Lithium battery performance score calculation method and system

Abstract

Disclosed are a method and a system for calculating a lithium battery performance score. The method includes: obtaining data information in the operation process of a lithium battery and uploading the data to a lithium battery performance score database; constructing a lithium battery performance score system from three dimensions of battery nameplate attributes, operation attributes, and environmental attributes using the lithium battery performance score database; and constructing a battery performance score calculation model using the fuzzy comprehensive evaluation method and calculating the performance index scores of each item of the lithium battery.

Description

[Technical Field]

[0001] This application is provided based on the Chinese patent application No. 2022107257073, filed on June 24, 2022, and priority is claimed from said Chinese patent application, and all contents of said Chinese patent application are incorporated into this application for reference. This disclosure relates to the field of energy storage, and more specifically, to a method and system for calculating lithium battery performance scores. [Background technology]

[0002] With the further development of the energy storage industry, many new energy generation systems, such as wind and solar power, are choosing to store electrical energy. Lithium batteries are widely used for energy storage due to their advantages such as high energy density, stable electrochemical properties, low pollution, and long cycle life, while simultaneously promoting the sustainable and rapid development of the economy. However, as the number of charge-discharge cycles for energy storage increases, lithium batteries undergo a gradual and irreversible aging phenomenon, which directly affects their practicality, economics, and safety. Therefore, being able to accurately and quickly evaluate the real-time performance status of lithium batteries will not only enhance safety in related fields but also save considerable funds and time for the energy storage sector. Thus, researching methods for accurately evaluating the performance status of lithium batteries is of significant importance for their practical application.

[0003] Conventional methods for evaluating the performance state of lithium batteries are highly fuzzy, their evaluation indicators are one-sided, they are susceptible to human influence, and they fail to accurately and comprehensively represent the performance state of lithium batteries, resulting in unconvincing evaluation results. [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] The lithium battery performance score calculation method and system provided in this disclosure solve the problems of lithium battery performance state evaluation methods in related technologies, which are characterized by significant fuzzyness, one-sided evaluation indices, human influence, and inability to accurately and comprehensively represent the performance state of lithium batteries, resulting in unconvincing evaluation results. [Means for solving the problem]

[0005] An embodiment of the first aspect of this disclosure provides a method for calculating lithium battery performance scores. The steps include acquiring data information during the operation process of a lithium battery and uploading the data to a lithium battery performance score database, The steps include constructing a lithium battery performance score system from three dimensions—battery nameplate attributes, operational attributes, and environmental attributes—using the aforementioned lithium battery performance score database, and This includes the step of constructing a battery performance score calculation model using a fuzzy integrated evaluation method.

[0006] An embodiment of a second aspect of this disclosure provides a lithium battery performance score calculation system, An acquisition module that acquires data information during the operation process of a lithium battery and uploads the data to a lithium battery performance score database, A construction module that constructs a lithium battery performance score system from three dimensions: battery nameplate attributes, operational attributes, and environmental attributes, using the aforementioned lithium battery performance score database. This includes a calculation module that constructs a battery performance score calculation model using a fuzzy logic integrated evaluation method and calculates the performance index score for each item of a lithium battery.

[0007] An embodiment of a third aspect of the present disclosure provides a computer device comprising memory, a processor, and a computer program stored in the memory and executable by the processor, which, when the processor executes the computer program, implements the lithium battery performance score calculation method of the first aspect of the present disclosure.

[0008] An embodiment of a fourth aspect of the present disclosure provides a non-temporary computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, it realizes the lithium battery performance score calculation method of the first aspect of the present disclosure.

[0009] An embodiment of a fifth aspect of this disclosure provides a computer program product which includes a computer program, and when the computer program is executed by a processor, implements the lithium battery performance score calculation method described in an embodiment of a first aspect of this disclosure.

[0010] A sixth embodiment of the present disclosure provides a computer program which includes computer program code, when the computer program code is executed on a computer, causes the computer to execute the lithium battery performance score calculation method described in the first embodiment of the present disclosure. [Effects of the Invention]

[0011] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects: This disclosure provides a lithium battery performance score calculation method and system, the method comprising the steps of: acquiring data information in the operation process of a lithium battery and uploading the data to a lithium battery performance score database; constructing a lithium battery performance score system from three dimensions: battery nameplate attributes, operation attributes, and environmental attributes using the lithium battery performance score database; and constructing a battery performance score calculation model using a fuzzy composite evaluation method and calculating the performance index score for each item of the lithium battery, thereby realizing real-time, rapid, and accurate calculation of lithium battery performance, and thereby evaluating the performance status of the lithium battery, improving the efficiency of lithium battery maintenance and inspection, and ensuring the safe and stable operation of the lithium battery.

[0012] Additional features and advantages of the present disclosure will be partially shown in the following description, some of which will become apparent from this description, or can be understood by implementing the present invention.

Brief Description of the Drawings

[0013] The above-mentioned and / or additional features and advantages of the present disclosure will become apparent and be easily understood from the description of embodiments with reference to the following attached drawings. [Figure 1] It is a flowchart of a method for calculating a lithium battery performance score provided by an embodiment of the present disclosure. [Figure 2] It is a specific flowchart of a method for calculating a lithium battery performance score provided by an embodiment of the present disclosure. [Figure 3] It is a principle diagram of a fuzzy comprehensive evaluation model in a method for calculating a lithium battery performance score provided by an embodiment of the present disclosure. [Figure 4] It is a visualization interface diagram of the analysis of the performance state of a lithium battery in a method for calculating a lithium battery performance score provided by an embodiment of the present disclosure. [Figure 5] It is a configuration diagram of a lithium battery performance score calculation system provided by an embodiment of the present disclosure.

Modes for Carrying Out the Invention

[0014] Hereinafter, embodiments of the present disclosure will be described in detail. Examples of this embodiment are shown in the drawings, and the same or similar reference numerals from beginning to end represent the same or similar elements, or elements having the same or similar functions. The embodiments described below with reference to the drawings are illustrative for explaining the present disclosure and should not be construed as a limitation of the present disclosure.

[0015] A lithium battery performance score calculation method and system provided by the present disclosure, wherein the method includes the steps of obtaining data information in the operation process of a lithium battery and uploading the data to a lithium battery performance score database; constructing a lithium battery performance score system from three dimensions of battery nameplate attributes, operation attributes, and environmental attributes using the lithium battery performance score database; constructing a battery performance score calculation model using the fuzzy comprehensive evaluation method and calculating the performance index scores of each item of the lithium battery, realizing the real-time, rapid, and accurate calculation of the performance of the lithium battery, evaluating the performance state of the lithium battery, improving the efficiency of lithium battery maintenance and inspection, and ensuring the safe and stable operation of the lithium battery.

[0016] Hereinafter, with reference to the drawings, a lithium battery performance score calculation method and system according to an embodiment of the present disclosure will be described.

[0017] Embodiment 1 FIG. 1 is a flowchart of a lithium battery performance score calculation method provided by an embodiment of the present disclosure. As shown in FIG. 1, the method includes steps 1-3.

[0018] Step 1: Obtain data information in the operation process of a lithium battery and upload the data to a lithium battery performance score database.

[0019] The data information in the operation process of the lithium battery includes lithium battery operation power, voltage, current, temperature, etc.

[0020] FIG. 2 is a specific flowchart of a lithium battery performance score calculation method provided by an embodiment of the present disclosure. As shown in FIG. 2, after uploading the data to the lithium battery performance score database, the method further includes the step of performing a cleaning process on the lithium battery performance data in the lithium battery performance score database.

[0021] The step of performing a cleanup process on the lithium battery performance data in the lithium battery performance score database includes filling in missing values ​​and handling abnormal values, Missing value filling refers to removing data for the current day if there are 5 or more missing values, and filling in missing values ​​using the average of the three preceding and succeeding data points if there are 5 or fewer missing values. Outlier processing refers to constructing an indicator outlier identification method using statistical analysis, box plots, etc., for outliers, and deleting or filling them in according to demand.

[0022] Step 2: Evaluation of Lithium Battery Performance Using the Lithium Battery Performance Score Database, a lithium battery performance score system is constructed from three dimensions: battery nameplate attributes, operating attributes, and environmental attributes.

[0023] In embodiments of this disclosure, before constructing a lithium battery performance score system from three dimensions—battery nameplate attributes, operational attributes, and environmental attributes—using the lithium battery performance score database, the further step includes constructing lithium battery index features related to the lithium battery, Methods for constructing lithium battery index features related to lithium batteries include descriptive statistics, association analysis, data transformation, data coding, binning, and feature combination.

[0024] Furthermore, the nameplate attributes include battery model number, battery capacity, battery shipping date, lot number, manufacturer, and location, Operating attributes include total operating power, total voltage, total current, maximum and minimum voltage, and maximum and minimum temperature, etc. Environmental attributes include external maximum and minimum temperature, maximum and minimum humidity, and meteorological data.

[0025] Step 3: Construct a battery performance score calculation model using the fuzzy composite evaluation method.

[0026] Figure 3 is a schematic diagram of a fuzzy overall evaluation model in a lithium battery performance score calculation method provided by one embodiment of the present disclosure. Specifically, the steps of constructing a battery performance score calculation model using the fuzzy overall evaluation method include the following steps: F1: The lithium battery performance scoring system is divided into levels: battery cell level, module level, battery cluster level, and battery tank level.

[0027] It is important to note that conventional lithium battery performance evaluations only assess performance at the battery cell level. However, energy storage power plants, as massive power systems, involve the operation of a large number of battery cells. Therefore, the method disclosed herein performs step-by-step evaluations not only at the battery cell level but also at the upper levels—module level, battery cluster level, and battery tank level—to provide a comprehensive evaluation of the overall performance of the energy storage power plant.

[0028] F2: The characteristic features of each item of lithium batteries at different levels are divided into different types of subjugation functions.

[0029] It is important to note that each unary index of a lithium battery can be divided into different types of subjugation functions, which include "parabolic," "positive S-type," and "linear" types.

[0030] F3: The degree of subjugation is calculated by inputting the characteristic features of each unary lithium battery index into the corresponding subjugation function, and the result is obtained by combining the single-element lithium battery evaluation matrix A for each level.

[0031] Furthermore, the formula for calculating the parabolic degree of subjugation function is as follows:

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[0032] Specifically, based on the degree of subjugation function and the set index critical value, the measured values ​​of the index are substituted into the formula for the corresponding degree of subjugation function to calculate the degree of subjugation. That is, the calculated values ​​of the parabolic degree of subjugation function, the positive S-linear degree of subjugation function, and the linear degree of subjugation function are used to construct a single-element evaluation matrix A.

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[0033] F4: Using a multivariate linear regression method, the weight coefficients for each index feature of the lithium battery are calculated, and the weight coefficient matrix R is constructed by constructing the weight coefficients that affect lithium battery performance.

[0034] F5: Using a fuzzy composite evaluation method, the composite evaluation index is calculated by multiplying a single-element evaluation matrix with a transposed weight coefficient matrix, constructing a battery performance score calculation model, and calculating and obtaining the score for each performance index of lithium batteries. This allows obtaining a composite score result for each performance index of lithium batteries at different levels, thereby achieving an accurate evaluation of the lithium battery performance state.

[0035] The steps of using the multivariate linear regression method to calculate the weight coefficients of each item index feature of a lithium battery, constructing a weight coefficient matrix R by configuring the weight coefficients that affect lithium battery performance, and using a fuzzy composite evaluation method to calculate the overall evaluation index by multiplying the single-element evaluation matrix and the transposed weight coefficient matrix, and constructing a battery performance score calculation model, specifically include the following steps: H1: The k-th index of a lithium battery

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[0036] It should be noted that since the weight acquisition methods such as the analytic hierarchy process are affected by artificial factors, this method uses the multiple linear regression method to calculate the weight coefficients of lithium battery indicators. Its principle is to determine the indicator weights based on the strength of the collinearity between each indicator of the lithium battery and other indicators, and there is no influence of artificial factors

[0037] Calculate the weight coefficients of lithium battery indicators using the multiple linear regression method, and determine the weights of indicators based on the strength of the collinearity between each indicator of the lithium battery and other indicators. That is, the larger the complex correlation coefficient Z between a certain indicator and other indicators, the stronger the collinear relationship between the said indicator and other indicators, the easier it is to be expressed by the linear combination of other indicators, and the more duplicate information there is, the smaller the weight of the said indicator should be

[0038] In the embodiments of the present disclosure, the lithium battery performance score calculation method is Based on the evaluation results, the lithium battery performance health status is classified into four levels: healthy (excellent), sub-healthy (good), unhealthy (relatively poor), and severely unhealthy (poor). The further step includes drawing a visualization interface for the lithium battery performance status.

[0039] The visualization interface includes the number of lithium battery devices, distribution topology, temperature, and performance status results, and is used to provide lithium battery unhealth alerts to the operational inspection department.

[0040] Specifically, Table 1 shows the health status corresponding to the evaluation score, and as shown in Table 1, [Table 1] Figure 4 shows a lithium battery performance state analysis visualization interface in a lithium battery performance score calculation method provided by one embodiment of the present disclosure. As shown in Figure 4, the lithium battery performance state overall score is connected to the visualization interface and used to intuitively display the performance state. The contents include, but are not limited to, the number, distribution, temperature, and health status results of lithium battery devices, and provide lithium battery unhealth alerts to the operational inspection department.

[0041] It is important to note that for lithium batteries in an unhealthy state, we should focus more on dimensions such as the number of years since installation, the load capacity ratio, and the number of times they have been heavily overloaded. We should perform a score analysis based on these dimensions, incorporate the dimensions with low scores into the equipment inspection scope, assist in locating faults, and improve inspection efficiency.

[0042] Based on the overall evaluation results, score analysis will be performed, and those with low scores will be incorporated into the equipment inspection scope to assist in fault location and improve inspection efficiency. Big data technology will be used to deploy real-time monitoring and alarms of lithium battery performance status, enabling full interaction between relevant staff and equipment, and realizing holographic sensing of lithium battery status.

[0043] As described above, the embodiments of this disclosure provide a lithium battery performance score calculation method, which includes the steps of: acquiring data information in the operation process of a lithium battery and uploading the data to a lithium battery performance score database; constructing a lithium battery performance score system from three dimensions: battery nameplate attributes, operation attributes, and environmental attributes using the lithium battery performance score database; constructing a battery performance score calculation model using a fuzzy composite evaluation method and calculating the performance index score for each item of the lithium battery, thereby realizing real-time, rapid, and accurate evaluation of the lithium battery performance status, improving the efficiency of lithium battery maintenance and inspection, ensuring safe and stable operation of lithium batteries, realizing accurate evaluation of lithium battery performance status, developing lithium battery performance status visualization scenes, and being used to intuitively display the real-time operation status of lithium batteries in energy storage units, and the disclosure can be used to support the creation of lithium battery inspection plan strategies and to guide independent repairs.

[0044] Example 2 Figure 5 is a diagram showing the configuration of a lithium battery performance score calculation system provided by an embodiment of the present disclosure. As shown in Figure 5, the system includes an acquisition module 100, a construction module 200, and a calculation module 300. The acquisition module 100 acquires data information in the operation process of the lithium battery and uploads the data to the lithium battery performance score database. The construction module 200 uses the lithium battery performance score database to construct a lithium battery performance score system from three dimensions: battery nameplate attributes, operational attributes, and environmental attributes. The calculation module 300 uses a fuzzy logic integrated evaluation method to construct a battery performance score calculation model and calculates the performance index scores for each item of the lithium battery.

[0045] The system further includes a cleaning unit, which is used to perform cleaning on lithium battery performance data uploaded to a lithium battery performance score database, specifically including filling in missing values ​​and processing abnormal values.

[0046] As described above, the lithium battery performance score calculation system provided by the embodiments of this disclosure enables real-time, rapid, and accurate calculation and evaluation of the performance status of a lithium battery.

[0047] Example 3 To realize the above-described embodiment, this embodiment further provides an electronic device.

[0048] The electronic device provided in this embodiment includes memory, a processor, and a computer program stored in the memory and executable by the processor, and when the processor executes the computer program, the lithium battery performance score calculation method of Embodiment 1 is realized.

[0049] Example 4 To realize the above embodiment, this embodiment further provides a non-temporary computer-readable storage medium.

[0050] The non-temporary computer-readable storage medium on which the computer program provided in this embodiment is stored implements the lithium battery performance score calculation method of Embodiment 1 when the computer program is executed by a processor.

[0051] Example 5 To realize the above-described embodiment, this embodiment further provides a computer program product.

[0052] The computer program product provided by this embodiment includes a computer program, and when the computer program is executed by a processor, it realizes the lithium battery performance score calculation method of Embodiment 1.

[0053] Example 6 To realize the above-described embodiment, this embodiment further provides a computer program.

[0054] The computer program provided by this embodiment includes computer program code, and when the computer program code is executed on a computer, it causes the computer to execute the lithium battery performance score calculation method of Embodiment 1.

[0055] It should be noted that the analysis and explanation of the embodiments of the lithium battery performance score calculation method described above also applies to the lithium battery performance score calculation system, electronic equipment, non-instantaneous computer-readable storage medium, computer program product, and computer program in Embodiments 2 to 6 of this disclosure, and will not be explained further here.

[0056] In this specification, descriptions that refer to "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" mean that the specific features, configurations, materials, or characteristics described in conjunction with such embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, exemplary descriptions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, configurations, materials, or characteristics described can be appropriately combined in any one or more embodiments or examples. Notwithstanding that they do not contradict each other, those skilled in the art can appropriately combine different embodiments and examples, and features of different embodiments and examples, as described in the present invention.

[0057] A flowchart or any description of a process or method described herein in any other way represents a module, fragment, or portion of code of one or more executable instructions that include steps for implementing a custom logical function or process, and the scope of preferred embodiments of the present disclosure includes other implementations, and that perform functions not in the order illustrated or discussed, but on a basis essentially concurrently or in reverse order based on the relevant functions, which should be understood by those skilled in the art in the embodiments of the present disclosure.

Claims

1. A method for calculating the performance score of a lithium battery, The steps include acquiring data information during the operation process of a lithium battery and uploading the data to a lithium battery performance score database, The steps include constructing a lithium battery performance score system from three dimensions—battery nameplate attributes, operational attributes, and environmental attributes—using the aforementioned lithium battery performance score database, and The steps include constructing a battery performance score calculation model using a fuzzy composite evaluation method and calculating the performance index score for each item of a lithium battery, Includes, The steps involve constructing a battery performance score calculation model using a fuzzy composite evaluation method and calculating the performance index scores for each item of a lithium battery. A step of classifying a lithium battery performance scoring system into levels, wherein the classifications are battery cell level, module level, battery cluster level, and battery tank level. The steps include: dividing the characteristic features of each item of lithium batteries at different levels into different types of subjugation functions; The steps include: calculating the degree of subjugation by inputting each unary lithium battery index characteristic into the corresponding subjugation function, and obtaining the result by combining the single-element lithium battery evaluation matrix A for each level; The steps include: calculating the weight coefficients of each index feature of a lithium battery using a multivariate linear regression method, constructing a weight coefficient matrix R by configuring the weight coefficients that affect lithium battery performance; The process includes the steps of: calculating an overall evaluation index by multiplying a single-element evaluation matrix and a transposed weight coefficient matrix using a fuzzy overall evaluation method; constructing a battery performance score calculation model; and calculating and obtaining lithium battery performance index score results for different levels. A lithium battery performance score calculation method in which the subjugation function type includes a parabolic subjugation function, a positive S-linear subjugation function, and a linear subjugation function.

2. The process further includes the step of uploading the data to the lithium battery performance score database and then performing a cleaning process on the lithium battery performance data in the lithium battery performance score database, The lithium battery performance score calculation method according to claim 1, wherein the step of performing a cleaning process on the lithium battery performance data in the lithium battery performance score database includes filling in missing values ​​and processing abnormal values.

3. Before constructing a lithium battery performance score system from three dimensions—battery nameplate attributes, operational attributes, and environmental attributes—using the aforementioned lithium battery performance score database, The process further includes the step of constructing lithium battery index features related to lithium battery performance, The step method for constructing lithium battery performance-related lithium battery index features includes descriptive statistics, correlation analysis, data transformation, data coding, binning, and feature combination. The aforementioned nameplate attributes include battery model number, battery capacity, battery shipping date, lot number, manufacturer, and location. The aforementioned operating attributes include total operating power, total voltage, total current, maximum and minimum voltage, and maximum and minimum temperature. The lithium battery performance score calculation method according to claim 1, wherein the environmental attributes include external maximum and minimum temperature, maximum and minimum humidity, and weather data.

4. The formula for calculating the parabolic degree of subjugation function is as follows: [Math 1] In the equation, u1(x) is the parabolic subjugation function value, and x １ represents the lower limit of the numerical value, x ２ x represents the lower limit of the optimal value, ３ x represents the upper limit of the optimal value, ４ This represents the upper limit of the numerical value. The formula for calculating the positive S-type subjugation function is as follows: [Math 2] In the equation, u²(x) represents the value of the positive S-type linear subjugation function, and x １ represents the lower limit of the numerical value, x ４ This represents the upper limit of the numerical value. The formula for calculating the linear degree of subjugation function is as follows: [Math 3] In the equation, u³(x) represents the value of the linear subordination function. [Math 4] x ４ x represents the upper limit of the numerical value, １ This represents the lower limit of the numerical value. The calculated values ​​of the parabolic subjugation function, the positive S-linear subjugation function, and the linear subjugation function are used to construct a single-element evaluation matrix A. [Math 5] In the formula: A is a matrix of m rows and n columns, m is the number of lithium battery samples, n is the number of lithium battery indicators, μ １１ is the membership degree of the first feature of the first battery sample, μ １ｎ is the membership degree of the nth feature of the first battery sample, μ ｍｎ is the membership degree of the nth feature of the mth battery sample. The lithium battery performance score calculation method according to claim 1.

5. The steps of using the multivariate linear regression method to calculate the weight coefficients of each item index feature of a lithium battery, constructing a weight coefficient matrix R by configuring the weight coefficients that affect lithium battery performance, and using a fuzzy composite evaluation method to calculate the overall evaluation index by multiplying the single-element evaluation matrix and the transposed weight coefficient matrix, and constructing a battery performance score calculation model, specifically include the following steps: H1: The k-th index of a lithium battery [Math 6] And we construct linear regression methods for other indicators, [Math 6] The formula for calculating this is as follows: [Number 7] In the formula: [Number 8] x is a constant term, n is the number of lithium battery indices, and x １ , x 2 ...x n This is in the lithium battery index. [Number 9] Other indicators, H2: Calculate the complex correlation coefficient of the indicators. The complex correlation coefficient Z of the k-th index ｋ The calculation formula is as follows: [Number 10] In the formula, [Math 11] is, X ｋ It is the average value, H3: Construct an index weight coefficient matrix, The reciprocal of the complex correlation coefficient of each indicator (1 / Z) ｋ After normalizing the data, obtain the weight coefficient r for each item index and construct a weight coefficient matrix R. [Math 12] In the formula, r 1 is the weighting coefficient for the first lithium battery index, and r ｎ This is the weighting coefficient for the nth lithium battery index, H4: Calculate the overall evaluation index B using fuzzy matrix synthesis. [Number 13] In the formula: Y １ This is the overall score of the initial lithium battery sample performance state, Y ｍ The lithium battery performance score calculation method according to claim 1, wherein m is the overall score of the m-th lithium battery sample, and m is the number of lithium battery samples.

6. The aforementioned method, Based on the evaluation results, the lithium battery performance health status is classified into four levels: healthy, subhealthy, unhealthy, and severely unhealthy. The process further includes the step of drawing a visualization interface for the lithium battery performance status, A lithium battery performance score calculation method according to claim 1, wherein the visualization interface includes the number of lithium battery devices, distribution topology, temperature, and performance status results, and is used to provide a lithium battery unhealthy alert to the operational inspection department.

7. A lithium battery performance score calculation system, An acquisition module that acquires data information during the operation process of a lithium battery and uploads the data to a lithium battery performance score database, A construction module that constructs a lithium battery performance score system from three dimensions: battery nameplate attributes, operational attributes, and environmental attributes, using the aforementioned lithium battery performance score database. A calculation module is provided to construct a battery performance score calculation model using a fuzzy logic integrated evaluation method and to calculate the performance index scores for each item of a lithium battery. Includes, The aforementioned calculation module further, The lithium battery performance scoring system is divided into levels: battery cell level, module level, battery cluster level, and battery tank level. The characteristic features of each item of lithium batteries at different levels are divided into different types of subjugation functions. The subjugation degree is calculated by inputting the characteristic features of each unary lithium battery index into the corresponding subjugation function, and the single-element evaluation matrix A for each level of lithium battery is obtained by combining these. Using a multivariate linear regression method, the weight coefficients for each index feature of a lithium battery are calculated, and the weight coefficient matrix R is constructed by constructing the weight coefficients that affect lithium battery performance. Using a fuzzy composite evaluation method, we calculated the composite evaluation index by multiplying the single-element evaluation matrix and the transposed weight coefficient matrix, constructed a battery performance score calculation model, and calculated and obtained lithium battery performance index score results at different levels. The lithium battery performance score calculation system includes, as the subjugation function types, a parabolic subjugation function, a positive S-linear subjugation function, and a linear subjugation function.

8. It is an electronic device, An electronic device comprising memory, a processor, and a computer program stored in memory and executable by the processor, wherein when the processor executes the program, it implements the lithium battery performance score calculation method according to any one of claims 1 to 6.

9. A computer-readable storage medium on which computer programs are stored, A computer-readable storage medium that enables the lithium battery performance score calculation method according to any one of claims 1 to 6 when the program is executed by a processor.

10. It is a computer program, The computer program includes computer program code, and when the computer program code is executed on a computer, the computer causes the computer to execute the lithium battery performance score calculation method according to any one of claims 1 to 6.

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