, used to acquire a second formation charging capacity; and a capacity prediction module, used to calculate the cell capacity of the target cell according to the second formation charging capacity and the first functional relationship.

[0007] According to another aspect of the present invention, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the battery cell capacity prediction method described in any embodiment of the present invention.

[0008] The technical solution of the embodiment of the present invention establishes a first functional relationship between the capacity-divided discharge capacity and the formation charge capacity by analyzing data of the capacity-divided discharge capacity and the formation charge capacity of multiple first sampled battery cells. In the subsequent production process, for any target battery cell produced, after obtaining the second formation charge capacity, the cell capacity of the target battery cell can be calculated according to the second formation charge capacity and the first functional relationship, without the need to perform capacity-divided processing on the target battery cell, thereby reducing the capacity-divided process in the battery cell production process, thereby reducing the production time and production cost of the battery cell, and improving the production efficiency of the battery cell; in addition, the multiple first sampled battery cells for which the first functional relationship is established have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charge capacity, thereby reducing the influence of the difference in the parameters of the battery cell itself on the accuracy of the battery cell capacity prediction result, and improving the accuracy of the battery cell capacity prediction result.

[0009] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 is a flow chart of a method for predicting battery cell capacity according to Embodiment 1 of the present invention;

[0012] Figure 2 is a flow chart of a method for predicting battery cell capacity according to Embodiment 2 of the present invention;

[0013] Figure 3 is a schematic structural diagram of a battery cell capacity prediction device provided according to Embodiment 3 of the present invention;

[0014] Figure 4It is a schematic diagram of the structure of an electronic device implementing the fourth embodiment of the present invention. Specific embodiments

[0015] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0016] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment 1

[0018] Figure 1 A flowchart of a method for predicting cell capacity is provided for the first embodiment of the present invention. The method can be performed by a cell capacity prediction device or other electronic device. The cell capacity prediction device or other electronic device can be implemented in the form of hardware and / or software. Figure 1 As shown, the method includes:

[0019] Step S101: providing a plurality of first sample battery cells, and obtaining a first formation charging capacity of each of the first sample battery cells.

[0020] In this step, the internal resistance before formation of multiple first sampling batteries is the same, the internal resistance change rate before and after formation is the same, and the formation charging capacity is the same. It is understandable that in the actual production process, due to the influence of measurement error and measurement process accuracy, there is also a certain difference between the measurement result of the internal resistance of the battery cell and the formation charging capacity and the actual battery cell internal resistance and the formation charging capacity, and there are almost no two identical batteries. Therefore, in the actual production process, the difference of the internal resistance before formation is less than or equal to 1%, that is, it is determined that the internal resistance before formation is the same, and in the same way, the difference of the internal resistance change rate before and after formation is less than or equal to 1% and the difference of the formation charging capacity is less than or equal to 1% and can be determined as both are the same. In addition, the aforementioned difference is less than or equal to 1% and can be determined as the same, which is only an example of a specific data in the present embodiment, and does not constitute a limitation. In other embodiments of the present invention, it can also be 1.5%, 2% and other numerical values, which can be flexibly selected according to the demand for accuracy.

[0021] Step S102: obtaining the divided capacity discharge capacity of each first sample battery cell.

[0022] In this step, each first sample battery cell may be discharged in a divided capacity manner to test its discharge capacity during the divided capacity process, and the divided capacity discharge capacity is the final battery cell capacity of the battery cell.

[0023] Step S103: establishing a first functional relationship between the divided-capacity discharge capacity and the formation charge capacity according to the plurality of first formation charge capacities and the divided-capacity discharge capacity of the plurality of first sample cells.

[0024] Specifically, each first formation charge capacity and the fractional capacity discharge capacity can be corresponded one by one to form a formation charge capacity-fractional capacity discharge capacity pair, and then a relational coordinate system of the formation charge capacity and the fractional capacity discharge capacity is constructed, and according to the distribution of the formation charge capacity-fractional capacity discharge capacity pairs in the coordinate system, a linear fitting is performed to obtain a linear relational expression between the fractional capacity discharge capacity and the formation charge capacity as a first functional relational expression.

[0025] It can be understood that the above is only a specific example of obtaining the first functional relationship in this embodiment, and does not constitute a limitation. In other embodiments of the present invention, the first functional relationship can also be obtained by other methods such as curve fitting of the formation charge capacity-divided capacity discharge capacity pair, and can be flexibly set according to actual needs.

[0026] Step S104: providing a target battery cell, acquiring a second formation charging capacity, and calculating the battery cell capacity of the target battery cell according to the second formation charging capacity and the first functional relationship.

[0027] In this step, the target battery cell is the battery cell for which capacity prediction is required. After obtaining the target battery cell for which capacity prediction is required, the target battery cell can be subjected to formation treatment to obtain the second formation charging capacity. After obtaining the second formation charging capacity, the second formation charging capacity is substituted into the first functional relationship for calculation. The calculation result is the prediction result of the battery cell capacitance of the target battery cell.

[0028] Compared with the prior art, in the first embodiment of the present invention, by analyzing the data of the divided capacity discharge capacity and the formation charge capacity of multiple first sampled battery cells, a first functional relationship between the divided capacity discharge capacity and the formation charge capacity is established. In the subsequent production process, for any target battery cell produced, after the second formation charge capacity is obtained, the cell capacity of the target battery cell can be calculated according to the second formation charge capacity and the first functional relationship, without the need to perform capacity division processing on the target battery cell, thereby reducing the capacity division process in the battery cell production process, thereby reducing the production time and production cost of the battery cell, and improving the production efficiency of the battery cell; in addition, the multiple first sampled battery cells for which the first functional relationship is established have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charge capacity, thereby reducing the influence of the difference in the parameters of the battery cell itself on the accuracy of the battery cell capacity prediction result, and improving the accuracy of the battery cell capacity prediction result.

[0029] Embodiment 2

[0030] Figure 2 This is a flow chart of a method for predicting the capacity of a battery cell provided in the second embodiment of the present invention. This embodiment is an improvement on the basis of the first embodiment. Figure 2 As shown, the method includes:

[0031] Step S201: providing a plurality of first sample battery cells, and obtaining a first formation charging capacity of each of the first sample battery cells.

[0032] Step S202: obtaining the divided capacity discharge capacity of each first sample battery cell.

[0033] Step S203: establishing a first functional relationship between the divided-capacity discharge capacity and the formation charge capacity according to the plurality of first formation charge capacities and the divided-capacity discharge capacity of the plurality of first sample cells.

[0034] It can be understood that steps S201 to S203 in this embodiment are substantially the same as steps S101 to S103 in the first embodiment, and are not described in detail here. For details, reference may be made to the specific description in the first embodiment.

[0035] Step S204: providing a plurality of second sample cells, and performing correction and compensation on the first functional relationship according to the change of the internal resistance parameter of each second sample cell before and after formation to obtain a second functional relationship.

[0036] In this step, the internal resistances of the multiple second sampled cells before formation are different, the internal resistance change rates before and after formation are the same, and the formation charging capacity is the same. It is understandable that, similar to the first sampled cell, the different internal resistances of the second sampled cells before formation are in the actual production process, that is, the difference in the internal resistances before formation of the multiple second sampled cells is greater than or equal to 1%, the internal resistance change rates before and after formation are the same, and the formation charging capacity is the same, that is, the difference in the internal resistance change rates before and after formation is less than or equal to 1%, and the difference in the formation charging capacity is less than or equal to 1%. Similarly, the aforementioned 1% is only a specific example in the present embodiment and does not constitute a limitation. In the actual production process, it can also be other thresholds such as 1.5%, 2%, etc., which can be flexibly set according to actual needs.

[0037] In this step, the change of the internal resistance parameter of the second sampled battery cell before and after formation includes at least one of the internal resistance change rate before and after formation and the internal resistance compensation coefficient. Among them, the internal resistance change rate before and after formation can reflect the difference in the first efficiency of the battery cell, and the internal resistance compensation coefficient can reflect the difference in the discharge platform of the battery cell. The internal resistance change rate before and after formation is the ratio of the absolute value of the difference between the internal resistance before formation and the internal resistance after formation to the internal resistance after formation, and the formula is expressed as Among them, δ i R′ is the change rate of internal resistance before and after formation. i is the internal resistance after formation, R i The internal resistance compensation coefficient is the ratio of the average value of the internal resistance of multiple second sampled cells before formation to the internal resistance of each second sampled cell before formation, that is, the average resistance R of multiple second sampled cells before formation is first calculated, and then the ratio of the average resistance to the internal resistance of each second sampled cell before formation is calculated.

[0038] Specifically, in this step, the slope of the first functional relationship is corrected and compensated according to the change of the internal resistance parameter of the second sampled battery cell before and after formation. For example, the first functional relationship is a linear functional relationship: Q′ i =A*Q i +B;

[0039] Among them, Q′ i is the capacity of the divided discharge, Q i is the charge capacity, A is the slope of the first functional equation, and B is a constant.

[0040] When the change of the internal resistance parameter before and after the formation only includes the internal resistance change rate before and after the formation, the second functional relationship can be Q′ i =(A+δ i )*Q i +B;

[0041] When the change of the internal resistance parameter before and after formation only includes the internal resistance compensation coefficient, the second functional relationship can be Q′i =(A+K i )*Q i +B;

[0042] When the change of the internal resistance parameter before and after the formation includes both the internal resistance change rate before and after the formation and the internal resistance compensation coefficient, the second functional relationship can be Q′ i =(A+δ i +K i )*Q i +B;

[0043] It can be understood that the above formula is only an example of the first functional relationship and the second functional relationship in this embodiment, and does not constitute a limitation. In other embodiments of the present invention, it can also be other types of functional relationships, which can be flexibly set according to actual conditions.

[0044] Step S205: providing a target battery cell, acquiring a second formation charging capacity, and calculating the battery cell capacity of the target battery cell according to the second formation charging capacity and a second functional relationship.

[0045] In this step, the parameters of the target battery cell can be obtained according to the compensation parameters in the second functional relationship. For example, when the second functional relationship includes the internal resistance change rate before and after formation, the internal resistance change rate before and after formation and the second formation charging capacity of the target battery cell can be substituted into the second functional relationship for calculation, and the calculation result is the predicted battery cell capacity of the target battery cell.

[0046] When the change of the internal resistance parameters before and after formation includes at least the internal resistance compensation coefficient, the internal resistance compensation coefficient of the target cell can be calculated with the help of auxiliary cells, that is, multiple auxiliary cells are obtained, the auxiliary cells and the target cell have different internal resistances before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; the average internal resistance of the multiple auxiliary cells and the target cell before formation is calculated; the ratio of the average internal resistance to the internal resistance before formation of each target cell is calculated to obtain the internal resistance compensation coefficient before formation of the target cell. The internal resistance compensation coefficient before formation of the target cell and the second formation charging capacity are respectively substituted into the second functional relationship for calculation, and the calculation result is the predicted cell capacity of the target cell.

[0047] Compared with the prior art, the battery cell capacity prediction method provided in the second embodiment of the present invention retains the technical effects of the first embodiment, and at the same time, corrects and compensates the first functional relationship according to the change of the internal resistance parameters of multiple second sampled battery cells before and after formation to obtain a second functional relationship, and uses the second functional relationship to predict the battery cell capacity. Since the change of the internal resistance parameters before and after formation includes at least one of the internal resistance change rate before and after formation and the internal resistance compensation coefficient, the internal resistance change rate before and after formation can reflect the first effect difference of the battery cell, and the internal resistance compensation coefficient can reflect the discharge platform difference of the battery cell. Therefore, correction parameters of the first effect difference of the battery cell and the discharge platform difference of the battery cell are added to the second functional relationship, reducing the influence of the first effect difference of the battery cell and the discharge platform difference of the battery cell on the battery cell capacity prediction result, and improving the accuracy of the battery cell capacity prediction result.

[0048] Embodiment 3

[0049] Figure 3 This is a schematic diagram of the structure of a battery cell capacity prediction device provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: a sampling cell data acquisition module 100, used to acquire a plurality of first formation charging capacities and divided-capacity discharge capacities, wherein the plurality of first sampled cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; a function acquisition module 200, used to establish a first functional relationship between the divided-capacity discharge capacity and the formation charging capacity according to the plurality of first formation charging capacities and the divided-capacity discharge capacities of the plurality of first sampled cells; a target cell data acquisition module 300, used to acquire a second formation charging capacity; and a capacity prediction module 400, used to calculate the cell capacity of the target cell according to the second formation charging capacity and the first functional relationship.

[0050] Optionally, the sampling cell data acquisition module 100 can also be used to obtain the change of the internal resistance parameter of the second sampling cell before and after formation. The function acquisition module 200 is also used to correct and compensate the first functional relationship according to the change of the internal resistance parameter of the second sampling cell before and after formation to obtain a second functional relationship. The target cell data acquisition module 300 is also used to obtain the change of the internal resistance parameter of the target cell before and after formation. The capacity prediction module 400 is also used to calculate the cell capacity of the target cell according to the second formation charging capacity, the change of the internal resistance parameter of the target cell before and after formation, and the second functional relationship.

[0051] Embodiment 4

[0052] Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0053] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0054] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0055] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the cell capacity prediction method provided in the aforementioned embodiment.

[0056] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0057] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0058] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting cell capacity, applied to a cell capacity prediction device, characterized in that: include: Providing a plurality of first sample cells, wherein the plurality of first sample cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same charging capacity after formation; Obtaining the divided capacity discharge capacity of each of the first sampling cells; Establishing a first functional relationship between the divided capacity discharge capacity and the formation charge capacity according to the first formation charge capacity of the plurality of first sample cells and the divided capacity discharge capacity of the plurality of first sample cells; Providing a target battery cell, obtaining a second formation charging capacity of the target battery cell, and calculating the battery cell capacity of the target battery cell according to the second formation charging capacity and the first functional relationship; After the first functional relationship between the divided capacity discharge capacity and the formation charge capacity is established, the method further includes: Providing a plurality of second sample cells, wherein the plurality of second sample cells have different internal resistances before formation, the same internal resistance change rates before and after formation, and the same formation charging capacity; Correcting and compensating the first functional relationship according to the change of the internal resistance parameter of each of the second sampled cells before and after formation to obtain a second functional relationship; The step of calculating the target cell capacity according to the second formation charging capacity and the first functional relationship includes: The cell capacity of the target cell is calculated according to the second formation charging capacity and the second functional relationship.

2. The method for predicting battery cell capacity according to claim 1, characterized in that: The first functional relationship between the divided capacity discharge capacity and the formation charge capacity is established, including: The first formation charging capacity and the fractional discharge capacity are matched one by one to form a formation charging capacity-fractional discharge capacity pair; Linear fitting is performed on a plurality of the formation charge capacity-divided capacity discharge capacity pairs to obtain a linear relationship between the divided capacity discharge capacity and the first formation charge capacity as the first functional relationship.

3. The method for predicting battery cell capacity according to claim 1, characterized in that: The change of the internal resistance parameter of the second sampling battery cell before and after formation includes at least one of the internal resistance change rate before and after formation and the internal resistance compensation coefficient.

4. The method for predicting battery cell capacity according to claim 3, characterized in that: The internal resistance compensation coefficient is a ratio of an average value of the internal resistances of the plurality of second sample cells before formation to the internal resistance of each second sample cell before formation.

5. The method for predicting battery cell capacity according to claim 4, characterized in that: The change of the internal resistance parameter before and after the formation at least includes the internal resistance compensation coefficient; Before calculating the target cell capacity according to the second formation charging capacity and the first functional relationship, the method further includes: Acquire internal resistance data of a plurality of auxiliary cells, wherein the auxiliary cells and the target cell have different internal resistances before formation, the same internal resistance change rates before and after formation, and the same formation charging capacities; Calculating the average internal resistance of the multiple auxiliary battery cells before formation and the internal resistance of the target battery cell before formation; Calculating the ratio of the average internal resistance to the internal resistance before formation of each of the target cells to obtain a compensation coefficient of the internal resistance before formation of the target cells; The step of calculating the target cell's divided-capacity discharge capacity according to the second formation charge capacity and the functional relationship includes: The second formation charging capacity and the pre-formation internal resistance compensation coefficient of the target battery cell are substituted into the second functional relationship to calculate the battery cell capacity of the target battery cell.

6. The method for predicting battery cell capacity according to claim 1, characterized in that: The first functional relationship is a linear functional relationship; The correcting and compensating the first functional relationship according to the change of the internal resistance parameter of each of the second sampling cells before and after formation specifically includes: The slope of the first functional relationship is corrected and compensated according to the change of the internal resistance parameter of the second sampling battery cell before and after formation.

7. The method for predicting battery cell capacity according to claim 6, characterized in that: The correcting and compensating the slope of the first functional relationship according to the change of the internal resistance parameter of the second sampling battery cell before and after formation includes: The sum of the slope of the first functional relationship and the change of the internal resistance parameter of the second sample battery cell before and after formation is taken as a new slope to obtain the second functional relationship.

8. A battery cell capacity prediction device, controlled by the battery cell capacity prediction method according to any one of claims 1 to 7, characterized in that: include: A sampling cell data acquisition module, used to acquire first formation charging capacity and fractional discharge capacity of a plurality of first sampling cells, wherein the plurality of first sampling cells have the same internal resistance before formation, the same internal resistance change rate before and after formation, and the same formation charging capacity; A function acquisition module, used for establishing a first functional relationship between the divided capacity discharge capacity and the formation charge capacity according to the plurality of first formation charge capacities and the divided capacity discharge capacity of the plurality of first sampling cells; A target cell data acquisition module is used to acquire the second formation charging capacity; A capacity prediction module is used to calculate the cell capacity of the target cell according to the second formation charging capacity and the first functional relationship.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the battery cell capacity prediction method according to any one of claims 1 to 7.

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