Method, device and electronic equipment for determining solid phase diffusion coefficient of battery material

Abstract

This application discloses a method, apparatus, and electronic device for determining the solid-phase diffusion coefficient of battery materials, belonging to the field of battery technology. The method for determining the solid-phase diffusion coefficient of the battery material includes: obtaining a first solid-phase diffusion coefficient based on the test parameters corresponding to the battery material to be tested; determining a correction parameter corresponding to the first solid-phase diffusion coefficient based on the first solid-phase diffusion coefficient and a preset correlation relationship; the preset correlation relationship is pre-constructed based on the particle size of various materials and the calculation formula of the first diffusion coefficient; and correcting the first solid-phase diffusion coefficient according to the correction parameter. The method for determining the solid-phase diffusion coefficient of battery materials in this application can correct the first solid-phase diffusion coefficient to a solid-phase diffusion coefficient closer to the true value according to the correction parameter, thereby improving the accuracy of battery material test results, and is simple and easy to implement.

Description

Technical Field

[0001] This application relates to the field of battery technology, and more specifically, to a method, apparatus, and electronic device for determining the solid-phase diffusion coefficient of a battery material. Background Technology

[0002] In battery material testing scenarios, the GITT measurement method is commonly used to measure the electrical performance data of spherical particulate materials in batteries under the premise of semi-infinite diffusion. The calculation formula based on GITT measurement contains approximate assumptions, and the actual measurement process usually deviates from these assumptions, resulting in large calculation errors and affecting the accuracy of the measurement values. Summary of the Invention

[0003] This application provides a method, apparatus, and electronic device for determining the solid-phase diffusion coefficient of a battery material, which corrects the first solid-phase diffusion coefficient to a solid-phase diffusion coefficient that is closer to the true value according to the correction parameters, thereby improving the accuracy of battery material test results, and is simple and easy to implement.

[0004] In a first aspect, embodiments of this application provide a method for determining the solid-phase diffusion coefficient of a battery material, comprising:

[0005] Based on the test parameters corresponding to the battery material to be tested, the first solid-phase diffusion coefficient is obtained;

[0006] Based on the first solid-phase diffusion coefficient and the preset correlation, a correction parameter corresponding to the first solid-phase diffusion coefficient is determined; the preset correlation is pre-constructed according to the material particle size of various materials and the calculation formula of the first diffusion coefficient.

[0007] The first solid-phase diffusion coefficient is corrected according to the correction parameters;

[0008] The test parameters are those used to test the solid-phase diffusion coefficient of battery electrode materials, and the test method is constant current intermittent titration.

[0009] The preset correlation relationship is used to characterize the correlation between the calculated value of the diffusion coefficient obtained by solving the approximate solution of the first diffusion coefficient calculation formula and the theoretical value of the solid diffusion coefficient.

[0010] The first diffusion coefficient calculation formula is the original equation used to characterize the change of surface concentration over time.

[0011] In the above technical solution, a preset correlation relationship is established between the calculated value and the theoretical value of the solid-phase diffusion coefficient of spherical particles under the premise of semi-infinite diffusion. In the actual test process, the correction parameter is determined based on the currently obtained solid-phase diffusion coefficient and the preset correlation relationship to correct the error between the approximate solution and the original solution in the calculation of the solid-phase diffusion coefficient. This allows the first solid-phase diffusion coefficient to be corrected to a solid-phase diffusion coefficient that is closer to the true value based on the correction parameter, thereby improving the accuracy of the battery material test results. Moreover, the operation is simple and easy to implement.

[0012] In some embodiments, the preset association relationship is pre-constructed based on the material particle size and first diffusion coefficient calculation formula of various materials, including:

[0013] Obtain the particle size of the target material and at least one second solid-phase diffusion coefficient corresponding to the particle size;

[0014] Based on the second solid-phase diffusion coefficient and the first analytical expression in the calculation formula of the first diffusion coefficient, the change in surface concentration at each time step is obtained.

[0015] Substituting the surface concentration change into the first diffusion coefficient calculation formula, and based on the approximate solution equation of the first analytical expression, the third solid-phase diffusion coefficient corresponding to each surface concentration change is obtained.

[0016] The preset correlation relationship is constructed based on the third solid-phase diffusion coefficient corresponding to the change in surface concentration and the second solid-phase diffusion coefficient corresponding to the change in surface concentration.

[0017] In the above technical solution, a preset correlation relationship is set according to the spherical particles of different material types. In the actual test process, the corresponding preset correlation relationship is selected according to the current material type to be tested to obtain the correction value. This can further improve the accuracy of the obtained correction value, thereby improving the correction effect and making the final solid diffusion coefficient closer to the true value, and has high flexibility.

[0018] In some embodiments, obtaining the surface concentration change corresponding to each time step based on the first analytical expression in the calculation formula of the second solid-phase diffusion coefficient and the first diffusion coefficient includes:

[0019] Substitute the second solid-phase diffusion coefficient into the first analytical expression to obtain the analytical value of the first analytical expression corresponding to each time step;

[0020] Substituting the analytical value, the material particle size, and the current flux into the first diffusion coefficient calculation formula, the surface concentration change corresponding to each time step is obtained.

[0021] In some embodiments, obtaining at least one second solid-phase diffusion coefficient corresponding to the particle size of the material includes:

[0022] Determine the theoretical range of the solid-phase diffusion coefficient corresponding to the target material;

[0023] Within the theoretical range, multiple different values ​​are set as the second solid-phase diffusion coefficient.

[0024] In the above technical solution, by setting the theoretical range of the solid-phase diffusion coefficient corresponding to the target material and the second solid-phase diffusion coefficient corresponding to the material particle size, it has high realism and calculation accuracy.

[0025] In some embodiments, determining the correction parameter corresponding to the first solid-phase diffusion coefficient based on the first solid-phase diffusion coefficient and a preset correlation includes:

[0026] Based on the material type of the battery material to be tested, a preset association relationship corresponding to the material type is determined;

[0027] The first solid-phase diffusion coefficient is processed according to the preset correlation to obtain the correction parameter.

[0028] In the above technical solution, a preset correlation relationship is set according to the spherical particles of different material types. In the actual test process, the corresponding preset correlation relationship is selected according to the current material type to be tested to obtain the correction value. This can further improve the accuracy of the obtained correction value, thereby improving the correction effect and making the final solid diffusion coefficient closer to the true value, and has high flexibility.

[0029] In some embodiments, before obtaining the first solid-phase diffusion coefficient based on the acquired test parameters corresponding to the battery material to be tested, the method further includes:

[0030] A GITT test is performed on a battery made from the battery material to be tested to obtain the test parameters.

[0031] In some embodiments, obtaining the first solid-phase diffusion coefficient based on the acquired test parameters corresponding to the battery material to be tested includes:

[0032] The test parameters are substituted into the second diffusion coefficient calculation formula to obtain the first solid-phase diffusion coefficient; the second diffusion coefficient calculation formula is derived from the first diffusion coefficient calculation formula.

[0033] In some embodiments, the test parameters include: the linear slope of the pulse voltage versus the square root of time, the thermodynamic equilibrium potential difference before and after the pulse, the pulse time, and the material particle size.

[0034] Secondly, embodiments of this application provide a device for determining the solid-phase diffusion coefficient of a battery material.

[0035] Thirdly, embodiments of this application provide an electronic device.

[0036] Fourthly, embodiments of this application provide a non-transitory computer-readable storage medium.

[0037] Fifthly, embodiments of this application provide a computer program product. Attached Figure Description

[0038] Figure 1 This is one of the flowcharts illustrating a method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application;

[0039] Figure 2 This is a second schematic flowchart illustrating a method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application.

[0040] Figure 3 This is the third flowchart illustrating the method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application.

[0041] Figure 4 This is one of the schematic diagrams showing intermediate results of the method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application;

[0042] Figure 5 This is a second schematic diagram illustrating intermediate results of the method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application.

[0043] Figure 6 A schematic diagram showing the results of a method for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application;

[0044] Figure 7 A schematic diagram of the structure of a device for determining the solid-phase diffusion coefficient of battery materials provided in some embodiments of this application;

[0045] Figure 8 The diagram shows the structure of an electronic device provided in some embodiments of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used in the description of this application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms "comprising" and "having," and any variations thereof, in the description, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the description, claims, or accompanying drawings of this application are used to distinguish different objects, not to describe a specific order or hierarchy.

[0048] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0049] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "attachment" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0050] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0051] In this application, "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0052] The following description, in conjunction with the accompanying drawings, details the method for determining the solid-phase diffusion coefficient of battery materials, the apparatus for determining the solid-phase diffusion coefficient of battery materials, the electronic equipment, and the readable storage medium provided in this application, through specific embodiments and application scenarios.

[0053] The method for determining the solid-phase diffusion coefficient of battery materials can be applied to the terminal, specifically by the hardware or software in the terminal.

[0054] The method for determining the solid-phase diffusion coefficient of battery materials provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the method for determining the solid-phase diffusion coefficient of battery materials. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The following uses an electronic device as the execution subject to illustrate the method for determining the solid-phase diffusion coefficient of battery materials provided in this application embodiment.

[0055] Among related technologies, GITT technology is the most commonly used method for measuring surface concentration (Ds). To simplify calculations, assumptions are usually introduced during the formula derivation. However, actual measurements often deviate from these assumptions, leading to significant calculation errors. The derivation of the Ds formula is based on Fick's second law, and under the premise of semi-infinite diffusion, a general formula for surface concentration versus time can be obtained: ;in, and Let represent the Li+ concentrations on the particle surface at time t and t=0, respectively, and j be the Li+ flux. Let be the particle radius, and F be the Faraday constant. Since... The analytical expression for Ds is quite complex and cannot be directly solved. In actual calculations, an approximate solution is used. However, this approximation has a precondition: In fact, even The error between the approximate solution and the original solution exceeds 5%, and the error will be further amplified after exponentiation, thus affecting the accuracy of the final measured solid diffusion coefficient.

[0056] Based on the above considerations, in order to solve the problem of low accuracy of the final measured solid diffusion coefficient, a method for determining the solid diffusion coefficient of battery materials is designed. The method includes obtaining a first solid diffusion coefficient based on the test parameters corresponding to the battery material to be tested; determining a correction parameter corresponding to the first solid diffusion coefficient based on the first solid diffusion coefficient and a preset correlation relationship; and correcting the first solid diffusion coefficient according to the correction parameter. The preset correlation relationship is pre-constructed based on the particle size of various materials and the calculation formula of the first diffusion coefficient.

[0057] In this method for determining the solid-phase diffusion coefficient of battery materials, a pre-defined correlation relationship is established between the calculated and theoretical values ​​of the solid-phase diffusion coefficient. During actual testing, correction parameters are determined based on the currently obtained solid-phase diffusion coefficient and the pre-defined correlation relationship to correct the error between the approximate solution and the original solution in the calculation of the solid-phase diffusion coefficient. This allows the first solid-phase diffusion coefficient to be corrected to a solid-phase diffusion coefficient that is closer to the true value based on the correction parameters, thereby improving the accuracy of the battery material test results. The method is also simple and easy to implement.

[0058] like Figure 1 As shown, the method for determining the solid-phase diffusion coefficient of the battery material includes steps 110, 120, and 130.

[0059] Step 110: Based on the test parameters corresponding to the battery material to be tested, obtain the first solid-phase diffusion coefficient;

[0060] In this step, the first solid-phase diffusion coefficient is the solid-phase diffusion coefficient obtained by approximating the solution of the equation.

[0061] The test parameters are those used to test the solid-phase diffusion coefficient of battery electrode materials, including: intrinsic material parameters, test condition parameters, and electrode structure parameters.

[0062] Constant current intermittent titration (GITT) or potentiometric intermittent titration (PITT) can be used.

[0063] Taking constant current intermittent titration as an example, a short-duration micro-current pulse can be applied to the battery, and then left to stand for a period of time to allow the system to return to equilibrium. By analyzing the voltage changes during the current pulse and the resting period, key information can be extracted and test parameters can be obtained.

[0064] In some embodiments, the test parameters include: the linear slope of the pulse voltage versus the square root of time, the thermodynamic equilibrium potential difference before and after the pulse, the pulse time, and the material particle size.

[0065] In this embodiment, the particle size of the material is the radius r of the active particles. s (Unit: cm), pulse time is the current pulse time. (Unit: s).

[0066] Thermodynamic equilibrium potential difference before and after the pulse (Unit: V), which is the steady-state voltage change after a single pulse, can be obtained by subtracting the thermodynamic potentials after two relaxations.

[0067] linear slope of pulse voltage versus the square root of time It can be obtained by linearly fitting the measured pulse voltage and the square root of time within a certain time range.

[0068] In some embodiments, prior to step 110, the method further includes:

[0069] GITT testing was performed on batteries made from the battery materials to be tested to obtain test parameters.

[0070] In this embodiment, such as Figure 2 As shown, the electrode sheet can be prepared first, the battery can be assembled, and then the GITT test can be performed to obtain the test parameters.

[0071] Electrode preparation methods include, but are not limited to: conventional wet coating, dry process, etc.

[0072] The assembled batteries can include, but are not limited to, button cell, stacked cell, and pouch cell types of full or half cells, and can also be assembled into three-electrode cells.

[0073] After battery assembly, formation and pre-cycling steps can be performed. Formation activates the battery, enabling it to charge and discharge for the first time and forming an SEI film on the negative electrode. After formation and venting, the battery undergoes a certain number of complete charge-discharge cycles (e.g., 1-3 times) to complete the pre-cycling.

[0074] Then charge the battery to full and perform a GITT test.

[0075] In some embodiments, performing a GITT test on a battery made from the battery material to be tested includes:

[0076] Apply a pulse current of the first duration to the battery;

[0077] After a second settling period, test parameters were collected.

[0078] In this embodiment, the pulse current is generally less than 4C, and the rate can be appropriately reduced according to the actual rate performance of the battery. For example, it can be adjusted to 0.5C~0.1C at a lower SOC.

[0079] The duration can be determined comprehensively based on the number of solid-phase diffusion coefficients obtained and the test time. A shorter pulse time can ensure that more solid-phase diffusion coefficients under SOC are obtained, while a longer pulse can shorten the overall test time.

[0080] The second duration can be determined comprehensively based on the effect of electrode balancing and the test time. A longer relaxation time can ensure electrode balancing, while a shorter relaxation time can shorten the test. In some embodiments, the second duration can be set between 300s and 7200s.

[0081] In some embodiments, the battery can also be subjected to multiple pulse-rest cycles. The cycle test can be determined according to the SOC change range of a single pulse to ensure that the electrode reaches full discharge after the GITT test. For example, the number of cycles is set to 30 for a pulse rate of 4C and a pulse time of 30s.

[0082] In some embodiments, a voltage cutoff condition can also be set to terminate the GITT test when the battery voltage is below the cutoff voltage, thereby reducing the risk of over-discharge of the battery. The cutoff voltage can be set according to the battery material; for example, for ternary materials (including lithium nickel cobalt manganese oxide or lithium nickel cobalt aluminum oxide, etc.), the cutoff voltage can be set to 2.5V~2.8V.

[0083] Continuing with the GITT test as an example, in order to simplify the calculation when using GITT to test the solid-phase diffusion coefficient, assumptions are usually introduced in the formula derivation. The derivation of the solid-phase diffusion coefficient formula is based on Fick's second law. Under the premise of semi-infinite diffusion, the general solution formula for surface concentration versus time can be obtained as follows:

[0084]

[0085] in, Let be the Li+ concentration on the particle surface at time t; t = 0 represents the Li+ concentration on the particle surface; j represents the Li+ flux, which is the given pulse current and can be determined based on the actual experimental scenario. Where is the particle size of the material; F is the Faraday constant; t is the solid-phase diffusion coefficient; t is time.

[0086] because The analytical expression is quite complex and cannot be solved directly. In actual calculations, an approximate solution is taken, and the approximate solution expression is as follows:

[0087]

[0088] In actual testing, after obtaining the test parameters, the test parameters can be substituted into the above approximate solution formula to obtain the first solid-phase diffusion coefficient.

[0089] In some embodiments, step 110 includes:

[0090] Substituting the test parameters into the second diffusion coefficient calculation formula yields the first solid-phase diffusion coefficient; the second diffusion coefficient calculation formula is derived from a modified version of the first diffusion coefficient calculation formula.

[0091] In this embodiment, the formula for calculating the second diffusion coefficient is as follows:

[0092]

[0093] in, The first solid-phase diffusion coefficient; The linear slope of the pulse voltage versus the square root of time; For material particle size; The thermodynamic equilibrium potential difference before and after the pulse; The pulse duration.

[0094] The formula for calculating the second diffusion coefficient is derived from a modified version of the formula for calculating the first diffusion coefficient.

[0095] The formula for calculating the first diffusion coefficient is the original equation used to characterize the change of surface concentration over time. The formula for calculating the first diffusion coefficient is shown below:

[0096]

[0097] in, t represents the change in Li+ concentration on the particle surface over time t; j represents the Li+ flux. Where is the particle size of the material; F is the Faraday constant; The solid-phase diffusion coefficient; The true analytical expression, i.e., the original solution, is shown below:

[0098]

[0099] in, for ; For the equation The nth positive root.

[0100] When the time is short, you can Substituting the approximate solution into the original equation simplifies the original equation to the following approximate solution: Solve the simplified equation:

[0101]

[0102] pass The approximate solution is used to solve the simplified equation, which is then transformed into a stoichiometric expression. Represented as:

[0103]

[0104] The GITT test can obtain data on the change of voltage E over time. When the stoichiometric coefficient x is difficult to measure directly, the relationship between the stoichiometric coefficient x and voltage E can be established, as shown below:

[0105]

[0106] in, The slope of the pulse voltage versus the square root of time is the linear slope.

[0107] Simplifying the above formula, we get:

[0108]

[0109] If the potential change caused by a short-term change in the stoichiometric coefficients of a material is linear, it can be calculated using the voltage change before and after the pulse:

[0110]

[0111]

[0112] Where A and V are the surface area and volume of the material, respectively. This refers to the change in voltage. For the duration; this formula can be understood as the change in stoichiometry caused by an electric current entering the material through its surface. For granular materials, spheres are generally used for calculation. The formula for calculating the second diffusion coefficient, obtained by integrating the formulas, is shown below:

[0113]

[0114] Step 120: Based on the first solid-phase diffusion coefficient and the preset correlation, determine the correction parameter corresponding to the first solid-phase diffusion coefficient;

[0115] In this step, the preset correlation is used to characterize the correlation between the calculated value of the diffusion coefficient obtained by solving the approximate solution of the solid diffusion coefficient calculation formula and the theoretical value of the solid diffusion coefficient. The preset correlation can be expressed as a correlation table, a functional relationship or other forms, which are not limited in this application.

[0116] The correction parameter is used to correct the error between the approximate solution and the original solution. The correction parameter can be the theoretical value corresponding to the first solid-phase diffusion coefficient, or it can be a parameter value that can correct the first solid-phase diffusion coefficient to the theoretical value through a certain calculation method using the correction parameter. This application does not limit it here.

[0117] Figure 4 An example of a preset correlation is provided to characterize the ratio of the calculated value Ds_test of the solid-phase diffusion coefficient to the theoretical value Ds_real of the solid-phase diffusion coefficient. The horizontal axis represents the theoretical value Ds_real of the solid-phase diffusion coefficient, and the vertical axis represents the ratio of the calculated value Ds_test of the solid-phase diffusion coefficient to the theoretical value Ds_real.

[0118] The preset association relationship is pre-constructed based on the material particle size and the first diffusion coefficient calculation formula of various materials. The specific construction method will be explained in the following embodiments, and will not be elaborated here.

[0119] In some embodiments, the preset association can also be constructed based on different categories of materials.

[0120] In some embodiments, step 120 includes:

[0121] Based on the material type of the battery material to be tested, determine the preset association relationship with the material type;

[0122] The first solid-phase diffusion coefficient is processed according to the preset correlation to obtain the correction parameter.

[0123] In this embodiment, preset correlation relationships corresponding to different types of materials can be pre-constructed. In actual application, the preset correlation relationship that matches the type of material to be tested is selected, and the corresponding correction value is obtained by combining the calculated value of the solid diffusion coefficient obtained by actual measurement with the preset correlation relationship.

[0124] According to the method for determining the solid diffusion coefficient of battery materials provided in the embodiments of this application, a preset correlation relationship is set according to the different material categories under spherical particles. In the actual test process, the corresponding preset correlation relationship is selected according to the current material type to be tested to obtain the correction value, which can further improve the accuracy of the obtained correction value, thereby improving the correction effect, making the final solid diffusion coefficient closer to the true value, and having high flexibility.

[0125] Step 130: Correct the first solid-phase diffusion coefficient according to the correction parameters.

[0126] In this step, the first solid-phase diffusion coefficient is corrected according to the correction parameters, and the final target solid-phase diffusion coefficient is closer to the true value.

[0127] Taking the preset correlation relationship as a direct correspondence between the calculated value and the theoretical value as an example, the correction value obtained by the first solid-phase diffusion coefficient and the preset correlation relationship can be approximately regarded as the theoretical value corresponding to the first solid-phase diffusion coefficient. Then, the first solid-phase diffusion coefficient can be directly corrected to this correction parameter.

[0128] Figure 5 The example demonstrates the calculation results of the solid-phase diffusion coefficient of a ternary material under different lithium intercalation amounts. Figure 6 An example of a sampling preset association pair Figure 5 The target solid-phase diffusion coefficient, after correction of the calculated solid-phase diffusion coefficient, is shown below. Figure 6The lower curve represents the solid-phase diffusion coefficient before correction, while the upper curve represents the solid-phase diffusion coefficient after correction.

[0129] In related technologies, there is also a method to obtain the solid-phase diffusion coefficient by comparing measured electrical performance data with simulation results and adjusting and optimizing simulation parameters. However, this method obtains the solid-phase diffusion coefficient by reversing the parameters through simulation, which makes the calculation results dependent on the accuracy of the simulation model and the accuracy of other parameters within the model, thus affecting the accuracy of the final obtained solid-phase diffusion coefficient.

[0130] According to the method for determining the solid-phase diffusion coefficient of battery materials provided in this application embodiment, a preset correlation relationship between the calculated value and the theoretical value of the solid-phase diffusion coefficient of spherical particles under the premise of semi-infinite diffusion is pre-constructed. In the actual test process, a correction parameter is determined based on the currently obtained solid-phase diffusion coefficient and the preset correlation relationship to correct the error between the approximate solution and the original solution in the calculation of the solid-phase diffusion coefficient. This allows the first solid-phase diffusion coefficient to be corrected to a solid-phase diffusion coefficient that is closer to the true value based on the correction parameter, thereby improving the accuracy of the battery material test results. The method is simple and easy to implement.

[0131] The following explains the specific construction method of the preset association relationship.

[0132] In some embodiments, the preset association relationship is pre-constructed based on the material particle size and first diffusion coefficient calculation formula of various materials, including:

[0133] Obtain the particle size of the target material and at least one second solid-phase diffusion coefficient corresponding to the particle size;

[0134] Based on the first analytical expression in the calculation formulas for the second solid-phase diffusion coefficient and the first diffusion coefficient, the change in surface concentration at each time step is obtained.

[0135] Substituting the surface concentration change into the first diffusion coefficient calculation formula, and based on the approximate solution of the first analytical equation, the third solid-phase diffusion coefficient corresponding to each surface concentration change is obtained.

[0136] A pre-defined correlation is constructed based on the third solid-phase diffusion coefficient corresponding to the change in surface concentration and the second solid-phase diffusion coefficient corresponding to the change in surface concentration.

[0137] In this embodiment, the target material can be any type of material.

[0138] The second solid-phase diffusion coefficient is the theoretical solid-phase diffusion coefficient of the target material at the current material particle size. It can be approximated as the true value, which can be determined based on prior knowledge or theoretical knowledge.

[0139] The third solid-phase diffusion coefficient is the calculated value of the solid-phase diffusion coefficient obtained by using the formula for calculating the first diffusion coefficient, which includes an approximate solution.

[0140] For the same particle size of the same target material, there may be one or more second solid-phase diffusion coefficients.

[0141] Taking the GITT test as an example, the first analytical expression is:

[0142]

[0143] The approximate solution equation for the first analytical expression is:

[0144]

[0145] The time step is a short time interval and can be user-defined. It should be noted that the time step can be consistent with the time step in the subsequent actual test process.

[0146] The change in surface concentration is the change in Li+ concentration on the particle surface.

[0147] Methods for measuring material particle size may include, but are not limited to, spectroscopic methods, electron microscopy, sedimentation methods, and specific surface area methods. In some embodiments, for material systems with a certain particle size distribution, statistically significant particle sizes, such as D50 / 2, may also be used.

[0148] According to the method for determining the solid diffusion coefficient of battery materials provided in the embodiments of this application, a preset correlation relationship is set according to the spherical particles of different material types. In the actual test process, the corresponding preset correlation relationship is selected according to the current material type to be tested to obtain the correction value, which can further improve the accuracy of the obtained correction value, thereby improving the correction effect, making the final solid diffusion coefficient closer to the true value, and having high flexibility.

[0149] In some embodiments, obtaining at least one second solid-phase diffusion coefficient corresponding to the material particle size includes:

[0150] Determine the theoretical range of the solid-phase diffusion coefficient corresponding to the target material type;

[0151] Within the theoretical range, several different values ​​are set as the second solid-phase diffusion coefficient.

[0152] In this embodiment, the theoretical range can be set according to the specific category of the target material to improve the accuracy and comprehensiveness of the obtained second solid-phase diffusion coefficient, while reducing unnecessary calculations; for example, for ternary materials, the theoretical range can be set to 10. -10 ~10 -20 m 2 s -1 .

[0153] The numerical values ​​within this theoretical range are extracted as the second solid-phase diffusion coefficient. It is understandable that the number of extracted second solid-phase diffusion coefficients can be set based on a combination of computational accuracy and computational speed; a larger number corresponds to higher computational accuracy, while a smaller number results in relatively faster computational efficiency.

[0154] In some embodiments, a first number of second solid-phase diffusion coefficients can be set for each order of magnitude within the theoretical range to balance computational speed and accuracy. The first number can be 100 or 110, etc. In some embodiments, multiple different values ​​can be collected within the theoretical range as the second solid-phase diffusion coefficients using a random or interval extraction method, which is not limited herein.

[0155] like Figure 2 As shown, for target materials, the particle size r can be measured first. s For material particle size r s Multiple theoretical values ​​for the second solid-phase diffusion coefficient Ds are set accordingly, and then the material particle size r is considered. s A preset correlation is generated between the theoretical value of the second solid-phase diffusion coefficient Ds and the first solid-phase diffusion coefficient. This preset correlation is used to correct the first solid-phase diffusion coefficient when subsequently measuring the solid-phase diffusion coefficient of materials of the same type as the target material.

[0156] According to the method for determining the solid-phase diffusion coefficient of battery materials provided in the embodiments of this application, a second solid-phase diffusion coefficient corresponding to the particle size of the material is set by using the theoretical range of the solid-phase diffusion coefficient corresponding to the spherical particles of the target material, which has high realism and calculation accuracy.

[0157] In some embodiments, the surface concentration change corresponding to each time step is obtained based on the first analytical expression in the formula for calculating the second solid-phase diffusion coefficient and the first diffusion coefficient, including:

[0158] Substituting the second solid-phase diffusion coefficient into the first analytical expression, the analytical value of the first analytical expression corresponding to each time step is obtained;

[0159] Substituting the analytical value, material particle size, and current flux into the formula for calculating the first diffusion coefficient, the change in surface concentration at each time step is obtained.

[0160] In this embodiment, the analytical value is the value obtained by solving the actual first analytical expression, which is the value obtained by substituting the second solid-phase diffusion coefficient into the first analytical expression. The value obtained.

[0161] Then, the obtained analytical values, material particle size, and current flux are substituted into the first diffusion coefficient calculation formula to obtain the surface concentration change corresponding to each time step.

[0162] The following is combined with Figure 3 According to the material particle size r s The specific implementation method for generating the preset correlation relationship of the second solid-phase diffusion coefficient Ds_theoretical value is explained.

[0163] In actual execution, for a given theoretical range and quantity, a set of Ds_theoretical values ​​can be generated.

[0164] Substitute each theoretical value of Ds into the formula for calculating the first diffusion coefficient. Generate a set ( The data pairs from t to t represent the surface concentration changes at each time step: First, determine the time range and quantity based on the single pulse time and time interval set in the actual test process. For example, t can be set as a time series data set of 1-30s with an interval of 0.1s. Substitute the theoretical value of Ds_ into the first analytical expression to calculate the corresponding ( ) at each time step t. ) values, resulting in multiple sets ( ) ~t data.

[0165] Each group ( Substitute the Cs-t data into the diffusion coefficient calculation formula to calculate the corresponding Ds value. In the process, the calculated value of the third solid-phase diffusion coefficient Ds_ is obtained.

[0166] Repeat the above steps, substituting all the given theoretical values ​​of Ds into the analytical expression to obtain ( The theoretical value of Ds is calculated by substituting the data into the approximate solution simulation to obtain the calculated value of Ds, thus obtaining multiple sets of theoretical values ​​of Ds and calculated values ​​of Ds. Then, the multiple sets of data are fitted to obtain a preset correlation relationship used to characterize the relationship between the theoretical value of Ds and the calculated value of Ds.

[0167] The fitting process may also include interpolation.

[0168] According to the method for determining the solid-phase diffusion coefficient of battery materials provided in this application embodiment, a preset correlation relationship between the calculated value and the theoretical value of the solid-phase diffusion coefficient of spherical particles under the premise of semi-infinite diffusion is pre-constructed. In the actual test process, a correction parameter is determined based on the currently obtained solid-phase diffusion coefficient and the preset correlation relationship to correct the error between the approximate solution and the original solution in the calculation of the solid-phase diffusion coefficient. This allows the first solid-phase diffusion coefficient to be corrected to a solid-phase diffusion coefficient that is closer to the true value based on the correction parameter, thereby improving the accuracy of the battery material test results. The method is simple and easy to implement.

[0169] The method for determining the solid-phase diffusion coefficient of battery materials provided in this application can be executed by a device for determining the solid-phase diffusion coefficient of battery materials. This application uses the device for determining the solid-phase diffusion coefficient of battery materials executing the method for determining the solid-phase diffusion coefficient of battery materials as an example to illustrate the device for determining the solid-phase diffusion coefficient of battery materials provided in this application.

[0170] This application also provides an apparatus for determining the solid-phase diffusion coefficient of a battery material.

[0171] like Figure 7 As shown, the device for determining the solid-phase diffusion coefficient of the battery material includes: a first processing module 710, a second processing module 720, and a third processing module 730.

[0172] The first processing module 710 is used to obtain the first solid-phase diffusion coefficient based on the test parameters corresponding to the battery material to be tested.

[0173] The second processing module 720 is used to determine the correction parameters corresponding to the first solid-phase diffusion coefficient based on the first solid-phase diffusion coefficient and the preset correlation relationship; the preset correlation relationship is pre-constructed based on the material particle size of various materials and the calculation formula of the first diffusion coefficient.

[0174] The third processing module 730 is used to correct the first solid-phase diffusion coefficient according to the correction parameters.

[0175] According to the solid diffusion coefficient determination device for battery materials provided in the embodiments of this application, a preset correlation relationship is established between the calculated value and the theoretical value of the solid diffusion coefficient of spherical particles under the premise of semi-infinite diffusion. In the actual test process, a correction parameter is determined based on the currently obtained solid diffusion coefficient and the preset correlation relationship to correct the error between the approximate solution and the original solution in the calculation of the solid diffusion coefficient. This allows the first solid diffusion coefficient to be corrected to a solid diffusion coefficient that is closer to the true value based on the correction parameter, thereby improving the accuracy of the battery material test results. The device is simple to operate and easy to implement.

[0176] In some embodiments, the device further includes a fourth processing module for:

[0177] Obtain the particle size of the target material and at least one second solid-phase diffusion coefficient corresponding to the particle size;

[0178] Based on the first analytical expression in the calculation formulas for the second solid-phase diffusion coefficient and the first diffusion coefficient, the change in surface concentration at each time step is obtained.

[0179] Substituting the surface concentration change into the first diffusion coefficient calculation formula, and based on the approximate solution of the first analytical equation, the third solid-phase diffusion coefficient corresponding to each surface concentration change is obtained.

[0180] A pre-defined correlation is constructed based on the third solid-phase diffusion coefficient corresponding to the change in surface concentration and the second solid-phase diffusion coefficient corresponding to the change in surface concentration.

[0181] In some embodiments, the fourth processing module is configured to:

[0182] Substituting the second solid-phase diffusion coefficient into the first analytical expression, the analytical value of the first analytical expression corresponding to each time step is obtained;

[0183] Substituting the analytical value, material particle size, and current flux into the formula for calculating the first diffusion coefficient, the change in surface concentration at each time step is obtained.

[0184] In some embodiments, the fourth processing module is configured to:

[0185] Determine the theoretical range of the solid-phase diffusion coefficient corresponding to the target material type;

[0186] Within the theoretical range, several different values ​​are set as the second solid-phase diffusion coefficient.

[0187] In some embodiments, the second processing module 720 is configured to:

[0188] Based on the material type of the battery material to be tested, determine the preset association relationship with the material type;

[0189] The first solid-phase diffusion coefficient is processed according to the preset correlation to obtain the correction parameter.

[0190] In some embodiments, the device further includes a fifth processing module for:

[0191] Before obtaining the first solid-phase diffusion coefficient based on the test parameters corresponding to the battery material to be tested, a GITT test is performed on the battery made from the battery material to be tested to obtain the test parameters.

[0192] In some embodiments, the first processing module 710 is configured to:

[0193] Substituting the test parameters into the second diffusion coefficient calculation formula yields the first solid-phase diffusion coefficient; the second diffusion coefficient calculation formula is derived from a modified version of the first diffusion coefficient calculation formula.

[0194] The device for determining the solid-phase diffusion coefficient of the battery material in this application embodiment can be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the specific device.

[0195] The device for determining the solid-phase diffusion coefficient of the battery material in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0196] The device for determining the solid-phase diffusion coefficient of battery materials provided in this application embodiment can achieve... Figures 1 to 6 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0197] In some embodiments, such as Figure 8 As shown, this application embodiment also provides an electronic device 800, including a processor 801, a memory 802, and a computer program stored in the memory 802 and executable on the processor 801. When the program is executed by the processor 801, it implements the various processes of the above-mentioned method embodiment for determining the solid-phase diffusion coefficient of battery materials and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0198] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0199] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method embodiment for determining the solid-phase diffusion coefficient of battery materials and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0200] This application also provides a computer program product, including a computer program that, when executed by a processor, implements a method for determining the solid-phase diffusion coefficient of the aforementioned battery material.

[0201] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0202] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described method embodiment for determining the solid-phase diffusion coefficient of battery materials, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0203] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0204] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0205] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of 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 solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer 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 (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0206] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0207] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0208] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for determining the solid-phase diffusion coefficient of a battery material, characterized in that, include: Based on the test parameters corresponding to the battery material to be tested, the first solid-phase diffusion coefficient is obtained; Based on the first solid-phase diffusion coefficient and the preset correlation relationship, a correction parameter corresponding to the first solid-phase diffusion coefficient is determined. The preset correlation relationship is pre-constructed based on the material particle size and first diffusion coefficient calculation formula of various materials; The first solid-phase diffusion coefficient is corrected according to the correction parameters; The test parameters are those used to test the solid-phase diffusion coefficient of battery electrode materials, and the test method is constant current intermittent titration. The preset correlation relationship is used to characterize the correlation between the calculated value of the diffusion coefficient obtained by solving the approximate solution of the first diffusion coefficient calculation formula and the theoretical value of the solid diffusion coefficient. The first diffusion coefficient calculation formula is the original equation used to characterize the change of surface concentration over time; The preset correlation relationship is pre-constructed based on the material particle size and first diffusion coefficient calculation formula of various materials, including: Obtain the particle size of the target material and at least one second solid-phase diffusion coefficient corresponding to the particle size; Based on the second solid-phase diffusion coefficient and the first analytical expression in the calculation formula of the first diffusion coefficient, the change in surface concentration at each time step is obtained. Substituting the surface concentration change into the first diffusion coefficient calculation formula, and based on the approximate solution equation of the first analytical expression, the third solid-phase diffusion coefficient corresponding to each surface concentration change is obtained. The preset correlation relationship is constructed based on the third solid-phase diffusion coefficient corresponding to the change in surface concentration and the second solid-phase diffusion coefficient corresponding to the change in surface concentration.

2. The method for determining the solid-phase diffusion coefficient of the battery material according to claim 1, characterized in that, The surface concentration change at each time step is obtained based on the first analytical expression in the calculation formula of the second solid-phase diffusion coefficient and the first diffusion coefficient, including: Substitute the second solid-phase diffusion coefficient into the first analytical expression to obtain the analytical value of the first analytical expression corresponding to each time step; Substituting the analytical value, the material particle size, and the current flux into the first diffusion coefficient calculation formula, the surface concentration change corresponding to each time step is obtained.

3. The method for determining the solid-phase diffusion coefficient of the battery material according to claim 1, characterized in that, Obtaining at least one second solid-phase diffusion coefficient corresponding to the particle size of the material includes: Determine the theoretical range of the solid-phase diffusion coefficient corresponding to the target material; Within the theoretical range, multiple different values ​​are set as the second solid-phase diffusion coefficient.

4. The method for determining the solid-phase diffusion coefficient of the battery material according to any one of claims 1-3, characterized in that, The step of determining the correction parameter corresponding to the first solid-phase diffusion coefficient based on the first solid-phase diffusion coefficient and the preset correlation relationship includes: Based on the material type of the battery material to be tested, a preset association relationship corresponding to the material type is determined; The first solid-phase diffusion coefficient is processed according to the preset correlation to obtain the correction parameter.

5. The method for determining the solid-phase diffusion coefficient of the battery material according to any one of claims 1-3, characterized in that, Before obtaining the first solid-phase diffusion coefficient based on the acquired test parameters corresponding to the battery material to be tested, the method further includes: A GITT test is performed on a battery made from the battery material to be tested to obtain the test parameters.

6. The method for determining the solid-phase diffusion coefficient of the battery material according to any one of claims 1-3, characterized in that, The first solid-phase diffusion coefficient is obtained based on the test parameters corresponding to the battery material to be tested, including: The test parameters are substituted into the second diffusion coefficient calculation formula to obtain the first solid-phase diffusion coefficient; the second diffusion coefficient calculation formula is derived from the first diffusion coefficient calculation formula.

7. The method for determining the solid-phase diffusion coefficient of the battery material according to any one of claims 1-3, characterized in that, The test parameters include: the linear slope of the pulse voltage versus the square root of time, the thermodynamic equilibrium potential difference before and after the pulse, the pulse time, and the material particle size.

8. An apparatus for determining the solid-phase diffusion coefficient of a battery material based on the method for determining the solid-phase diffusion coefficient of a battery material as described in any one of claims 1-7, characterized in that, include: The first processing module is used to obtain the first solid-phase diffusion coefficient based on the test parameters corresponding to the battery material to be tested. The second processing module is used to determine the correction parameter corresponding to the first solid-phase diffusion coefficient based on the first solid-phase diffusion coefficient and the preset correlation relationship. The preset correlation relationship is pre-constructed based on the material particle size and first diffusion coefficient calculation formula of various materials; The third processing module is used to correct the first solid-phase diffusion coefficient according to the correction parameters; The test parameters are those used to test the solid-phase diffusion coefficient of battery electrode materials, and the test method is constant current intermittent titration. The preset correlation relationship is used to characterize the correlation between the calculated value of the diffusion coefficient obtained by solving the approximate solution of the first diffusion coefficient calculation formula and the theoretical value of the solid diffusion coefficient. The first diffusion coefficient calculation formula is the original equation used to characterize the change of surface concentration over time.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for determining the solid-phase diffusion coefficient of the battery material as described in any one of claims 1-7.

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