Lithium ion battery formation control method and formation system

Abstract

The present application provides a formation control method and formation system for lithium-ion batteries. The method includes: determining the film quality of the target lithium-ion battery; obtaining multiple formation data sets of the lithium-ion battery, the formation data sets including the historical film quality, SEI film impedance and interface charge transfer impedance corresponding to multiple formation moments of the formation process; determining the optimal film quality corresponding to each formation moment from the multiple formation data sets according to the constraint conditions, and obtaining the expected film quality corresponding to each formation moment, the constraint conditions including: the SEI film impedance corresponding to the historical film quality at each formation moment is less than a first threshold, and the interface charge transfer impedance corresponding to the historical film quality at each formation moment is less than a second threshold; when the deviation between the film quality and the expected film quality does not meet the predetermined requirements, adjusting the target parameters according to the parameter adjustment sequence corresponding to the deviation, so that the deviation corresponding to the formation process after the target parameters are adjusted meets the predetermined requirements.

Description

Technical Field

[0001] The present application relates to the field of lithium-ion battery formation, and in particular to a lithium-ion battery formation control method and a formation system. Background Art

[0002] The formation process is used to form a SEI (Solid Electrolyte Interface) film at the negative electrode of the battery cell during the first charging process. The quality of the SEI film directly determines the short-term electrical performance and long-term cycle / storage performance of the battery cell, and is a prerequisite for the stability of the battery cell's electrical performance.

[0003] The existing formation process usually uses a constant 2-3 stage current charging, and the negative pressure is continuously drawn during the process to remove the gas produced during the film formation process. In the mass production process from powder feeding to conversion into battery cells, there will inevitably be differences in material batches and accumulation of dimensional tolerances, resulting in performance differences between battery cells. The existing formation process is obviously unable to adapt to the differences between battery cells, exacerbating the differences in the formation of SEI films between battery cells in the formation process, thereby exacerbating the problem of inconsistent electrical performance of the battery cells. Summary of the invention

[0004] The main purpose of the present application is to provide a formation control method and a formation system for a lithium-ion battery, so as to at least solve the problem of large differences in the formation of SEI films in the formation process of the prior art.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a formation control method for a lithium-ion battery is provided, comprising: determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process; obtaining multiple formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to multiple formation moments of the formation process; determining the optimal film quality corresponding to each formation moment from the multiple formation data sets according to constraints, and obtaining the expected film quality corresponding to each formation moment, wherein the constraints include: the historical film quality at each formation moment The corresponding SEI film impedance is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each formation moment is less than a second threshold value; when the deviation between the film quality and the expected film quality does not meet the predetermined requirements, the target parameters are adjusted according to the parameter adjustment sequence corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment sequence is the adjustment sequence of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film quality.

[0006] Optionally, the formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold.

[0007] Optionally, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the rate of change of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; inputting multiple formation data sets into the planning model, and according to the constraint conditions, determining the optimal solution for each formation moment, to obtain the optimal film quality corresponding to multiple formation moments.

[0008] Optionally, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method further includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation.

[0009] Optionally, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining, according to the film-forming reaction equation of the formation process, that the formation process parameters include formation current, remaining power and formation temperature; after obtaining the expected film-forming quality corresponding to each formation moment, before adjusting the target parameter according to the parameter adjustment sequence corresponding to the deviation, the method further includes: when the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; when the deviation is greater than the sixth threshold, determining that the target parameter includes the formation temperature, the remaining power and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power and the formation temperature in sequence.

[0010] Optionally, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0011] In addition to the value ranges described above, those skilled in the art can flexibly set the value ranges of the first threshold, the second threshold, and the third threshold according to design requirements.

[0012] Optionally, determining the film quality of a target lithium-ion battery includes: obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameters and the film quality; and determining the film quality corresponding to the actual parameter value based on the film quality prediction model and the actual parameter value.

[0013] Optionally, a film quality prediction model is established, including: obtaining a training data set, the training data set including multiple groups of training data, each group of training data including: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; establishing an initial prediction model; and adjusting model parameters of the initial prediction model according to the training data set to obtain the film quality prediction model.

[0014] Optionally, before determining the film formation quality of the target lithium-ion battery, the method further includes: determining, based on the P2D theoretical model of the target lithium-ion battery, that the evaluation parameters of the film formation quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage.

[0015] According to another aspect of the present application, a lithium-ion battery formation system is provided, comprising: a lithium-ion battery formation device for executing a formation process of the lithium-ion battery; a control device for the formation device, comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the methods described.

[0016] By applying the technical solution of the present application, the expected film-forming quality at each formation moment in the formation process is determined from multiple formation data sets, and according to the deviation between the actual film-forming quality of the lithium-ion battery in the formation process and the expected film-forming quality, the target parameters affecting the film-forming quality are adjusted in a parameter adjustment order, so that the adjusted deviation meets the predetermined requirements, that is, the adjusted SEI film-forming quality is close to the expected film-forming quality, thereby realizing online regulation of the SEI film-forming quality during the formation of the lithium-ion battery, ensuring a high consistency in the SEI film-forming quality of different battery cells, solving the problem of large differences in the film-forming of the SEI film during the formation process of the prior art, and thus ensuring good consistency in the electrical performance of the battery cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A schematic flow chart of a formation control method for a lithium-ion battery provided in accordance with an embodiment of the present application is shown;

[0019] Figure 2 A structural block diagram of a formation control device for a lithium-ion battery provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] As introduced in the background technology, the formation of SEI film in the formation process of the prior art has great differences. In order to solve the above technical problems, the embodiments of the present application provide a formation control method and a formation system for a lithium-ion battery.

[0022] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0023] In this embodiment, a formation control method for a lithium-ion battery running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 11 is a flow chart of a formation control method for a lithium-ion battery according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0025] Step S201, determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0026] Specifically, the film quality refers to the actual quality of the formed SEI film.

[0027] Step S202, obtaining a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0028] Specifically, in the formation data set, each formation moment corresponds to a data set including historical film quality, SEI film impedance and interface charge transfer impedance; different formation data sets correspond to the same formation moment, for example, multiple formation data sets include the first formation moment, the second formation moment, ..., the nth formation moment, etc. Therefore, in multiple formation data sets, each formation moment corresponds to multiple data sets including historical film quality, SEI film impedance and interface charge transfer impedance.

[0029] Step S203, according to the constraint conditions, determining the optimal film quality corresponding to each of the formation moments from the plurality of the formation data sets, and obtaining the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0030] Specifically, among multiple data groups corresponding to a formation moment, the historical film quality in the data group satisfying that the SEI film impedance is less than the first threshold and the interface charge transfer impedance is less than the second threshold is the optimal film quality corresponding to the formation moment.

[0031] Step S204, when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, adjust the target parameters according to the parameter adjustment order corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0032] Specifically, the magnitude of the deviation is different, and the corresponding chemical formation process parameters to be adjusted are also different.

[0033] Through the embodiment, the film quality of the target lithium-ion battery in the formation process is first determined; then, multiple formation data sets of the lithium-ion battery are obtained, each of which includes the historical film quality, SEI film impedance and interface charge transfer impedance of the lithium-ion battery at multiple formation moments in the formation process; then, according to the constraint conditions, the optimal film quality corresponding to the multiple formation moments of the formation process is determined from the multiple formation data sets to obtain the expected film quality at the multiple formation moments, and the constraint conditions include that the SEI film impedance corresponding to the historical film quality at each formation moment is less than a first threshold value and the corresponding interface charge transfer impedance is less than a second threshold value; finally, when the deviation between the film quality of the target lithium-ion battery and the expected film quality does not meet the predetermined requirements, according to the parameter adjustment sequence, the target parameters affecting the film quality are adjusted in sequence so that the adjusted deviation meets the predetermined requirements. The present application determines the expected film-forming quality at each formation moment in the formation process from a plurality of formation data sets, and adjusts the target parameters affecting the film-forming quality according to the parameter adjustment sequence according to the deviation between the actual film-forming quality of the lithium-ion battery in the formation process and the expected film-forming quality, so that the deviation after adjustment meets the predetermined requirements, that is, the adjusted SEI film-forming quality is close to the expected film-forming quality, thereby realizing the online regulation of the SEI film-forming quality during the formation process of the lithium-ion battery, ensuring the high consistency of the SEI film-forming quality of different battery cells, solving the problem of large differences in the film-forming of the SEI film during the formation process of the prior art, and thus ensuring the good consistency of the electrical performance of the battery cells.

[0034] In an optional solution, the formation conditions of any two of the formation data sets are different, the formation data set also includes the formation gas production data corresponding to the multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than the third threshold. In other words, this application determines the change of the expected film quality under the optimal conditions with the formation moment based on the principles of stable change of formation gas production data, small SEI film impedance and small interface charge transfer impedance.

[0035] Specifically, different working conditions (such as different charging rates, formation negative pressures, and states of charge, etc.) are applied to the battery for formation, and formation data sets under different formation conditions are collected to obtain multiple formation data sets. Among them, different charging rates can be selected from 0.01C (characterizing that the battery is charged at a rate of 0.01 times its rated capacity per hour), 0.02C (characterizing that the battery is charged at a rate of 0.02 times its rated capacity per hour) and 0.1C (characterizing that the battery is charged at a rate of 0.1 times its rated capacity per hour), etc., different formation negative pressures can be selected from -60kPa, -70kPa and -80kPa, etc., and different states of charge can be selected from 6%, 15% and 30%, etc. Of course, the formation conditions are not limited to the charging rates, formation negative pressures and states of charge, and can also be other working conditions in the formation process. The specific data of the charging rate, the formation negative pressure and the state of charge are not limited to the data described above, and those skilled in the art can flexibly set the working conditions of the formation working condition and the specific values ​​of different formation working conditions according to actual conditions.

[0036] The gas production data of the chemical formation may specifically be the gas production rate of the chemical formation, which can be obtained by obtaining the gas production amount in the chemical formation process and then calculating the gas production rate based on the gas production amount. The change rate of the gas production data of the chemical formation is obtained by calculating the change rate of the gas production rate.

[0037] In addition, the SEI film impedance and the interface charge transfer impedance can be obtained by testing the EIS (Electrochemical Impedance Spectroscopy) spectrum of the lithium-ion battery and identifying the EIS spectrum.

[0038] Those skilled in the art can set specific values ​​of the first threshold, the second threshold and the third threshold according to actual needs, so as to select the historical film-forming quality corresponding to a data group from multiple data groups corresponding to each formation moment as the optimal film-forming quality.

[0039] In an optional solution, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0040] In order to further ensure that the optimal film quality corresponding to each formation moment can be determined relatively quickly, in some other optional embodiments of the present application, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the change rate of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; multiple formation data sets are input into the planning model, and according to the constraint conditions, the optimal solution of each formation moment is determined to obtain the optimal film quality corresponding to multiple formation moments. In this embodiment, the historical film quality is used as a variable, the weighted sum of the change rate of the formation gas production data, the SEI film impedance and the interface charge transfer impedance is minimized as the goal, a planning model is established, and the planning model is used to calculate the optimal solution for multiple formation data sets, so that the optimal film quality corresponding to each formation moment that satisfies the conditions of the most stable change rate of the formation gas production data, the smallest SEI film impedance and the smallest interface charge transfer impedance can be obtained quickly and efficiently.

[0041] Among them, in the objectives of the planning model, the weight values ​​of the change rate of the formation gas production data, the SEI film impedance and the interface charge transfer impedance can be the same or different. The specific numerical values ​​of the weight values ​​are not specifically limited in this application, and those skilled in the art can flexibly set them as needed.

[0042] In this embodiment, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method also includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation. Since each formation moment in the formation process corresponds to an expected film-forming quality, in order to further ensure that the control of the SEI film-forming quality is more accurate, the present application, after determining the expected film-forming qualities corresponding to multiple formation moments, and before adjusting the target parameters in the formation process, first determines the acquisition moment of the film-forming quality of the target lithium-ion battery as the target moment, and the expected film-forming quality corresponding to the target moment is the target expected quality, thereby determining the target expected quality as the expected film-forming quality corresponding to the film-forming quality, and calculating the difference between the film-forming quality and the target expected quality as the deviation, thereby ensuring that the determined deviation is more accurate, thereby further ensuring that the regulation of the SEI film-forming quality according to the deviation is more accurate, thereby further ensuring that the SEI film-forming quality of different battery cells after adjustment has a high consistency.

[0043] According to some further exemplary schemes of the present application, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining the formation process parameters including formation current, remaining power and formation temperature according to the film formation reaction equation of the formation process. This embodiment identifies factors affecting the film formation quality of the SEI film based on the film formation reaction equation of the SEI film in the formation process, and obtains the formation process parameters including formation current, remaining power and formation temperature, thereby ensuring that the determined formation process parameters are relatively accurate, and facilitating the subsequent efficient and accurate adjustment of the film formation quality according to these formation process parameters.

[0044] On this basis, after obtaining the expected film quality corresponding to each of the formation moments, and before adjusting the parameter adjustment sequence corresponding to the deviation situation and before adjusting the target parameter, the method further includes:

[0045] Step S205: when the deviation is greater than a fourth threshold value and less than or equal to a fifth threshold value, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence;

[0046] Specifically, when the deviation is greater than the fourth threshold and less than or equal to the fifth threshold, it indicates that the deviation is small, and at this time, the target parameters are determined to include the formation current and the remaining power, but not the formation temperature.

[0047] Step S206: when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameters include the formation temperature and the formation current, and determining that the parameter adjustment order is to adjust the formation current and the formation temperature in sequence;

[0048] Specifically, when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, it indicates that the deviation is relatively large. At this time, the target parameters are determined to include the formation temperature and the formation current, but not the remaining power.

[0049] Step S207: When the deviation is greater than the sixth threshold, determining that the target parameters include the formation temperature, the remaining power and the formation current, and determining the parameter adjustment order to adjust the formation current, the remaining power and the formation temperature in sequence.

[0050] Specifically, when the deviation is greater than the sixth threshold, it indicates that the deviation is very large, and at this time, the target parameters determined include the formation current, the remaining power, and the formation temperature.

[0051] In the described embodiment, the predetermined requirements include a fourth threshold, a fifth threshold, and a sixth threshold. The adjustment of the formation process is divided into three stages according to the size of the deviation. When the deviation is greater than the fourth threshold but not greater than the fifth threshold, the first stage is entered. Compared with the predetermined requirements, the deviation of the film quality in this stage is not large. At this time, the target parameters are determined to include the formation current and the remaining power, and it is determined that the target parameters are adjusted in the order of adjusting the formation current and the remaining power in sequence; when the deviation value is greater than the fifth threshold but not greater than the sixth threshold, the second stage is entered. Compared with the predetermined requirements, the deviation of the film quality in this stage is large. At this time, the target parameters are determined to include the formation current and the formation temperature, and it is determined that the formation current and the remaining power are adjusted in sequence. The target parameters are adjusted in the order of formation current and formation temperature; and when the deviation value is greater than the sixth threshold value, the third stage is entered. Compared with the predetermined requirement, the film formation quality deviation in this stage is greater. At this time, the target parameters are determined to include formation temperature, remaining power and formation current, and it is determined that the target parameters are adjusted in the order of adjusting formation current, remaining power and formation temperature in sequence. By dividing the adjustment of the formation process into stages and determining the target parameters corresponding to each stage and the parameter adjustment sequence, the deviation can be efficiently and quickly adjusted to no more than the fourth threshold value, thereby further ensuring that the film formation quality of the formation process is relatively stable and the effect is better, thereby further ensuring that the electrical performance consistency between battery cells is better.

[0052] Specifically, in each adjustment stage, the sizes of multiple target parameters in the formation process are adjusted in turn according to the parameter adjustment order, and after each target parameter is adjusted, it is determined whether the deviation meets the predetermined requirements. By cyclically adjusting multiple target parameters, closed-loop fine-tuning of the film quality is achieved.

[0053] In addition, step S201: determining the film quality of the target lithium-ion battery includes: obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameter and the film quality; and determining the film quality corresponding to the actual parameter value according to the film quality prediction model and the actual parameter value. In this embodiment, by analyzing the actual parameter value of the formation process parameter through the film quality prediction model, a more accurate film quality corresponding to the actual parameter value can be obtained, so as to provide more accurate data support for the process parameters of the subsequent formation process.

[0054] The formation process parameters involved in the film quality prediction model include at least the following parts: formation current, remaining power and formation temperature.

[0055] The film quality prediction model can be any suitable prediction model. In the embodiment of the present application, the film quality prediction model is established, including: obtaining a training data set, the training data set includes multiple groups of training data, each group of the training data includes: the historical parameter values ​​of the formation process parameters, and the historical film quality of the lithium-ion battery formed using the historical parameter values; establishing an initial prediction model; according to the training data set, adjusting the model parameters of the initial prediction model to obtain the film quality prediction model. In this embodiment, the film quality prediction model is obtained by establishing a prediction model and training the model using the training data set. During the training process, the prediction model can automatically complete some repetitive tasks by learning the patterns and rules in the data, thereby improving the efficiency and accuracy of film quality prediction.

[0056] The prediction model includes one or a coupling of machine learning models, deep learning models and semi-empirical models, specifically including but not limited to linear regression models, logistic regression models, support vector machine (SVM) models, decision tree models and random forest models.

[0057] Optionally, before determining the film quality of the target lithium-ion battery, the method further includes: according to the P2D theoretical model of the target lithium-ion battery, determining that the evaluation parameters of the film quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, integral value of the battery voltage differential capacity to voltage. In other words, the film quality is characterized by at least one of the battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage. The present application is based on the electrochemical reaction mechanism of lithium-ion batteries and identifies the evaluation parameters of film quality through the P2D model, wherein the P2D model uses diffusion equations and current equations to describe the charge and current distribution in the electrode, and can obtain evaluation parameters that can more accurately evaluate the film quality.

[0058] The performance data comparison table of the lithium ion battery obtained by the method of the present application and the lithium ion battery obtained by the existing process is shown in Table 1.

[0059] Table 1

[0060]

[0061] It can be seen from Table 1 that, compared with the prior art, the method of the present application can ensure the stability and consistency of the film quality of different lithium-ion batteries, thereby improving the consistency of the electrical performance of the battery cells.

[0062] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the formation control method of the lithium-ion battery of the present application will be described in detail below in conjunction with specific embodiments.

[0063] This embodiment relates to a specific formation control method for a lithium ion battery, the method comprising the following steps:

[0064] Step S1: setting the initial formation current and negative pressure, charging and forming the battery cell, and measuring the current and voltage data in real time;

[0065] Step S2: Based on the electrochemical reaction mechanism, the characteristic quantity that affects the quality of SEI film formation when participating in the electrochemical reaction of the battery cell is identified according to the P2D theoretical model, which is also called the evaluation parameter of film formation quality, and the peak value of the battery DC internal resistance, battery capacity, battery voltage differential capacity and the integral value of the battery voltage differential capacity to the voltage are identified;

[0066] Step S3: Comprehensively considering SEI film impedance, interface charge transfer impedance and formation gas production data, offline calibrating the expected film quality at each formation moment in the formation process, and determining the expected film quality curve under the optimal conditions based on the principle that the gas production rate curve is the most stable and the SEI film impedance and interface charge transfer impedance are the smallest;

[0067] Step S4: based on the SEI film formation reaction equation, extract the formation process parameters that affect the film formation quality, and obtain the formation current, residual power and formation temperature;

[0068] Step S5: Establish a prediction model, train the prediction model according to the formation process parameters and the corresponding film quality, and obtain a film quality prediction model, wherein the data training model is collected during the initial trial run of the production line, and the model is optimized by continuously collecting data during the mass production process. The prediction model can use machine learning + deep learning AI algorithms;

[0069] Step S6: Based on the film quality prediction model, the film quality of the lithium-ion battery in the formation process is predicted in seconds, and the deviation between the film quality and the expected film quality is monitored, and at least part of the formation process parameters are closed-loop fine-tuned according to the deviation in the parameter adjustment sequence until the formation process is completed.

[0070] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0071] The present application embodiment also provides a kind of formation control device of lithium ion battery, it should be noted that the formation control device of the lithium ion battery of the present application embodiment can be used for executing the formation control method for lithium ion battery provided by the present application embodiment.This device is used to realize the described embodiment and preferred implementation mode, and the description has been made no more.As used below, the term "module" can realize the combination of software and / or hardware of predetermined function.Although the device described in the following embodiments is preferably realized with software, the realization of hardware, or the combination of software and hardware is also possible and conceived.

[0072] The formation control device for a lithium-ion battery provided in an embodiment of the present application is introduced below.

[0073] Figure 2 Schematic diagram of a formation control device for a lithium-ion battery according to an embodiment of the present application. Figure 2 As shown, the device comprises:

[0074] A first determination unit 10 is used to determine the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0075] Specifically, the film quality refers to the actual quality of the formed SEI film.

[0076] An acquisition unit 20 is used to acquire a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0077] Specifically, in the formation data set, each formation moment corresponds to a data set including historical film quality, SEI film impedance and interface charge transfer impedance; different formation data sets correspond to the same formation moment, for example, multiple formation data sets include the first formation moment, the second formation moment, ..., the nth formation moment, etc. Therefore, in multiple formation data sets, each formation moment corresponds to multiple data sets including historical film quality, SEI film impedance and interface charge transfer impedance.

[0078] A second determination unit 30 is used to determine the optimal film quality corresponding to each of the formation moments from the plurality of formation data sets according to a constraint condition, and obtain the expected film quality corresponding to each of the formation moments, wherein the constraint condition includes: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0079] Specifically, among multiple data groups corresponding to a formation moment, the historical film quality in the data group satisfying that the SEI film impedance is less than the first threshold and the interface charge transfer impedance is less than the second threshold is the optimal film quality corresponding to the formation moment.

[0080] The adjustment unit 40 is used to adjust the target parameters according to the parameter adjustment order corresponding to the deviation when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0081] Specifically, the magnitude of the deviation is different, and the corresponding chemical formation process parameters to be adjusted are also different.

[0082] According to the embodiment, the film quality of the target lithium-ion battery in the formation process is determined by the first determination unit; a plurality of formation data sets of the lithium-ion battery are obtained by the acquisition unit, each of which includes the historical film quality, SEI film impedance and interface charge transfer impedance of the lithium-ion battery at multiple formation moments in the formation process; the optimal film quality corresponding to multiple formation moments of the formation process is determined from the plurality of formation data sets by the second determination unit according to the constraint conditions, and the expected film quality at multiple formation moments is obtained, and the constraint conditions include that the SEI film impedance corresponding to the historical film quality at each formation moment is less than a first threshold value and the corresponding interface charge transfer impedance is less than a second threshold value; when the deviation between the film quality of the target lithium-ion battery and the expected film quality does not meet the predetermined requirements, the target parameters affecting the film quality are adjusted in sequence according to the parameter adjustment sequence, so that the adjusted deviation meets the predetermined requirements. The present application determines the expected film-forming quality at each formation moment in the formation process from a plurality of formation data sets, and adjusts the target parameters affecting the film-forming quality according to the parameter adjustment sequence according to the deviation between the actual film-forming quality of the lithium-ion battery in the formation process and the expected film-forming quality, so that the deviation after adjustment meets the predetermined requirements, that is, the adjusted SEI film-forming quality is close to the expected film-forming quality, thereby realizing the online regulation of the SEI film-forming quality during the formation process of the lithium-ion battery, ensuring the high consistency of the SEI film-forming quality of different battery cells, solving the problem of large differences in the film-forming of the SEI film during the formation process of the prior art, and thus ensuring the good consistency of the electrical performance of the battery cells.

[0083] The formation control device of the lithium-ion battery includes a processor and a memory, wherein the first determination unit, the acquisition unit, the second determination unit, and the adjustment unit are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0084] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the formation control method of the lithium-ion battery.

[0085] Specifically, the formation control method of a lithium-ion battery includes:

[0086] Step S201, determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0087] Specifically, the film quality refers to the actual quality of the formed SEI film.

[0088] Step S202, obtaining a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0089] Specifically, in the formation data set, each formation moment corresponds to a data set including historical film quality, SEI film impedance and interface charge transfer impedance; different formation data sets correspond to the same formation moment, for example, multiple formation data sets include the first formation moment, the second formation moment, ..., the nth formation moment, etc. Therefore, in multiple formation data sets, each formation moment corresponds to multiple data sets including historical film quality, SEI film impedance and interface charge transfer impedance.

[0090] Step S203, according to the constraint conditions, determining the optimal film quality corresponding to each of the formation moments from the plurality of the formation data sets, and obtaining the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0091] Specifically, among multiple data groups corresponding to a formation moment, the historical film quality in the data group satisfying that the SEI film impedance is less than the first threshold and the interface charge transfer impedance is less than the second threshold is the optimal film quality corresponding to the formation moment.

[0092] Step S204, when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, adjust the target parameters according to the parameter adjustment order corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0093] Specifically, the magnitude of the deviation is different, and the corresponding chemical formation process parameters to be adjusted are also different.

[0094] Optionally, the formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold.

[0095] Optionally, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the rate of change of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; inputting multiple formation data sets into the planning model, and according to the constraint conditions, determining the optimal solution for each formation moment, to obtain the optimal film quality corresponding to multiple formation moments.

[0096] Optionally, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method further includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation.

[0097] Optionally, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining, according to the film-forming reaction equation of the formation process, that the formation process parameters include formation current, remaining power and formation temperature; after obtaining the expected film-forming quality corresponding to each formation moment, before adjusting the target parameter according to the parameter adjustment sequence corresponding to the deviation, the method further includes: when the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; when the deviation is greater than the sixth threshold, determining that the target parameter includes the formation temperature, the remaining power and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power and the formation temperature in sequence.

[0098] Optionally, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0099] In addition to the value ranges described above, those skilled in the art can flexibly set the value ranges of the first threshold, the second threshold, and the third threshold according to design requirements.

[0100] Optionally, determining the film quality of a target lithium-ion battery includes: obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameters and the film quality; and determining the film quality corresponding to the actual parameter value based on the film quality prediction model and the actual parameter value.

[0101] Optionally, a film quality prediction model is established, including: obtaining a training data set, the training data set including multiple groups of training data, each group of training data including: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; establishing an initial prediction model; and adjusting model parameters of the initial prediction model according to the training data set to obtain the film quality prediction model.

[0102] Optionally, before determining the film formation quality of the target lithium-ion battery, the method further includes: determining, based on the P2D theoretical model of the target lithium-ion battery, that the evaluation parameters of the film formation quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage.

[0103] An embodiment of the present invention provides a processor, which is used to run a program, wherein the lithium-ion battery formation control method is executed when the program is run.

[0104] Specifically, the formation control method of a lithium-ion battery includes:

[0105] Step S201, determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0106] Specifically, the film quality refers to the actual quality of the formed SEI film.

[0107] Step S202, obtaining a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0108] Specifically, in the formation data set, each formation moment corresponds to a data set including historical film quality, SEI film impedance and interface charge transfer impedance; different formation data sets correspond to the same formation moment, for example, multiple formation data sets include the first formation moment, the second formation moment, ..., the nth formation moment, etc. Therefore, in multiple formation data sets, each formation moment corresponds to multiple data sets including historical film quality, SEI film impedance and interface charge transfer impedance.

[0109] Step S203, according to the constraint conditions, determining the optimal film quality corresponding to each of the formation moments from the plurality of the formation data sets, and obtaining the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0110] Specifically, among multiple data groups corresponding to a formation moment, the historical film quality in the data group satisfying that the SEI film impedance is less than the first threshold and the interface charge transfer impedance is less than the second threshold is the optimal film quality corresponding to the formation moment.

[0111] Step S204, when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, adjust the target parameters according to the parameter adjustment order corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0112] Specifically, the magnitude of the deviation is different, and the corresponding chemical formation process parameters to be adjusted are also different.

[0113] Optionally, the formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold.

[0114] Optionally, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the rate of change of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; inputting multiple formation data sets into the planning model, and according to the constraint conditions, determining the optimal solution for each formation moment, to obtain the optimal film quality corresponding to multiple formation moments.

[0115] Optionally, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method further includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation.

[0116] Optionally, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining, according to the film-forming reaction equation of the formation process, that the formation process parameters include formation current, remaining power and formation temperature; after obtaining the expected film-forming quality corresponding to each formation moment, before adjusting the target parameter according to the parameter adjustment sequence corresponding to the deviation, the method further includes: when the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; when the deviation is greater than the sixth threshold, determining that the target parameter includes the formation temperature, the remaining power and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power and the formation temperature in sequence.

[0117] Optionally, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0118] In addition to the value ranges described above, those skilled in the art can flexibly set the value ranges of the first threshold, the second threshold, and the third threshold according to design requirements.

[0119] Optionally, determining the film quality of a target lithium-ion battery includes: obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameters and the film quality; and determining the film quality corresponding to the actual parameter value based on the film quality prediction model and the actual parameter value.

[0120] Optionally, a film quality prediction model is established, including: obtaining a training data set, the training data set including multiple groups of training data, each group of training data including: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; establishing an initial prediction model; and adjusting model parameters of the initial prediction model according to the training data set to obtain the film quality prediction model.

[0121] Optionally, before determining the film formation quality of the target lithium-ion battery, the method further includes: determining, based on the P2D theoretical model of the target lithium-ion battery, that the evaluation parameters of the film formation quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage.

[0122] An embodiment of the present invention provides a lithium ion battery formation system, comprising:

[0123] The lithium-ion battery formation equipment is used to perform the lithium-ion battery formation process;

[0124] The control device of the formation device comprises one or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and when the one or more processors execute the one or more programs, at least the following steps are implemented:

[0125] Step S201, determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0126] Specifically, the film quality refers to the actual quality of the formed SEI film.

[0127] Step S202, obtaining a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0128] Specifically, in the formation data set, each formation moment corresponds to a data set including historical film quality, SEI film impedance and interface charge transfer impedance; different formation data sets correspond to the same formation moment, for example, multiple formation data sets include the first formation moment, the second formation moment, ..., the nth formation moment, etc. Therefore, in multiple formation data sets, each formation moment corresponds to multiple data sets including historical film quality, SEI film impedance and interface charge transfer impedance.

[0129] Step S203, according to the constraint conditions, determining the optimal film quality corresponding to each of the formation moments from the plurality of the formation data sets, and obtaining the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0130] Specifically, among multiple data groups corresponding to a formation moment, the historical film quality in the data group satisfying that the SEI film impedance is less than the first threshold and the interface charge transfer impedance is less than the second threshold is the optimal film quality corresponding to the formation moment.

[0131] Step S204, when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, adjust the target parameters according to the parameter adjustment order corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0132] Specifically, the magnitude of the deviation is different, and the corresponding chemical formation process parameters to be adjusted are also different.

[0133] Through the embodiments, in the formation system of the lithium ion battery, the formation process is performed by the formation equipment of the lithium ion battery, and the formation control method of the lithium ion battery is performed by the control equipment of the formation equipment. The method determines the expected film quality at each formation moment in the formation process from multiple formation data sets, and according to the deviation between the actual film quality of the lithium ion battery and the expected film quality in the formation process, the target parameters affecting the film quality are adjusted according to the parameter adjustment sequence, so that the adjusted deviation meets the predetermined requirements, that is, the adjusted SEI film quality approaches the expected film quality, and the online regulation of the SEI film quality in the formation process of the lithium ion battery is realized, which ensures that the consistency of the SEI film quality of different battery cells is high, solves the problem of large film formation differences of the SEI film in the formation process of the prior art, and thus ensures that the electrical performance consistency of the battery cells prepared by the formation system is good.

[0134] The control device in this article can be a server, PC, PAD, mobile phone, etc.

[0135] Optionally, the formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold.

[0136] Optionally, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the rate of change of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; inputting multiple formation data sets into the planning model, and according to the constraint conditions, determining the optimal solution for each formation moment, to obtain the optimal film quality corresponding to multiple formation moments.

[0137] Optionally, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method further includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation.

[0138] Optionally, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining, according to the film-forming reaction equation of the formation process, that the formation process parameters include formation current, remaining power and formation temperature; after obtaining the expected film-forming quality corresponding to each formation moment, before adjusting the target parameter according to the parameter adjustment sequence corresponding to the deviation, the method further includes: when the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; when the deviation is greater than the sixth threshold, determining that the target parameter includes the formation temperature, the remaining power and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power and the formation temperature in sequence.

[0139] Optionally, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0140] In addition to the value ranges described above, those skilled in the art can flexibly set the value ranges of the first threshold, the second threshold, and the third threshold according to design requirements.

[0141] Optionally, determining the film quality of a target lithium-ion battery includes: obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameters and the film quality; and determining the film quality corresponding to the actual parameter value based on the film quality prediction model and the actual parameter value.

[0142] Optionally, a film quality prediction model is established, including: obtaining a training data set, the training data set including multiple groups of training data, each group of training data including: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; establishing an initial prediction model; and adjusting model parameters of the initial prediction model according to the training data set to obtain the film quality prediction model.

[0143] Optionally, before determining the film formation quality of the target lithium-ion battery, the method further includes: determining, based on the P2D theoretical model of the target lithium-ion battery, that the evaluation parameters of the film formation quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage.

[0144] The present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement at least the following method steps:

[0145] Step S201, determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process;

[0146] Step S202, obtaining a plurality of formation data sets of the lithium-ion battery, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to a plurality of formation moments of the formation process;

[0147] Step S203, according to the constraint conditions, determining the optimal film quality corresponding to each of the formation moments from the plurality of the formation data sets, and obtaining the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value;

[0148] Step S204, when the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, adjust the target parameters according to the parameter adjustment order corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment order is the adjustment order of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality.

[0149] Optionally, the formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to multiple formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold.

[0150] Optionally, according to the constraint conditions, the optimal film quality corresponding to each formation moment is determined from multiple formation data sets, including: establishing a planning model, the variable of the planning model is the historical film quality, the goal of the planning model is to minimize the weighted sum of the rate of change of the formation gas production data, the SEI film impedance and the interface charge transfer impedance at the same formation moment; inputting multiple formation data sets into the planning model, and according to the constraint conditions, determining the optimal solution for each formation moment, to obtain the optimal film quality corresponding to multiple formation moments.

[0151] Optionally, after obtaining the expected film formation quality corresponding to each of the formation moments, and before adjusting the target parameters according to the parameter adjustment order corresponding to the deviation situation, the method further includes: determining the formation moment corresponding to the film formation quality as the target moment, and determining the expected film formation quality corresponding to the target moment as the target expected quality, the target expected quality being the expected film formation quality corresponding to the film formation quality; calculating the difference between the film formation quality and the target expected quality to obtain the deviation situation.

[0152] Optionally, before obtaining the actual parameter value of the formation process parameter of the target lithium-ion battery, the method further includes: determining, according to the film-forming reaction equation of the formation process, that the formation process parameters include formation current, remaining power and formation temperature; after obtaining the expected film-forming quality corresponding to each formation moment, before adjusting the target parameter according to the parameter adjustment sequence corresponding to the deviation, the method further includes: when the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; when the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; when the deviation is greater than the sixth threshold, determining that the target parameter includes the formation temperature, the remaining power and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power and the formation temperature in sequence.

[0153] Optionally, the value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

[0154] In addition to the value ranges described above, those skilled in the art can flexibly set the value ranges of the first threshold, the second threshold, and the third threshold according to design requirements.

[0155] Optionally, determining the film quality of a target lithium-ion battery includes: obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the formation process parameters and the film quality; and determining the film quality corresponding to the actual parameter value based on the film quality prediction model and the actual parameter value.

[0156] Optionally, a film quality prediction model is established, including: obtaining a training data set, the training data set including multiple groups of training data, each group of training data including: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; establishing an initial prediction model; and adjusting model parameters of the initial prediction model according to the training data set to obtain the film quality prediction model.

[0157] Optionally, before determining the film formation quality of the target lithium-ion battery, the method further includes: determining, based on the P2D theoretical model of the target lithium-ion battery, that the evaluation parameters of the film formation quality include at least one of the following: battery DC internal resistance, battery capacity, peak value of battery voltage differential capacity, and integral value of the battery voltage differential capacity to voltage.

[0158] From the above description, it can be seen that the embodiments described in this application achieve the following technical effects:

[0159] The formation control method of a lithium-ion battery of the present application first determines the film quality of a target lithium-ion battery in a formation process; then, obtains multiple formation data sets of the lithium-ion battery, each of which includes historical film quality, SEI film impedance and interface charge transfer impedance at multiple formation moments of the lithium-ion battery in the formation process; then, according to constraint conditions, determines the optimal film quality corresponding to multiple formation moments of the formation process from the multiple formation data sets, and obtains the expected film quality at multiple formation moments, and the constraint conditions include that the SEI film impedance corresponding to the historical film quality at each formation moment is less than a first threshold value and the corresponding interface charge transfer impedance is less than a second threshold value; finally, when the deviation between the film quality of the target lithium-ion battery and the expected film quality does not meet the predetermined requirements, according to the parameter adjustment sequence, the target parameters affecting the film quality are adjusted in sequence, so that the adjusted deviation meets the predetermined requirements. The present application determines the expected film-forming quality at each formation moment in the formation process from a plurality of formation data sets, and adjusts the target parameters affecting the film-forming quality according to the parameter adjustment sequence according to the deviation between the actual film-forming quality of the lithium-ion battery in the formation process and the expected film-forming quality, so that the deviation after adjustment meets the predetermined requirements, that is, the adjusted SEI film-forming quality is close to the expected film-forming quality, thereby realizing the online regulation of the SEI film-forming quality during the formation process of the lithium-ion battery, ensuring the high consistency of the SEI film-forming quality of different battery cells, solving the problem of large differences in the film-forming of the SEI film during the formation process of the prior art, and thus ensuring the good consistency of the electrical performance of the battery cells.

[0160] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A formation control method for a lithium ion battery, characterized in that: include: Determining the film quality of a target lithium-ion battery, wherein the target lithium-ion battery is a lithium-ion battery in a formation process; Acquire multiple formation data sets of lithium-ion batteries, wherein the formation data sets include historical film quality, SEI film impedance, and interface charge transfer impedance corresponding to multiple formation moments of the formation process; According to the constraint conditions, the optimal film quality corresponding to each of the formation moments is determined from the plurality of the formation data sets to obtain the expected film quality corresponding to each of the formation moments, wherein the constraint conditions include: the SEI film impedance corresponding to the historical film quality at each of the formation moments is less than a first threshold value, and the interface charge transfer impedance corresponding to the historical film quality at each of the formation moments is less than a second threshold value; In the case where the deviation between the film forming quality and the expected film forming quality does not meet the predetermined requirements, the target parameters are adjusted according to the parameter adjustment sequence corresponding to the deviation, so that the deviation corresponding to the formation process after adjusting the target parameters meets the predetermined requirements, the target parameters are the formation process parameters to be adjusted corresponding to the deviation, the parameter adjustment sequence is the adjustment sequence of the target parameters, and the formation process parameters are the process parameters in the formation process that affect the film forming quality. The formation conditions of any two of the formation data sets are different, the formation data set also includes formation gas production data corresponding to a plurality of the formation moments of the formation process, and the constraint condition also includes: the change rate of the formation gas production data corresponding to the historical film quality at each formation moment is less than a third threshold value, According to the constraint conditions, determining the optimal film quality corresponding to each formation moment from the plurality of formation data sets includes: Establishing a planning model, wherein the variable of the planning model is the historical film quality, and the goal of the planning model is to minimize the weighted sum of the change rate of the formation gas production data, the SEI film impedance, and the interface charge transfer impedance at the same formation time; Inputting a plurality of the formation data sets into the planning model, and determining the optimal solution of each formation time according to the constraint conditions, and obtaining the optimal film quality corresponding to the plurality of formation times, Before obtaining the actual parameter values ​​of the formation process parameters of the target lithium-ion battery, the method further includes: determining the formation process parameters including formation current, remaining power and formation temperature according to the film forming reaction equation of the formation process, After obtaining the expected film quality corresponding to each of the formation moments, and before adjusting the parameter adjustment sequence according to the deviation situation and before adjusting the target parameter, the method further includes: When the deviation is greater than a fourth threshold and less than or equal to a fifth threshold, determining that the target parameter includes the formation current and the remaining power, and determining that the parameter adjustment sequence is to adjust the formation current and the remaining power in sequence; When the deviation is greater than the fifth threshold and less than or equal to the sixth threshold, determining that the target parameter includes the formation temperature and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current and the formation temperature in sequence; When the deviation is greater than the sixth threshold, determining that the target parameters include the formation temperature, the remaining power, and the formation current, and determining that the parameter adjustment sequence is to adjust the formation current, the remaining power, and the formation temperature in sequence, Determine the film quality of the target lithium-ion battery, including: Obtaining actual parameter values ​​of the formation process parameters of the target lithium-ion battery; Establishing a film quality prediction model, wherein the film quality prediction model is a model that characterizes the corresponding relationship between the chemical formation process parameters and the film quality; The film quality corresponding to the actual parameter value is determined according to the film quality prediction model and the actual parameter value.

2. The method according to claim 1, characterized in that After obtaining the expected film quality corresponding to each of the formation moments, and before adjusting the parameter adjustment sequence corresponding to the deviation situation and before adjusting the target parameter, the method further includes: Determine the formation time corresponding to the film formation quality as a target time, and determine the expected film formation quality corresponding to the target time as a target expected quality, wherein the target expected quality is the expected film formation quality corresponding to the film formation quality; The difference between the film forming quality and the target expected quality is calculated to obtain the deviation.

3. The method according to claim 1, characterized in that The value range of the first threshold is 0.5Ω±5%, the value range of the second threshold is 2Ω±5%, and the value range of the third threshold is 16mL / V±5%.

4. The method according to claim 1, characterized in that: Establish a film quality prediction model, including: Acquire a training data set, wherein the training data set includes multiple sets of training data, and each set of the training data includes: historical parameter values ​​of the formation process parameters, and historical film quality of lithium-ion batteries formed using the historical parameter values; Build an initial forecasting model; According to the training data set, the model parameters of the initial prediction model are adjusted to obtain the film quality prediction model.

5. A lithium ion battery formation system, characterized in that: include: The lithium-ion battery formation equipment is used to perform the lithium-ion battery formation process; The control device of the formation device includes one or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 4.

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