A method for predicting the service life of lithium batteries based on monitoring of their usage

Abstract

The present invention discloses a service life prediction method based on monitoring of lithium battery usage, which relates to the technical field of battery life detection, including: collecting electrolyte samples to be analyzed at at least two locations and times; obtaining basic information of conductive ions by measuring the physical parameters of conductive ions in the electrolyte samples to be analyzed; extracting features by determining the chemical composition of conductive ions in the electrolyte samples to be analyzed; performing sample pretreatment on the electrolyte samples to be analyzed; obtaining the resistance change ratio of the electrolyte samples by analyzing the resistance characteristics of chemical byproducts in the electrolyte samples to be analyzed; correlating the extracted physical, chemical and resistance characteristic data with the data in the historical sample processing database; and predicting the service life of lithium batteries. By comprehensively extracting the characteristics of conductive ions to understand the properties of conductive ions and estimating the overall usage of electrolyte samples, the service life of lithium batteries can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of battery life detection, and in particular to a method for predicting the service life of a lithium battery based on monitoring the use of the lithium battery. Background Art

[0002] During the manufacturing process of lithium-ion batteries, due to consistency and stability issues in equipment and processes, the manufactured batteries will have differences in consistency, such as high and low capacity, large and small internal resistance, inconsistent self-discharge rate, etc. These batteries need to be screened for consistency when they are grouped. Generally, batteries with similar voltage, capacity, internal resistance, and self-discharge rate are selected. Although the initial consistency of the battery after screening is good, due to slight differences in the production process of each battery, the temperature distribution of each battery is different during use, resulting in inconsistent attenuation of each battery. Therefore, during the use of the battery pack, balancing is also required.

[0003] With the continuous use of lithium-ion battery packs, the attenuation of some batteries continues to increase. Although equalization can improve the consistency of the battery pack, frequent equalization will lead to a decrease in work efficiency and even lead to the inability to charge or discharge. The existing BMS technology is difficult to evaluate the life of the battery, and can only evaluate the health status (SOH) of the entire battery system. The overall health status assessment cannot reflect the attenuation of each battery, and the battery cannot be maintained in time, so the economic benefits of the battery pack cannot be fully utilized. Summary of the invention

[0004] In order to solve the above technical problems, a service life prediction method based on lithium battery usage monitoring is provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for predicting the service life of a lithium battery based on monitoring the usage of the lithium battery, comprising:

[0007] The electrolyte sample to be analyzed is collected at at least two positions and times; the basic information of the conductive ions is obtained by measuring the physical parameters of the conductive ions in the electrolyte sample to be analyzed, wherein the physical parameters include density, water content, particle size and distribution; feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed to obtain the composition and properties of the conductive ions in the sample; the electrolyte sample to be analyzed is pretreated to remove impurities and interfering substances in the electrolyte sample to be analyzed; the resistance change ratio of the electrolyte sample is obtained by analyzing the resistance characteristics of chemical by-products in the electrolyte sample to be analyzed; the extracted physical, chemical and resistance characteristic data are correlated with the data in the historical sample processing database; and the service life of the lithium battery is predicted based on the correlation analysis between the feature data of the electrolyte sample to be analyzed and the data in the historical sample processing database.

[0008] Preferably, the obtaining basic information of the conductive ions by measuring the physical parameters of the conductive ions in the electrolyte sample to be analyzed specifically includes:

[0009] Measuring the total mass of the electrolyte sample to be analyzed and the sedimentation volume and residual liquid volume of the conductive ions therein after standing and stratifying; calculating the density of the conductive ions in the electrolyte sample to be analyzed using the sedimentation method formula;

[0010] The laser scattering principle is used to calculate the size and distribution of the conductive ion particles in the electrolyte sample to be analyzed by measuring the angle and intensity of light scattering; the electrolyte sample to be analyzed is dried, and the mass change of the electrolyte sample to be analyzed before and after drying is measured; the water content of the electrolyte sample to be analyzed is calculated using the weight method formula; the sedimentation method formula is: , where is the density of conductive ions in the electrolyte sample to be analyzed, is the total mass of the electrolyte sample to be analyzed, is the density of water, is the remaining liquid volume of the electrolyte sample to be analyzed after standing and stratification. is the sedimentation volume of the conductive ions after static stratification; the weight method formula is:

[0011] , where is the water content of the electrolyte sample to be analyzed, is the mass of the electrolyte sample to be analyzed after drying.

[0012] Preferably, the feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed, and the composition and properties of the conductive ions in the sample are obtained specifically including:

[0013] A test tube containing conductive ions, potassium dichromate solution and concentrated sulfuric acid mixed solution is placed in a heating device and heated to boiling to fully oxidize the organic interfering substances in the conductive ions; a preset volume of o-phenanthroline indicator is added to the test solution and the blank solution respectively; the ferrous sulfate standard solution is titrated until the solution changes from orange-yellow to blue-green and then to brown-red, and the volume of the ferrous sulfate standard solution consumed during the titration is recorded; the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed is calculated using the potassium dichromate method formula; the inorganic content of the conductive ions in the electrolyte sample to be analyzed is analyzed using an X-ray fluorescence spectrometer; the pH value of the conductive ions in the electrolyte sample to be analyzed is determined by a pH meter; the potassium dichromate method formula is: , where is the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed, is the molar mass of carbon atom, is the volume of ferrous sulfate standard solution consumed when titrating the blank solution, is the volume of ferrous sulfate standard solution consumed when titrating the solution to be tested, is the concentration of ferrous sulfate standard solution.

[0014] Preferably, the sample pretreatment of the electrolyte sample to be analyzed to remove impurities and interfering substances in the electrolyte sample to be analyzed specifically includes:

[0015] Aluminum hydroxide is used as a chemical flocculant to condense the colloidal impurities in the electrolyte sample to be analyzed into large particles, which are then placed and settled. A filtration device is used to remove suspended matter and particulate impurities in the electrolyte sample to be analyzed. A sulfuric acid-nitric acid system is used as an oxidant to decompose organic matter and inorganic salt interfering substances in the electrolyte sample to be analyzed. Activated carbon is used as an adsorbent to remove heavy metals in the electrolyte sample to be analyzed. Membrane separation technology is used to remove dissolved matter in the electrolyte sample to be analyzed using the selective permeability of a semipermeable membrane.

[0016] Preferably, obtaining the resistance change ratio of the electrolyte sample by analyzing the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed specifically includes:

[0017] The conductive ion sample in the electrolyte sample to be analyzed is placed in a sealed container and connected to a voltage of a preset value; the sealed container is placed at a constant temperature for a preset time, and the current change in the sealed container is measured, and the preset time is the length of time when the current no longer changes; the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed are calculated using the in-bottle method formula; the increase ratio of the resistance characteristics of the chemical byproducts relative to the last monitoring is obtained; the increase ratio is used as the resistance change ratio in the electrolyte sample to be analyzed; the in-bottle method formula is: , where The resistance characteristics of the chemical byproducts in the conductive ions in the electrolyte sample to be analyzed, For preset time, is the initial current in the closed container, The current that flows in a sealed container after it has been kept at a constant temperature for a preset period of time.

[0018] Preferably, the correlating analysis of the extracted physical, chemical and resistance characteristic data with the data in the historical sample processing database specifically includes:

[0019] Descriptive statistics are used to analyze the relationship between the physical, chemical and resistive properties of conductive ions and the sample treatment effect. Descriptive statistics are used to summarize the basic characteristics of the data, including the mean, median and standard deviation. The relationship between the physical, chemical and resistive properties of conductive ions and the sample treatment effect is intuitively displayed by drawing visual charts such as scatter plots or line graphs. Association rules are extracted from conductive ion characteristic data and sample treatment databases. Based on the extracted association rules and machine learning algorithms, a prediction model between conductive ion types and sample treatment effects is constructed.

[0020] Preferably, the prediction of the service life of the lithium battery based on the correlation analysis of the characteristic data of the electrolyte sample to be analyzed and the data in the historical sample processing database specifically includes:

[0021] Obtain the historical service life of the historical samples in the historical sample processing database; obtain the average change ratio of the physical, chemical and resistance characteristic data of the electrolyte sample to be analyzed relative to the physical, chemical and resistance characteristic data of the historical samples; multiply the historical service life of the historical samples by the average change ratio and take the average to obtain the predicted service life of the lithium battery.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] Comprehensive extraction of conductive ion characteristics is achieved. This comprehensive feature extraction helps to more accurately understand the properties and processing requirements of conductive ions, thus providing a basis for precise sample processing. Correlation analysis helps to estimate the overall usage of electrolyte samples based on the actual characteristics of conductive ions, and thus can more accurately predict the life of lithium batteries based on multi-angle analysis of electrolyte samples. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of a method for predicting the service life of a lithium battery based on monitoring the usage of the lithium battery of the present invention;

[0025] Figure 2A flow chart of a method for obtaining basic information of conductive ions by measuring physical parameters of conductive ions in an electrolyte sample to be analyzed according to the present invention;

[0026] Figure 3 This is a flow chart of a method for extracting features by measuring the chemical composition of conductive ions in an electrolyte sample to be analyzed according to the present invention;

[0027] Figure 4 A flow chart of a method for obtaining a resistance change ratio of an electrolyte sample by analyzing the resistance characteristics of chemical byproducts in an electrolyte sample to be analyzed according to the present invention;

[0028] Figure 5 A flow chart of a method for correlating and analyzing the extracted physical, chemical and resistance characteristic data with the data in the historical sample processing database according to the present invention;

[0029] Figure 6 This is a flow chart of a sample pretreatment method for an electrolyte sample to be analyzed according to the present invention;

[0030] Figure 7 This is a flow chart of the method for predicting the service life of a lithium battery according to the present invention. DETAILED DESCRIPTION

[0031] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0032] Reference Figure 1 As shown, a service life prediction method based on lithium battery usage monitoring includes:

[0033] The electrolyte sample to be analyzed is collected at at least two positions and times; the basic information of the conductive ions is obtained by measuring the physical parameters of the conductive ions in the electrolyte sample to be analyzed, wherein the physical parameters include density, water content, particle size and distribution; feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed to obtain the composition and properties of the conductive ions in the sample; the electrolyte sample to be analyzed is pretreated to remove impurities and interfering substances in the electrolyte sample to be analyzed; the resistance change ratio of the electrolyte sample is obtained by analyzing the resistance characteristics of chemical by-products in the electrolyte sample to be analyzed; the extracted physical, chemical and resistance characteristic data are correlated with the data in the historical sample processing database; and the service life of the lithium battery is predicted based on the correlation analysis between the feature data of the electrolyte sample to be analyzed and the data in the historical sample processing database.

[0034] As shown in FIG2 , the basic information of the conductive ions obtained by measuring the physical parameters of the conductive ions in the electrolyte sample to be analyzed specifically includes:

[0035] The total mass of the electrolyte sample to be analyzed and the sedimentation volume and residual liquid volume of the conductive ions therein after standing and stratifying are measured; the density of the conductive ions in the electrolyte sample to be analyzed is calculated using the sedimentation method formula; the size and distribution of the conductive ion particles in the electrolyte sample to be analyzed are calculated by measuring the angle and intensity of light scattering based on the principle of laser scattering; the electrolyte sample to be analyzed is dried and the mass change of the electrolyte sample to be analyzed before and after drying is measured; the water content of the electrolyte sample to be analyzed is calculated using the weight method formula; the sedimentation method formula is: , where is the density of conductive ions in the electrolyte sample to be analyzed, is the total mass of the electrolyte sample to be analyzed, is the density of water, is the remaining liquid volume of the electrolyte sample to be analyzed after standing and stratification. is the sedimentation volume of the conductive ions after static stratification. The weight method formula is: , where is the water content of the electrolyte sample to be analyzed, is the mass of the electrolyte sample to be analyzed after drying.

[0036] According to the characteristics of the sample and the experimental requirements, select a suitable drying method, such as natural air drying, oven drying, etc., for drying, place the sample in a drying device or an appropriate container, and dry it according to the selected method until the sample reaches a constant weight state, that is, the mass no longer changes; by combining these measurement technologies, a complete electrolyte ion property database can be established to provide a scientific basis for material design and process optimization. Modern measurement systems often combine multiple technologies to obtain more comprehensive ion behavior information.

[0037] As shown in FIG3 , feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed, and the composition and properties of the conductive ions in the sample are obtained, including:

[0038] A test tube containing conductive ions, potassium dichromate solution and concentrated sulfuric acid mixed solution is placed in a heating device and heated to boiling to fully oxidize the organic interfering substances in the conductive ions; a preset volume of o-phenanthroline indicator is added to the test solution and the blank solution respectively; the ferrous sulfate standard solution is titrated until the solution changes from orange-yellow to blue-green and then to brown-red, and the volume of the ferrous sulfate standard solution consumed during the titration is recorded; the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed is calculated using the potassium dichromate method formula; and the inorganic content of the conductive ions in the electrolyte sample to be analyzed is analyzed using an X-ray fluorescence spectrometer;

[0039] The pH value of the conductive ions in the electrolyte sample to be analyzed is measured by a pH meter; the formula of the potassium dichromate method is: , where is the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed, is the molar mass of carbon atom, is the volume of ferrous sulfate standard solution consumed when titrating the blank solution, is the volume of ferrous sulfate standard solution consumed when titrating the solution to be tested, is the concentration of ferrous sulfate standard solution.

[0040] Potassium dichromate solution and concentrated sulfuric acid are mixed in a certain proportion to form a strong oxidant system, which is used to oxidize organic interfering substances in conductive ions. The o-phenanthroline indicator is used to indicate the titration end point, that is, when the iron ion concentration in the solution reaches a certain value, the color of the solution will change. The test solution is a solution containing the oxidation products of conductive ions, while the blank solution is the same oxidant system without conductive ions, which is used to calibrate and eliminate background interference solutions. The color changes from orange-yellow to blue-green and then to brown-red, which is a typical color change of the reaction between iron ions and o-phenanthroline indicator.

[0041] As shown in FIG4 , the sample pretreatment of the electrolyte sample to be analyzed to remove impurities and interfering substances in the electrolyte sample to be analyzed specifically includes:

[0042] Aluminum hydroxide is used as a chemical flocculant to condense the colloidal impurities in the electrolyte sample to be analyzed into large particles, which are then placed and settled. A filtration device is used to remove suspended matter and particulate impurities in the electrolyte sample to be analyzed. A sulfuric acid-nitric acid system is used as an oxidant to decompose organic matter and inorganic salt interfering substances in the electrolyte sample to be analyzed. Activated carbon is used as an adsorbent to remove heavy metals in the electrolyte sample to be analyzed. Membrane separation technology is used to remove dissolved matter in the electrolyte sample to be analyzed using the selective permeability of a semipermeable membrane.

[0043] Select the appropriate type and dosage of aluminum hydroxide to ensure that the colloidal impurities in the sample can be effectively flocculated. After adding aluminum hydroxide, stir and mix thoroughly to ensure that the flocculant is evenly dispersed in the sample. According to the sample characteristics and processing requirements, set a reasonable standing time to allow the colloidal impurities to fully settle. The strong oxidizing properties of sulfuric acid and nitric acid can destroy the structure of organic matter and convert it into small molecules or carbon dioxide and water; at the same time, inorganic salt interfering substances may also be oxidized or converted into a more easily handled form. In this way, substances that affect subsequent resistance changes can be removed, and the accuracy of resistance change measurements can be improved. For the use of lithium batteries, resistance plays a vital role. When the resistance continues to increase, its service life will also decrease, but the parameters affecting the service life are not limited to resistance, but are also related to changes in the ionic properties of the electrolyte.

[0044] Reference Figure 5 As shown, the resistance change ratio of the electrolyte sample obtained by analyzing the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed specifically includes:

[0045] The conductive ion sample in the electrolyte sample to be analyzed is placed in a sealed container and connected to a voltage of a preset value; the sealed container is placed at a constant temperature for a preset time, and the current change in the sealed container is measured, and the preset time is the length of time when the current no longer changes; the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed are calculated using the in-bottle method formula; the increase ratio of the resistance characteristics of the chemical byproducts relative to the last monitoring is obtained; and the increase ratio is used as the resistance change ratio in the electrolyte sample to be analyzed;

[0046] The in-bottle method formula is: , where The resistance characteristics of the chemical byproducts in the conductive ions in the electrolyte sample to be analyzed, For preset time, is the initial current in the closed container, The current that flows in a sealed container after it has been kept at a constant temperature for a preset period of time.

[0047] By analyzing the resistance characteristics of chemical byproducts in the electrolyte, the degree of electrolyte aging, the progress of side reactions and system reliability can be evaluated. By systematically analyzing the resistance characteristics of byproducts, a quantitative relationship between electrolyte aging and electrical performance degradation can be established, providing a scientific basis for optimizing electrolyte formulation and extending device life, and realizing the correlation analysis of resistance characteristics and chemical composition.

[0048] Reference Figure 6 As shown in the figure, the extracted physical, chemical and resistance characteristic data and the data in the historical sample processing database are correlated and analyzed, including:

[0049] Descriptive statistics are used to analyze the relationship between the physical, chemical and resistive properties of conductive ions and the sample treatment effect. Descriptive statistics are used to summarize the basic characteristics of the data, including the mean, median and standard deviation. The relationship between the physical, chemical and resistive properties of conductive ions and the sample treatment effect is intuitively displayed by drawing visual charts such as scatter plots or line graphs. Association rules are extracted from conductive ion characteristic data and sample treatment databases. Based on the extracted association rules and machine learning algorithms, a prediction model between conductive ion types and sample treatment effects is constructed.

[0050] Association rules are extracted from the conductive ion characteristic data and sample processing database to reveal the intrinsic connection between the conductive ion characteristics and the sample processing effect. The association rules are extracted from a large amount of data using data mining technology to find the strong correlation between the conductive ion characteristics and the sample processing effect. The extracted association rules can be used to explain how the conductive ion characteristics affect the sample processing effect, providing a basis for the subsequent prediction model construction.

[0051] As shown in FIG. 7 , based on the correlation analysis between the characteristic data of the electrolyte sample to be analyzed and the data in the historical sample processing database, the service life of the lithium battery is predicted to include:

[0052] Obtain the historical service life of the historical samples in the historical sample processing database; obtain the average change ratio of the physical, chemical and resistance characteristic data of the electrolyte sample to be analyzed relative to the physical, chemical and resistance characteristic data of the historical samples; multiply the historical service life of the historical samples by the average change ratio and take the average to obtain the predicted service life of the lithium battery.

[0053] This method predicts the lifespan by comparing the characteristic differences between the current electrolyte sample and the historical sample, combined with the historical lifespan data. This method is particularly suitable for battery production or research environments with rich historical data. When making a comparison, it is recommended that the number of historical samples taken from the historical sample processing database is greater than or equal to 50 groups. By utilizing historical experience data, this method can achieve a prediction accuracy of about 85% (with an error of less than ±15% from the actual lifespan) while maintaining computational efficiency. For key application scenarios, it is recommended to combine a physics-based degradation model for cross-validation.

[0054] Furthermore, the present solution also proposes a computer-readable storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned service life prediction method based on lithium battery usage monitoring is executed.

[0055] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0056] To sum up, the advantages of the present invention are: it realizes comprehensive extraction of conductive ion characteristics, and this comprehensive feature extraction helps to more accurately understand the properties and processing requirements of conductive ions, thereby providing a basis for realizing precise sample processing. Correlation analysis helps to estimate the overall usage of electrolyte samples based on the actual characteristics of conductive ions, and thus can estimate the life of lithium batteries more accurately based on multi-angle analysis of electrolyte samples.

[0057] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for predicting the service life of a lithium battery based on the monitoring of its usage, characterized in that: include: collecting electrolyte samples to be analyzed at at least two locations and times; Obtaining basic information about the conductive ions by measuring the physical parameters of the conductive ions in the electrolyte sample to be analyzed, wherein the physical parameters include density, water content, particle size and distribution; Feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed, and the composition and properties of the conductive ions in the sample are obtained; Perform sample pretreatment on the electrolyte sample to be analyzed to remove impurities and interfering substances in the electrolyte sample to be analyzed; The resistance change ratio of the electrolyte sample is obtained by analyzing the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed; Correlation analysis is performed between the extracted physical, chemical and resistance property data and the data in the historical sample processing database; Predict the service life of lithium batteries based on correlation analysis between the characteristic data of the electrolyte sample to be analyzed and the data in the historical sample processing database; The method of obtaining basic information of conductive ions by measuring the physical parameters of conductive ions in the electrolyte sample to be analyzed specifically includes: Measuring the total mass of the electrolyte sample to be analyzed and the sedimentation volume of the conductive ions therein after standing and stratifying and the residual liquid volume; The density of the conductive ions in the electrolyte sample to be analyzed is calculated using the sedimentation method formula; Using the principle of laser scattering, the size and distribution of conductive ion particles in the electrolyte sample to be analyzed are calculated by measuring the angle and intensity of light scattering; Drying the electrolyte sample to be analyzed, and measuring the mass change of the electrolyte sample to be analyzed before and after drying; Calculate the water content of the electrolyte sample to be analyzed using the gravimetric formula; The sedimentation method formula is: ， In the formula, is the density of conductive ions in the electrolyte sample to be analyzed, is the total mass of the electrolyte sample to be analyzed, is the density of water, is the remaining liquid volume of the electrolyte sample to be analyzed after standing and stratification. is the sedimentation volume of the conductive ions after static stratification; The gravimetric formula is: ， In the formula, is the water content of the electrolyte sample to be analyzed, is the mass of the electrolyte sample to be analyzed after drying; The step of obtaining the resistance change ratio of the electrolyte sample by analyzing the resistance characteristics of the chemical byproducts in the electrolyte sample to be analyzed specifically includes: Put the conductive ion sample in the electrolyte sample to be analyzed into a closed container and connect it to a voltage of a preset value; The sealed container is placed at a constant temperature for a preset time, and the current change in the sealed container is measured. The preset time is the length of time during which the current no longer changes. The resistance characteristics of chemical byproducts in the electrolyte sample to be analyzed are calculated using the in-bottle method formula; Obtaining the increase ratio of the resistance characteristic of the chemical byproduct relative to the last monitoring; The increase ratio is used as the resistance change ratio in the electrolyte sample to be analyzed; The in-bottle method formula is: ， In the formula, The resistance characteristics of the chemical byproducts in the conductive ions in the electrolyte sample to be analyzed, For preset time, is the initial current in the closed container, The current that flows in a sealed container after it has been kept at a constant temperature for a preset period of time.

2. A method for predicting the service life of a lithium battery based on monitoring the usage of a lithium battery according to claim 1, characterized in that: The feature extraction is performed by measuring the chemical composition of the conductive ions in the electrolyte sample to be analyzed, and the composition and properties of the conductive ions in the sample are obtained specifically including: Place a test tube containing conductive ions, potassium dichromate solution and concentrated sulfuric acid mixed solution in a heating device and heat to boiling to fully oxidize the organic interfering substances in the conductive ions; Adding a preset volume of o-phenanthroline indicator to the test solution and the blank solution respectively; Titrate the ferrous sulfate standard solution until the solution changes from orange-yellow to blue-green and then to brown-red, and record the volume of the ferrous sulfate standard solution consumed during the titration; The potassium dichromate method formula is used to calculate the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed; The inorganic content of the conductive ions in the electrolyte sample to be analyzed is analyzed by using an X-ray fluorescence spectrometer; The pH value of the conductive ions in the electrolyte sample to be analyzed is measured by a pH meter; The potassium dichromate method formula is: ， In the formula, is the content of organic interfering substances in the conductive ions in the electrolyte sample to be analyzed, is the molar mass of carbon atom, is the volume of ferrous sulfate standard solution consumed when titrating the blank solution, is the volume of ferrous sulfate standard solution consumed when titrating the solution to be tested, is the concentration of ferrous sulfate standard solution.

3. The method for predicting the service life of a lithium battery based on the monitoring of the usage of a lithium battery according to claim 2, characterized in that: The sample pretreatment of the electrolyte sample to be analyzed to remove impurities and interfering substances in the electrolyte sample to be analyzed specifically includes: Aluminum hydroxide is used as a chemical flocculant to condense colloidal impurities in the electrolyte sample to be analyzed into large particles, which are then subjected to static sedimentation treatment; Using a filtering device to remove suspended matter and particulate impurities from the electrolyte sample to be analyzed; Using sulfuric acid-nitric acid system as oxidant, organic matter and inorganic salt interfering substances in the electrolyte sample to be analyzed are decomposed; Using activated carbon as an adsorbent to remove heavy metals from the electrolyte sample to be analyzed; Membrane separation technology is used to remove dissolved substances in the electrolyte sample to be analyzed by utilizing the selective permeability of the semipermeable membrane.

4. The method for predicting the service life of a lithium battery based on the monitoring of the usage of a lithium battery according to claim 3, characterized in that: The correlating analysis of the extracted physical, chemical and resistance characteristic data with the data in the historical sample processing database specifically includes: Descriptive statistical methods were used to analyze the relationship between the physical, chemical and resistive properties of conductive ions and the effects of sample treatment. Descriptive statistics were used to summarize the basic characteristics of the data, including mean, median, and standard deviation; By drawing a scatter plot or line graph, the relationship between the physical, chemical and resistive properties of the conductive ions and the sample treatment effect can be intuitively displayed; Extracting association rules from conductive ion feature data and sample processing database; Based on the extracted association rules and machine learning algorithms, a prediction model between conductive ion types and sample treatment effects was constructed.

5. The method for predicting the service life of a lithium battery based on the monitoring of the usage of a lithium battery according to claim 4, characterized in that: The prediction of the service life of the lithium battery based on the correlation analysis of the characteristic data of the electrolyte sample to be analyzed and the data in the historical sample processing database specifically includes: Obtain the historical service life of historical samples in the historical sample processing database; Obtaining the average change ratio of the physical, chemical and resistance characteristic data of the electrolyte sample to be analyzed relative to the physical, chemical and resistance characteristic data of the historical samples; The historical service life of the historical samples is multiplied by the average change ratio and the average is taken to obtain the predicted service life of the lithium battery.

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