Battery cell performance parameter prediction method and apparatus, and electronic device

Abstract

Disclosed in the present application are a battery cell performance parameter prediction method and apparatus, and an electronic device. The method comprises: acquiring a target slurry, wherein the target slurry is used for constructing a battery cell of a target type; determining test data corresponding to the target slurry under experimental parameters, wherein the test data comprises impedance test data; inputting the impedance test data into an equivalent circuit model and performing fitting, so as to obtain a plurality of circuit parameter values, wherein the equivalent circuit model is constructed on the basis of the battery cell of the target type; and on the basis of the plurality of circuit parameter values, predicting performance parameters of a battery cell manufactured using the target slurry under the experimental parameters. The present application solves the technical problem in the related art of it being difficult to conveniently determine battery-cell-related performance parameters on the basis of a slurry.

Description

Methods, devices and electronic equipment for predicting battery cell performance parameters

[0001] This application claims priority to Chinese Patent Application No. 202411843309.7, filed on December 13, 2024, entitled “Method, Apparatus and Electronic Equipment for Predicting Battery Cell Performance Parameters”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of batteries, and more specifically, to a method, apparatus, and electronic device for predicting battery cell performance parameters. Background Technology

[0003] Lithium-ion batteries consist of a positive electrode, a negative electrode, and an electrolyte, and the conductivity of the electrode slurry is an important indicator for evaluating electrode performance. Conductivity refers to a material's ability to conduct electric current, and the conductivity of each component in the battery directly affects the battery's capacity and rate performance.

[0004] The conductivity of electrode slurries is generally used to evaluate their conductivity. Currently, for testing the resistivity of conductive slurries in battery materials, Chinese patent CN108303592A discloses a method for testing the conductivity of lithium-ion battery electrode coating layers, and Chinese patent CN108226641A discloses a method for testing the conductivity of lithium-ion battery cathode materials. However, the internal composition of conductive slurries in lithium-ion battery electrodes is complex, and the aforementioned traditional methods cannot quickly obtain data on the internal conductive network. This makes it impossible to determine the composition of the conductive network within the slurry, and further hinders the screening of conductive agent types and contents, as well as the content of main materials. This makes the screening of electrode slurry formulations cumbersome and inefficient, and presents a technical problem of difficulty in conveniently determining cell-related performance parameters based on the slurry.

[0005] There is currently no effective solution to the above problems. Summary of the Invention

[0006] This disclosure provides a method, apparatus, and electronic device for predicting battery cell performance parameters, thereby at least solving the technical problem in the related art that it is difficult to conveniently determine the performance parameters related to the battery cell based on the paste.

[0007] According to one aspect of the present disclosure, a method for predicting battery cell performance parameters is provided, comprising: obtaining a target paste, wherein the target paste is used to construct a battery cell of a target type; determining test data corresponding to the target paste under experimental parameters, wherein the test data includes impedance test data; inputting the impedance test data into an equivalent circuit model for fitting to obtain multiple circuit parameter values, wherein the equivalent circuit model is constructed based on the battery cell of the target type, and the equivalent circuit model includes four sub-circuits, the first sub-circuit including a charge transfer resistor, the second sub-circuit being a solution resistor connected in parallel with a first phase constant element, the third sub-circuit being... The active material resistor is connected in parallel with the second phase-changing element. The fourth sub-circuit consists of a double-layer resistor and capacitor connected in parallel with the third phase-changing element. The first phase-changing element represents the interfacial characteristics between the binder and the solvent. The second phase-changing element represents the interfacial characteristics between the binder and the active material. The third phase-changing element represents the interfacial characteristics between the conductive agent and the active material. The double-layer resistor and capacitor are obtained by connecting the double-layer resistor and the double-layer capacitor in series. The four sub-circuits are connected in series in sequence. Based on the multiple circuit parameter values, the performance parameters of the battery cell made using the target slurry under the test parameters are predicted.

[0008] Optionally, predicting the performance parameters of a battery cell made using the target slurry under the test parameters based on the plurality of circuit parameter values ​​includes: determining the charge transfer efficiency performance between the solvent and the electrode material based on the fitted charge transfer resistance value; determining the impedance of the conductive path formed by the binder and the conductive material based on the fitted solution resistance value; determining the active material impedance of the active material inside the electrode material based on the fitted active material resistance value; determining the charge transport performance between the conductive agent and the active material based on the fitted double layer resistance value; determining the dispersion performance of each component inside the target slurry based on the fitted phase constant element value; and predicting the performance parameters of a battery cell made using the target slurry under the test parameters based on the charge transfer efficiency performance, the conductive path impedance, the active material impedance, the charge transport performance, and the dispersion performance.

[0009] Optionally, predicting the performance parameters of a battery cell made using the target slurry under the test parameters based on the charge transfer efficiency performance, the conductive path impedance, the active material impedance, the charge transport performance, and the dispersion performance includes: when the electrode material further includes a binder, and the fitted phase constant element value includes a first phase constant element value, a second phase constant element value, and a third phase constant element value; determining the first sub-contact performance between the binder and the solvent based on the first phase constant element value; determining the second sub-contact performance between the binder and the active material based on the second phase constant element value; determining the third sub-contact performance between the conductive agent and the active material based on the third phase constant element value; determining the contact performance corresponding to the electrode material based on the first sub-contact performance, the second sub-contact performance, and the third sub-contact performance; and predicting the performance parameters of a battery cell made using the target slurry under the test parameters based on the charge transfer efficiency performance, the conductive path impedance, the active material impedance, the charge transport performance, the dispersion performance, and the contact performance.

[0010] Optionally, determining the test data corresponding to the target slurry under the test parameters includes: transferring the target slurry to a predetermined test fixture, wherein the predetermined test fixture includes a target test tube, a first conductive electrode, and a second conductive electrode, the first conductive electrode being located on a first side of the target test tube, and the second conductive electrode being located on a second side of the target test tube; activating the predetermined test fixture under the test parameters to obtain the test data.

[0011] Optionally, the frequency band of the AC test current corresponding to the second sub-circuit is greater than the frequency band of the AC test current corresponding to the third sub-circuit, and the frequency band of the AC test current corresponding to the third sub-circuit is greater than the frequency band of the AC test current corresponding to the fourth sub-circuit.

[0012] Optionally, after predicting the performance parameters of the battery cell made using the target paste under the test parameters based on the plurality of circuit parameter values, the method further includes: if the performance parameters are less than a predetermined threshold, determining the composition parameters of the target paste; adjusting the composition parameters to obtain an updated paste, and determining the performance parameters corresponding to the updated paste.

[0013] Optionally, before inputting the impedance test data into the equivalent circuit model for fitting to obtain multiple circuit parameter values, the method further includes: obtaining a sample slurry and a sample battery constructed from the sample slurry, wherein the sample battery is a battery of the target type; determining the sample performance parameters of the sample battery; determining the correlation between the composition of the sample slurry and the sample performance parameters; and constructing the equivalent circuit model based on the correlation.

[0014] According to one aspect of the present disclosure, a battery cell performance parameter prediction device is provided, comprising: an acquisition module configured to acquire a target paste, wherein the target paste is used to construct a battery cell of a target type; a determination module configured to determine test data corresponding to the target paste under experimental parameters, wherein the test data includes impedance test data; and a fitting module configured to input the impedance test data into an equivalent circuit model for fitting to obtain multiple circuit parameter values, wherein the equivalent circuit model is constructed based on the battery cell of the target type, and the equivalent circuit model includes four sub-circuits, the first sub-circuit including a charge transfer resistor, the second sub-circuit being a solution resistor and a first phase constant element in parallel. The circuit consists of four sub-circuits: a third sub-circuit (the active material resistor and the second phase-constant element connected in parallel), a fourth sub-circuit (the double-layer resistor and capacitor connected in parallel with the third phase-constant element), a first phase-constant element representing the interfacial characteristics between the binder and the solvent, a second phase-constant element representing the interfacial characteristics between the binder and the active material, and a third phase-constant element representing the interfacial characteristics between the conductive agent and the active material. The double-layer resistor and capacitor are connected in series. The four sub-circuits are connected in series in sequence. The prediction module is configured to predict the performance parameters of the battery cell made using the target slurry under the test parameters based on the multiple circuit parameter values.

[0015] According to one aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory configured to store processor-executable instructions; wherein the processor is configured to execute the instructions to implement the cell performance parameter prediction method described in any of the preceding claims.

[0016] According to one aspect of the present disclosure, a computer-readable storage medium is provided that, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the cell performance parameter prediction method described in any of the preceding claims.

[0017] In this embodiment, a target slurry is obtained, which is used to construct a target type of battery cell. Test data corresponding to the target slurry under experimental parameters is determined, including impedance test data. The impedance test data is input into an equivalent circuit model for fitting, obtaining multiple circuit parameter values. The equivalent circuit model is constructed based on the target type of battery cell and includes four sub-circuits: a first sub-circuit includes a charge-movement resistor; a second sub-circuit is a solution resistor connected in parallel with a first phase-changing element; a third sub-circuit is an active material resistor connected in parallel with a second phase-changing element; and a fourth sub-circuit is an electric double-layer resistor-capacitor connected in parallel with a third phase-changing element. The first phase-changing element represents the interfacial characteristics between the binder and solvent; the second phase-changing element represents the interfacial characteristics between the binder and the active material; the third phase-changing element represents the interfacial characteristics between the conductive agent and the active material; and the electric double-layer resistor-capacitor is obtained by connecting an electric double-layer resistor and an electric double-layer capacitor in series. The four sub-circuits are connected in series sequentially. Based on the multiple circuit parameter values, the performance parameters of the battery cell made using the target slurry under the experimental parameters are predicted. Because it determined the test data corresponding to the target slurry under the test parameters, and then input the impedance test data into the equivalent circuit model for fitting, it obtained multiple circuit parameter values. By fitting the circuit parameter values, it predicted the performance parameters of the battery cell, thereby solving the technical problem in related technologies that it is difficult to conveniently determine the performance parameters related to the battery cell based on the slurry. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this disclosure and form part of this application, illustrate exemplary embodiments of this disclosure and are used to explain this disclosure, but do not constitute an undue limitation of this disclosure. In the drawings:

[0019] Figure 1 is a flowchart of a cell performance parameter prediction method according to an embodiment of the present disclosure.

[0020] Figure 2 is a schematic diagram of the test fixture provided in an optional embodiment of this disclosure.

[0021] Figure 3 is a schematic diagram of the slurry internal impedance fitting circuit provided in an optional embodiment of this disclosure.

[0022] Figure 4 is a comparison chart of slurry impedance data with different conductive agent contents provided by the optional embodiments of this disclosure.

[0023] Figure 5 shows the slurry internal impedance fitting data provided by an optional embodiment of this disclosure.

[0024] Figure 6 is a structural block diagram of a cell performance parameter prediction device according to an embodiment of the present disclosure. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Example 1

[0028] According to an embodiment of the present disclosure, an embodiment of a method for predicting battery cell performance parameters is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] Figure 1 is a flowchart of a cell performance parameter prediction method according to an embodiment of the present disclosure. As shown in Figure 1, the method includes the following steps:

[0030] Step S102: Obtain the target slurry, wherein the target slurry is used to construct the target type of battery cell;

[0031] In step S102 of this application, a target paste for constructing a target type of battery cell is obtained.

[0032] This involves target slurries. In lithium-ion battery manufacturing, electrode slurries are fluid materials prepared by mixing electrode active materials (main materials, such as lithium cobalt oxide, lithium iron phosphate, etc.), conductive agents, binders, and other components with solvents. Target slurries refer to electrode slurries that are carefully formulated according to specific battery performance requirements or design standards. The formulation, component ratios, and preparation processes of such slurries are optimized to meet the specific performance indicators of the target battery cell, such as improving energy density, enhancing cycle stability, and increasing power output.

[0033] This includes the target type of battery cell, which refers to a battery cell designed for specific applications and possessing specific performance parameters. Examples include high-energy-density cells for electric vehicles or high-cycle-life cells for energy storage systems.

[0034] Obtaining the target slurry means that a slurry formulation has been designed. This slurry will be used to construct the target type of battery cell, that is, to transform the slurry into a battery cell that meets the design standards through a series of manufacturing processes.

[0035] Step S104: Determine the test data corresponding to the target slurry under the test parameters, wherein the test data includes impedance test data;

[0036] In step S104 of this application, the test data corresponding to the target slurry under the test parameters are determined.

[0037] This involves experimental parameters, which refer to the conditions set during the testing process, including but not limited to temperature, frequency, disturbance voltage, and test environment. In electrochemical impedance spectroscopy (EIS), these parameters are crucial to the accuracy and reliability of the results. For example, the range of test frequencies affects the sensitivity to different components of the slurry impedance (such as charge transport resistance and diffusion resistance).

[0038] This involves test data, which are results obtained through experimental measurements and contain key information about the performance of the target slurry. In this application, the test data mainly refers to impedance test data, including information such as resistance (R), capacitance (C), inductance (L), and impedance phase angle.

[0039] In this step, determining the test data corresponding to the target slurry under the experimental parameters means that after setting specific test conditions (such as temperature, frequency range, etc.), impedance testing is performed on the target slurry, and the impedance test data is collected and recorded. These data will reflect the electrochemical characteristics of the slurry under given conditions, including the integrity of the internal conductive network, the resistance to charge transport in the slurry, and the interaction between the slurry and the test electrode.

[0040] Step S106: Input the impedance test data into the equivalent circuit model for fitting to obtain multiple circuit parameter values. The equivalent circuit model is constructed based on the target type of cell and includes four sub-circuits. The first sub-circuit includes a charge movement resistor, the second sub-circuit is a solution resistor connected in parallel with the first constant phase element, the third sub-circuit is an active material resistor connected in parallel with the second constant phase element, and the fourth sub-circuit is an electric double layer resistor and capacitor connected in parallel with the third constant phase element. The first constant phase element is a constant phase element representing the interface characteristics between the binder and the solvent, the second constant phase element is a constant phase element representing the interface characteristics between the binder and the active material, and the third constant phase element represents the constant phase element representing the interface characteristics between the conductive agent and the active material. The electric double layer resistor and capacitor are obtained by connecting the electric double layer resistor and the electric double layer capacitor in series. The four sub-circuits are connected in series in sequence.

[0041] In step S106 of this application, impedance test data is input into an equivalent circuit model for fitting, resulting in multiple circuit parameter values.

[0042] This involves equivalent circuit models, which, in electrochemical impedance spectroscopy (EIS) analysis, are a method of simulating the impedance characteristics of an electrochemical cell or slurry using electronic circuit components (such as resistors, capacitors, and inductors). By adjusting the parameters of the components in the model, the model's output impedance is matched to the actual measured impedance.

[0043] This includes charge movement resistance, which represents the resistance encountered by charges as they move within the electrode slurry and is typically related to the dispersion of conductive agents and active materials.

[0044] This involves solution resistance. Inside the battery, the migration of ions in the electrolyte encounters resistance, which is called solution resistance. It is usually related to the type and concentration of the electrolyte and the battery's operating temperature.

[0045] This involves first, second, and third phase-constant elements, which are components designed to simulate the behavior of non-ideal capacitors or parallel combinations of capacitors and resistors. In the equivalent circuit model of the battery slurry, the first phase-constant element simulates the interfacial characteristics between the binder and the solvent, the second phase-constant element simulates the interfacial characteristics between the binder and the active material, and the third phase-constant element simulates the interfacial characteristics between the conductive agent and the active material.

[0046] This involves double-layer resistance and capacitance. The electric double layer refers to the electrochemical layer formed between the electrode surface and the electrolyte interface, which consists of tightly adsorbed charges and opposite charges, forming a capacitor. Double-layer resistance and capacitance (part of the Randle circuit) combines double-layer resistance (Rdl) and double-layer capacitance (Cdl) to simulate the electrochemical behavior at the electrode / electrolyte interface.

[0047] This involves multiple circuit parameter values: In electrochemical impedance spectroscopy (EIS) analysis, after fitting the impedance test data with an equivalent circuit model, a series of circuit parameter values ​​are obtained. These may include parameters such as charge transport resistance (Rct), solution resistance (Rs), active material resistance (Ractive), double layer resistance (Rdl), and phase-state element (CPE). These parameter values ​​reflect electrochemical processes such as charge transport within the electrode slurry, solution conductivity, electrochemical reactions of the active material, and material interface properties.

[0048] By fitting impedance test data into an equivalent circuit model, multiple circuit parameter values ​​can be obtained. The parameter values ​​obtained during the fitting process can reveal the interactions between the components in the slurry and how they affect the conductivity and electrochemical stability of the electrodes. Furthermore, analysis based on the equivalent circuit model can guide the selection of battery materials and the optimization of slurry formulations to improve battery efficiency and reliability.

[0049] Step S108: Based on multiple circuit parameter values, predict the performance parameters of the battery cell made using the target paste under the test parameters.

[0050] In step S108 provided in this application, the performance parameters of the battery cell made using the target paste under the test parameters are predicted based on multiple circuit parameter values.

[0051] This involves the performance parameters of the battery cell, the basic unit of a battery. These parameters include energy density, power density, cycle life, impedance, charge / discharge efficiency, temperature stability, and safety. These parameters directly determine the overall performance and application range of the battery.

[0052] In this step, multiple circuit parameter values ​​are input into an equivalent circuit model based on the target slurry characteristics, allowing prediction of the performance parameters of battery cells made using this slurry under set experimental parameters. Based on the analysis of these circuit parameter values, more suitable slurry components and proportions can be selected, such as choosing more efficient conductive agents and optimizing the type and content of active materials to achieve ideal battery cell performance.

[0053] Through steps S102-S108 above, a target slurry is obtained, which is used to construct a target type of battery cell. Test data corresponding to the target slurry under experimental parameters is determined, including impedance test data. The impedance test data is input into an equivalent circuit model for fitting, obtaining multiple circuit parameter values. The equivalent circuit model is constructed based on the target type of battery cell and includes four sub-circuits: the first sub-circuit includes a charge-movement resistor; the second sub-circuit is a solution resistor connected in parallel with a first phase-changing element; the third sub-circuit is an active material resistor connected in parallel with a second phase-changing element; and the fourth sub-circuit is an electric double-layer resistor and capacitor connected in parallel with a third phase-changing element. The first phase-changing element represents the interfacial characteristics between the binder and solvent; the second phase-changing element represents the interfacial characteristics between the binder and the active material; the third phase-changing element represents the interfacial characteristics between the conductive agent and the active material; and the electric double-layer resistor and capacitor are obtained by connecting an electric double-layer resistor and a double-layer capacitor in series. The four sub-circuits are connected in series sequentially. Based on multiple circuit parameter values, the performance parameters of a battery cell made using a target paste under experimental parameters are predicted. Since the test data corresponding to the target paste under the experimental parameters is determined, and the impedance test data is input into an equivalent circuit model for fitting, multiple circuit parameter values ​​are obtained. By fitting these circuit parameter values, the performance parameters of the battery cell are predicted, thus solving the technical problem in related technologies where it is difficult to conveniently determine the performance parameters related to the battery cell based on the paste.

[0054] As an optional embodiment, the performance parameters of a battery cell made using the target slurry under experimental parameters are predicted based on multiple circuit parameter values. This includes: when the target slurry includes electrode materials, a conductive agent, and a solvent; the electrode materials include active materials; and the multiple circuit parameter values ​​include a fitted charge-movement resistance value Rs, a fitted solution resistance value Rso, a fitted active material resistance value Rp, a fitted double-layer resistance value Rdl, and a fitted phase-constant element value CPE, the following are determined: based on the fitted charge-movement resistance value Rs, the charge transfer efficiency performance between the solvent and the electrode materials is determined; based on the fitted solution resistance value Rso, the impedance of the conductive path formed by the binder and the conductive material is determined; based on the fitted active material resistance value Rp, the active material impedance within the electrode materials is determined; based on the fitted double-layer resistance value Rdl, the charge transport performance between the conductive agent and the active material is determined; based on the fitted phase-constant element value CPE, the dispersion performance of each component within the target slurry is determined; and based on the charge transfer efficiency performance, conductive path impedance, active material impedance, charge transport performance, and dispersion performance, the performance parameters of a battery cell made using the target slurry under experimental parameters are predicted.

[0055] In this embodiment, the steps for predicting the performance parameters of a battery cell made using a target paste under experimental parameters are described.

[0056] This involves electrode materials, which include active materials and conductive agents. The active materials are responsible for the energy storage and conversion of the battery, while the conductive agents improve the electron transport efficiency inside the electrode.

[0057] This involves conductive agents such as carbon nanotubes, graphene, and conductive carbon black, which are used to enhance the electronic conductivity inside the electrode and between the electrode and the current collector.

[0058] This involves solvents: liquid media used in the preparation of electrode slurries, such as N-methylpyrrolidone, water, ethanol, etc., with appropriate solvents selected according to different battery types.

[0059] This involves fitting the charge movement resistance value Rs: reflecting the resistance to charge movement within the electrode material and at the interface, which is directly related to the charge transfer efficiency of the battery.

[0060] This involves fitting the solution resistance value Rso: representing the resistance to ion migration in the electrolyte, and determining the impedance of the conductive path formed by the binder and the conductive material.

[0061] This involves fitting the resistance value Rp of the active material: representing the charge transport resistance of the active material itself, which can determine the active material impedance inside the electrode material.

[0062] This involves fitting the double-layer resistance value Rdl: simulating the charge resistance at the interface between the conductive agent and the active material, and evaluating the charge transport performance.

[0063] Among them, the fitted constant phase element value CPE is involved: used to describe the behavior of non-ideal capacitors or parallel combinations of capacitors and resistors, reflecting the dispersion performance between materials, including the dispersion performance of interfaces such as binder and active material, solvent and active material.

[0064] When the target slurry contains electrode materials, conductive agents, and solvents, and the equivalent circuit model successfully fits the values ​​of charge-movement resistance Rs, solution resistance Rso, active material resistance Rp, double-layer resistance Rdl, and phase-constant element CPE, these parameters can correspond to different electrochemical processes within the electrode slurry. By analyzing these circuit parameters, a deeper understanding of the electrochemical behavior within the slurry can be achieved, thereby predicting the performance parameters of the battery cell made using the target slurry under set experimental parameters (such as temperature and frequency range), including energy density, power density, cycle life, and impedance characteristics. Through parameter analysis, the slurry formulation can be optimized in a targeted manner, such as adjusting the type and content of conductive agents, to improve the electrochemical performance of the battery.

[0065] As an optional embodiment, based on charge transfer efficiency performance, conductive path impedance, active material impedance, charge transport performance, and dispersion performance, the performance parameters of a battery cell made using the target slurry under test parameters are predicted, including: when the electrode material also includes a binder, and the fitted phase constant element values ​​include a first phase constant element value, a second phase constant element value, and a third phase constant element value; determining the first sub-contact performance between the binder and the solvent based on the first phase constant element value CPEs; determining the second sub-contact performance between the binder and the active material based on the second phase constant element value CPEp; determining the third sub-contact performance between the conductive agent and the active material based on the third phase constant element value CPEdl; determining the contact performance corresponding to the electrode material based on the first sub-contact performance, the second sub-contact performance, and the third sub-contact performance; and predicting the performance parameters of a battery cell made using the target slurry under test parameters based on charge transfer efficiency performance, conductive path impedance, active material impedance, charge transport performance, dispersion performance, and contact performance.

[0066] In this embodiment, the steps for determining contact performance to determine performance parameters are described.

[0067] This involves the constant-phase element value (CPE), which is used in electrochemical impedance spectroscopy to describe the capacitive characteristics of complex systems, especially when traditional capacitance models cannot accurately describe non-ideal interfacial behavior. The magnitude of the CPE value is related to the roughness and uniformity of the interface, as well as the interaction between the electrode material and the electrolyte or binder.

[0068] Among them, the first constant phase element value (CPEs) is involved, which reflects the interfacial characteristics between the binder and the solvent and describes the complex capacitive behavior when the two are in contact, including charge distribution, adsorption and desorption processes.

[0069] This involves the second constant phase element value CPEp, which simulates the interfacial characteristics between the binder and the active material, especially the contact efficiency between the surface of the active material particles and the binder, which directly affects the mechanical strength of the electrode and the formation of the electronic conductive network.

[0070] This involves the third constant phase element value CPEdl, which represents the interfacial characteristics between the conductive agent and the active material, including the coverage of the conductive agent on the surface of the active material, the formation of the conductive network, and the charge transfer efficiency between the two.

[0071] The steps provided in this embodiment, based on the fitted CPE values, allow for a hierarchical evaluation of the contact performance between materials within the electrode slurry. By combining the first, second, and third sub-contact performances, a comprehensive assessment of the internal contact performance of the electrode slurry—that is, the interactions and contact states between its components—can be achieved, leading to a better determination of the cell's performance parameters. This information is crucial for understanding the battery's internal structure and electrochemical processes, thereby optimizing slurry formulations and battery performance.

[0072] As an optional embodiment, determining the test data corresponding to the target slurry under the test parameters includes: transferring the target slurry to a predetermined test fixture, wherein the predetermined test fixture includes a target test tube, a first conductive electrode, and a second conductive electrode, the first conductive electrode being located on a first side of the target test tube and the second conductive electrode being located on a second side of the target test tube; and starting the predetermined test fixture under the test parameters to obtain the test data.

[0073] In this embodiment, the steps for obtaining test data are described.

[0074] This involves a pre-designed test fixture, which is a device specifically designed and prepared for electrochemical impedance spectroscopy testing. It includes key components such as a target test tube, a first conductive electrode, and a second conductive electrode, and is configured to precisely control the state of the slurry under test conditions.

[0075] This involves target test tubes, which are used to hold slurry. Target test tubes can be visualization test tubes, which are transparent or semi-transparent containers that allow observers to see the state of the slurry inside, including its distribution, contact, and reaction, either directly or through imaging devices. This helps to control the uniformity and content of the slurry.

[0076] This involves a first conductive electrode and a second conductive electrode, electrodes in the testing fixture, designed to contact the slurry and transfer current to obtain electrochemical impedance data. These electrodes are typically made of highly conductive materials such as copper, aluminum, or gold.

[0077] In this method, to obtain electrochemical impedance spectroscopy (EIS) data of a target slurry under specific conditions, the slurry is first transferred to a predetermined testing fixture. This fixture includes a target test tube and a first and a second conductive electrode located on either side of the test tube, while also facilitating the fixation of the test tube. When the target test tube is a visualization tube, the visualization design allows researchers to visually observe the distribution of the slurry between the electrodes, helping to ensure the uniformity and controllable content of the slurry. Then, under the set experimental parameters (such as temperature and frequency range), the testing fixture is activated, and the impedance of the slurry is measured using an electrochemical impedance spectroscopy system. The final result of this series of operations is a set of test data containing the impedance characteristics of the slurry in different electrochemical processes, such as charge transfer, solution resistance, active material resistance, and double-layer resistance.

[0078] The design of the test fixture ensures the stability and consistency of the slurry structure during testing, which is crucial for the accuracy and repeatability of impedance testing. The fixture provides a standardized environment, ensuring consistency in key parameters such as slurry thickness, contact area, and pressure for each test, thereby reducing variability in test results and improving data reliability. The conductive electrodes on both sides of the test fixture guarantee precise contact with the slurry. Good electrical contact is a prerequisite for obtaining accurate impedance data; poor contact between the electrodes and the slurry may lead to inflated impedance values ​​in the test results, affecting the accurate assessment of the slurry's electrochemical performance. The test fixture can perform tests within a specific temperature range, which helps evaluate the slurry's impedance performance under different temperature conditions, thus providing a better understanding of the slurry's behavior in actual battery operating environments.

[0079] As an optional embodiment, the frequency band of the AC test current corresponding to the second sub-circuit is greater than the frequency band of the AC test current corresponding to the third sub-circuit, and the frequency band of the AC test current corresponding to the third sub-circuit is greater than the frequency band of the AC test current corresponding to the fourth sub-circuit.

[0080] In this embodiment, the frequency band of the AC test current is involved. In electrochemical impedance spectroscopy (EIS) testing, an AC signal is used. AC signals of different frequency bands can detect the electrochemical response of a sample (such as an electrode slurry) at different time scales. High-frequency signals (such as those in the MHz range) are generally associated with fast electrochemical processes such as solution resistance, while low-frequency signals (such as those in the Hz range) are associated with slower electrochemical processes such as charge transfer and diffusion.

[0081] In electrochemical impedance spectroscopy (EIS), AC test currents at different frequency bands correspond to different sub-circuits in the circuit model. The AC test current corresponding to the second sub-circuit has a higher frequency band than that of the third sub-circuit, indicating that the second sub-circuit mainly reflects the faster electrochemical processes within the electrode slurry, while the third sub-circuit corresponds to relatively slower electrochemical processes. Similarly, the frequency band of the third sub-circuit is higher than that of the fourth sub-circuit, indicating that the fourth sub-circuit simulates the slowest electrochemical process. This correspondence between frequency bands and sub-circuits helps to distinguish and identify the timescale of electrochemical processes, thereby more accurately resolving the electrochemical mechanisms in the slurry.

[0082] By using AC test currents at different frequency bands, fast, medium, and slow electrochemical processes within the slurry can be distinguished. This correspondence allows for more accurate allocation and optimization of circuit parameters, such as resistance and capacitance values, when fitting electrochemical impedance spectroscopy to reflect the characteristics of different electrochemical processes.

[0083] Processes in electrochemical systems often exhibit different kinetic rates. Fast processes (such as solution resistance) are typically observed at high frequencies, while slow processes (such as charge transfer resistance and diffusion processes) are more pronounced at low frequencies. By correlating the components of an equivalent circuit with specific frequency ranges, the impedance contribution of different processes in the electrochemical system can be analyzed one by one, leading to a deeper understanding of the mechanisms. Since the impedance characteristics of different components vary at different frequencies—for example, capacitors exhibit significant capacitive characteristics at high frequencies, while these characteristics may be masked by the characteristics of other impedance components at low frequencies—dividing the circuit into multiple orders, each optimized and fitted for a specific frequency range, can improve the accuracy and reliability of the overall impedance spectrum fitting, ensuring that each electrochemical process is accurately reflected. By distinguishing these frequency bands, various physical and chemical parameters in the electrochemical system can be more clearly identified and quantified. Understanding the frequency response of different electrochemical processes helps optimize the performance of battery materials.

[0084] As an optional embodiment, after predicting the performance parameters of a battery cell made using the target paste under test parameters based on multiple circuit parameter values, the method further includes: determining the composition parameters of the target paste if the performance parameters are less than a predetermined threshold; adjusting the composition parameters to obtain an updated paste, and then determining the performance parameters corresponding to the updated paste.

[0085] In this embodiment, the process of obtaining an updated slurry to determine the performance parameters corresponding to the updated slurry is described.

[0086] This involves predetermined thresholds, which are the minimum or maximum allowable values ​​of a series of parameters set during the battery design phase to achieve the expected battery performance. For example, to meet the application requirements of electric vehicles, the energy density threshold of the battery cell may be set above a specific value.

[0087] This involves compositional parameters, which are the material composition and proportions in the electrode slurry, such as the types and contents of active materials, conductive agents, binders, and solvents.

[0088] This involves updating the slurry, which is a slurry that is re-prepared after adjusting its composition parameters based on a comparison of performance prediction results and predetermined thresholds.

[0089] After predicting the performance parameters of a battery cell made using a target slurry based on electrochemical impedance spectroscopy (EIS) test data, if these performance parameters do not meet or fall below pre-set thresholds, further analysis of circuit parameter values ​​is needed to determine which compositional parameters (such as material type, content, or proportion) require adjustment. By purposefully changing the compositional parameters of the slurry, a new slurry is prepared, and EIS testing is performed again. Based on the new test data, the battery cell performance parameters are re-predicted until they meet or exceed the pre-set thresholds. This process may require multiple iterations until the optimal slurry formulation is found. This feedback loop between EIS testing and performance parameter prediction accelerates the slurry formulation optimization process, avoiding the time-consuming and resource-intensive nature of traditional experimental methods. Based on the analysis of circuit parameter values, the compositional parameters of the slurry can be adjusted more precisely to achieve refined control over battery performance.

[0090] As an optional embodiment, before inputting impedance test data into an equivalent circuit model for fitting to obtain multiple circuit parameter values, the method further includes: obtaining a sample slurry and a sample cell constructed from the sample slurry, wherein the sample cell is a target type of cell; determining the sample performance parameters of the sample cell; determining the correlation between the composition of the sample slurry and the sample performance parameters; and constructing an equivalent circuit model based on the correlation.

[0091] In this embodiment, the process of constructing the equivalent circuit is illustrated.

[0092] This involves sample slurry, which is a slurry with a specific formulation used for the preparation of battery electrodes. Its composition and proportions reflect the initial or optimized selection of electrode materials in the battery design.

[0093] This includes sample batteries, which are cells prepared from sample slurry according to the target type of battery structure and process requirements, and are used to evaluate the performance of a specific slurry formulation in a real battery.

[0094] This includes sample performance parameters, which are the performance indicators of the sample battery under various test conditions (such as charge-discharge cycles, temperature, current, etc.), including energy density, power density, cycle life, impedance characteristics, etc.

[0095] This involves a control relationship, which is the relationship between the composition of the sample slurry obtained through experiments and the performance parameters of the sample battery. This relationship can be used to guide the construction of equivalent circuit models and parameter fitting.

[0096] In battery development, the first step is to prepare a sample slurry and fabricate a sample battery according to the target battery type and requirements. Next, a series of performance tests are conducted to determine the performance parameters of the sample battery, such as energy density and charge / discharge efficiency. Then, by comparing the slurry's components (such as the types and proportions of active materials, conductive agents, binders, and solvents) with the measured performance parameters, a deeper understanding of the impact of each component on battery performance can be achieved. Finally, based on these comparisons, an equivalent circuit model of electrochemical impedance spectroscopy is constructed or optimized to more accurately simulate the internal electrochemical processes of the battery and the electrochemical characteristics of the slurry.

[0097] This method, through comparative analysis, identifies which slurry components significantly impact battery performance, allowing for targeted adjustments to the slurry formulation and optimization of battery performance. The construction and fitting of equivalent circuit models enables researchers to gain a deeper understanding of the internal electrochemical processes of the battery, including ion migration, charge transfer, and diffusion, providing a theoretical basis for battery design. Feedback based on sample performance parameters can reduce unnecessary slurry component usage or process experiments, lowering R&D costs and time consumption.

[0098] Based on the above embodiments and optional embodiments, an optional implementation method is provided, which is described in detail below.

[0099] This disclosure provides, in optional embodiments, a method for testing and analyzing the impedance of lithium-ion battery electrode slurry and its application, as well as a system for analyzing the internal conductive network of lithium-ion cathode slurry, including a method for testing and analyzing the impedance of lithium-ion battery electrode slurry and a testing fixture.

[0100] (I) Test method for impedance of lithium-ion battery electrode slurry:

[0101] S1: Mix the main material, binder, conductive agent, dispersant, and functional additives with the solvent at proportions of 50-100%, 0-20%, 0-20%, 0-10%, and 0-10%, respectively, but not limited to these proportion ranges, to prepare a mixed slurry, with a total proportion of 100%.

[0102] Optionally, the main material, binder, conductive agent, dispersant, and functional additives can be mixed with the solvent at proportions of 50-100%, 0-20%, 0-20%, 0-10%, and 0-10%, respectively, but not limited to these proportion ranges, to prepare a mixed slurry with a total proportion of 100%.

[0103] S2: Transfer the mixed slurry to the designed test fixture.

[0104] S3: The slurry impedance is tested again using an electrochemical impedance spectroscopy system.

[0105] Prepare lithium-ion cathode slurry samples with different proportions of conductive agent content, conduct conductivity tests on the slurry samples using a novel testing fixture, analyze the conductivity performance of the slurry under different conductive agent contents, evaluate the structure and connection of the internal conductive network of the slurry based on the corresponding equivalent circuit, and screen out the best cathode conductive agent material and the best conductive agent content based on the analysis results.

[0106] Specifically, the fitting method includes: performing an energizing test on the conductive paste to obtain impedance test data of the conductive paste; using impedance analysis software, fitting the initial values ​​of the component impedance in the equivalent circuit of the electrochemical impedance test based on the impedance test data; and using impedance analysis software, fitting the electrochemical impedance spectrum of the conductive paste based on the initial values ​​of the component impedance.

[0107] Optionally, in step S3, the electrochemical impedance testing system includes a first-order equivalent circuit, a second-order equivalent circuit, and a third-order equivalent circuit connected in series, with the first-order equivalent circuit connected in series with the charge transfer resistor; the impedance analysis software: based on the impedance test data, fits the initial values ​​of the component impedances in the electrochemical impedance testing equivalent circuit to obtain the electrochemical impedance spectrum of the conductive slurry.

[0108] Optionally, the slurry preparation and impedance testing in steps S1, S2, and S3 can be performed at temperatures ranging from -20 to 100°C.

[0109] Optionally, in step S3, the frequency range of the impedance test is 0.01Hz-8MHz.

[0110] Optionally, in step S3, the disturbance voltage range for the impedance test is 10mV-1V.

[0111] Optionally, the solvent may include, but is not limited to, lithium battery solvents such as N-methylpyrrolidone, water, ethanol, and isopropanol.

[0112] Optionally, the solid content of the mixed slurry is 10%-100%, where solid content refers to the content of solid matter.

[0113] Optionally, the conductive agent (conductive paste) includes any one or a combination of at least two of conductive carbon black, carbon nanotubes, carbon nanorods, carbon fibers, or graphene.

[0114] Optionally, the main material includes any one or a combination of at least two of the following: lithium cobalt oxide, lithium manganese oxide, lithium nickel manganese cobalt oxide, lithium iron phosphate, lithium manganese iron phosphate, lithium nickel cobalt alumina, lithium titanate, graphite, and silicon.

[0115] Optionally, the adhesive includes any one or a combination of at least two of the following: polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), carboxymethyl cellulose (CMC), styrene-butadiene rubber (SBR), polyacrylic acid (PAA), polyacrylonitrile (PAN), polyimide (PI), perfluorosulfonic acid ionomers (Nafion), natural extract adhesives, conductive adhesives, self-healing adhesives, and thermoplastic polymers.

[0116] Optionally, the dispersant includes oil-based system dispersants and water-based system dispersants.

[0117] Optional functional additives include wetting agents, thickeners, and anti-cracking agents. Wetting agents are used to reduce slurry viscosity and promote the formation of a stable suspension. Thickeners are used to increase the viscosity and stability of the slurry. Anti-cracking agents are used to prevent cracking during the coating process.

[0118] (II) Testing Fixtures:

[0119] Figure 2 is a schematic diagram of the test fixture provided in the optional embodiment of this disclosure. As shown in Figure 2, it includes two electrodes and a content visualization test tube, which is used to test the conductivity of lithium-ion cathode slurry samples. It includes a test fixture with specific structure and function, a test instrument, and a third-order equivalent circuit fitting method for electrochemical impedance spectroscopy.

[0120] Optional testing fixtures include electrodes on both sides and a test tube for content visualization.

[0121] Optionally, the electrodes on both sides of the test fixture include at least one metal selected from the following: iron (Fe), copper (Cu), gold (Au), silver (Ag), aluminum (Al), cobalt (Co), chromium (Cr), manganese (Mn), molybdenum (Mo), titanium (Ti), zirconium (Zr), tin (Sn), vanadium (V), niobium (Nb), tantalum (Ta), hafnium (Hf), or a combination of these metals.

[0122] Optional materials for the test tubes used to visualize the content of the test fixtures include, but are not limited to, polyvinyl chloride (PVC), unplasticized polyvinyl chloride (UPVC), polypropylene (PP), polyethylene (PE), polypropylene random copolymer (PPR), cross-linked polyethylene (PEX), glass, mica sheets, and inorganic ceramic materials.

[0123] (III) Third-order equivalent circuit of electrochemical impedance spectroscopy:

[0124] Figure 3 is a schematic diagram of the slurry internal impedance fitting circuit provided in an optional embodiment of this disclosure. As shown in Figure 3, the equivalent circuit model of the conductive slurry is constructed based on the chemical composition analysis of the electrode slurry. The third-order equivalent circuit includes a first-order equivalent circuit, a second-order equivalent circuit, and a third-order equivalent circuit connected in series. The first-order equivalent circuit is connected in series with the charge transfer resistor. The frequency band of the AC test current corresponding to the first-order equivalent circuit is greater than the frequency band of the AC test current corresponding to the second-order equivalent circuit, and the frequency band of the AC test current corresponding to the second-order equivalent circuit is greater than the frequency band of the AC test current corresponding to the third-order equivalent circuit.

[0125] In this diagram, Rso represents the solution resistance, Rp represents the transport path resistance, Rdl represents the double-layer resistance between the conductive agent and the host material, and CPE (not shown in the diagram, used to introduce CPES) is a component used to fit the non-ideal capacitive behavior in the impedance spectrum. It can describe the phase change characteristics of the dielectric material at different frequencies because the capacitance of real materials usually does not exhibit the 90-degree phase of ideal capacitance at all frequencies. CPEs are used to describe the phase-constant element at the interface between the binder and the solvent. It describes the capacitive behavior at the interface between the solution and the solute, which helps to understand the interaction and dispersion state between the two. CPEp usually represents the phase-constant element at the interface between the binder and the host material (such as the active material in lithium-ion batteries), reflecting the surface electrochemical properties of the active material and the formation of the double layer. CPEdl represents the phase-constant element at the interface between the conductive agent and the host material. It describes the capacitive behavior at the interface between the conductive agent and the active material, which helps to understand the interaction and dispersion state between the two. Cdl usually refers to "double layer capacitance", which is an important parameter in electrochemical systems. In electrochemical impedance spectroscopy (EIS) analysis, Cdl is a measure of the capacitance properties of the double-layer structure formed at the electrochemical interface (usually the electrode / electrolyte interface). When ions in the electrolyte come into contact with the charged electrode surface, a double layer is formed, consisting of the electrode surface charge and the electrolyte ions that counteract it. The formation and changes of this double layer have a significant impact on the rate and efficiency of electrochemical reactions.

[0126] As an optional implementation, the materials used in the test tubes for visualizing the content of the testing fixture include, but are not limited to, PVC, UPVC, PP, PE, PPR, PEX, glass, mica sheets, and inorganic ceramic materials. In the following embodiments, lithium manganese iron phosphate is used as the main material, conductive carbon black SP as the conductive agent, copper wire as the fixture electrode, and PVC as the test tube material. A designed third-order equivalent circuit of electrochemical impedance spectroscopy is employed, with 10mV as the perturbation voltage and a measurement frequency range of 0.01Hz-1MHz, to provide a more detailed explanation of the application of the testing and analysis method for the impedance of lithium-ion battery electrode slurry.

[0127] Figure 4 is a comparison chart of slurry impedance data with different conductive agent contents provided by the optional embodiments of this disclosure. The test results are shown in Figure 4. 095-2 represents Method 1, 250-2 represents Method 2, and 450-2 represents Method 3. The addition of "fit" indicates that the curve was fitted using Zview software combined with a third-order equivalent circuit. The fit curve is very close to the original actual curve, which is used to illustrate the accuracy of the third-order equivalent circuit. The difference between the three methods is the change in the conductive agent content; other formulations remain unchanged. 095 represents 0.95% conductive agent.

[0128] 1) Method 1:

[0129] Add appropriate amounts of PVDF and N-methylpyrrolidone (NMP) to a vacuum mixer and stir to form a gel solution for later use. Add 0.95% conductive slurry (based on the content of conductive agent SP) to a homogenizing tank, then add the gel solution containing 1.5% PVDF. Stir at 850 rpm for 10 minutes using a homogenizer. Slowly add 97.55% lithium manganese iron phosphate and stir at 850 rpm for 10 minutes to prepare a mixture with a total weight of 80g and a total solids content of approximately 50%. After stirring, transfer the mixture to a testing fixture and test it using an impedance meter. The test results are shown in Figure 4.

[0130] 2) Method Two:

[0131] Add an appropriate amount of PVDF and NMP to a vacuum mixer and stir to form a slurry for later use. Add 2.5% conductive slurry (calculated based on the content of conductive agent SP) to a homogenizing tank, then add the slurry containing 1.5% PVDF. Stir at 850 rpm for 10 minutes. Slowly add 96% lithium manganese iron phosphate and stir at 850 rpm for 10 minutes to prepare a mixture with a total weight of 80g and a total solids content of approximately 50%. After stirring, transfer the mixture to a testing fixture and test it using an impedance meter. The test results are shown in Figure 4.

[0132] 3) Method Three:

[0133] Add an appropriate amount of PVDF and NMP to a vacuum mixer and stir to form a slurry for later use. Add 4.5% conductive slurry (based on the content of conductive agent SP) to a homogenizing tank, then add the slurry containing 1.5% PVDF. Stir at 850 rpm for 10 minutes. Slowly add 94% lithium manganese iron phosphate and stir at 850 rpm for 10 minutes to prepare a mixture with a total weight of 80g and a total solids content of approximately 50%. After stirring, transfer the mixture to a testing fixture and test it using an impedance meter. The test results are shown in Figure 4.

[0134] The test results from methods one to three were imported into impedance analysis software, and the results were fitted using a third-order equivalent circuit of electrochemical impedance spectroscopy. The following conclusions were drawn.

[0135] Conclusion: Figure 5 shows the fitting data of the internal impedance of the slurry provided by the optional embodiment of this disclosure. As shown in Figures 4 and 5, the curves 095-2-fit, 250-2-fit, and 450-2-fit fitted by the designed fitting circuit are very close to the actual curves, indicating that the equivalent circuit accurately presents the state of the conductive network inside the slurry. Furthermore, with the increase of SP content in the conductive slurry, the resistance of Rso solution and the resistance of Rp transmission path decrease significantly, that is, the increase of conductive agent improves the conductivity of the electrode slurry and reduces the resistance. The double layer resistance between the conductive agent and the main material Rdl first decreases and then increases, which indicates the dispersion status between the conductive agent and the main material. The CPEp and CPEdl data further illustrate the dispersion status between the conductive agent, the main material, and the PVDF binder.

[0136] The above optional implementation methods can achieve at least the following beneficial effects:

[0137] (1) An optional embodiment of this disclosure provides a fixture that can be directly used to test the impedance of slurry. The content visualization can be used to control the slurry content. Fixed fixture and unified variables make the data results more accurate and reduce random errors. The test electrodes on both sides facilitate the mixing and transfer of slurry.

[0138] (2) An optional embodiment of this disclosure provides an electrochemical impedance testing system and analysis method based on the chemical composition analysis of electrode slurry, which can accurately and quickly obtain the composition of the internal conductive network of the slurry, and can quickly and accurately reveal the situation of the internal conductive network of the slurry, and be used to screen positive electrode conductive agent materials.

[0139] (3) An optional embodiment of this disclosure provides a method for rapidly screening the types and contents of conductive agents and the contents of main materials, utilizing the aforementioned analysis system to evaluate and screen slurries with different conductive agent contents. This addresses the shortcomings of cumbersome and inefficient screening of electrode slurry formulations, achieving the goal of rapidly and accurately evaluating the internal conductive network of slurries under different formulations. It allows for a more comprehensive understanding of the internal conductive network structure of electrode slurries, providing important references for the design and optimization of lithium-ion electrode materials, thereby optimizing battery performance.

[0140] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions, because according to this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this disclosure.

[0141] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solutions of this disclosure, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this disclosure.

[0142] Example 2

[0143] According to an embodiment of this disclosure, an apparatus for implementing the above-described method for predicting battery cell performance parameters is also provided. FIG6 is a structural block diagram of the battery cell performance parameter prediction apparatus according to an embodiment of this disclosure. As shown in FIG6, the apparatus includes: an acquisition module 602, a determination module 604, a fitting module 606, and a prediction module 608. The apparatus will be described in detail below.

[0144] The acquisition module 602 is configured to acquire the target slurry, wherein the target slurry is used to construct a target type of battery cell; the determination module 604, connected to the acquisition module 602, is configured to determine the test data corresponding to the target slurry under experimental parameters, wherein the test data includes impedance test data; the fitting module 606, connected to the determination module 604, is configured to input the impedance test data into an equivalent circuit model for fitting to obtain multiple circuit parameter values, wherein the equivalent circuit model is constructed based on the target type of battery cell, and the equivalent circuit model includes four sub-circuits, the first sub-circuit includes a charge transfer resistor, the second sub-circuit is a solution resistor connected in parallel with a first constant phase element, the third sub-circuit includes a charge transfer resistor, the fourth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the fifth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the sixth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the seventh sub-circuit is a solution resistor connected in parallel with a first constant phase element, the eighth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the ninth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the tenth sub-circuit is a solution resistor connected in parallel with a first constant phase element, the eleven ... The circuit consists of an active material resistor connected in parallel with a second phase-constant element, and a fourth sub-circuit consisting of an electric double-layer resistor and capacitor connected in parallel with a third phase-constant element. The first phase-constant element represents the interfacial characteristics between the binder and the solvent, the second phase-constant element represents the interfacial characteristics between the binder and the active material, and the third phase-constant element represents the interfacial characteristics between the conductive agent and the active material. The electric double-layer resistor and capacitor are obtained by connecting an electric double-layer resistor and an electric double-layer capacitor in series. The four sub-circuits are connected in series in sequence. The prediction module 608 is connected to the above-mentioned fitting module 606 and is set to predict the performance parameters of the battery cell made using the target paste under the experimental parameters based on multiple circuit parameter values.

[0145] It should be noted here that the above-mentioned acquisition module 602, determination module 604, fitting module 606 and prediction module 608 correspond to steps S102 to S108 in the method for predicting battery cell performance parameters. The multiple modules and the corresponding steps are the same in terms of implementation examples and application scenarios, but are not limited to the content disclosed in the above embodiment 1.

[0146] Example 3

[0147] According to another aspect of the present disclosure, an electronic device is also provided, comprising: a processor; and a memory configured to store processor-executable instructions, wherein the processor is configured to execute instructions to implement the cell performance parameter prediction method of any of the above embodiments.

[0148] Example 4

[0149] According to another aspect of the present disclosure, a computer-readable storage medium is also provided, which, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the cell performance parameter prediction method described above.

[0150] The sequence numbers of the embodiments disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0151] In the above embodiments of this disclosure, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0152] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0153] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0155] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0156] The above description is only a preferred embodiment of this disclosure. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles of this disclosure, and these improvements and modifications should also be considered within the scope of protection of this disclosure. Industrial applicability

[0157] The solution provided in this application can be applied to the battery field. In this application embodiment, a target slurry is obtained, which is used to construct a target type of battery cell; test data corresponding to the target slurry under experimental parameters is determined, including impedance test data; the impedance test data is input to an equivalent circuit model for fitting, resulting in multiple circuit parameter values, wherein the equivalent circuit model is constructed based on the target type of battery cell; and based on the multiple circuit parameter values, the performance parameters of a battery cell made using the target slurry under the experimental parameters are predicted. This implementation solves the technical problem in related technologies where it is difficult to conveniently determine battery cell-related performance parameters based on the slurry, achieving the goal of quickly and accurately revealing the internal electrochemical characteristics of the slurry, thereby improving the efficiency and accuracy of determining battery cell-related performance parameters based on the slurry.

Claims

1. A method for predicting performance parameters of an electric cell, comprising: obtaining a target slurry, wherein the target slurry is used to construct an electric cell of a target type; determining test data corresponding to the target slurry under test parameters, wherein the test data comprises impedance test data; inputting the impedance test data into an equivalent circuit model for fitting to obtain a plurality of circuit parameter values, wherein the equivalent circuit model is constructed according to the electric cell of the target type, and the equivalent circuit model comprises four sub-circuits, a first sub-circuit comprising a charge transfer resistance, a second sub-circuit comprising a solution resistance and a first constant phase element in parallel, a third sub-circuit comprising an active material resistance and a second constant phase element in parallel, and a fourth sub-circuit comprising a double layer resistance-capacitance and a third constant phase element in parallel, the first constant phase element representing an interface characteristic between a binder and a solvent, the second constant phase element representing an interface characteristic between the binder and an active material, the third constant phase element representing an interface characteristic between a conductive agent and the active material, the double layer resistance-capacitance being obtained by connecting a double layer resistance and a double layer capacitance in series, and the four sub-circuits being connected in series; predicting performance parameters of an electric cell made of the target slurry under the test parameters according to the plurality of circuit parameter values.

2. The method of claim 1, wherein, The predicting performance parameters of the electric cell made of the target slurry under the test parameters according to the plurality of circuit parameter value comprises: in a case where the target slurry comprises an electrode material, a conductive agent, a solvent, the electrode material comprises an active material, and the plurality of circuit parameter values comprise a fitted charge transfer resistance value, a fitted solution resistance value, a fitted active material resistance value, a fitted double layer resistance value, and a fitted constant phase element value, determining a charge transfer efficiency performance of the solvent and the electrode material according to the fitted charge transfer resistance value; determining an impedance of a conductive path formed by the binder and the conductive agent according to the fitted solution resistance value; determining an active material impedance of the active material inside the electrode material according to the fitted active material resistance value; determining a charge transport performance between the conductive agent and the active material according to the fitted double layer resistance value; determining a dispersion performance of each component inside the target slurry according to the fitted constant phase element value; predicting the performance parameters of the electric cell made of the target slurry under the test parameters according to the charge transfer efficiency performance, the impedance of the conductive path, the active material impedance, the charge transport performance, and the dispersion performance.

3. The method of claim 2, wherein, The predicting the performance parameters of the electric cell made of the target slurry under the test parameters according to charge transfer efficiency performance, the impedance of the conductive path, the active material impedance, the fitted double layer resistance value, and the fitted constant phase element value comprises: in a case where the electrode material further comprises a binder, and the fitted constant phase element value comprises a first constant phase element value, a second constant phase element value, and a third constant phase element value, determining a first sub-contact performance between the binder and the solvent according to the first constant phase element value. determine a second sub-contact property between the binder and the active material according to the second constant phase element value; determine a third sub-contact property between the conductive agent and the active material according to the third constant phase element value; determine a contact property corresponding to the electrode material according to the first sub-contact property, the second sub-contact property and the third sub-contact property; predict a performance parameter of a battery cell made of the target slurry under the test parameters according to the charge transfer efficiency property, the conductive path impedance, the active material impedance, the charge transport property, the dispersion property and the contact property.

4. The method of claim 1, wherein, The determining the test data corresponding to the target slurry under the test parameters comprises: transferring the target slurry to a predetermined test tool, wherein the predetermined test tool comprises a target test tube, a first conductive electrode and a second conductive electrode, the first conductive electrode is located at a first side of the target test tube, and the second conductive electrode is located at a second side of the target test tube; starting the predetermined test tool under the test parameters to obtain the test data.

5. The method of claim 1, wherein, The frequency band of the alternating current test current corresponding to the second sub-circuit is greater than the frequency band of the alternating current test current corresponding to the third sub-circuit, and the frequency band of the alternating current test current corresponding to the third sub-circuit is greater than the frequency band of the alternating current test current corresponding to the fourth sub-circuit.

6. The method of claim 1, wherein, After the predicting the performance parameter of the battery cell made of the target slurry under the test parameters according to the plurality of circuit parameter values, the method further comprises: determining a composition parameter of the target slurry when the performance parameter is less than a predetermined threshold value; adjusting the composition parameter to obtain an updated slurry, and determining a performance parameter corresponding to the updated slurry.

7. The method of any one of claims 1 to 6, wherein, Before the inputting the impedance test data into the equivalent circuit model for fitting to obtain the plurality of circuit parameter values, the method further comprises: obtaining a sample slurry and a sample battery constructed by the sample slurry, wherein the sample battery is a battery of the target type; determining a sample performance parameter of the sample battery; determining a control relationship between a composition of the sample slurry and the sample performance parameter; constructing the equivalent circuit model according to the control relationship.

8. A battery cell performance parameter prediction device, comprising: an obtaining module configured to obtain a target slurry, wherein the target slurry is used to construct a battery cell of a target type; a determining module configured to determine test data corresponding to the target slurry under test parameters, wherein the test data comprises impedance test data; The fitting module is configured to input the impedance test data into an equivalent circuit model for fitting to obtain a plurality of circuit parameter values, wherein the equivalent circuit model is constructed according to the target type of the battery cell, and the equivalent circuit model includes four sub-circuits, the first sub-circuit includes a charge transfer resistance, the second sub-circuit is a solution resistance and a first constant phase element in parallel, the third sub-circuit is an active material resistance and a second constant phase element in parallel, and the fourth sub-circuit is a double-layer resistance-capacitance and a third constant phase element in parallel, the first constant phase element is a constant phase element representing the interface characteristics between the binder and the solvent, the second constant phase element is a constant phase element representing the interface characteristics between the binder and the active material, the third constant phase element is a constant phase element representing the interface characteristics between the conductive agent and the active material, the double-layer resistance-capacitance is a double-layer resistance and a double-layer capacitance in series, and the four sub-circuits are connected in series. The prediction module is configured to predict a performance parameter of a battery cell made of the target slurry under the test parameters according to the plurality of circuit parameter values.

9. An electronic device comprising: a processor; a memory configured to store instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the battery cell performance parameter prediction method of any one of claims 1 to 7.

10. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, enable the electronic device to perform the battery cell performance parameter prediction method of any one of claims 1 to 7.

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