Intelligent lithium ion solid-state battery production quality control method and system

Abstract

The invention relates to the field of solid-state batteries, and discloses an intelligent lithium ion solid-state battery production quality control method and system, and the method comprises the steps: analyzing the cycle state of a charge-discharge solid-state battery; when the circulation mode meets the circulation standard, constructing a direct-current voltage environment of the lithium-ion solid-state battery, identifying the battery voltage and the battery current of the lithium-ion solid-state battery in the direct-current voltage environment, and identifying the conductivity state of the lithium-ion solid-state battery; when the conductivity state meets the conductivity standard, collecting a battery image of the lithium ion solid-state battery, and identifying the appearance state of the lithium ion solid-state battery; when the appearance state meets the appearance standard, calculating the active material density of the lithium-ion solid-state battery, and judging the active material state of the lithium-ion solid-state battery; and analyzing the abnormal coefficient of the lithium-ion solid-state battery, and constructing an abnormal analysis report of the lithium-ion solid-state battery. According to the invention, the production quality control effect of the intelligent lithium ion solid-state battery can be improved.

Description

Technical Field

[0001] The present invention relates to the field of solid-state batteries, and in particular to a method and system for intelligent lithium-ion solid-state battery production quality control. Background Art

[0002] Solid-state batteries, as a type of lithium-ion battery, use solid electrolytes instead of traditional liquid electrolytes and are expected to provide higher safety and energy density, making them an ideal energy solution for electric vehicles, portable electronics and other fields.

[0003] Although solid-state batteries show great potential, their production process faces a series of challenges. Among them, the interface compatibility between electrolyte and electrode materials, the high-precision control requirements of the production process, and the economy and efficiency of large-scale production are the key technical problems that need to be solved urgently. In the traditional solid-state battery production process, quality control mainly relies on the later battery performance test to evaluate, which not only increases the production cost, but also prolongs the production cycle. Once deviations occur in the production process, a large number of battery products may be unqualified, affecting the overall production efficiency and product quality. Summary of the invention

[0004] The present invention provides a method and system for production quality control of intelligent lithium-ion solid-state batteries, the main purpose of which is to improve the production quality control effect of intelligent lithium-ion solid-state batteries.

[0005] To achieve the above-mentioned purpose, the present invention provides a method for intelligent lithium-ion solid-state battery production quality control, comprising:

[0006] Performing a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identifying the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyzing the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity;

[0007] When the cycle mode meets the cycle standard, constructing a DC voltage environment for the lithium-ion solid-state battery, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity;

[0008] When the conductivity state meets the conductivity standard, collecting a battery image of the lithium-ion solid-state battery, analyzing surface defects of the lithium-ion solid-state battery based on the battery image, and identifying the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects;

[0009] When the appearance state meets the appearance standard, performing electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data, calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and judging the active material state of the lithium-ion solid-state battery based on the active material density;

[0010] Based on the cycle state, the conductivity state, the appearance state and the active material state, the abnormal coefficient of the lithium-ion solid-state battery is analyzed, and based on the abnormal coefficient, an abnormal analysis report of the lithium-ion solid-state battery is constructed.

[0011] Optionally, analyzing the cycle state of the charge-discharge solid-state battery based on the cycle number and the discharge capacity includes:

[0012] Determining an initial cycle and a termination cycle of the charge-discharge solid-state battery;

[0013] Based on the discharge capacity, marking the initial cycle capacity of the initial cycle;

[0014] Analyzing the capacity loss coefficient of the charge-discharge solid-state battery;

[0015] Calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles;

[0016] Based on the remaining capacity and a preset standard capacity, the cycle state of the charge-discharge solid-state battery is analyzed.

[0017] Optionally, the calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles includes:

[0018] Based on the initial cycle capacity, the capacity loss coefficient and the number of cycles, the remaining capacity at the end of the cycle is calculated using the following formula:

[0019]

[0020] Among them, C_{f} represents the remaining capacity of the termination cycle, f represents the number of cycles corresponding to the termination cycle, and A h 1 represents the initial cycle capacity, Indicates the capacitance loss factor.

[0021] Optionally, the calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current includes:

[0022] Calculating the resistance value of the lithium-ion solid-state battery based on the battery voltage and the battery current;

[0023] Feeding back the resistance value to the intelligent battery quality control system corresponding to the lithium-ion solid-state battery;

[0024] Using the ultrasonic thickness gauge corresponding to the intelligent battery quality control system to obtain the electrolyte thickness and electrolyte cross-sectional area of ​​the lithium-ion solid-state battery;

[0025] The electrical conductivity of the lithium-ion solid-state battery is calculated based on the resistance value, the electrolyte thickness, and the electrolyte cross-sectional area.

[0026] Optionally, the calculating the conductivity of the lithium-ion solid-state battery based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area includes:

[0027] Based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area, the resistivity of the lithium-ion solid-state battery is calculated using the following formula:

[0028] R rho ={E1\B1}*{L}

[0029] Among them, R rho represents the resistivity of the lithium-ion solid-state battery, E1 represents the resistance value of the lithium-ion solid-state battery, B1 represents the electrolyte cross-sectional area of ​​the lithium-ion solid-state battery, and L represents the electrolyte thickness of the lithium-ion solid-state battery;

[0030] Based on the electrolyte thickness, the conductivity of the lithium-ion solid-state battery is calculated using the following formula:

[0031] D={1\R rho}

[0032] Where D represents the conductivity of the lithium-ion solid-state battery, R rho Represents the resistivity of lithium-ion solid-state batteries.

[0033] Optionally, analyzing the surface defects of the lithium-ion solid-state battery based on the battery image includes:

[0034] Denoising the battery image to obtain a denoised battery image; identifying image corner points of the denoised battery image;

[0035] Based on the image corner points, registering the denoised battery image to obtain a registered battery image;

[0036] Extracting battery features of the lithium-ion solid-state battery based on the registered battery image;

[0037] Based on the battery characteristics, surface defects of the lithium-ion solid-state battery are identified.

[0038] Optionally, extracting battery features of the lithium-ion solid-state battery based on the registered battery image includes:

[0039] Scanning the registered battery image to obtain the battery appearance characteristics of the lithium-ion solid-state battery;

[0040] Gray-scaling the registered battery image to obtain a gray-scale battery image;

[0041] constructing a co-occurrence matrix of the grayscale battery image;

[0042] Extracting battery texture features of the lithium-ion solid-state battery based on the co-occurrence matrix;

[0043] Based on the battery appearance characteristics and the battery texture characteristics, the battery characteristics of the lithium-ion solid-state battery are analyzed.

[0044] Optionally, constructing the co-occurrence matrix of the grayscale battery image includes:

[0045] Determining a neighborhood area of ​​the grayscale battery image;

[0046] Defining co-occurrence matrix parameters of the neighborhood area;

[0047] Based on the co-occurrence matrix parameters and the neighborhood area, the co-occurrence matrix of the grayscale battery image is constructed using the following formula:

[0048]

[0049] Among them, PLCM represents the co-occurrence matrix of the grayscale battery image, V represents the number of gray levels in the grayscale battery image, P(x, y) represents the grayscale value of the coordinate (x, y) of the grayscale battery image, h represents the distance between the pixel coordinate (x, y) and the coordinate (r, u) in the neighborhood area, θ represents the matrix rotation angle corresponding to the co-occurrence matrix parameter, and cos(θ) represents the cosine value of the matrix rotation angle corresponding to the co-occurrence matrix parameter.

[0050] Optionally, the calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data includes:

[0051] Based on the electrode scanning data, identifying the electrode volume of the lithium-ion solid-state battery;

[0052] Based on the electrode scanning data, identifying the amount of active material in the electrode volume;

[0053] Based on the electrode volume and the amount of the active material, the active material density of the lithium-ion solid-state battery is calculated using the following formula:

[0054]

[0055] Wherein, Y represents the active material density of the lithium-ion solid-state battery, W represents the amount of active materials in the lithium-ion solid-state battery, Z represents the standard amount of active materials in the lithium-ion solid-state battery, V represents the electrode volume of the lithium-ion solid-state battery, and O A Represents the Avogadro constant for lithium-ion solid-state batteries.

[0056] In order to solve the above problems, the present invention also provides a system for intelligent lithium-ion solid-state battery production quality control, the system comprising:

[0057] A cycle state analysis module is used to perform a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identify the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyze the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity;

[0058] A conductivity state analysis module, for constructing a DC voltage environment for the lithium-ion solid-state battery when the circulation mode meets the circulation standard, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity;

[0059] an appearance state analysis module, configured to collect a battery image of the lithium-ion solid-state battery when the conductivity state meets the conductivity standard, analyze surface defects of the lithium-ion solid-state battery based on the battery image, and identify the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects;

[0060] an active material state analysis module, configured to perform an electrode scan on the lithium-ion solid-state battery to obtain electrode scan data when the appearance state meets the appearance standard, calculate the active material density of the lithium-ion solid-state battery based on the electrode scan data, and determine the active material state of the lithium-ion solid-state battery based on the active material density;

[0061] The abnormal analysis report analysis module is used to analyze the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state, and construct an abnormal analysis report of the lithium-ion solid-state battery based on the abnormal coefficient.

[0062] The embodiment of the present invention analyzes the cycle state of the charge-discharge solid-state battery based on the number of cycles and the discharge capacity to evaluate whether the charge-discharge cycle of the charge-discharge solid-state battery is qualified; the embodiment of the present invention calculates the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, which can be used as data for evaluating the conductive performance of the lithium-ion solid-state battery. According to the embodiment of the present invention, by identifying the conductivity state of the lithium-ion solid-state battery, it can be evaluated whether the conductivity of the lithium-ion solid-state battery meets the requirements, thereby improving the quality analysis effect of the lithium-ion solid-state battery; further, the embodiment of the present invention analyzes the surface defects of the lithium-ion solid-state battery based on the battery image to extract the appearance defects of the lithium-ion solid-state battery, thereby improving the quality control of the lithium-ion solid-state battery. Further, the embodiment of the present invention is based on the battery characteristics and the Surface defects, identifying the appearance state of the lithium-ion solid-state battery can identify batteries with abnormal appearance, thereby improving the quality control effect of the battery. Furthermore, the embodiment of the present invention calculates the active material density of the lithium-ion solid-state battery based on the electrode scanning data, which can be used as a data basis for evaluating the active material state of the lithium-ion solid-state battery. The embodiment of the present invention determines the active material state of the lithium-ion solid-state battery based on the active material density, which can evaluate whether the active material of the lithium-ion solid-state battery meets the requirements, thereby improving the quality control effect of the lithium-ion solid-state battery. Finally, the embodiment of the present invention analyzes the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state, which can evaluate the abnormal degree of the lithium-ion solid-state battery, thereby improving the quality control of the battery. Therefore, the method and system for production quality control of intelligent lithium-ion solid-state batteries proposed in the present invention can improve the production quality control effect of intelligent lithium-ion solid-state batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A schematic diagram of a process for intelligent lithium-ion solid-state battery production quality control method provided by one embodiment of the present invention;

[0064] Figure 2 A functional module diagram of a system for intelligent lithium-ion solid-state battery production quality control provided by an embodiment of the present invention;

[0065] Figure 3 A schematic diagram of the structure of an electronic device of a system for intelligent lithium-ion solid-state battery production quality control provided by an embodiment of the present invention;

[0066] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0068] The embodiment of the present application provides a method for quality control of the production of intelligent lithium-ion solid-state batteries. The execution subject of the method for quality control of the production of intelligent lithium-ion solid-state batteries includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for quality control of the production of intelligent lithium-ion solid-state batteries can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0069] Reference Figure 1 FIG. 1 is a flow chart of a method for quality control of intelligent lithium-ion solid-state battery production provided by an embodiment of the present invention. In this embodiment, the method for quality control of intelligent lithium-ion solid-state battery production includes:

[0070] S1. Use the battery tester corresponding to the intelligent battery quality control system to perform charge and discharge tests on the lithium-ion solid-state battery to obtain a charge and discharge solid-state battery, identify the cycle number and discharge capacity of the charge and discharge solid-state battery, and analyze the cycle state of the charge and discharge solid-state battery based on the cycle number and the discharge capacity.

[0071] In the embodiment of the present invention, the charge-discharge solid-state battery refers to the lithium-ion solid-state battery that is charged and discharged. The number of cycles refers to the number of cycles of charge and discharge of the charge-discharge solid-state battery, and the discharge capacity refers to the amount of charge that can be released by a battery or capacitor during the discharge process.

[0072] Optionally, the embodiment of the present invention analyzes the cycle state of the charge-discharge solid-state battery based on the cycle number and the discharge capacity to evaluate whether the charge-discharge cycle of the charge-discharge solid-state battery is qualified. The cycle state includes a qualified mode and an abnormal mode.

[0073] Optionally, as an embodiment of the present invention, the analyzing the cycle state of the charge-discharge solid-state battery based on the number of cycles and the discharge capacity includes: determining the initial cycle and the termination cycle of the charge-discharge solid-state battery; marking the initial cycle capacity of the initial cycle based on the discharge capacity; analyzing the capacity loss coefficient of the charge-discharge solid-state battery; calculating the remaining capacity of the termination cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles; analyzing the cycle state of the charge-discharge solid-state battery based on the remaining capacity and a preset standard capacity.

[0074] Among them, the initial cycle and the termination cycle refer to the first cycle and the last cycle of the charge-discharge solid-state battery, the capacity loss coefficient refers to the degree of loss of the charge-discharge solid-state battery each time it is charged and discharged, and the standard capacity refers to the parameter for judging whether the charge-discharge solid-state battery meets the cycle standard.

[0075] Further, in an optional embodiment of the present invention, the calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles includes: calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles using the following formula:

[0076]

[0077] Among them, C_{f} represents the remaining capacity of the termination cycle, f represents the number of cycles corresponding to the termination cycle, and A h 1 represents the initial cycle capacity, Indicates the capacitance loss factor.

[0078] Among them, the qualified mode: if the remaining capacity of the battery after cycling is greater than the standard capacity, it is a qualified product.

[0079] The abnormal mode: if the remaining capacity of the battery after cycling is less than the standard capacity, it is a substandard product.

[0080] S2. When the cycle mode meets the cycle standard, a DC voltage environment of the lithium-ion solid-state battery is constructed, the battery voltage and the battery current of the lithium-ion solid-state battery under the DC voltage environment are identified, the conductivity of the lithium-ion solid-state battery is calculated based on the battery voltage and the battery current, and the conductivity state of the lithium-ion solid-state battery is identified based on the conductivity.

[0081] In the embodiment of the present invention, when the circulation mode meets the circulation standard, it means that the circulation mode meets the qualified mode. The DC voltage environment refers to a voltage environment that does not cause battery reaction and damage after the corresponding four-point detector probe of the intelligent battery quality control system contacts the lithium-ion solid-state battery. The battery voltage and battery current refer to the current and voltage of the sensor in the battery detection state under the DC voltage environment.

[0082] Optionally, the embodiment of the present invention calculates the conductivity of the lithium-ion solid-state battery based on the battery voltage and battery current, which can be used as a data basis for evaluating the conductive performance of the lithium-ion solid-state battery. The conductivity refers to the ability of the lithium-ion solid-state battery to allow current to pass through.

[0083] Optionally, as an embodiment of the present invention, the calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current includes: calculating the resistance value of the lithium-ion solid-state battery based on the battery voltage and the battery current; feeding back the resistance value to an intelligent battery quality control system corresponding to the lithium-ion solid-state battery; obtaining the electrolyte thickness and electrolyte cross-sectional area of ​​the lithium-ion solid-state battery using an ultrasonic thickness gauge corresponding to the intelligent battery quality control system; and calculating the conductivity of the lithium-ion solid-state battery based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area.

[0084] Among them, the resistance value refers to the degree to which the material hinders the flow of current, the ultrasonic thickness gauge is an instrument that uses the ultrasonic principle to measure the thickness of the material, and the electrolyte thickness and electrolyte cross-sectional area refer to the layer thickness of the electrolyte in the battery and the cross-sectional area covered by the electrolyte.

[0085] Further, in an optional embodiment of the present invention, the conductivity of the lithium-ion solid-state battery is calculated based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area, including: based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area, the resistivity of the lithium-ion solid-state battery is calculated using the following formula:

[0086] R rho ={E1\B1}*{L}

[0087] Among them, R rho represents the resistivity of the lithium-ion solid-state battery, E1 represents the resistance value of the lithium-ion solid-state battery, B1 represents the electrolyte cross-sectional area of ​​the lithium-ion solid-state battery, and L represents the electrolyte thickness of the lithium-ion solid-state battery;

[0088] Based on the electrolyte thickness, the conductivity of the lithium-ion solid-state battery is calculated using the following formula:

[0089] D={1\Rrho}

[0090] Where D represents the conductivity of the lithium-ion solid-state battery, R rho Represents the resistivity of lithium-ion solid-state batteries.

[0091] The embodiment of the present invention can evaluate whether the conductivity of the lithium-ion solid-state battery meets the requirements by identifying the conductivity state of the lithium-ion solid-state battery, thereby improving the quality analysis effect of the lithium-ion solid-state battery. The conductivity state includes: a normal conductivity mode and an abnormal conductivity mode. In detail, the normal conductivity mode: the current battery conductivity is qualified within the preset standard conductivity range, and the abnormal mode: the battery conductivity is unqualified if it is lower than the preset standard conductivity range.

[0092] S3. When the conductivity state meets the conductivity standard, a battery image of the lithium-ion solid-state battery is collected, surface defects of the lithium-ion solid-state battery are analyzed based on the battery image, and the appearance state of the lithium-ion solid-state battery is identified based on the battery characteristics and the surface defects.

[0093] In the embodiment of the present invention, when the conductivity state meets the conductivity standard, it means that the conductivity state meets the normal conductivity mode. The battery image refers to the battery appearance image of the lithium-ion solid-state battery collected from multiple angles.

[0094] Optionally, the embodiment of the present invention can analyze the surface defects of the lithium-ion solid-state battery based on the battery image to extract the appearance defects of the lithium-ion solid-state battery, thereby improving the quality control of the lithium-ion solid-state battery. The appearance defects refer to defects in the appearance of the lithium-ion solid-state battery, and the appearance defects include but are not limited to: abnormal battery size, surface cracks, surface scratches, surface bulges and other defects.

[0095] Optionally, as an embodiment of the present invention, analyzing the surface defects of the lithium-ion solid-state battery based on the battery image includes: denoising the battery image to obtain a denoised battery image; identifying image corner points of the denoised battery image; registering the denoised battery image based on the image corner points to obtain a registered battery image; extracting battery features of the lithium-ion solid-state battery based on the registered battery image; and identifying surface defects of the lithium-ion solid-state battery based on the battery features.

[0096] Among them, the denoised battery image refers to the image after noise is removed from the battery image, the image corner point refers to the point in the image with specific attributes or identifiable features, and the registered battery image refers to the image after multiple angles of the denoised battery image are registered through image corner points. In detail, the registered battery image can be achieved by matching image corner points, and the battery feature refers to the characteristic attributes of the lithium-ion solid-state battery, such as battery size, battery color, battery texture, battery structure and other characteristic attributes.

[0097] Furthermore, in an optional embodiment of the present invention, extracting the battery characteristics of the lithium-ion solid-state battery based on the registered battery image includes: scanning the registered battery image to obtain the battery appearance characteristics of the lithium-ion solid-state battery; graying the registered battery image to obtain a grayed battery image; constructing a co-occurrence matrix of the grayed battery image; extracting the battery texture characteristics of the lithium-ion solid-state battery based on the co-occurrence matrix; and analyzing the battery characteristics of the lithium-ion solid-state battery based on the battery appearance characteristics and the battery texture characteristics.

[0098] Among them, the battery appearance features refer to the state features of the appearance of the lithium-ion solid-state battery, such as battery size, battery color, battery structure and other features; the grayscale battery image refers to the image after the registered battery image is grayscaled; the co-occurrence matrix refers to a matrix used to describe the statistical relationship between different gray levels in the image; the battery texture features refer to the state features of the surface details of the lithium-ion solid-state battery, such as fine lines on the battery surface, battery surface flatness and other states.

[0099] Optionally, in an optional embodiment of the present invention, constructing the co-occurrence matrix of the grayscale battery image includes: determining a neighborhood area of ​​the grayscale battery image; defining co-occurrence matrix parameters of the neighborhood area; and constructing the co-occurrence matrix of the grayscale battery image based on the co-occurrence matrix parameters and the neighborhood area using the following formula:

[0100]

[0101] Among them, PLCM represents the co-occurrence matrix of the grayscale battery image, V represents the number of gray levels in the grayscale battery image, P(x, y) represents the grayscale value of the coordinate (x, y) of the grayscale battery image, h represents the distance between the pixel coordinate (x, y) and the coordinate (r, u) in the neighborhood area, θ represents the matrix rotation angle corresponding to the co-occurrence matrix parameter, and cos(θ) represents the cosine value of the matrix rotation angle corresponding to the co-occurrence matrix parameter.

[0102] The neighborhood area refers to a fixed area for dividing the quantized battery image, the neighborhood size is an odd number, such as 3x3, 5x5, etc., and the co-occurrence matrix parameters refer to the parameters of the co-occurrence matrix, and the co-occurrence matrix parameters include: matrix rotation angle and pixel distance.

[0103] The embodiment of the present invention can identify the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects, and can identify batteries with abnormal appearance, thereby improving the quality control effect of the battery. The appearance state includes: a normal appearance state and an abnormal appearance state. When the lithium-ion solid-state battery has defects such as cracks, bulges, and uneven sizes on the appearance, it is an abnormal appearance state, and when there are no defects on the appearance, it is a normal appearance state.

[0104] S 4. When the appearance state meets the appearance standard, perform electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data, calculate the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and judge the active material state of the lithium-ion solid-state battery based on the active material density.

[0105] In the embodiment of the present invention, when the appearance state meets the appearance standard means that the appearance state meets the normal appearance state. The electrode scanning data refers to a data set obtained by performing electrode scanning on the lithium-ion solid-state battery through an X-ray diffractometer.

[0106] Optionally, the embodiment of the present invention calculates the active material density of the lithium-ion solid-state battery based on the electrode scanning data, which can be used as a data basis for evaluating the state of the active material of the lithium-ion solid-state battery. Wherein, the active material density refers to the density of the active material in the solid-state battery electrode.

[0107] Optionally, as an embodiment of the present invention, the calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data includes: identifying the electrode volume of the lithium-ion solid-state battery based on the electrode scanning data; identifying the amount of active material in the electrode volume based on the electrode scanning data; and calculating the active material density of the lithium-ion solid-state battery based on the electrode volume and the amount of active material using the following formula:

[0108]

[0109] Wherein, Y represents the active material density of the lithium-ion solid-state battery, W represents the amount of active materials in the lithium-ion solid-state battery, Z represents the standard amount of active materials in the lithium-ion solid-state battery, V represents the electrode volume of the lithium-ion solid-state battery, and O A Represents the Avogadro constant for lithium-ion solid-state batteries.

[0110] Among them, the electrode volume refers to the electrode capacity of the lithium-ion solid-state battery, the amount of active substances refers to the number of particle atoms in the lithium-ion solid-state battery electrode, the standard amount of active substances refers to the standard number of particle atoms in a lithium-ion solid-state battery with a normal electrode of the same volume, and the Avogadro constant refers to a basic constant, which is expressed under standard conditions (temperature is 298K and pressure is 1 atmosphere).

[0111] The embodiment of the present invention determines the active material state of the lithium-ion solid-state battery based on the active material density, and can evaluate whether the active material of the lithium-ion solid-state battery meets the requirements, thereby improving the quality control effect of the lithium-ion solid-state battery. Among them, the active material state includes: normal active material state and abnormal active material state. In detail, the judgment of the active material state is determined by analyzing whether the active material density is within a preset range. Within the range, the active material state is the normal active material state, otherwise, the active material state is not the normal active material state.

[0112] S5. Analyze the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state, and the active material state, and construct an abnormal analysis report of the lithium-ion solid-state battery based on the abnormal coefficient.

[0113] The embodiment of the present invention analyzes the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state to evaluate the abnormal degree of the lithium-ion solid-state battery, thereby improving the quality control of the battery. Among them, the abnormal coefficient refers to the degree of quality abnormality of the lithium-ion solid-state battery. In detail, the abnormal coefficient refers to the number of abnormal batteries of the lithium-ion solid-state battery detected by the above means.

[0114] Finally, the embodiment of the present invention constructs an abnormal analysis report of the lithium-ion solid-state battery based on the abnormal coefficient to achieve quality control of the lithium-ion solid-state battery. The abnormal analysis report includes: the number of abnormal batteries, the type of abnormal batteries, etc.

[0115] The embodiment of the present invention analyzes the cycle state of the charge-discharge solid-state battery based on the number of cycles and the discharge capacity to evaluate whether the charge-discharge cycle of the charge-discharge solid-state battery is qualified; the embodiment of the present invention calculates the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, which can be used as data for evaluating the conductive performance of the lithium-ion solid-state battery. According to the embodiment of the present invention, by identifying the conductivity state of the lithium-ion solid-state battery, it can be evaluated whether the conductivity of the lithium-ion solid-state battery meets the requirements, thereby improving the quality analysis effect of the lithium-ion solid-state battery; further, the embodiment of the present invention analyzes the surface defects of the lithium-ion solid-state battery based on the battery image to extract the appearance defects of the lithium-ion solid-state battery, thereby improving the quality control of the lithium-ion solid-state battery. Further, the embodiment of the present invention is based on the battery characteristics and the Surface defects, identifying the appearance state of the lithium-ion solid-state battery can identify batteries with abnormal appearance, thereby improving the quality control effect of the battery. Furthermore, the embodiment of the present invention calculates the active material density of the lithium-ion solid-state battery based on the electrode scanning data, which can be used as a data basis for evaluating the active material state of the lithium-ion solid-state battery. The embodiment of the present invention determines the active material state of the lithium-ion solid-state battery based on the active material density, which can evaluate whether the active material of the lithium-ion solid-state battery meets the requirements, thereby improving the quality control effect of the lithium-ion solid-state battery. Finally, the embodiment of the present invention analyzes the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state, which can evaluate the abnormal degree of the lithium-ion solid-state battery, thereby improving the quality control of the battery. Therefore, the method for production quality control of intelligent lithium-ion solid-state batteries proposed in the present invention can improve the production quality control effect of intelligent lithium-ion solid-state batteries.

[0116] like Figure 2 , which is a functional module diagram of a system for intelligent lithium-ion solid-state battery production quality control provided by an embodiment of the present invention.

[0117] The intelligent lithium-ion solid-state battery production quality control system 200 of the present invention can be installed in an electronic device. According to the functions implemented, the intelligent lithium-ion solid-state battery production quality control system 200 can include a circulation state analysis module 201, a conductivity state analysis module 202, an appearance state analysis module 203, an active substance state analysis module 204 and an abnormal analysis report analysis module 205. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0118] In this embodiment, the functions of each module / unit are as follows:

[0119] The cycle state analysis module 201 is used to perform a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to the intelligent battery quality control system to obtain a charge and discharge solid-state battery, identify the cycle number and discharge capacity of the charge and discharge solid-state battery, and analyze the cycle state of the charge and discharge solid-state battery based on the cycle number and the discharge capacity;

[0120] The conductivity state analysis module 202 is used to construct a DC voltage environment for the lithium-ion solid-state battery when the circulation mode meets the circulation standard, identify the battery voltage and battery current of the lithium-ion solid-state battery under the DC voltage environment, calculate the conductivity of the lithium-ion solid-state battery based on the battery voltage and battery current, and identify the conductivity state of the lithium-ion solid-state battery based on the conductivity;

[0121] The appearance state analysis module 203 is used to collect a battery image of the lithium-ion solid-state battery when the conductivity state meets the conductivity standard, analyze the surface defects of the lithium-ion solid-state battery based on the battery image, and identify the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects;

[0122] The active material state analysis module 204 is used to perform electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data when the appearance state meets the appearance standard, calculate the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and determine the active material state of the lithium-ion solid-state battery based on the active material density;

[0123] The abnormal analysis report analysis module 205 is used to analyze the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state, and construct an abnormal analysis report of the lithium-ion solid-state battery based on the abnormal coefficient.

[0124] In detail, the modules described in the system 200 for intelligent lithium-ion solid-state battery production quality control in the embodiment of the present invention adopt the same technical means as the method for intelligent lithium-ion solid-state battery production quality control described in the accompanying drawings when used, and can produce the same technical effects, which will not be repeated here.

[0125] An embodiment of the present invention provides an electronic device for implementing a method for intelligent lithium-ion solid-state battery production quality control.

[0126] See also Figure 3As shown, the electronic device may include a processor 30, a memory 31, a communication bus 32 and a communication interface 33, and may also include a computer program stored in the memory 31 and executable on the processor 30, such as a method program for intelligent lithium-ion solid-state battery production quality control.

[0127] Among them, the processor in some embodiments may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips, etc. The processor is the control core (Control Unit) of the electronic device, which uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes the programs or modules stored in the memory (for example, the program for executing the quality control of the production of intelligent lithium-ion solid-state batteries, etc.), and calls the data stored in the memory to execute various functions of the electronic device and process data.

[0128] The memory includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory may be an internal storage unit of an electronic device in some embodiments, such as a mobile hard disk of the electronic device. The memory may also be an external storage device of an electronic device in other embodiments, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory may also include both an internal storage unit of the electronic device and an external storage device. The memory may be used not only to store application software and various types of data installed in the electronic device, such as the code of a program based on the production quality control of smart lithium-ion solid-state batteries, but also to temporarily store data that has been output or is to be output.

[0129] The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory and at least one processor, etc.

[0130] The communication interface is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0131] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor through a power management system, so that the power management system can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0132] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0133] The program for intelligent lithium-ion solid-state battery production quality control stored in the memory in the electronic device is a combination of multiple instructions, and when running in the processor, it can achieve:

[0134] Performing a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identifying the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyzing the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity;

[0135] When the cycle mode meets the cycle standard, constructing a DC voltage environment for the lithium-ion solid-state battery, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity;

[0136] When the conductivity state meets the conductivity standard, collecting a battery image of the lithium-ion solid-state battery, analyzing surface defects of the lithium-ion solid-state battery based on the battery image, and identifying the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects;

[0137] When the appearance state meets the appearance standard, performing electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data, calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and judging the active material state of the lithium-ion solid-state battery based on the active material density;

[0138] Based on the cycle state, the conductivity state, the appearance state and the active material state, the abnormal coefficient of the lithium-ion solid-state battery is analyzed, and based on the abnormal coefficient, an abnormal analysis report of the lithium-ion solid-state battery is constructed.

[0139] Specifically, the specific implementation method of the processor for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0140] Furthermore, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0141] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0142] Performing a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identifying the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyzing the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity;

[0143] When the cycle mode meets the cycle standard, constructing a DC voltage environment for the lithium-ion solid-state battery, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity;

[0144] When the conductivity state meets the conductivity standard, collecting a battery image of the lithium-ion solid-state battery, analyzing surface defects of the lithium-ion solid-state battery based on the battery image, and identifying the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects;

[0145] When the appearance state meets the appearance standard, performing electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data, calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and judging the active material state of the lithium-ion solid-state battery based on the active material density;

[0146] Based on the cycle state, the conductivity state, the appearance state and the active material state, the abnormal coefficient of the lithium-ion solid-state battery is analyzed, and based on the abnormal coefficient, an abnormal analysis report of the lithium-ion solid-state battery is constructed.

[0147] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0148] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0149] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0150] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0151] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0152] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0153] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems stated in a system claim can also be implemented by one unit or system through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for quality control of intelligent lithium-ion solid-state battery production, characterized in that: The method comprises: Performing a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identifying the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyzing the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity; When the cycle mode meets the cycle standard, constructing a DC voltage environment for the lithium-ion solid-state battery, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity; When the conductivity state meets the conductivity standard, collecting a battery image of the lithium-ion solid-state battery, analyzing surface defects of the lithium-ion solid-state battery based on the battery image, and identifying the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects; When the appearance state meets the appearance standard, performing electrode scanning on the lithium-ion solid-state battery to obtain electrode scanning data, calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data, and judging the active material state of the lithium-ion solid-state battery based on the active material density; Based on the cycle state, the conductivity state, the appearance state and the active material state, the abnormal coefficient of the lithium-ion solid-state battery is analyzed, and based on the abnormal coefficient, an abnormal analysis report of the lithium-ion solid-state battery is constructed.

2. The method for quality control of intelligent lithium-ion solid-state battery production according to claim 1, characterized in that: The analyzing the cycle state of the charge-discharge solid-state battery based on the cycle number and the discharge capacity includes: Determining an initial cycle and a termination cycle of the charge-discharge solid-state battery; Based on the discharge capacity, marking the initial cycle capacity of the initial cycle; Analyzing the capacity loss coefficient of the charge-discharge solid-state battery; Calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles; Based on the remaining capacity and a preset standard capacity, the cycle state of the charge-discharge solid-state battery is analyzed.

3. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 2, characterized in that: The calculating the remaining capacity at the end of the cycle based on the initial cycle capacity, the capacity loss coefficient and the number of cycles includes: Based on the initial cycle capacity, the capacity loss coefficient and the number of cycles, the remaining capacity at the end of the cycle is calculated using the following formula: Among them, C_{f} represents the remaining capacity of the termination cycle, f represents the number of cycles corresponding to the termination cycle, and A h 1 represents the initial cycle capacity, and θ represents the capacity loss coefficient.

4. The method for quality control of intelligent lithium-ion solid-state battery production according to claim 1, characterized in that: The step of calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current comprises: Calculating the resistance value of the lithium-ion solid-state battery based on the battery voltage and the battery current; Feeding back the resistance value to the intelligent battery quality control system corresponding to the lithium-ion solid-state battery; Using the ultrasonic thickness gauge corresponding to the intelligent battery quality control system to obtain the electrolyte thickness and electrolyte cross-sectional area of ​​the lithium-ion solid-state battery; The electrical conductivity of the lithium-ion solid-state battery is calculated based on the resistance value, the electrolyte thickness, and the electrolyte cross-sectional area.

5. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 4, characterized in that: The calculating the conductivity of the lithium-ion solid-state battery based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area includes: Based on the resistance value, the electrolyte thickness and the electrolyte cross-sectional area, the resistivity of the lithium-ion solid-state battery is calculated using the following formula: R rho ={E1\B1}*{L} Among them, R rho represents the resistivity of the lithium-ion solid-state battery, E1 represents the resistance value of the lithium-ion solid-state battery, B1 represents the electrolyte cross-sectional area of ​​the lithium-ion solid-state battery, and L represents the electrolyte thickness of the lithium-ion solid-state battery; Based on the electrolyte thickness, the conductivity of the lithium-ion solid-state battery is calculated using the following formula: D={1\R rho } Where D represents the conductivity of the lithium-ion solid-state battery, R rho Represents the resistivity of lithium-ion solid-state batteries.

6. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 1, characterized in that: The analyzing the surface defects of the lithium-ion solid-state battery based on the battery image includes: Denoising the battery image to obtain a denoised battery image; identifying image corner points of the denoised battery image; Based on the image corner points, registering the denoised battery image to obtain a registered battery image; Extracting battery features of the lithium-ion solid-state battery based on the registered battery image; Based on the battery characteristics, surface defects of the lithium-ion solid-state battery are identified.

7. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 6, characterized in that: The step of extracting the battery features of the lithium-ion solid-state battery based on the registered battery image comprises: Scanning the registered battery image to obtain the battery appearance characteristics of the lithium-ion solid-state battery; Gray-scaling the registered battery image to obtain a gray-scale battery image; constructing a co-occurrence matrix of the grayscale battery image; Extracting battery texture features of the lithium-ion solid-state battery based on the co-occurrence matrix; Based on the battery appearance characteristics and the battery texture characteristics, the battery characteristics of the lithium-ion solid-state battery are analyzed.

8. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 7, characterized in that: The constructing the co-occurrence matrix of the grayscale battery image comprises: Determining a neighborhood area of ​​the grayscale battery image; Defining co-occurrence matrix parameters of the neighborhood area; Based on the co-occurrence matrix parameters and the neighborhood area, the co-occurrence matrix of the grayscale battery image is constructed using the following formula: Among them, PLCM represents the co-occurrence matrix of the grayscale battery image, V represents the number of gray levels in the grayscale battery image, P(x, y) represents the grayscale value of the coordinate (x, y) of the grayscale battery image, h represents the distance between the pixel coordinate (x, y) and the coordinate (r, u) in the neighborhood area, θ represents the matrix rotation angle corresponding to the co-occurrence matrix parameter, and cos(θ) represents the cosine value of the matrix rotation angle corresponding to the co-occurrence matrix parameter.

9. The method for quality control of production of intelligent lithium-ion solid-state batteries according to claim 1, characterized in that: The calculating the active material density of the lithium-ion solid-state battery based on the electrode scanning data includes: Based on the electrode scanning data, identifying the electrode volume of the lithium-ion solid-state battery; Based on the electrode scanning data, identifying the amount of active material in the electrode volume; Based on the electrode volume and the amount of the active material, the active material density of the lithium-ion solid-state battery is calculated using the following formula: Wherein, Y represents the active material density of the lithium-ion solid-state battery, W represents the amount of active materials in the lithium-ion solid-state battery, Z represents the standard amount of active materials in the lithium-ion solid-state battery, V represents the electrode volume of the lithium-ion solid-state battery, and O A Represents the Avogadro constant for lithium-ion solid-state batteries.

10. A smart lithium-ion solid-state battery production quality control system, characterized in that: A method for executing intelligent lithium-ion solid-state battery production quality control as claimed in any one of claims 1 to 9, the system comprising: A cycle state analysis module is used to perform a charge and discharge test on a lithium-ion solid-state battery using a battery tester corresponding to an intelligent battery quality control system to obtain a charge and discharge solid-state battery, identify the number of cycles and the discharge capacity of the charge and discharge solid-state battery, and analyze the cycle state of the charge and discharge solid-state battery based on the number of cycles and the discharge capacity; A conductivity state analysis module, for constructing a DC voltage environment for the lithium-ion solid-state battery when the circulation mode meets the circulation standard, identifying a battery voltage and a battery current of the lithium-ion solid-state battery under the DC voltage environment, calculating the conductivity of the lithium-ion solid-state battery based on the battery voltage and the battery current, and identifying the conductivity state of the lithium-ion solid-state battery based on the conductivity; an appearance state analysis module, configured to collect a battery image of the lithium-ion solid-state battery when the conductivity state meets the conductivity standard, analyze surface defects of the lithium-ion solid-state battery based on the battery image, and identify the appearance state of the lithium-ion solid-state battery based on the battery characteristics and the surface defects; an active material state analysis module, configured to perform an electrode scan on the lithium-ion solid-state battery to obtain electrode scan data when the appearance state meets the appearance standard, calculate the active material density of the lithium-ion solid-state battery based on the electrode scan data, and determine the active material state of the lithium-ion solid-state battery based on the active material density; The abnormal analysis report analysis module is used to analyze the abnormal coefficient of the lithium-ion solid-state battery based on the cycle state, the conductivity state, the appearance state and the active material state, and construct an abnormal analysis report of the lithium-ion solid-state battery based on the abnormal coefficient.

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