A method for characterizing lithium-ion battery performance based on the three-dimensional morphology of the electrode surface

Abstract

The present application provides a method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of the pole piece surface, comprising the following steps: selecting a sampling area on the battery pole piece; photographing the sampling area to obtain a three-dimensional image; obtaining surface data through the three-dimensional image; determining the reference deflection surface of the pole piece and obtaining the reference surface data of the reference deflection surface; subtracting the surface data from the reference surface data to obtain difference data; obtaining calculation parameters of the difference data, the calculation parameters are used to characterize the roughness of the pole piece surface; selecting multiple sampling areas, and judging whether the calculation parameters obtained multiple times fall within a set interval, falling within the set interval indicates that the battery performance is good, and falling outside the set interval indicates that the battery performance is poor. The present application provides a method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of the pole piece surface, which judges the performance of the battery according to the changes in the morphology of the pole piece surface before and after the battery decays, providing a new idea for the study of battery life decay.

Description

Technical Field

[0001] The present disclosure generally relates to the technical field of battery pole piece research, and specifically to a lithium-ion battery performance characterization method based on the three-dimensional morphology of the pole piece surface. Background Art

[0002] With the continuous depletion of fossil fuels and the worsening environmental problems caused by them, lithium-ion batteries, as a symbol of new energy, have attracted more and more attention due to their great potential in efficient energy storage and environmental sustainability. At present, lithium-ion batteries are not only used in portable electronic products such as computers and mobile phones, but also in electric or hybrid vehicles. In fact, due to the excellent performance and energy density of lithium-ion batteries, they will become more and more popular in the future. In addition, due to the advantages of high specific capacity, high specific voltage, no memory, good cycle performance, low self-discharge, and wide operating temperature range, lithium-ion batteries currently dominate the portable electronic product battery market.

[0003] However, after repeated charge and discharge cycles, the capacity of lithium-ion batteries will gradually decrease. Battery aging will affect the safety and reliability of equipment and even cause serious accidents, such as spontaneous combustion of cars and explosion of mobile phones. Many studies have been conducted on capacity degradation.

[0004] Various causes of battery degradation have been proposed in some literatures, including the formation and development of anode solid electrolyte interface (SEI), mechanical fracture of electrode active materials, deposition of metallic lithium at the anode, and other side reactions of the battery that consume active lithium and electrolyte. Among them, SEI growth has been shown to be the main cause of battery capacity loss and resistance increase under normal use conditions. The aging mechanism of lithium-ion batteries can be divided into three categories: lithium inventory loss (LLI), loss of active materials (LAM), and reaction kinetic degradation. In addition, LAM can be further divided into two categories: loss of positive electrode active materials (LAMPE) and loss of negative electrode active materials (LAMNE). Identifying the battery aging mechanism is the most important part of battery diagnosis. The incremental capacity analysis (ICA) method and the differential voltage analysis (DVA) method are effective and non-destructive electrochemical analysis methods for identifying battery aging mechanisms. Each peak in the incremental capacity (IC) curve or the differential voltage (DV) curve represents a specific electrochemical reaction process occurring in the battery. Therefore, their evolution with battery aging can be used to identify the battery aging mechanism. In addition, by taking microscopic morphology pictures of the battery surface at the end of its life through SEM, the performance of active particles can also be analyzed, and the microscopic state of the battery can be characterized by the particle breakage. However, due to the high cost of shooting and scanning transmission, the range of battery pole piece samples is limited, and the quantification of pole piece particle breakage is also affected by the location of the sampling point. Summary of the invention

[0005] In view of the above-mentioned defects or deficiencies in the prior art, it is desired to provide a lithium-ion battery performance characterization method based on the three-dimensional morphology of the electrode surface to solve the above-mentioned problems.

[0006] The present application provides a method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface, comprising the following steps:

[0007] S1: Obtain a pole piece of a battery and select a sampling area on the pole piece;

[0008] S2: photographing the sampling area to obtain a three-dimensional image of the surface of the pole piece;

[0009] S3: obtaining surface data through the three-dimensional image, wherein the surface data includes a plurality of height data on the three-dimensional image;

[0010] S4: determining a reference deflection surface of the pole piece, and obtaining reference surface data of the reference deflection surface; the reference deflection surface is a surface with the smallest distance variance to each of the height data;

[0011] S5: Subtract the surface data from the reference surface data to obtain difference data;

[0012] S6: Obtaining calculation parameters of the difference data, wherein the calculation parameters are used to characterize the roughness of the electrode surface;

[0013] S7: Repeat the above S1 to S6 to select multiple sampling areas;

[0014] S8: Determine whether the calculated parameters obtained multiple times fall within a set range. If they fall within the set range, it indicates that the battery performance is good; if they fall outside the set range, it indicates that the battery performance is poor.

[0015] According to the technical solution provided in the embodiment of the present application, the calculation parameters obtained multiple times satisfy the normal distribution, and the setting interval is (μ-3σ, μ+3σ), where μ represents the mathematical expectation of the calculation parameters obtained multiple times, and σ represents the standard deviation of the calculation parameters obtained multiple times.

[0016] According to the technical solution provided in the embodiment of the present application, in step S3, the surface data is denoised.

[0017] According to the technical solution provided in the embodiment of the present application, in step S4, determining the reference deflection surface of the pole piece includes the following steps:

[0018] According to formula (1), construct the first surface function

[0019] f(x i ,y j )=a 0 +a1 x+a 2 y+a 3 x 2 +a 4 xy+a 5 y 2 (one);

[0020] According to formula (II), the fitting error is determined

[0021]

[0022] A 0 、a 1 、a 2 、a 3 、a 4 、a 5 Take the partial derivative of the fitting error and make the partial derivatives equal to zero to obtain a 0 、a 1 、a 2 、a 3 、a 4 、a 5 The value of is used to determine the reference deflection surface.

[0023] According to the technical solution provided in the embodiment of the present application, in step S1, the positive electrode sheet and the negative electrode sheet of the battery are obtained and analyzed simultaneously, and the sampling area is selected at the edge and center of the electrode sheet.

[0024] According to the technical solution provided in the embodiment of the present application, the calculation parameter is the ten-point height S Z , arithmetic mean deviation S a , Root mean square deviation S q , maximum peak height S p , maximum valley depth S v , the height skewness S sk , the kurtosis S of the height score ku One of them.

[0025] The beneficial effects of the present application are: by obtaining the pole piece of the battery, a sampling area is selected on the pole piece; the sampling area is photographed to obtain a three-dimensional image of the pole piece surface; surface data is obtained through the three-dimensional image; the reference deflection surface of the several pieces is determined, and the reference surface data of the reference deflection surface is obtained; the surface data is subtracted from the reference surface data to obtain difference data, and the difference data is obtained, so that the three-dimensional morphology of the pole piece surface can be intuitively reflected; by obtaining the calculation parameters of the difference data, multiple sampling areas are selected, and it is determined whether the calculation parameters obtained multiple times fall within the set interval, so that the state of the pole piece surface can be determined, and then the performance of the battery can be characterized. The present application provides a lithium-ion battery performance characterization method based on the three-dimensional morphology of the pole piece surface, which judges the performance of the battery according to the morphological changes of the pole piece surface before and after the battery decays, providing a new idea for the study of battery life decay. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0027] Figure 1 A flow chart of the steps of a lithium-ion battery performance characterization method based on the three-dimensional morphology of the pole piece surface provided in this application;

[0028] Figure 2 A schematic diagram of a three-dimensional image taken by a three-dimensional profilometer;

[0029] Figure 3 A schematic diagram of an image after denoising the surface data;

[0030] Figure 4 is a reference deflection surface diagram of the pole piece;

[0031] Figure 5 It is the difference data surface graph after the surface data is subtracted from the reference surface data. DETAILED DESCRIPTION

[0032] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0033] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0034] Please refer to Figure 1The present application provides a method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface, which is characterized by comprising the following steps:

[0035] S1: Obtain a pole piece of a battery and select a sampling area on the pole piece;

[0036] S2: photographing the sampling area to obtain a three-dimensional image of the surface of the pole piece;

[0037] S3: obtaining surface data through the three-dimensional image, wherein the surface data includes a plurality of height data on the three-dimensional image;

[0038] S4: determining a reference deflection surface of the pole piece, and obtaining reference surface data of the reference deflection surface; the reference deflection surface is a surface with the smallest distance variance to each of the height data;

[0039] S5: Subtract the surface data from the reference surface data to obtain difference data;

[0040] S6: Obtaining calculation parameters of the difference data, wherein the calculation parameters are used to characterize the roughness of the electrode surface;

[0041] S7: Repeat the above S1 to S6 to select multiple sampling areas;

[0042] S8: Determine whether the calculated parameters obtained multiple times fall within a set range. If they fall within the set range, it indicates that the battery performance is good; if they fall outside the set range, it indicates that the battery performance is poor.

[0043] Working principle: by obtaining the pole piece of the battery, a sampling area is selected on the pole piece; the sampling area is photographed to obtain a three-dimensional image of the pole piece surface; surface data is obtained through the three-dimensional image; the reference deflection surface of the several pieces is determined, and the reference surface data of the reference deflection surface is obtained; the surface data is subtracted from the reference surface data to obtain difference data, and the difference data is obtained so that the three-dimensional morphology of the pole piece surface can be intuitively reflected; by obtaining the calculation parameters of the difference data, multiple sampling areas are selected, and it is determined whether the calculation parameters obtained multiple times fall within the set interval, so that the state of the pole piece surface can be determined, and then the performance of the battery can be characterized. The present application provides a lithium-ion battery performance characterization method based on the three-dimensional morphology of the pole piece surface, which judges the battery performance according to the morphological changes of the pole piece surface before and after the battery decays, and provides a new idea for the study of battery life decay.

[0044] Furthermore, multiple sampling areas are selected as much as possible, and the calculated parameters obtained multiple times satisfy the normal distribution. It is determined whether the calculated parameters fall within the set interval (μ-3σ, μ+3σ). If they fall within the set interval, it indicates that the battery performance is good; if they fall outside the set interval, it indicates that the battery performance is poor; wherein μ represents the mathematical expectation of the calculated parameters obtained multiple times, and σ represents the standard deviation of the calculated parameters obtained multiple times; the more concentrated the distribution of the calculated parameters within the set interval is, the more consistent the aging degree of each point on the electrode during charging and discharging of the battery is, and the better the battery performance can be represented.

[0045] Further, in a certain embodiment, step S3 is implemented by using the wdencmp function when performing wavelet threshold denoising on the surface data, wherein the wavelet adopts the sym4 wavelet and the number of decomposition layers is 3; by using the wdencmp function, the data points of the denoised surface data correspond to the data points of the actual sampling data, which is convenient for direct difference; Figure 2 As shown, the surface data is obtained by the three-dimensional image taken by the three-dimensional topography instrument, and the plane is obtained by the surface data; as shown Figure 3 As shown, the plane obtained by denoising the plane data through the wdencmp function is flatter than before denoising, thereby avoiding the inability to extract the height data due to the influence of noise.

[0046] Further, in one embodiment, step S4 determines the reference deflection surface of the pole piece by the least square method, and the specific steps are as follows:

[0047] First, according to formula (1), construct the first surface function:

[0048] f(x i ,y j )=a 0 +a 1 x+a 2 y+a 3 x 2 +a 4 xy+a 5 y 2 (one);

[0049] When evaluating parameters using the least squares method, the weighted sum of squared deviations is minimized. According to formula (2), the fitting error is determined as:

[0050]

[0051] A 0 、a 1 、a 2 、a 3 、a 4 、a5 Take partial derivatives of the error in the above formula and make them equal to zero, so as to obtain a 0 、a 1 、a 2 、a 3 、a 4 、a 5 The value of , and then the reference deflection surface is obtained, the reference deflection surface is as follows Figure 4 shown.

[0052] Specifically, the discrete points used to calculate the surface roughness of the pole piece can be expressed as formula (III):

[0053] η(x i ,y j )=z i,j -f(x i ,y j ) (three).

[0054] Furthermore, in step S1, the positive electrode sheet and the negative electrode sheet of the battery are obtained and analyzed simultaneously, the sampling area is selected at the edge or center position of the electrode sheet, and sampling is performed at multiple sampling areas at the edge or center position of the electrode sheet.

[0055] Further, in a certain embodiment, ISO25178 defines three-dimensional parameters as height parameters, spacing parameters, mixing parameters, functional parameters, characteristic parameters and other parameters. Since the present application analyzes the height data in the surface data, the height parameter of the surface is selected, and the height parameter includes ten-point height S Z , arithmetic mean deviation S a , Root mean square deviation S q , maximum peak height S p , maximum valley depth S v , the height skewness S sk , the kurtosis S of the height score ku ; The calculation parameters in this application are the above-mentioned height parameters;

[0056] In this application, the ten-point height S Z The expression is formula (IV):

[0057]

[0058] where η hi represents the value of the highest point in the sampling area, η li represents the value of the lowest point of the sampling area;

[0059] The arithmetic mean deviation S a The expression of is formula (5):

[0060]

[0061] For the irregular pole piece surface with strong randomness, S a The highest degree of use; the surface root mean square deviation S q The expression of is formula (six):

[0062]

[0063] Where S q Compare S a The random features of the surface can be described in some detail;

[0064] The maximum peak height S of the surface p The expression of is formula (VII):

[0065]

[0066] The maximum valley depth S of the surface v The expression of is formula (eight):

[0067]

[0068] The skewness S of the height distribution sk The expression of is formula (9):

[0069]

[0070] The kurtosis S of the surface height distribution ku The expression of is formula (10):

[0071]

[0072] Furthermore, in this application, the calculation parameters are selected from the ten-point height S Z , arithmetic mean deviation S a , Root mean square deviation S q , maximum peak height S p , maximum valley depth S v , the height skewness S sk , the kurtosis S of the height score ku One of them.

[0073] In one embodiment, the calculation parameter is selected as the arithmetic mean deviation S a Step S7 selects as many sampling areas as possible to obtain multiple arithmetic mean deviations S a , multiple arithmetic mean deviations S a Satisfying the normal distribution, the setting interval at this time is (μ-3σ, μ+3σ), where μ represents the arithmetic mean deviation S obtained multiple times aThe mathematical expectation of σ represents the arithmetic mean deviation S obtained multiple times. a The standard deviation of each arithmetic mean deviation S a Whether it falls within the set interval, if the arithmetic mean deviation S a If the arithmetic mean deviation S falls within the set range, it indicates that the battery performance is good; a Falling outside the set range indicates poor battery performance; multiple arithmetic mean deviations S a The more concentrated the distribution is within the set interval, the more consistent the aging degree of each point on the electrode during charging and discharging of the battery is, and the better the battery performance is.

[0074] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

Claims

1. A method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface, characterized in that: The following steps are involved: S1: Obtain a pole piece of a battery and select a sampling area on the pole piece; S2: photographing the sampling area to obtain a three-dimensional image of the surface of the pole piece; S3: obtaining surface data through the three-dimensional image, wherein the surface data includes a plurality of height data on the three-dimensional image; S4: determining a reference deflection surface of the pole piece, and obtaining reference surface data of the reference deflection surface; the reference deflection surface is a surface with the smallest distance variance to each of the height data; S5: Subtract the surface data from the reference surface data to obtain difference data; S6: Obtaining calculation parameters of the difference data, wherein the calculation parameters are used to characterize the roughness of the electrode surface; S7: Repeat the above S1 to S6 to select multiple sampling areas; S8: Determine whether the calculated parameters obtained multiple times fall within a set range. If they fall within the set range, it indicates that the battery performance is good; if they fall outside the set range, it indicates that the battery performance is poor; Determining the reference deflection surface of the pole piece comprises the following steps: According to formula (1), construct the first surface function: f(x i ,y j )=a0+a1x+a2y+a3x 2 +a4xy+a5y 2 (one); Among them, f(x i ,y j ) represents the height value of the i-th row and j-th column position in the reference deflection surface, a0 represents the constant term coefficient of the reference deflection surface, a1 and a2 represent the first-order term coefficients of the reference deflection surface, and a3, a4 and a5 represent the second-order term coefficients of the reference deflection surface; According to formula (II), the fitting error is determined: Wherein, ω represents the fitting error, m represents the total number of rows of the matrix composed of the surface data, n represents the total number of columns of the matrix composed of the surface data, and z i,j Representing the height data at the i-th row and j-th column position in the matrix composed of the surface data; Take partial derivatives of a0, a1, a2, a3, a4, and a5 with respect to the fitting error, make the partial derivatives all equal to zero, obtain the values ​​of a0, a1, a2, a3, a4, and a5, and determine the reference deflection surface.

2. A method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface according to claim 1, characterized in that: The calculation parameters obtained multiple times satisfy the normal distribution, and the setting interval is (μ-3σ, μ+3σ), where μ represents the mathematical expectation of the calculation parameters obtained multiple times, and σ represents the standard deviation of the calculation parameters obtained multiple times.

3. A method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface according to claim 1, characterized in that: In step S3, the surface data is denoised.

4. A method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of a pole piece surface according to claim 1, characterized in that: In step S1, the positive electrode sheet and the negative electrode sheet of the battery are obtained and analyzed simultaneously, and the sampling area is selected at the edge and center of the electrode sheet.

5. The method for characterizing the performance of a lithium-ion battery based on the three-dimensional morphology of the electrode surface according to claim 1, characterized in that: The calculation parameter is the ten-point height S Z , arithmetic mean deviation S a , Root mean square deviation S q , maximum peak height S p , maximum valley depth S v , the height skewness S sk , the kurtosis S of the height score ku One of them.

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