Lithium ion battery

Abstract

The lithium ion battery comprises a positive plate, a diaphragm, a negative plate and an electrolyte used for transmitting lithium ions, a positive active material layer is attached to the surface of the positive plate, a negative active material layer is attached to the surface of the negative plate, the surface defect degree of a graphite powder raw material adopted by the negative active material layer is alpha, the particle size Dv50 is beta [mu] m, the lithium ion diffusion coefficient of the electrolyte at room temperature is gamma * 10 <-6 > cm < 2 > / s, the charging rate model of the lithium ion battery is K = 1.5 * e (6a + 0.2b + 1.2 c), a = alpha-w1, b = beta-w2, and c = gamma-w3; w1, w2 and w3 are correction coefficients of alpha, beta and gamma respectively, w1 is equal to 0.2, w2 is equal to 12, w3 is equal to 2.8, and when K is greater than or equal to 0.5 and less than or equal to 3, the charging rate window of the lithium ion battery is greater than or equal to 5C. A mathematical model is established, a battery charging rate window is rapidly measured and calculated, a battery charging decision during application is guided, a subsequent battery optimization direction is guided, and the efficiency of lithium ion battery optimization iteration is improved.

Description

Technical Field

[0001] The present application relates to the technical field of lithium-ion batteries, and in particular to a lithium-ion battery. Background Art

[0002] During the charging process of lithium-ion batteries, lithium ions are driven by an external electric field to escape from the positive electrode active material, migrate to the negative electrode active material through the electrolyte and embed into its lattice. At the same time, electrons are transferred through the external circuit. Correspondingly, the factors that mainly affect the charge rate performance of lithium-ion batteries are: the surface defect degree α of the graphite powder raw material in the negative electrode active material and its particle size Dv50β and the diffusion coefficient γ of lithium ions in the electrolyte. Among them, during the migration of lithium ions in the electrolyte, the diffusion coefficient γ of lithium ions in the electrolyte can affect the migration speed of lithium ions in the electrolyte. If the diffusion coefficient γ of lithium ions in the electrolyte is too small, it is not conducive to the rapid migration of lithium ions in the battery system, and the charging rate is low; if it is too large, it will reduce the stability of the electrolyte, accelerate the side reactions in the system, and significantly reduce the stability of the battery; in the process of lithium ions embedding into the lattice of the negative electrode active material, the surface defect degree α of the graphite powder raw material can reflect the active site density on the surface of the negative electrode active material layer, thereby affecting the lithium ion embedding efficiency; and the particle size Dv50β of the graphite powder raw material can affect the structure of the positive electrode active material layer. Graphite powder raw materials with too small particle size are difficult to disperse, easily agglomerate particles, and have poor stability; conversely, the diffusion resistance of lithium ions in the negative electrode active material layer increases, and the ideal charging rate cannot be achieved.

[0003] To improve the charge rate window of lithium-ion batteries and meet users' fast-charging needs, a common charging optimization approach involves adjusting the three-dimensional dimensions and surface properties of the negative electrode active material or the electrolyte formulation to create corresponding lithium-ion batteries. The corresponding charge rate window information is then derived from charge-discharge experimental data from actual batteries. This approach requires the production of a set of lithium-ion batteries for each variable and the conduction of charge-discharge experiments, resulting in high testing costs, low variable screening efficiency, and a long R&D cycle. Summary of the Invention

[0004] In order to solve the above problems, a mathematical model is established to associate the three-dimensional variables of the surface defect degree α of the graphite powder raw material, the particle size Dv50β of the graphite powder raw material, and the diffusion coefficient γ of lithium ions in the electrolyte, so as to realize the rapid measurement of the charging rate window of lithium-ion batteries under different designs. The first aspect of the present application provides a lithium-ion battery, which includes a positive electrode sheet, a separator, a negative electrode sheet, and an electrolyte for transmitting lithium ions. A positive electrode active material layer is attached to the surface of the positive electrode sheet, and a negative electrode active material layer is attached to the surface of the negative electrode sheet. The surface defect degree of the graphite powder raw material used in the negative electrode active material layer is α, the particle size Dv50 is βμm, and the lithium ion diffusion coefficient of the electrolyte at room temperature is γ×10 -6 cm 2 / s, the charging rate model of lithium-ion batteries is K = 1.5*e^(6a+0.2b+1.2c),

[0005] Wherein, a=α-w1, b=β-w2, c=γ-w3; w1, w2, w3 are correction coefficients of α, β, and γ, respectively, and w1=0.2, w2=12, w3=2.8, and it satisfies: when 0.5≤K≤3, the charge rate window of the lithium-ion battery is ≥5C.

[0006] In some optional embodiments, the surface defect degree α is characterized by Raman spectroscopy, α=ID / IG, wherein 0.1≤α≤0.3, ID is the intensity of the D peak at 1350 cm-1, and IG is the intensity of the G peak at 1580 cm-1.

[0007] In some optional embodiments, the particle size Dv50 is measured using a Malvern 3000 particle size analyzer and satisfies 8≤β≤14.

[0008] In some optional embodiments, the specific test method for the lithium ion diffusion coefficient γ of the electrolyte is:

[0009] S11: taking the electrolyte used in the lithium-ion battery, and assembling it with a separator and two lithium sheets into a button battery, wherein the two lithium sheets serve as two electrodes of the button battery;

[0010] S12: Apply 0.2 mA / cm to the button cell 2 A constant alternating positive and negative current pulse is applied for 30 minutes, and then the current is turned off;

[0011] S13: measuring the change of the open circuit voltage (OCV) of the button battery over time to obtain an OCV relaxation curve; and

[0012] S14: The calculation formula of the lithium ion diffusion coefficient γ of the electrolyte is γ=d^2*k*ε / (π^2), d is the thickness of the diaphragm, k is the natural logarithm slope of the OCV relaxation curve, and ε is the tortuosity of the diaphragm.

[0013] In some optional embodiments, the range of the lithium ion diffusion coefficient γ of the electrolyte is: (1.5-3.5)×10 -6 cm 2 / s.

[0014] In some optional embodiments, the correction coefficient w3 is an experimentally calibrated compensation parameter used to eliminate model calculation deviations caused by differences in intrinsic properties of different electrolyte systems. The calibration method of the correction coefficient w3 includes the following steps:

[0015] S21: Prepare multiple sets of electrolytes and calculate the lithium ion diffusion coefficient γ at room temperature in parallel;

[0016] S22: selecting a uniform graphite powder raw material and combining it with the multiple groups of electrolytes in S21 to prepare corresponding multiple groups of lithium-ion batteries, and controlling the variables of each group of lithium-ion batteries to be different only by the electrolyte; and

[0017] S23: Establish a model to be corrected: K = 1.5*e^(6α+0.2β+1.2γ), use the known parameters α, β, and γ values in each group of lithium-ion batteries to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D1, perform charging rate tests on the multiple groups of lithium-ion batteries in S22, measure the charging rate window experimental range D2, compare the charging rate window prediction range D1 with the charging rate window experimental range D2, introduce the correction coefficient w3 of γ, use a numerical optimization algorithm to solve the value of the correction coefficient w3, and correct the model to: K = 1.5*e^[6α+0.2β+1.2(γ-w3)].

[0018] In some optional embodiments, the correction coefficients w1 and w2 are experimentally calibrated compensation parameters used to eliminate model calculation deviations caused by differences in intrinsic properties of different graphite powder raw materials. The calibration method of the correction coefficients w1 and w2 includes the following steps:

[0019] S31: Collect graphite powder raw materials from multiple sources and perform surface defect α and particle size Dv50β measurements in parallel;

[0020] S32: preparing a unified electrolyte, analyzing the lithium ion diffusion coefficient γ of the electrolyte at room temperature, and preparing corresponding multiple groups of lithium-ion batteries using the multiple groups of graphite powder raw materials obtained in S31, wherein the only variable in each group of lithium-ion batteries is the difference in the graphite powder raw materials;

[0021] S33: Establish a model to be corrected: K = 1.5*e^[6α+0.2β+1.2c], c = γ-w3, use the known parameters α, β, γ values in each group of lithium-ion batteries and the correction coefficient w3 to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D3, perform charging rate tests on the multiple groups of lithium-ion batteries in S32, measure the charging rate window experimental range D4, introduce the correction coefficient w1 of α and the correction coefficient w2 of β, compare the charging rate window prediction range D3 with the charging rate window experimental range D4, use a numerical optimization algorithm to solve the values of the correction coefficients w1 and w2, and correct the model to: K = 1.5*e^(6a+0.2b+1.2c), a = α-w1, b = β-w2.

[0022] In some optional embodiments, the lithium-ion battery is subjected to a charge rate test, and the method for measuring the charge rate window experimental range includes the following steps:

[0023] S41: Take a brand new lithium-ion battery and charge and discharge it at a rate of 0.1C to complete the formation and aging of the battery; S42: Perform a charge and discharge test on the lithium-ion battery that has completed formation and aging, charge the lithium-ion battery at a rate of 1C at 25°C to a rated charge cut-off voltage of 4.2V, then charge it at a constant voltage to a current less than or equal to 0.05C, let it stand for 30 minutes, and then discharge it at a rate of 0.2C to a discharge cut-off voltage of 2.5V; and S43: Repeat the above step S42, increasing the charge rate by 0.33C each time, until the temperature rise coefficient of the lithium-ion battery is ηK / (min*Ah)≥3, and record the current charge rate as the maximum value of the charge rate window of the lithium-ion battery.

[0024] In some optional embodiments, the method for preparing the negative electrode active material layer includes the following steps: S51: adding deionized water to a solid material of 95.5-98.5wt% of silicon-carbon material, 0-1.5wt% of negative electrode conductive agent, 0.5-1.5wt% of thickener and 0-3.0wt% of negative electrode binder, stirring to form a negative electrode slurry, and adjusting the solid content of the negative electrode slurry to 35-50%; and

[0025] S52: Apply the negative electrode slurry to both sides of the negative electrode current collector, dry and cold press to form a negative electrode sheet. The compaction density of the negative electrode sheet is 1.4-1.8 g / cm 3 ;

[0026] The silicon-carbon material comprises 1.0-25.0 wt% of silicon raw material and 75.0-99.0 wt% of graphite powder raw material, and the sum of the mass percentages of the negative electrode conductor and the negative electrode binder is in the range of 1.0-3.0 wt%.

[0027] In some optional embodiments, the negative electrode conductive agent is selected from carbon nanotubes or a combination of carbon nanotubes and carbon black; the thickener is selected from one or a combination of two or more of sodium carboxymethyl cellulose, hydroxyethyl cellulose and carbomer; the negative electrode binder is selected from one or a combination of two or more of polyacrylic acid, polyacrylonitrile and polystyrene-acrylic acid.

[0028] In some optional embodiments, the electrolyte comprises a lithium salt, an additive, and an organic solvent, wherein the lithium ion concentration is 0.8-1.5 mol / L;

[0029] The lithium salt is selected from any one of lithium hexafluorophosphate, lithium difluorophosphate, lithium difluorooxalatoborate, lithium bis(fluorosulfonyl)imide, and lithium bis(trifluoromethylsulfonyl)imide, or a combination of two or more thereof;

[0030] The organic solvent is selected from any one or a combination of two or more of ethylene carbonate, dimethyl carbonate, diethyl carbonate and vinyl sulfate;

[0031] The additive is selected from any one or a combination of two or more of propylene carbonate, butylene carbonate, ethyl acetate, ethyl methyl carbonate and fluoroethylene carbonate.

[0032] In some optional embodiments, the capacity N / P ratio of the negative electrode sheet to the positive electrode sheet of the lithium ion battery is 1:(1.02-1.1).

[0033] This application has at least the following technical effects:

[0034] The present application provides a lithium-ion battery. By constructing a mathematical model K = 1.5*e^(6α+0.2β+1.2γ), three key parameters closely related to the fast charging performance of the lithium-ion battery are associated: the surface defect α of the graphite powder raw material and the particle size Dv50β of its particles and the lithium ion diffusion coefficient γ in the electrolyte. The three-dimensional coupling of α, β and γ, combined with the correction coefficients w1, w2, and w3, the corrected model is: K = 1.5*e^(6a+0.2b+1.2c), where , a=α-w1, b=β-w2, c=γ-w3, and the values of the correction coefficients w1, w2, and w3 are determined to be 0.2, 12, and 2.8 through experimental calibration, which meets the following requirements: when 0.5≤K≤3, the corresponding charging rate window of the lithium-ion battery is ≥5C. By simply judging the K value, the charging rate window threshold of the lithium-ion battery under the corresponding design idea can be quickly obtained, which can guide the battery charging decision during application, screen the subsequent battery optimization direction, and improve the efficiency of lithium-ion battery optimization iteration. DETAILED DESCRIPTION

[0035] The following describes in detail embodiments of this embodiment. In this description, "several" means one or more, "many" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The terms "first" and "second" are used solely to distinguish technical features and are not to be construed as indicating or implying relative importance, or as implicitly specifying the number or order of the technical features.

[0036] In the description of this embodiment, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this embodiment based on the specific content of the technical solution.

[0037] The common structure of existing lithium-ion batteries includes a casing with an opening at one end, a winding core assembled into the casing through the opening, an electrolyte injected into the casing, and a cap positioned over the casing opening. It is understood that the lithium-ion battery can be a cylindrical lithium-ion battery or a prismatic lithium-ion battery.

[0038] The core is formed by winding a stacked positive electrode sheet, a separator and a negative electrode sheet. The positive electrode sheet includes a positive electrode collector and a positive electrode active material layer coated on both sides of the positive electrode collector. The negative electrode sheet includes a negative electrode collector and a negative electrode active material layer coated on both sides of the negative electrode collector. The thickness of the active material coating is greater than the thickness of the current collector. Lithium ions complete the conversion between chemical energy and electrical energy by inserting or deinserting reactions on the surfaces of the positive electrode active material layer and the negative electrode active material layer.

[0039] The present application provides a lithium-ion battery, which includes a positive electrode sheet, a separator, a negative electrode sheet, and an electrolyte for transmitting lithium ions. The positive electrode sheet is attached to the surface of the positive electrode sheet, and the negative electrode sheet is attached to the surface of the negative electrode sheet. The graphite powder raw material used in the negative electrode active material layer has a surface defect degree of α and a particle size Dv50 of βμm. The lithium ion diffusion coefficient of the electrolyte at room temperature is γ×10-6cm 2 / s, the charging rate model of lithium-ion batteries is K = 1.5*e^(6a+0.2b+1.2c),

[0040] Wherein, a=α-w1, b=β-w2, c=γ-w3; w1, w2, w3 are correction coefficients of α, β, and γ respectively, w1=0.2, w2=12, w3=2.8, and it satisfies: when 0.5≤K≤3, the charge rate window of the lithium-ion battery is ≥5C.

[0041] Furthermore, the surface defect degree α is characterized by Raman spectroscopy, α=ID / IG, wherein 0.1≤α≤0.3, ID is the intensity of the D peak at 1350 cm-1, and IG is the intensity of the G peak at 1580 cm-1.

[0042] Specifically, a laser confocal Raman spectrometer is used to perform FTIR characterization on the graphite powder raw material and calculate the surface defectivity. The test process is as follows:

[0043] S61: 50 mg of graphite powder raw material was mixed with KBr at a ratio of 1:100 and pressed into a tablet; and

[0044] S62: Use mapping to collect D peak intensity, G peak intensity, and peak width. The calculation formula is:

[0045]

[0046] Among them, A D is the D peak area, γ D is the half-height width of the D peak, A G is the G peak area, γ G is the half-height width of the G peak. As is known, the D peak is: 2 The breathing vibration mode (A1g symmetry) induced by defects or edges in the carbon atom lattice reflects the existence of disorder or defects in the graphite powder raw material; G peak: from sp 2 The in-plane stretching vibrations of carbon atoms characterize the crystallinity and ordered structure of the graphite powder raw material. The surface defectivity α: α = ID / IG. A larger ratio indicates a higher defectivity. The surface defectivity of the graphite powder raw material and the silicon in the negative electrode active material exhibit a synergistic effect. During charge and discharge, the surface defects of the graphite powder raw material induce a local electric field enhancement effect, which can improve the lithium insertion kinetics of silicon particles. Therefore, the surface defectivity of the graphite powder raw material can be used as a characterization of the electrochemical activity of the negative electrode active material layer. A higher defectivity in the graphite powder raw material corresponds to more active sites, but this also increases side reactions, which is detrimental to structural stability. A too low defectivity results in too few active sites, which reduces lithium ion insertion efficiency and affects the charge rate. When α is between 0.1 and 0.3, the graphite powder raw material has a low to moderate defectivity, balancing active site density with structural stability, which is beneficial for improving lithium-ion battery performance.

[0047] Furthermore, the particle size Dv50β is measured using a Malvern 3000 particle size analyzer and satisfies 8≤β≤14, expressed in μm. Specifically, a 1-2g sample of graphite powder raw material is dissolved in 5ml of deionized water using deionized water as a dispersant to obtain a liquid dispersion sample. After subtracting the background signal, the liquid dispersion sample is manually added to the water until the obscuration reaches 8-12%. Test data is obtained, and the average of the two tests is taken as the particle size Dv50β. The Malvern 3000 particle size analyzer can accurately measure the Dv50 of powder raw materials in the range of 8-14μm, with a relative expanded uncertainty of <5%. With obscuration control and repeatability verification, it effectively balances detection efficiency and accuracy, making it suitable for industrial quality control of graphite powder raw materials for battery negative electrode materials.

[0048] In some optional implementation methods, a specific test method for the lithium ion diffusion coefficient γ of the electrolyte is as follows: S11: taking the electrolyte used in the lithium ion battery, assembling it with a separator and two lithium sheets into a button battery, wherein the two lithium sheets serve as two electrodes of the button battery;

[0049] S12: Apply 0.2 mA / cm to the button cell 2 A constant alternating positive and negative current pulse is applied for 30 minutes, and then the current is turned off;

[0050] S13: measuring the change of the open circuit voltage (OCV) of the button battery over time to obtain an OCV relaxation curve; and

[0051] S14: The calculation formula of the lithium ion diffusion coefficient γ of the electrolyte is γ=d^2*k*ε / (π^2), d is the thickness of the diaphragm, k is the natural logarithm slope of the OCV relaxation curve, and ε is the tortuosity of the diaphragm.

[0052] In the specific implementation process, the diaphragm includes: a PE base film, a ceramic coating coated on both sides of the PE base film, and a PVDF coating coated on the surface of the ceramic coating. The thickness of the diaphragm is the sum of the thicknesses of the PE base film, the ceramic coating and the PVDF coating. The thickness of the PE base film is 9 μm, the thickness of the ceramic coating is 1 μm, and the thickness of the PVDF coating is 1 μm. The tortuosity ε of the diaphragm is equal to the tortuosity of the PE base film used, and the tortuosity of the PE base film is 3.5.

[0053] Furthermore, the range of the lithium ion diffusion coefficient γ of the electrolyte is: (1.5-3.5)×10 -6 cm 2 / s. The lithium ion diffusion coefficient γ represents the migration rate of lithium ions under a unit concentration gradient. The higher the γ value, the faster the lithium ions are transported in the electrolyte and the faster the electrode reaction kinetics, which is conducive to high-rate charge and discharge. However, too high a γ value may lead to the intensification of side reactions, affecting the safety and cycle performance of the battery.

[0054] In some optional implementation methods, the correction coefficient w3 is an experimentally calibrated compensation parameter used to eliminate the model calculation deviation caused by the differences in the intrinsic properties of different electrolyte systems. The calibration method of the correction coefficient w3 includes the following steps:

[0055] S21: Prepare multiple sets of electrolytes and calculate the lithium ion diffusion coefficient γ at room temperature in parallel;

[0056] S22: selecting a uniform graphite powder raw material and combining it with the multiple groups of electrolytes in S21 to prepare corresponding multiple groups of lithium-ion batteries, and controlling the variables of each group of lithium-ion batteries to be different only in terms of the electrolyte;

[0057] S23: Establish a model to be corrected: K = 1.5*e^(6α+0.2β+1.2γ), use the known parameters α, β, and γ values in each group of lithium-ion batteries to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D1, perform charging rate tests on the multiple groups of lithium-ion batteries in S22, measure the charging rate window experimental range D2, compare the charging rate window prediction range D1 with the charging rate window experimental range D2, introduce the correction coefficient w3 of γ, use a numerical optimization algorithm to solve the value of the correction coefficient w3, and correct the model to: K = 1.5*e^[6α+0.2β+1.2(γ-w3)]. In some optional implementation methods, the correction coefficients w1 and w2 are experimentally calibrated compensation parameters used to eliminate the model measurement deviation caused by the differences in the intrinsic properties of different graphite powder raw materials. The calibration method of the correction coefficients w1 and w2 includes the following steps:

[0058] S31: Collect graphite powder raw materials from multiple sources and perform surface defect α and particle size Dv50β measurements in parallel;

[0059] S32: preparing a unified electrolyte, analyzing the lithium ion diffusion coefficient γ of the electrolyte at room temperature, and preparing corresponding multiple groups of lithium-ion batteries using the multiple groups of graphite powder raw materials obtained in S31, wherein the only variable in each group of lithium-ion batteries is the difference in the graphite powder raw materials;

[0060] S33: Establish a model to be corrected: K = 1.5*e^[6α+0.2β+1.2c], c = γ-w3, use the known parameters α, β, γ values in each group of lithium-ion batteries and the correction coefficient w3 to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D3, perform charging rate tests on the multiple groups of lithium-ion batteries in S32, measure the charging rate window experimental range D4, introduce the correction coefficient w1 of α and the correction coefficient w2 of β, compare the charging rate window prediction range D3 with the charging rate window experimental range D4, use a numerical optimization algorithm to solve the values of the correction coefficients w1 and w2, and correct the model to: K = 1.5*e^(6a+0.2b+1.2c), a = α-w1, b = β-w2.

[0061] Furthermore, the method for performing a charge rate test on a lithium-ion battery and measuring the charge rate window experimental range includes the following steps:

[0062] S41: Take a new lithium-ion battery and charge and discharge it at a rate of 0.1C to complete the formation and aging of the battery; S42: Perform a charge and discharge test on the lithium-ion battery that has completed the formation and aging, charging the lithium-ion battery at a rate of 1C at 25°C to a rated charge cut-off voltage of 4.2V, then charging it at a constant voltage to a current of less than or equal to 0.05C, standing it for 30 minutes, and then discharging it at a rate of 0.2C to a discharge cut-off voltage of 2.5V; and

[0063] S43: Repeat the above step S42, increasing the charging rate by 0.33C each time, until the temperature rise coefficient of the lithium-ion battery is ηK / (min*Ah)≥3, and record the current charging rate as the maximum value of the charging rate window of the lithium-ion battery.

[0064] In a specific implementation process, the test method of the temperature rise coefficient η further includes the following steps:

[0065] S44: charging the lithium-ion battery at 1C rate to a rated charge cut-off voltage of 4.2V at 25°C, then charging at a constant voltage until the current is less than or equal to 0.05C, standing for 30 minutes, and then discharging at a 0.2C rate to a discharge cut-off voltage of 2.5V. The discharge capacity of the battery in the first charge and discharge test is recorded as C0;

[0066] S45: The lithium-ion battery is allowed to stand for 30 minutes, and the cylindrical lithium-ion battery is charged again at a rate of 1C to a charge cut-off voltage of 4.2V. The battery temperature is tested, and the charging time t / min and the battery temperature rise value ΔT / K are recorded. The battery is then charged at a constant voltage until the current is less than or equal to 0.05C. The cylindrical lithium-ion battery is allowed to stand for another 30 minutes, and discharged at a rate of 0.2C to a discharge cut-off voltage of 2.5V.

[0067] S46: Based on the 1C rate, increase the rate by 0.33C per cycle, repeat step S45, record the charging time as t minutes, the battery temperature rise value △T, the temperature rise coefficient η is: η = △T / (t*C0), the unit is K / (min*Ah), when η ≥ 3, end the cycle.

[0068] In some optional implementation methods, the method for preparing the negative electrode active material layer includes the following steps:

[0069] S51: adding deionized water to a solid material of 95.5-98.5 wt % of silicon-carbon material, 0-1.5 wt % of negative electrode conductive agent, 0.5-1.5 wt % of thickener, and 0-3.0 wt % of negative electrode binder, stirring to form a negative electrode slurry, and adjusting the solid content of the negative electrode slurry to 35-50%; and

[0070] S52: Apply the negative electrode slurry to both sides of the negative electrode current collector, dry and cold press to form a negative electrode sheet. The compaction density of the negative electrode sheet is 1.4-1.8 g / cm 3 ;

[0071] The silicon-carbon material comprises 1.0-25.0 wt% of silicon raw material and 75.0-99.0 wt% of graphite powder raw material, and the sum of the mass percentages of the negative electrode conductor and the negative electrode binder is in the range of 1.0-3.0 wt%.

[0072] In some optional implementation methods, the molecular formula of the positive electrode active material is expressed as: Li a Ni x Co y Mn z M b O2; wherein, 0.9<a<1.2, 0.8≤x≤0.93, 0.1≤y<0.4, 0.05≤z<0.4, 0≤b≤0.1, and M represents at least one element selected from Zr, W, Ti, Al, Sr, La, B, and Nd.

[0073] Furthermore, the negative electrode conductive agent is selected from a combination of carbon nanotubes and / or carbon black; the thickener is selected from one or a combination of two or more of sodium carboxymethyl cellulose, hydroxyethyl cellulose and carbomer; and the negative electrode binder is selected from one or a combination of two or more of polyacrylic acid, polyacrylonitrile and polystyrene-acrylic acid.

[0074] In some optional implementation methods, the electrolyte includes a lithium salt, an additive, and an organic solvent, wherein the lithium ion concentration is 0.8-1.5 mol / L;

[0075] The lithium salt is selected from any one of lithium hexafluorophosphate, lithium difluorophosphate, lithium difluorooxalatoborate, lithium bis(fluorosulfonyl)imide, and lithium bis(trifluoromethylsulfonyl)imide, or a combination of two or more thereof;

[0076] The organic solvent is selected from any one or a combination of two or more of ethylene carbonate, dimethyl carbonate, diethyl carbonate and vinyl sulfate;

[0077] The additive is selected from any one or a combination of two or more of propylene carbonate, butylene carbonate, ethyl acetate, ethyl methyl carbonate and fluoroethylene carbonate.

[0078] Furthermore, the capacity N / P ratio of the negative electrode sheet to the positive electrode sheet of the lithium ion battery is 1:(1.02-1.1).

[0079] The technical solution of the present application is described below with reference to Examples 1-12 and Comparative Examples 1-6.

[0080] Example 1 provides a lithium-ion battery comprising the following specific steps:

[0081] 1. Production of positive electrode:

[0082] Take the positive electrode active material (Li1Ni 0.9 Co 0.3 Mn 0.1 Al 0.05 O2), conductive carbon black, single-walled carbon nanotubes and polyvinylidene fluoride (PVDF) were thoroughly stirred and mixed in an N-methylpyrrolidone solvent system at a mass ratio of 96:1:1:2 to obtain a positive electrode slurry, and then the positive electrode slurry was coated on a 12.0 μm thick aluminum foil, and after drying and cold pressing, a positive electrode sheet was obtained;

[0083] 2. Production of negative electrode sheet:

[0084] The negative electrode sheet includes a negative electrode current collector copper foil and a negative electrode slurry coated on both sides of the copper foil. Calculated by mass percentage, the negative electrode slurry includes 96.0% silicon-carbon material, 1.5% carbon nanotubes, 1.0% thickener sodium carboxymethyl cellulose (CMC), and 1.5% binder polyacrylic acid (PAA). The above substances are added to deionized water and stirred to form a negative electrode slurry with a solid content of 40%. The negative electrode slurry is then coated on both sides of the negative electrode current collector (copper foil). After drying and cold pressing, the negative electrode sheet is formed with a compaction density of 1.5g / cm 3 , wherein the silicon-carbon material comprises 10.0wt% Si and 90.0wt% graphite powder raw material, the surface defectivity of the graphite powder raw material is: 0.22, and the particle size Dv50 is 8μm;

[0085] 3. Preparation of electrolyte:

[0086] Lithium hexafluorophosphate was mixed with organic solvents ethylene carbonate (EC): fluoroethylene carbonate (FEC): ethyl methyl carbonate (EMC): dimethyl carbonate (DMC) in a ratio of 15:15:20:50 to obtain an electrolyte. The concentration of lithium hexafluorophosphate in the electrolyte was adjusted to 1.0 mol / L. The lithium ion diffusion coefficient γ of the prepared electrolyte at room temperature was found to be 2.5×10 -6 cm 2 / s;

[0087] 4. Diaphragm:

[0088] A high-porosity diaphragm is selected, in which the thickness of the base film PE is 9 μm, the thickness of the ceramic coating on both sides of the base film is 1.0 μm, and the thickness of the PVDF coating is 1.0 μm. The air permeability of the diaphragm is ≤100s / 100mL;

[0089] 5. Assembly of lithium-ion batteries:

[0090] The positive and negative electrode sheets are rolled and slit, respectively, and then wound together with the separator to obtain a 21700 cylindrical battery core. The battery core is then welded to the connecting sheet and loaded into the battery casing. After completing the injection, sealing, and formation processes, the lithium-ion battery of Example 1 is obtained. The casing of the lithium-ion battery is cylindrical, and its dimensional parameters are: diameter: 16-55 mm, and length: 63-140 mm.

[0091] Example 2

[0092] Example 2 provides a lithium-ion battery. The difference between Example 2 and Example 1 is that the surface defect degree of the graphite powder raw material is 0.26, and the other conditions are the same as those of Example 1.

[0093] Example 3

[0094] Example 3 provides a lithium-ion battery. The difference between Example 3 and Example 1 is that the surface defect degree of the graphite powder raw material is 0.13, and the other conditions are the same as those of Example 1.

[0095] Example 4

[0096] Example 4 provides a lithium-ion battery. The difference between Example 4 and Example 1 is that the surface defect degree of the graphite powder raw material is 0.3, and the other conditions are the same as those of Example 1.

[0097] Example 5

[0098] Example 5 provides a lithium-ion battery. The difference between Example 5 and Example 1 is that the particle size Dv50 of the graphite powder raw material is 8.4 μm, and the other conditions are the same as those of Example 1.

[0099] Example 6

[0100] Example 6 provides a lithium-ion battery. The difference between Example 6 and Example 1 is that the particle size Dv50 of the graphite powder raw material is 13.7 μm, and the other conditions are the same as those of Example 1.

[0101] Example 7

[0102] Example 7 provides a lithium-ion battery. The difference between Example 7 and Example 1 is that the particle size Dv50 of the graphite powder raw material is 9.5 μm, and the other conditions are the same as those of Example 1.

[0103] Example 8

[0104] Example 8 provides a lithium-ion battery. The difference between Example 8 and Example 1 is that the graphite powder particle size Dv50 is 11.3 μm, and the other conditions are the same as those in Example 1.

[0105] Example 9

[0106] Example 9 provides a lithium ion battery. The difference between Example 9 and Example 1 is that the concentration of lithium salt in the electrolyte is changed to 1.5 mol / L LiPF6, and the lithium ion diffusion coefficient is 2.1×10 -6 cm 2 / s, and the other conditions are the same as those in Example 1.

[0107] Example 10

[0108] Example 10 provides a lithium ion battery. The difference between Example 10 and Example 1 is that ethylene carbonate (VC) is used instead of ethyl methyl carbonate (EMC) in the electrolyte, and the lithium ion diffusion coefficient is 2.8×10 -6 cm 2 / s, and the other conditions are the same as those in Example 1.

[0109] Example 11

[0110] Example 11 provides a lithium ion battery. The difference between Example 11 and Example 1 is that LiBOB is used instead of ethyl methyl carbonate EMC, an additive in the electrolyte, and the lithium ion diffusion coefficient is 2.3×10 -6 cm 2 / s, and the other conditions are the same as those in Example 1.

[0111] Example 12

[0112] Example 12 provides a lithium ion battery. The difference between Example 12 and Example 1 is that ethylene sulfate (DTD) is used instead of fluoroethylene carbonate (FEC) as an additive in the electrolyte, and the lithium ion diffusion coefficient is 2.9×10 -6 cm 2 / s, and the other conditions are the same as those in Example 1.

[0113] Comparative Example 1

[0114] Comparative Example 1 provides a lithium ion battery. The difference between Comparative Example 1 and Example 1 is that the surface defect degree of the graphite powder raw material is 0.04, and the other conditions are the same as those of Example 1.

[0115] Comparative Example 2

[0116] Comparative Example 2 provides a lithium-ion battery. The difference between Comparative Example 2 and Example 1 is that the surface defect degree of the graphite powder raw material is 0.5, and the other conditions are the same as those of Example 1.

[0117] Comparative Example 3

[0118] Comparative Example 3 provides a lithium-ion battery. The difference between Comparative Example 3 and Example 1 is that the particle size of the graphite powder raw material Dv50 is 6 μm, and the other conditions are the same as those in Example 1.

[0119] Comparative Example 4

[0120] Comparative Example 4 provides a lithium ion battery. The difference between Comparative Example 4 and Example 1 is that the particle size Dv50 of the graphite powder raw material is 19 μm, and the other conditions are the same as those of Example 1.

[0121] Comparative Example 5

[0122] Comparative Example 5 provides a lithium-ion battery. The difference between Comparative Example 5 and Example 1 is that the electrolyte composition of ethylene carbonate (EC): fluoroethylene carbonate (FEC): ethyl methyl carbonate (EMC): dimethyl carbonate (DMC) is 35:15:20:30, and the other conditions are the same as those in Example 1.

[0123] Comparative Example 6

[0124] Comparative Example 6 provides a lithium-ion battery. The difference between Comparative Example 6 and Example 1 is that the electrolyte contains ethylene carbonate (EC): fluoroethylene carbonate (FEC): ethyl methyl carbonate (EMC): dimethyl carbonate (DMC) = 20:20:25:35, and the other conditions are the same as those in Example 1.

[0125] test:

[0126] (1) The surface defect degree of the graphite powder raw material used in each group of lithium-ion batteries of the examples and comparative examples was measured according to the aforementioned test method for the surface defect degree of the graphite powder raw material of the lithium-ion battery.

[0127] (2) The particle size Dv50 of the graphite powder raw material used in each group of lithium-ion batteries of the embodiment and the comparative example was measured according to the aforementioned test method for the particle size Dv50 of the graphite powder raw material of the lithium-ion battery.

[0128] (3) The lithium ion diffusion coefficient γ of the electrolyte used in each group of lithium ion batteries of the embodiment and the comparative example was measured according to the test method of the lithium ion diffusion coefficient in the electrolyte at room temperature of the lithium ion battery.

[0129] (4) The charge rate window of the lithium-ion battery of each group of examples and comparative examples was obtained according to the aforementioned lithium-ion battery charge rate window experimental method.

[0130] The surface defect degree of the graphite powder raw materials of Examples 1-12 and Comparative Examples 1-6, the particle size Dv50 of the graphite powder raw materials, the electrolyte lithium ion diffusion coefficient, the temperature rise coefficient corresponding to the lithium ion battery charge rate window and the design parameters of the related batteries actually measured according to the above method are shown in the following table:

[0131]

[0132]

[0133] From the results of Examples 1-4 and Comparative Examples 1-2 in the table, it can be seen that Example 1 has the highest charge rate window, which is 8.33C, and too high or too low defectivity will affect the charge rate performance. This is because within a certain range, high defects can improve the Li + Embedding activity, while defects can form dipole interactions or hydrogen bonds with functional groups such as hydroxyl groups on carbon nanotubes, thereby making the carbon nanotubes more evenly dispersed in the three-dimensional cross-linked network structure of the negative electrode active material layer, thereby improving the conductivity of the negative electrode sheet. However, when there are too many defects, excessive active surface areas will be formed, and side reactions will consume more active lithium. At the same time, they will plunder some of the cross-linking agents that help the carbon nanotubes to be evenly dispersed on the surface of the active material, resulting in blocked conductive paths and ultimately affecting the overall conductive performance.

[0134] The results of Examples 5-8 and Comparative Examples 3-4 in the table show that, within a certain range, as the graphite particle size decreases, the charge rate window also increases. This is because a smaller particle size increases the specific surface area, increasing the active reaction area, facilitating rapid lithium ion insertion, and achieving higher charge rates. However, when the particle size is too small, the porosity deteriorates, increasing the electrode pore impedance, and adversely affecting charging performance.

[0135] In summary, after the lithium-ion battery design meets the following parameter ranges: graphite surface defect (Raman ID / IG ratio) α: 0.1-0.3; graphite particle size Dv50 (μm) β: 8--14; electrolyte lithium ion diffusion coefficient (×10-6cm 2 / s)γ: 1.5-3.5; the constructed mathematical model: K = 1.5*e^(6a+0.2b+1.2c), wherein, a = α-w1 = α-0.2, b = β-w2 = β-12, c = γ-w3 = γ-2.8, when 0.5≤K≤3, it is possible to quickly determine that the corresponding charging rate window of the lithium-ion battery is ≥5C. The lithium-ion battery provided in the present application can use the constructed theoretical mathematical model to quickly calculate the charging rate window by adjusting the surface defectivity and particle size parameters of the negative electrode graphite powder raw material and the electrolyte parameters, thereby guiding the battery charging decision during application, improving the battery cycle life, and guiding the subsequent battery optimization direction, thereby improving the efficiency of lithium-ion battery optimization iteration.

[0136] Although examples of the present embodiment have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and intent of the present embodiment, and the scope of the present embodiment is defined by the claims and their equivalents.

Claims

1. A lithium-ion battery comprising a positive electrode sheet, a separator, a negative electrode sheet, and an electrolyte for transporting lithium ions, wherein a positive electrode active material layer is attached to the surface of the positive electrode sheet, and a negative electrode active material layer is attached to the surface of the negative electrode sheet, characterized in that: The surface defect of the graphite powder raw material used in the negative electrode active material layer is α, the particle size Dv50 is βμm, and the lithium ion diffusion coefficient of the electrolyte at room temperature is γ×10 -6 cm 2 / s, the charging rate model of lithium-ion batteries is K = 1.5*e^(6a+0.2b+1.2c), Wherein, a=α-w1, b=β-w2, c=γ-w3; w1, w2, w3 are correction coefficients of α, β, and γ, respectively, and w1=0.2, w2=12, w3=2.8, and it satisfies: when 0.5≤K≤3, the charge rate window of the lithium-ion battery is ≥5C.

2. The lithium-ion battery according to claim 1, wherein The surface defect degree α is characterized by Raman spectroscopy, where α=ID / IG, wherein 0.1≤α≤0.3, ID is the intensity of the D peak at 1350 cm-1, and IG is the intensity of the G peak at 1580 cm-1.

3. The lithium-ion battery according to claim 1, wherein The particle size Dv50 is measured using a Malvern 3000 particle size analyzer and satisfies 8≤β≤14.

4. The lithium-ion battery according to claim 1, wherein The specific test method for the lithium ion diffusion coefficient γ of the electrolyte is: S11: taking the electrolyte used in the lithium-ion battery, assembling it with a separator and two lithium sheets into a button battery, wherein the two lithium sheets serve as two electrodes of the button battery; S12: Apply 0.2 mA / cm to the button cell 2 A constant alternating positive and negative current pulse is applied for 30 minutes, and then the current is turned off; S13: measuring the change of the open circuit voltage (OCV) of the button battery over time to obtain an OCV relaxation curve; and S14: The calculation formula of the lithium ion diffusion coefficient γ of the electrolyte is γ=d^2*k*ε / (π^2), d is the thickness of the diaphragm, k is the natural logarithm slope of the OCV relaxation curve, and ε is the tortuosity of the diaphragm.

5. The lithium-ion battery according to claim 4, characterized in that The range of the lithium ion diffusion coefficient γ of the electrolyte is: (1.5-3.5)×10 -6 cm 2 / s.

6. The lithium-ion battery according to claim 4, characterized in that The correction coefficient w3 is a compensation parameter calibrated experimentally, which is used to eliminate the model calculation deviation caused by the difference in the intrinsic characteristics of different electrolyte systems. The calibration method of the correction coefficient w3 includes the following steps: S21: Prepare multiple sets of electrolytes and calculate the lithium ion diffusion coefficient γ at room temperature in parallel; S22: selecting a uniform graphite powder raw material and combining it with the multiple groups of electrolytes in S21 to prepare corresponding multiple groups of lithium-ion batteries, and controlling the variables of each group of lithium-ion batteries to be different only by the electrolyte; and S23: Establish a model to be corrected: K = 1.5*e^(6α+0.2β+1.2γ), use the known parameters α, β, and γ values in each group of lithium-ion batteries to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D1, perform charging rate tests on the multiple groups of lithium-ion batteries in S22, measure the charging rate window experimental range D2, compare the charging rate window prediction range D1 with the charging rate window experimental range D2, introduce the correction coefficient w3 of γ, use a numerical optimization algorithm to solve the value of the correction coefficient w3, and correct the model to: K = 1.5*e^[6α+0.2β+1.2(γ-w3)].

7. The lithium-ion battery according to claim 6, characterized in that The correction coefficients w1 and w2 are experimentally calibrated compensation parameters used to eliminate the model calculation deviation caused by the differences in the intrinsic properties of different graphite powder raw materials. The calibration method of the correction coefficients w1 and w2 includes the following steps: S31: Collect graphite powder raw materials from multiple sources and perform surface defect α and particle size Dv50β measurements in parallel; S32: preparing a unified electrolyte, analyzing the lithium ion diffusion coefficient γ of the electrolyte at room temperature, and preparing corresponding multiple groups of lithium-ion batteries using the multiple groups of graphite powder raw materials obtained in S31, wherein the only variable in each group of lithium-ion batteries is the difference in the graphite powder raw materials; S33: Establish a model to be corrected: K = 1.5*e^[6α+0.2β+1.2c], c = γ-w3, use the known parameters α, β, γ values in each group of lithium-ion batteries and the correction coefficient w3 to obtain the K value corresponding to each group of lithium-ion batteries, and determine the corresponding charging rate window prediction range D3, perform charging rate tests on the multiple groups of lithium-ion batteries in S32, measure the charging rate window experimental range D4, introduce the correction coefficient w1 of α and the correction coefficient w2 of β, compare the charging rate window prediction range D3 with the charging rate window experimental range D4, use a numerical optimization algorithm to solve the values of the correction coefficients w1 and w2, and correct the model to: K = 1.5*e^(6a+0.2b+1.2c), a = α-w1, b = β-w2.

8. The lithium-ion battery according to claim 7, characterized in that The method for performing a charge rate test on a lithium-ion battery and measuring a charge rate window experimental range comprises the following steps: S41: Take a new lithium-ion battery and charge and discharge it at a rate of 0.1C to complete the battery formation and aging; S42: performing a charge and discharge test on the formed and aged lithium-ion battery, charging the lithium-ion battery at a rate of 1C at 25° C. to a rated charge cut-off voltage of 4.2V, then charging the battery at a constant voltage to a current of less than or equal to 0.05C, standing the battery for 30 minutes, and then discharging the battery at a rate of 0.2C to a discharge cut-off voltage of 2.5V; and S43: Repeat the above step S42, increasing the charging rate by 0.33C each time, until the temperature rise coefficient of the lithium-ion battery is ηK / (min*Ah)≥3, and record the current charging rate as the maximum value of the charging rate window of the lithium-ion battery.

9. The lithium-ion battery according to claim 1, wherein The method for preparing the negative electrode active material layer comprises the following steps: S51: adding deionized water to a solid material of 95.5-98.5 wt % of silicon-carbon material, 0-1.5 wt % of negative electrode conductive agent, 0.5-1.5 wt % of thickener, and 0-3.0 wt % of negative electrode binder, stirring to form a negative electrode slurry, and adjusting the solid content of the negative electrode slurry to 35-50%; and S52: Apply the negative electrode slurry to both sides of the negative electrode current collector, dry and cold press to form a negative electrode sheet. The compaction density of the negative electrode sheet is 1.4-1.8 g / cm 3 ; The silicon-carbon material comprises 1.0-25.0 wt% of silicon raw material and 75.0-99.0 wt% of graphite powder raw material, and the sum of the mass percentages of the negative electrode conductor and the negative electrode binder is in the range of 1.0-3.0 wt%.

10. The lithium-ion battery according to claim 9, characterized in that The negative electrode conductive agent is selected from carbon nanotubes or a combination of carbon nanotubes and carbon black; the thickener is selected from one or a combination of two or more of sodium carboxymethyl cellulose, hydroxyethyl cellulose and carbomer; the negative electrode binder is selected from one or a combination of two or more of polyacrylic acid, polyacrylonitrile and polystyrene-acrylic acid.

11. The lithium-ion battery according to claim 1, wherein The electrolyte comprises a lithium salt, an additive and an organic solvent, wherein the lithium ion concentration is 0.8-1.5 mol / L; The lithium salt is selected from any one of lithium hexafluorophosphate, lithium difluorophosphate, lithium difluorooxalatoborate, lithium bis(fluorosulfonyl)imide, and lithium bis(trifluoromethylsulfonyl)imide, or a combination of two or more thereof; The organic solvent is selected from any one or a combination of two or more of ethylene carbonate, dimethyl carbonate, diethyl carbonate and vinyl sulfate; The additive is selected from any one or a combination of two or more of propylene carbonate, butylene carbonate, ethyl acetate, ethyl methyl carbonate and fluoroethylene carbonate.

12. The lithium-ion battery according to claim 1, wherein The capacity N / P ratio of the negative electrode sheet to the positive electrode sheet of the lithium ion battery is 1:(1.02-1.1).

Images