A real-time porosity prediction method and system for silicon-based negative electrodes of lithium-ion batteries

Abstract

The present invention relates to a method and system for predicting the real-time porosity of a silicon-based negative electrode for a lithium-ion battery, in the field of lithium-ion batteries. The method comprises obtaining the weight fraction, density, initial porosity, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active and inactive materials; determining the real-time volume of each component particle based on the weight fraction, density, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; determining the initial volume of the silicon-based negative electrode based on the initial porosity and initial volume of each component particle; determining the real-time volume of the silicon-based negative electrode based on the weight fraction, density, and initial volume of the active material component of the silicon-based negative electrode; and determining the real-time porosity of the silicon-based negative electrode based on the real-time volume of the negative electrode and the real-time volume of each component particle. The present invention reduces the difficulty of predicting real-time porosity by using readily available parameters.

Description

Technical Field

[0001] The present invention relates to the field of lithium-ion batteries, and in particular to a method and system for predicting the real-time porosity of a silicon-based negative electrode of a lithium-ion battery. Background Art

[0002] The porosity of lithium-ion battery electrodes is a critical parameter that influences the battery's electrochemical performance. Specifically, porosity is closely related to the electrode's transport properties, internal resistance, and battery cycling performance. Existing porosity tests primarily focus on the initial porosity of the electrode. However, as lithium is inserted and removed, the electrode undergoes volume changes, and its porosity also fluctuates continuously. Understanding the real-time porosity changes of the electrode is crucial for analyzing battery performance. Unfortunately, real-time measurement of electrode porosity is very difficult, resulting in an urgent need for a simple, accurate, and real-time porosity prediction method.

[0003] There are numerous porosity testing methods, with mercury intrusion porosimetry (HIP) being the most common method used to measure electrode porosity. While existing porosity testing methods can measure electrode porosity, they are lossy and unsuitable for measuring real-time electrode porosity. Therefore, it is necessary to develop theoretical prediction methods to study real-time electrode porosity changes.

[0004] Silicon is considered one of the most promising negative electrode materials due to its highest specific energy density. Currently, silicon-based negative electrodes have been commercially used on a small scale, but the proportion of added silicon material components is generally low. This is because the silicon material undergoes a large volume deformation during the lithium insertion process, causing large stress inside the electrode, ultimately causing electrode damage and attenuation of electrochemical performance. Generally speaking, the volume deformation of the electrode component particles affects not only the porosity of the electrode, but also the volume of the electrode. For active materials with small deformation, such as graphite, the porosity and electrode volume deformation do not change much, and the porosity can be approximated to be unchanged. However, for silicon-based negative electrodes, large volume deformation of the silicon material may cause large changes in porosity.

[0005] Therefore, there is a need to develop a method for real-time porosity prediction using readily available parameters. Summary of the Invention

[0006] The purpose of the present invention is to provide a real-time porosity prediction method and system for lithium-ion battery silicon-based negative electrodes, which reduces the difficulty of real-time porosity calculation and experimental measurement through easily available parameters.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A real-time porosity prediction method for a lithium-ion battery silicon-based negative electrode comprises:

[0009] Obtaining the weight fraction, density, initial porosity, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components;

[0010] Determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state;

[0011] Determining the initial volume of the negative electrode according to the initial porosity of the silicon-based negative electrode and the initial volume of each of the component particles;

[0012] determining the real-time volume of the negative electrode according to the weight fraction of the active material component of the silicon-based negative electrode, the density, and the initial volume of the negative electrode;

[0013] The real-time porosity of the silicon-based negative electrode is determined according to the real-time volume of the negative electrode and the real-time volume of each component particle.

[0014] Optionally, determining the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state specifically includes:

[0015] Determine the initial volume of each component particle according to the weight fraction of each component and the density of the silicon-based negative electrode;

[0016] The real-time volume of each component particle is determined according to the initial volume of each component particle, the expansion coefficient of each component particle and the charge state.

[0017] Optionally, the expression for the real-time volume of each component particle is:

[0018] V p-i / V p-i0 =1+η i SOC,

[0019] Among them, V p-i is the real-time volume of the i-component particle, V p-i0 is the initial volume of the i-component particle, η i is the expansion coefficient of the i-component particles, and SOC is the state of charge.

[0020] Optionally, determining the real-time volume of the negative electrode according to the weight fraction of the active material component of the silicon-based negative electrode, the density and the initial volume of the negative electrode specifically includes:

[0021] Determining the volume fraction of each active material of the silicon-based negative electrode to the total active material according to the weight fraction of the active material component of the silicon-based negative electrode and the density;

[0022] Determine the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode according to the weight fraction of each component of the silicon-based negative electrode, the density and the initial volume of the negative electrode;

[0023] Determining a universal expansion coefficient based on the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode, the charge state, and the expansion coefficient of the active material component particles in each component;

[0024] The real-time volume of the negative electrode is determined according to the universal expansion coefficient, the volume fraction of each active material of the silicon-based negative electrode to the total active material, and the initial volume of the negative electrode.

[0025] Optionally, the volume fraction of each active material in the total active material is calculated as follows:

[0026]

[0027] Among them, ξ j is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j.

[0028] Optionally, the calculation formula for the volume fraction of each active material component in the battery negative electrode is:

[0029]

[0030] in, is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j, ω i is the weight fraction of component i, ρ i is the density of component i, V0 is the initial volume of the negative electrode, and ε0 is the initial porosity.

[0031] Optionally, the calculation formula of the universal expansion coefficient is:

[0032]

[0033] Among them, g j is the universal expansion coefficient of active material j, is the volume fraction of active material j in the negative electrode of the battery, η j is the expansion coefficient of active material j particles, and SOC is the state of charge.

[0034] Optionally, the calculation formula for the real-time volume of the negative electrode is:

[0035]

[0036] Where V is the real-time volume of the negative electrode, V0 is the initial volume of the negative electrode, ξ j is the volume fraction of active material j in the total active materials, η j is the expansion coefficient of active material j particle, SOC is the state of charge, g j is the universal expansion coefficient of active material j.

[0037] Optionally, the calculation formula for the real-time porosity of the silicon-based negative electrode is:

[0038]

[0039] Where ε is the real-time porosity of the negative electrode, V p-i is the real-time volume of the particles of component i, V is the real-time volume of the negative electrode, and i is the component type.

[0040] A real-time porosity prediction system for silicon-based negative electrodes of lithium-ion batteries, comprising:

[0041] An acquisition module is used to obtain the weight fraction, density, initial porosity, particle expansion coefficient and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components;

[0042] A module for determining the real-time volume of each component particle, configured to determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle, and the charge state;

[0043] A negative electrode initial volume determination module, configured to determine the negative electrode initial volume according to the initial porosity of the silicon-based negative electrode and the initial volume of each component particle;

[0044] A negative electrode real-time volume determination module, configured to determine the real-time volume of the negative electrode according to the weight fraction of the active material component of the silicon-based negative electrode, the density, and the initial volume of the negative electrode;

[0045] The silicon-based negative electrode real-time porosity determination module is used to determine the real-time porosity of the silicon-based negative electrode according to the real-time volume of the negative electrode and the real-time volume of each component particle.

[0046] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0047] The present invention provides a method and system for predicting the real-time porosity of a silicon-based negative electrode for a lithium-ion battery. The method obtains the weight fraction, density, initial porosity, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active materials and inactive materials; the real-time volume of each component particle is determined based on the weight fraction, density, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; the initial volume of the negative electrode is determined based on the initial porosity and initial volume of each component particle; the real-time volume of the negative electrode is determined based on the weight fraction, density, and initial volume of the active material component of the silicon-based negative electrode; and the real-time porosity of the silicon-based negative electrode is determined based on the real-time volume of the negative electrode and the real-time volume of each component particle. The real-time porosity prediction can be completed using readily available parameters, namely the weight fraction, density, initial porosity, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode. The method is simple and convenient, avoiding the problems of difficult operation, loss, and high cost in experiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 Flowchart of the real-time porosity prediction method for silicon-based negative electrodes of lithium-ion batteries provided by the present invention;

[0050] Figure 2 A schematic flow chart of the method for predicting the real-time porosity of silicon-based negative electrodes for lithium-ion batteries provided by the present invention;

[0051] Figure 3 This is a curve of real-time porosity change with SOC of silicon-based negative electrode with an initial porosity of 55% and the weight fractions of silicon, Nafion and carbon black being 50%, 25% and 25% respectively. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] The purpose of the present invention is to provide a real-time porosity prediction method and system for lithium-ion battery silicon-based negative electrodes, which reduces the difficulty of real-time porosity calculation and experimental measurement through easily available parameters.

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] like Figure 1 As shown, the present invention provides a real-time porosity prediction method for a lithium-ion battery silicon-based negative electrode, comprising:

[0056] Step 101: Obtain the weight fraction, density, initial porosity, particle expansion coefficient and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components.

[0057] Step 102: Determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state. Step 102 specifically includes:

[0058] The initial volume of each component particle is determined according to the weight fraction of each component and the density of the silicon-based negative electrode.

[0059] The real-time volume of each component particle is determined according to the initial volume of each component particle, the expansion coefficient of each component particle and the charge state.

[0060] The expression for the real-time volume of each component particle is:

[0061] V p-i / V p-i0 =1+η i SOC,

[0062] Among them, V p-i is the real-time volume of the i-component particle, V p-i0 is the initial volume of the i-component particle, η i is the expansion coefficient of the i-component particles, and SOC is the state of charge.

[0063] Step 103: Determine the initial volume of the negative electrode according to the initial porosity of the silicon-based negative electrode and the initial volume of each component particle.

[0064] Step 104: Determine the real-time volume of the negative electrode based on the weight fraction of the active material component of the silicon-based negative electrode, the density, and the initial volume of the negative electrode. Step 104 specifically includes:

[0065] The volume fraction of each active material in the silicon-based negative electrode to the total active material is determined based on the weight fraction of the active material component of the silicon-based negative electrode and the density. The volume fraction of each active material to the total active material is calculated as follows:

[0066]

[0067] Among them, ξ j is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j.

[0068] The volume fraction of the silicon-based negative electrode active material component in the battery negative electrode is determined based on the weight fraction of each component of the silicon-based negative electrode, the density, and the initial volume of the negative electrode. The calculation formula for the volume fraction of each active material component in the battery negative electrode is:

[0069]

[0070] in, is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j, ω i is the weight fraction of component i, ρ i is the density of component i, V0 is the initial volume of the negative electrode, and ε0 is the initial porosity.

[0071] The universal expansion coefficient is determined based on the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode, the charge state, and the expansion coefficient of the active material component particles in each component. The calculation formula of the universal expansion coefficient is:

[0072]

[0073] Among them, g j is the universal expansion coefficient of active material j, is the volume fraction of active material j in the negative electrode of the battery, η j is the expansion coefficient of active material j particles, and SOC is the state of charge.

[0074] The real-time volume of the negative electrode is determined according to the universal expansion coefficient, the volume fraction of each active material of the silicon-based negative electrode to the total active materials, and the initial volume of the negative electrode.

[0075] The calculation formula of the real-time volume of the negative electrode is:

[0076]

[0077] Where V is the real-time volume of the negative electrode, V0 is the initial volume of the negative electrode, ξ j is the volume fraction of active material j in the total active materials, η j is the expansion coefficient of active material j particle, SOC is the state of charge, g j is the universal expansion coefficient of active material j.

[0078] Step 105: Determine the real-time porosity of the silicon-based negative electrode according to the real-time volume of the negative electrode and the real-time volume of each component particle.

[0079] The calculation formula for the real-time porosity of the silicon-based negative electrode is:

[0080]

[0081] Where ε is the real-time porosity of the negative electrode, V p-i is the real-time volume of the particles of component i, V is the real-time volume of the negative electrode, and i is the component type.

[0082] The present invention also provides a real-time porosity prediction system for lithium-ion battery silicon-based negative electrodes corresponding to the real-time porosity prediction method for lithium-ion battery silicon-based negative electrodes, comprising:

[0083] An acquisition module is used to obtain the weight fraction, density, initial porosity, particle expansion coefficient and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components.

[0084] The module for determining the real-time volume of each component particle is used to determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state.

[0085] The negative electrode initial volume determination module is used to determine the negative electrode initial volume according to the initial porosity of the silicon-based negative electrode and the initial volume of each component particle.

[0086] The real-time volume determination module of the negative electrode is used to determine the real-time volume of the negative electrode according to the weight fraction of the active material component of the silicon-based negative electrode, the density and the initial volume of the negative electrode.

[0087] The silicon-based negative electrode real-time porosity determination module is used to determine the real-time porosity of the silicon-based negative electrode according to the real-time volume of the negative electrode and the real-time volume of each component particle.

[0088] The present invention provides a method for predicting the real-time porosity of silicon-based negative electrodes of lithium-ion batteries, which belongs to the field of electrode porosity prediction of lithium-ion batteries. The present invention deconstructs the volume deformation of active particles into the influence on porosity and the influence on electrode volume. Only the readily available initial parameters are used to calculate the real-time porosity of the negative electrode, thus solving the problem of difficulty in predicting the real-time porosity of the electrode. Figure 2 The specific steps are as follows:

[0089] S10, extracting the initial porosity, weight fraction of each component and density of the silicon-based negative electrode as known conditions; the initial porosity, weight fraction of each component and density of the silicon-based negative electrode in step S10 are data that are easily obtained or measured.

[0090] S20, calculating the real-time volume of the solid component based on the relationship between the volume deformation of each component particle and the state of charge SOC; Step S20 includes the following steps:

[0091] S21, assuming the real-time volume V of each component particle p-i As SOC changes linearly, that is, V p-i / V p-i0 =1+η i SOC, where η i is the expansion coefficient of the i component particle, V p-i0 is the initial volume of the particles of component i.

[0092] S22. Calculate the total real-time volume of each component particle These include active particles and inactive particles.

[0093] S30, calculating the real-time volume of the negative electrode based on the relationship between the volume deformation of the negative electrode and the volume deformation of each component particle; step S30 includes the following steps:

[0094] S31, assuming that the real-time volume deformation V of the silicon-based negative electrode is related to the volume deformation V of each component particle p-i The relationship is V / V0=(V p-i / V p-i0 ) g , where V0 is the initial volume of the negative electrode, which is determined by the initial porosity and the initial volume of each component particle V p-i0 Calculated, g is the universal expansion coefficient.

[0095] S32. Calculate the volume fraction of each active material in the total active material based on the weight fraction and density of each active material component ξ j ; Weight fraction of active material components when preparing batteries ω j , density ρ j is a known condition. The volume fraction of each active material component to the total active material is as follows:

[0096]

[0097] Note: Battery electrode components include active materials (such as silicon, graphite, and other lithium-intercalating materials) and inactive materials (such as conductive agents and adhesives).

[0098] S33. Calculate the volume fraction of each active material component in the entire electrode based on the weight fraction, density and initial volume of the electrode Weight fraction of each component when preparing the battery ω i , density ρ i is a known condition. The initial volume of the electrode is given by Calculated. Where ε0 is the initial porosity, obtained according to existing technology. Then the volume fraction of each active material component in the entire electrode is calculated as follows:

[0099]

[0100] Here, j refers to each active material and i refers to each electrode component.

[0101] S34: The electrode volume deformation is generally along the thickness direction, and the transverse deformation can be ignored. Combined with the relationship described in step S31, the universal expansion coefficient g is calculated. j ,Right now

[0102] S35, using the relationship described in step S31 and the active volume fractions ξ described in step S32 j and the general expansion coefficient g described in step S34 j , the real-time volume V of the negative electrode can be calculated, that is

[0103] S40. Calculate the real-time porosity of the negative electrode according to the real-time volume of the solid component and the real-time volume of the negative electrode.

[0104] Step S40 includes the following steps:

[0105] S41. The calculation formula for the real-time porosity ε of the silicon-based negative electrode is:

[0106] The present invention can be applied to the optimized design of silicon-based negative electrodes for lithium-ion batteries, and to the analysis of the relationship between electrode process parameters and battery electrochemical performance. The present invention is based on deconstructing the volume deformation of the microscopic electrode component particles into the part that affects the porosity and the part that affects the electrode volume to achieve the prediction of the real-time porosity of the electrode. The present invention only needs to use easily available electrode parameters, namely the initial porosity, the weight fraction of each component, the density and the expansion coefficient of each component particle to calculate the real-time porosity. The method is simple and convenient, saves testing costs, and avoids the problems of experimental difficulty, loss and high cost faced by the real-time porosity testing method. It has important guidance and practical significance for the design of silicon-based negative electrodes, the analysis of electrochemical performance, the optimization design of process parameters, etc., and is conducive to promoting the development of high-capacity lithium-ion batteries.

[0107] The present invention provides a specific example of a method for predicting the real-time porosity of a silicon-based negative electrode of a lithium-ion battery in practical application, comprising the following steps:

[0108] S10, extract the initial porosity, weight fraction of each component, and density of the silicon-based negative electrode as known conditions. In this example, a silicon-based negative electrode with an initial porosity of 55%, a silicon, Nafion, and carbon black weight fractions of 50%, 25%, and 25%, respectively, and a silicon density of 2.33 g / cm 3 The density of Nafion is 1.97 g / cm 3 , the carbon black density is 1.60g / cm 3 .

[0109] S20, calculate the real-time volume of the solid component according to the relationship between the volume deformation of each component particle and the charge state SOC. Assume that the real-time volume of each component particle V pi As SOC changes linearly, that is, V p-i / V pi0 =1+η i SOC, where η i is the particle expansion coefficient of component i, i.e., in this embodiment, η Si =3,η Nafion =0,η 炭黑 =0, V pi0 is the initial volume of the i-component particle, which is obtained by dividing the mass of the i-component by the density of the i-component.

[0110] Calculate the real-time volume of solid components

[0111] S30, calculate the real-time volume of the negative electrode based on the relationship between the volume deformation of the negative electrode and the volume deformation of each component particle. Assume that the real-time volume deformation V of the silicon-based negative electrode and the volume deformation V of each component particle are p-i The relationship is V / V0=(V p-i / V p-i0 ) g , where V0 is the initial volume of the negative electrode, which is determined by the initial porosity of 55% and the initial volume of each component particle V p-i0 Calculated, g is the universal expansion coefficient.

[0112] Calculate the volume fraction of each active material in the total active material by the weight fraction and density of each active material component ξ j In this embodiment, the active material is only silicon, so ξ Si =1.

[0113] Calculate the volume fraction of each active material component in the entire electrode based on the weight fraction, density and initial volume of the electrode The silicon volume fraction calculated in this embodiment is

[0114] The volume deformation of the electrode is generally along the thickness direction, and the lateral deformation is ignored. Therefore, the real-time volume deformation V of the silicon negative electrode and the volume deformation V of each component particle are combined.p-i The relationship converts the negative electrode volume deformation into the negative electrode thickness deformation to calculate the universal expansion coefficient g j ,Right now In this embodiment, only the universal expansion coefficient g of the active material silicon needs to be calculated. Si =ln(1+0.582SOC) / ln(1+3SOC), the volumes of inactive materials Nafion and carbon black remain unchanged.

[0115] Using the real-time volume deformation V of the silicon anode and the volume deformation V of each component particle p-i Relationship, each active volume fraction ξ j And the universal expansion coefficient g, the real-time volume V of the negative electrode can be calculated, that is,

[0116] S40. Calculate the real-time porosity ε of the negative electrode based on the real-time volume of the solid component and the real-time volume of the negative electrode. The expression is as follows:

[0117]

[0118] The real-time porosity is only related to the unknown SOC; once the SOC is determined, the real-time porosity of the electrode can be obtained.

[0119] Using the initial porosity of 50% in the embodiment, the weight fractions of silicon, Nafion and carbon black are 55%, 25% and 25% respectively, and the silicon density is 2.33 g / cm 3 The density of Nafion is 1.97 g / cm 3 , the carbon black density is 1.60g / cm 3 , η Si =3,η Nafion =0,η 炭黑 = 0, and the real-time porosity versus SOC curve is obtained, such as Figure 3 The real-time porosity results of the present invention are compared with the results reported by Wang et al. (Influence of polymeric binders on mechanical properties and microstructure evolution of silicon composite electrodes during electrochemical cycling [J]. Journal of Power Sources, 2019, 425: 170-178), as shown in Table 1. The real-time porosity predicted by the present invention is consistent with the porosity results of the silicon-based negative electrode with Nafion as the binder reported in the literature. This verifies the applicability and effectiveness of the real-time porosity prediction method for lithium-ion battery silicon-based negative electrode provided by the present invention.

[0120] Table 1 Comparison of the real-time porosity prediction results of the present invention with those of Wang et al.

[0121]

[0122] The role of real-time porosity is similar to that of porosity (referring to initial porosity) in general. Conventional battery electrodes experience very little deformation, and the porosity is assumed to be constant, so only initial porosity is of interest. For batteries containing silicon active components, the volume deformation is large, and the porosity of the electrode will change during charging and discharging. On the one hand, porosity is a fundamental parameter characterizing battery structure and is generally closely related to the battery's electrochemical performance, directly affecting the battery's diffusion properties and ionic conductivity. Obtaining real-time porosity evolution data is helpful in analyzing the performance degradation behavior of silicon-based lithium-ion batteries. On the other hand, when designing silicon-based electrodes, the volume deformation and porosity evolution of silicon particles need to be considered to avoid designing a porosity that is too small, which causes the silicon particles to be squeezed together after deformation, thereby causing mechanical damage to the electrode particles. Real-time porosity is primarily used to analyze the performance degradation of silicon-based lithium-ion batteries and in the design of silicon-based electrodes.

[0123] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0124] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A real-time porosity prediction method for silicon-based negative electrodes of lithium-ion batteries, characterized in that: include: Obtaining the weight fraction, density, initial porosity, particle expansion coefficient, and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components; Determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state; Determining the initial volume of the negative electrode according to the initial porosity of the silicon-based negative electrode and the initial volume of each component particle; Determining the real-time volume of the negative electrode according to the weight fraction of the active material components of the silicon-based negative electrode, the density, and the initial volume of the negative electrode, specifically comprising: determining the volume fraction of each active material of the silicon-based negative electrode to the total active material according to the weight fraction of the active material components of the silicon-based negative electrode and the density; Determine the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode according to the weight fraction of each component of the silicon-based negative electrode, the density and the initial volume of the negative electrode; determine the universal expansion coefficient according to the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode, the charge state and the expansion coefficient of the active material component particles in each component; determine the real-time volume of the negative electrode according to the universal expansion coefficient, the volume fraction of each active material of the silicon-based negative electrode in the total active material and the initial volume of the negative electrode; The real-time porosity of the silicon-based negative electrode is determined according to the real-time volume of the negative electrode and the real-time volume of each component particle.

2. The method for predicting the real-time porosity of a lithium-ion battery silicon-based negative electrode according to claim 1, wherein: Determining the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle and the charge state specifically includes: Determine the initial volume of each component particle according to the weight fraction of each component and the density of the silicon-based negative electrode; The real-time volume of each component particle is determined according to the initial volume of each component particle, the expansion coefficient of each component particle and the charge state.

3. The method for predicting the real-time porosity of a silicon-based negative electrode for a lithium-ion battery according to claim 1, wherein: The expression for the real-time volume of each component particle is: 5 p-i / V p-i0 =1+η i SOC, Among them, V p-i is the real-time volume of the i-component particle, V p-i0 is the initial volume of the i-component particle, η i is the expansion coefficient of the i-component particles, and SOC is the state of charge.

4. The method for predicting the real-time porosity of a silicon-based negative electrode for a lithium-ion battery according to claim 1, wherein: The calculation formula for the volume fraction of each active material to the total active material is: Among them, ξ j is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j.

5. The method for real-time porosity prediction of a lithium-ion battery silicon-based negative electrode according to claim 1, wherein: The calculation formula for the volume fraction of each active material component in the battery negative electrode is: in, is the volume fraction of active material j, ω j is the weight fraction of active material j, ρ j is the density of active material j, ω i is the weight fraction of component i, ρ i is the density of component i, V0 is the initial volume of the negative electrode, and ε0 is the initial porosity.

6. The method for real-time porosity prediction of a lithium-ion battery silicon-based negative electrode according to claim 1, characterized in that: The calculation formula of the universal expansion coefficient is: Among them, g j is the universal expansion coefficient of active material j, is the volume fraction of active material j in the negative electrode of the battery, η j is the expansion coefficient of active material j particles, and SOC is the state of charge.

7. The method for real-time porosity prediction of a lithium-ion battery silicon-based negative electrode according to claim 1, characterized in that: The calculation formula of the real-time volume of the negative electrode is: Where V is the real-time volume of the negative electrode, V0 is the initial volume of the negative electrode, ξ j is the volume fraction of active material j in the total active materials, η j is the expansion coefficient of active material j particle, SOC is the state of charge, g j is the universal expansion coefficient of active material j.

8. The method for real-time porosity prediction of a lithium-ion battery silicon-based negative electrode according to claim 1, wherein: The calculation formula of the real-time porosity of the silicon-based negative electrode is: Where ε is the real-time porosity of the negative electrode, V p-i is the real-time volume of the particles of component i, V is the real-time volume of the negative electrode, and i is the component type.

9. A real-time porosity prediction system for silicon-based negative electrodes of lithium-ion batteries, characterized in that: include: An acquisition module is used to obtain the weight fraction, density, initial porosity, particle expansion coefficient and charge state of each component of the silicon-based negative electrode; the components of the silicon-based negative electrode include active material components and inactive material components; A module for determining the real-time volume of each component particle, configured to determine the real-time volume of each component particle according to the weight fraction of each component of the silicon-based negative electrode, the density, the expansion coefficient of each component particle, and the charge state; A negative electrode initial volume determination module, configured to determine the negative electrode initial volume according to the initial porosity of the silicon-based negative electrode and the initial volume of each component particle; A negative electrode real-time volume determination module is used to determine the real-time volume of the negative electrode according to the weight fraction of the active material components of the silicon-based negative electrode, the density and the initial volume of the negative electrode, specifically comprising: determining the volume fraction of each active material of the silicon-based negative electrode to the total active material according to the weight fraction of the active material components of the silicon-based negative electrode and the density; Determine the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode according to the weight fraction of each component of the silicon-based negative electrode, the density and the initial volume of the negative electrode; determine the universal expansion coefficient according to the volume fraction of each active material component of the silicon-based negative electrode in the battery negative electrode, the charge state and the expansion coefficient of the active material component particles in each component; determine the real-time volume of the negative electrode according to the universal expansion coefficient, the volume fraction of each active material of the silicon-based negative electrode in the total active material and the initial volume of the negative electrode; The silicon-based negative electrode real-time porosity determination module is used to determine the real-time porosity of the silicon-based negative electrode according to the real-time volume of the negative electrode and the real-time volume of each component particle.

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