A method for analyzing a lithium battery electrolyte

Abstract

This invention discloses an analytical method for lithium battery electrolyte, relating to the field of lithium battery electrolyte analysis technology. The method includes steps S1: collecting a lithium battery electrolyte sample under an inert atmosphere and pre-treating the sample to obtain a diluent for testing; Step S2: injecting the diluent into an analytical detection system to obtain characteristic response signals of each component in the lithium battery electrolyte; Step S3: calculating the content of the target component based on a preset quantitative analysis model and the characteristic response signals; Step S4: detecting the free acid content in the electrolyte; Step S5: detecting trace moisture in the electrolyte; and Step S6: data feedback and evaluation. This application can solve the problems of easy degradation of sensitive components in the electrolyte and quantitative deviation caused by solvent evaporation, achieving integrated and accurate analysis of organic and inorganic components. Combined with embedded closed-loop feedback logic, it significantly improves product consistency and data fidelity in the lithium battery electrolyte production process.

Description

Technical Field

[0001] This invention relates to the field of lithium battery electrolyte analysis technology, and in particular to an analytical method for lithium battery electrolyte. Background Technology

[0002] With the rapid development of new energy vehicles and large-scale energy storage industries, lithium batteries, as core power sources, have received widespread attention for their safety and energy density. As an important component of lithium-ion batteries, the composition, impurity content, and chemical stability of electrolytes directly determine the cycle life and electrochemical performance of batteries. To ensure the consistency of battery products, establishing a high-precision, full-component electrolyte analysis and evaluation system has become a key link in the fields of battery manufacturing and materials research and development.

[0003] Among them, the detection of organic solvents, lithium salts, additives, trace amounts of moisture, and hydrofluoric acid in electrolytes mainly relies on gas chromatography, mass spectrometry, and various titration techniques. This technical approach aims to monitor the quality changes of electrolytes during production, storage, and use by quantitatively identifying each component, thereby building a quality assurance capability for high-performance battery manufacturing.

[0004] Existing technologies for full-component analysis of electrolytes still have the problem that sensitive components in the electrolyte are easily affected by environmental factors during room temperature sampling and pretreatment, resulting in trace degradation or hydrolysis, which leads to a deviation between the component state of the sample and the original electrolyte.

[0005] Therefore, an analytical method for lithium battery electrolytes is proposed to solve the above problems. Summary of the Invention

[0006] The main objective of this invention is to provide an analytical method for lithium battery electrolytes to address the problems mentioned in the background.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is: an analytical method for lithium battery electrolyte, comprising the following steps:

[0008] Step S1: Collect lithium battery electrolyte samples under an inert atmosphere and pre-treat the samples to obtain the diluent to be tested;

[0009] S11: Place the collected electrolyte sample in a low-temperature environment and let it stand.

[0010] S12: Add anhydrous organic diluent to the settled sample, specifically acetonitrile, and the volume ratio of the anhydrous organic diluent to the sample is (5-10):1;

[0011] S13: Add internal standard solution; the internal standard is selected from any one of di-n-propyl carbonate, adiponitrile, and sulfolane.

[0012] Step S2: Inject the diluent to be tested into the analysis and detection system to obtain the characteristic response signals of each component in the lithium battery electrolyte;

[0013] S21: Use gas chromatography to separate organic solvent components, set the initial temperature of the chromatographic column to 40℃, and increase the temperature to 220℃ at a rate of 5-8℃ / min.

[0014] S22: Use a mass spectrometer detector to scan the separated components and obtain the mass-to-charge ratio and corresponding ion current intensity of each component;

[0015] Step S3: Based on a preset quantitative analysis model, calculate the content of the target component using the characteristic response signal; the quantitative analysis model incorporates a solvent degradation correction factor. The calculation formula is as follows:

[0016] ;

[0017] in, The mass fraction of the target component. The characteristic peak area of ​​the target component. For the mass of the internal standard, The characteristic peak area of ​​the internal standard. For sample quality, This is a relative correction factor. This is a solvent degradation correction factor;

[0018] The solvent degradation correction factor The calculation method is as follows:

[0019] ;

[0020] in, For the first The volatility coefficient of each solvent component, This represents the change in viscosity of the component during the analysis process. To analyze the absolute temperature of the environment, To analyze the real-time pressure within the system;

[0021] Step S4: Detect the hydrofluoric acid content in the electrolyte;

[0022] Step S5: Detect trace amounts of moisture in the electrolyte;

[0023] Step S6: Data feedback and evaluation.

[0024] Further, S11 specifically involves: placing the collected electrolyte sample in a low-temperature environment of -20℃ to -10℃ and letting it stand for 10 to 15 minutes; S13 specifically involves: adding an internal standard solution with a mass concentration of 0.5% to 1.2%, shaking to mix, and then passing it through a 0.22... An organic filter membrane was used to obtain the diluted solution to be tested.

[0025] Furthermore, obtaining the characteristic response signal in step S2 also includes the following steps:

[0026] S23: Simultaneously detect the intensity of metal cations in the sample using an inductively coupled plasma atomic emission spectrometer.

[0027] Furthermore, the sub-step of calculating the content of the target component in step S3 includes:

[0028] S31: Extract the area of ​​characteristic peaks and the peak area of ​​the internal standard The relative correction factor is determined based on the standard curve in S32. ;

[0029] S32: Establish a linear regression equation based on standard samples of known concentrations. The linear correlation coefficient of the linear regression equation is: ;

[0030] S33: Substitute the characteristic response signal into the quantitative analysis model to calculate the percentage content of each solvent component and additive.

[0031] Furthermore, step S4 specifically includes:

[0032] S41: Take 5 mL of the test solution and add neutral ethanol solvent for secondary dilution;

[0033] S42: Potentiometric titration was performed using bromothymol blue as an indicator and a 0.01 mol / L sodium hydroxide standard solution.

[0034] S43: Calculate the mass percentage of hydrofluoric acid based on the abrupt jump point at the titration endpoint.

[0035] Furthermore, step S5 specifically includes:

[0036] S51: The Karl Fischer coulometric analyzer is used, and the injection volume is set to 0.5 g to 1.0 g;

[0037] S52: The amount of electricity consumed is measured by the redox reaction between iodine generated by electrolysis and water in the sample;

[0038] S53: Calculate the water content in the sample based on the product of electrolysis current and time; the detection limit should not exceed 1. .

[0039] Furthermore, the chromatographic column is a capillary column with polyethylene glycol stationary phase, having a length of 30 m to 60 m, an inner diameter of 0.25 mm to 0.32 mm, and a film thickness of 0.25 mm. Up to 0.5 .

[0040] Furthermore, step S6 specifically includes:

[0041] S61: Compare the calculated component content with the preset standard component range;

[0042] S62: If the deviation exceeds ±2%, an abnormal alarm will be triggered and the electrolyte batch will be either replenished or discarded.

[0043] Furthermore, the inert atmosphere environment described in S1 is provided by a glove box filled with high-purity argon gas. The glove box integrates a gas circulation and purification unit, which reduces the content of active substances in the environment through deoxygenation and dehydration columns. The sampling container is a light-proof glass bottle with a sealing gasket. During the pretreatment process, the sample stays in a low-temperature cold trap for a preset time, thereby reducing the chemical activity of the thermosensitive lithium salt. The anhydrous organic diluent is selected from acetonitrile, and the volume ratio of the diluent to the sample is set within a preset range. The internal standard is weighed using a precision electronic balance and prepared into a standard solution of a specific concentration, which is then injected into the sample mixture using a pipette. The microporous filtration barrier is an organic filter membrane, installed in the filter housing at the front end of the syringe.

[0044] Furthermore, the gas phase separation path in S2 employs capillary column separation technology, and a pressure regulating valve and a flow compensator are provided in the carrier gas flow path; the mass spectrometry sensing array executes a full scan mode or a selected ion monitoring mode during the detection process, and the ion beam generated by the ionization source is screened by the mass-to-charge ratio by a mass analyzer; in the plasma excitation flow path, the sample is converted into an aerosol by a nebulizer and enters the high-temperature inductively coupled plasma torch region, where the radiation intensity at a specific wavelength is recorded by a photomultiplier tube; the separation of organic components and the spectral detection of inorganic ions are synchronously triggered on the time axis, and the timestamp is recorded by a unified data processing center.

[0045] Furthermore, S1 also includes a real-time environmental condition monitoring step: real-time acquisition of environmental dew point and oxygen content values ​​through a water and oxygen sensor integrated in the sampling environment, and using them as the basis for judging the effectiveness of preprocessing; if the environmental parameters deviate from the preset tolerance range, the batch of samples is marked as high-risk samples in the data processing terminal, and the compensation weight is increased or a retest instruction is executed in the subsequent correction factor calculation.

[0046] Furthermore, after S2, signal baseline optimization processing is also included: adaptive noise floor subtraction is performed on the acquired original feature response signal, a polynomial fitting algorithm is used to identify the signal baseline, high-frequency pulse random interference superimposed on defect echoes or impurity peaks is filtered out, and continuous and smooth target component response curves are retained.

[0047] Furthermore, the relative correction factor mentioned in S3 Calibration was performed using a series of standard reference solutions with varying concentration gradients, with the preparation path of the standard reference solutions consistent with the sample pretreatment path. A linear regression method was used to establish the correspondence between the response value and the concentration, requiring the goodness of fit of the regression equation to reach a preset high correlation standard. During the calculation process, the processor automatically retrieved the calibration curve database in the memory and matched the corresponding correction parameters according to the retention time of the target component.

[0048] An analysis system for lithium battery electrolyte includes a controlled sampling module, a multidimensional signal acquisition unit, an embedded algorithm processing platform, and a data visualization terminal;

[0049] The controlled sampling module includes a sampling robot and a low-temperature constant temperature bath set inside an inert gas protective cover. The end effector of the sampling robot grabs the sampling bottle and places it in the hole of the constant temperature bath, which is lined with a semiconductor cooling chip.

[0050] The multidimensional signal acquisition unit includes a gas chromatograph, a tandem mass spectrometer, and an inductively coupled plasma atomic emission spectrometer. The outlet of the gas chromatograph is physically connected to the sample inlet of the mass spectrometer through a heated transmission line to ensure that the gaseous components do not condense.

[0051] The embedded algorithm processing platform is equipped with a high-speed computing processor, whose internal logic circuit is divided into a signal receiving area, a model calculation area and a feedback control area, and runs the aforementioned degradation correction model and quantitative calculation program.

[0052] The data visualization terminal is connected to the processing platform via a communication bus, and the display screen shows component content trend charts, abnormal alarm indicator lights, and a structured analysis report export interface.

[0053] Furthermore, the sample introduction system in the multidimensional signal acquisition unit is equipped with an automatic rotary sampler, and the injection needle stroke is driven by a stepper motor; the gas chromatograph is equipped with a capillary column of a specific material, and the two ends of the column are respectively sealed and connected to the vaporization chamber and the splitter through graphite gaskets; the embedded algorithm processing platform has a built-in non-volatile memory chip for recording electrolyte reference formulation data and correction factor historical curves of different production batches.

[0054] Furthermore, when the embedded algorithm processing platform executes step S3, it calls the corresponding evaporation rate coefficient from the index table based on the real-time temperature and pressure signals fed back by the sensor, and calculates the viscosity change by combining the fluid dynamics equation, thereby dynamically generating the degradation correction factor for each analysis cycle. In the feedback control logic, if the content of the target component is lower than the preset threshold, the system sends a pulse signal to the external feeding actuator to control the feeding pump to perform precise volume supplementation of the component.

[0055] The present invention has the following beneficial effects:

[0056] 1. In this invention, by integrating low-temperature static equilibrium and high-ratio dilution under an inert atmosphere, a physicochemical stabilization barrier for sensitive components of the electrolyte is constructed. By reducing the frequency of contact between environmental heat energy and active molecules, the hydrolysis process of lithium salts such as lithium hexafluorophosphate in the sampling and pretreatment stages is significantly attenuated. Combined with the mechanical interception of impurities by the microporous filtration barrier, the risk of particulate matter clogging the sample inlet flow path and the scattering interference to the signal are eliminated, so that the component distribution of the test solution can be truly restored to the original state, significantly improving the data fidelity in the initial stage of analysis.

[0057] 2. In this invention, an integrated detection mode from organic to inorganic is established by physically coupling the gas phase separation path, the mass spectrometry sensing array, and the plasma excitation flow path, as well as by synchronous triggering of the time axis. Comprehensive information on solvent, additives, and metal impurity ions can be obtained in a single analysis cycle, solving the problems of fragmented detection processes and poor data correlation in traditional technologies. By utilizing carrier gas pressure compensation and ionization source energy control, signal interference under complex matrices is suppressed, significantly shortening the cycle of full component analysis and improving the detection throughput in laboratories and production lines.

[0058] 3. This invention abandons the traditional static linear quantitative model and introduces a solvent degradation correction factor that includes volatility coefficient, viscosity evolution variable, and environmental temperature and pressure parameters. A dynamic compensation calculation model was established. This model eliminates the quantitative deviation caused by environmental fluctuations by performing mathematical deconvolution on the concentration effect caused by trace solvent volatilization during the analysis process, which significantly enhances the reproducibility of the calculation results. Even under the harsh conditions of long-term and continuous monitoring, it can still maintain high-precision component quantification capability, solving the problem of falsely high content caused by solvent loss in the existing technology.

[0059] 4. In this invention, by integrating potentiometric titration and coulometric electrolysis technologies, highly sensitive and specific quantification of hydrofluoric acid and trace moisture in the electrolyte is performed. By utilizing a jump point identification algorithm and Faraday's law integration, precise monitoring of key failure indicators is achieved. The full-process analysis results are evaluated in a closed loop through an embedded platform. When the data deviates from the standard process range, an alarm is automatically triggered and the feeding mechanism is linked, realizing automated connection from analysis detection to process compensation. This significantly improves the product consistency and chemical stability in the lithium battery electrolyte production process and provides reliable data support for high-performance battery manufacturing. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating the overall steps of the analytical method of the present invention;

[0061] Figure 2 This is a flowchart illustrating the specific preprocessing of the sample in step S1 of the present invention.

[0062] Figure 3 This is a flowchart illustrating the specific process of obtaining the characteristic response signal in step S2 of the present invention.

[0063] Figure 4 This is a flowchart illustrating the specific process of calculating the target component content in step S3 of the present invention.

[0064] Figure 5 This is a schematic diagram of the specific process of step S4 of the present invention;

[0065] Figure 6 This is a schematic diagram of the specific process of step S5 of the present invention;

[0066] Figure 7 This is a schematic diagram of the specific process of step S6 of the present invention. Detailed Implementation

[0067] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0068] Please refer to Figures 1 to 7 As shown: An analytical method and system for lithium battery electrolyte, mainly used for high-precision qualitative and quantitative analysis of electrolyte components in the lithium battery production process.

[0069] The system consists of a controlled sampling module, a multi-dimensional signal acquisition unit, an embedded algorithm processing platform, and a data visualization terminal in terms of physical architecture. These components are connected by signal cables, material transfer pipelines, and communication buses to form an organic technical whole.

[0070] In terms of hardware construction, the core area of ​​the controlled sampling module is enclosed within an inert gas shield. This shield is made of high-purity acrylic or stainless steel with excellent sealing properties, and its internal space is filled with high-purity argon gas through a circulating purification system to maintain extremely low moisture and oxygen content. A water-oxygen sensor is installed in the middle of the inner wall of the inert gas shield. This sensor transmits real-time dew point data and oxygen concentration values ​​to an embedded algorithm processing platform via signal lines. A sampling robot is mounted on a base inside the shield. This robot uses a six-axis robotic arm structure, and its end effector is equipped with an adjustable mechanical gripper for grasping sampling bottles placed on a material rack. A cryogenic constant temperature bath is set within the operating radius of the sampling robot. The bath is lined with a semiconductor cooling chip and filled with heat-conducting oil or ethylene glycol as a cooling medium. Multiple holes matching the outer diameter of the sampling bottle are opened on the upper surface of the bath, allowing the sampling bottle to undergo a preset period of low-temperature static equilibrium before entering the analysis process, thereby reducing the chemical activity of heat-sensitive components in the electrolyte.

[0071] The multidimensional signal acquisition unit consists of a gas chromatograph, a tandem mass spectrometer, and an inductively coupled plasma atomic emission spectrometer (ICP-AES). The gas chromatograph's inlet is connected to an automated rotary sampler via a stainless steel capillary tube, and the sampler's needle stroke is driven by a high-precision stepper motor. Inside the gas chromatograph, a capillary column of specific polarity is installed in the column oven. The column inlet is connected to the vaporization chamber, and the outlet is physically connected to the ion source injection interface of the tandem mass spectrometer via a heated transfer line. This heated transfer line maintains the temperature of the gaseous components during transport, preventing condensation of high-boiling-point solvents. The tandem mass spectrometer contains an electron impact source or an electrospray source, followed by a mass analyzer. Simultaneously, the ICP-AES injection system is connected to the pretreatment flow path via a three-way switching valve. The sample diluent, driven by a peristaltic pump, enters the nebulizer, where it is converted into fine aerosol particles before entering the plasma torch zone generated by a high-frequency induction coil.

[0072] The system also integrates a dedicated unit for physicochemical index detection, including an automatic titration stage and a Karl Fischer electrolytic cell. An automatic burette is mounted above the titration stage, its piston monitored by a micro-displacement sensor. The burette opening is connected to a storage bottle containing standard alkali solution via a PTFE hose. The titration cup is placed on a rotor with magnetic stirring, and the composite electrode is immersed in the titrant to capture potential jumps in real time. The Karl Fischer electrolytic cell employs a double platinum needle electrode structure and is sealed with a ground glass stopper, filled with a dedicated coulometric electrolyte.

[0073] The embedded algorithm processing platform, serving as the nerve center of the entire system, has its internal logic circuits divided into a signal receiving area, a model calculation area, and a feedback control area. The signal receiving area acquires raw current or voltage signals from chromatographs, mass spectrometers, and spectrometers via a parallel interface. The model calculation area stores preset quantitative analysis models and degradation correction models. The feedback control area is connected to the feeding actuator via a communication cable. This feeding actuator includes a precision metering pump and a solenoid valve assembly installed on the electrolyte circulation pipeline.

[0074] Based on the above hardware structure, the specific execution steps of the lithium battery electrolyte analysis method described in this embodiment are as follows:

[0075] S1. Sample Collection and Pretreatment Co-stabilization Process: After receiving the start command, the sampling robot drives the end effector to grab the sampling bottle containing the original electrolyte from the conveyor belt and move it to the low-temperature constant temperature bath inside the inert gas protective cover. In the low-temperature constant temperature bath, the sample undergoes static equilibrium in an environment of -20℃ to 0℃. This process can effectively inhibit the hydrolysis reaction of lithium hexafluorophosphate with trace amounts of water to generate hydrofluoric acid. Subsequently, the sampling robot moves the sample bottle to the automatic liquid addition station, injects a preset volume of anhydrous acetonitrile as a dilution medium into the bottle, and adds a known mass of internal standard, such as o-dichlorobenzene. After ultrasonic vibration, the mixture is filtered through a 0.22-micron organic filter membrane installed at the front end of the syringe to remove any possible small particles, finally obtaining the diluent to be tested.

[0076] S2. Synchronous Acquisition and Separation of Multi-Component Signals: The diluent to be tested is divided into two paths. The first path enters the gas chromatograph. In the gas chromatograph, each organic solvent component, such as ethylene carbonate and dimethyl carbonate, is spatially separated on the time axis according to the difference in their partition coefficients in the stationary and mobile phases. The separated components are sequentially introduced into a tandem mass spectrometer, where electron bombardment generates molecular fragment ions with characteristic property-charge ratios, forming a total ion chromatogram. The second path of the diluent enters an inductively coupled plasma atomic emission spectrometer. Under the action of high-temperature plasma, metal elements such as lithium ions, sodium ions, and iron ions in the electrolyte are excited and emit characteristic spectra of specific wavelengths. The embedded algorithm processing platform ensures that the chromatographic retention time and the spectral acquisition time are aligned on the same time axis through synchronous trigger pulses.

[0077] S3. Component Quantification Process Based on Degradation Correction Model: The embedded algorithm processing platform first performs adaptive noise reduction on the acquired feature response signal, and then uses a polynomial fitting algorithm to identify the baseline and perform smoothing. Subsequently, the processor extracts the characteristic peak areas of the target component and the internal standard. At this point, the system calls the degradation correction model to compensate for the data. This model introduces a solvent degradation correction factor. The calculation formula is as follows:

[0078] ;

[0079] In actual operation, the processor obtains the ambient temperature from the water and oxygen sensor. Real-time pressure is obtained from the pressure sensor inside the chromatograph. ; Volatilization rate coefficient Retrieved from the index table of the built-in non-volatile memory chip; dynamic viscosity change characteristic value. Then, reverse calculation is performed by monitoring pump pressure fluctuations in the sample injection path; the result calculated using this formula... This value can compensate for the artificially high concentration caused by trace amounts of solvent evaporation; finally, using the formula:

[0080] ;

[0081] Calculate the precise mass fraction of each component. .

[0082] S4. Determination procedure for hydrofluoric acid content: Take a preset volume of the diluted solution to be tested and place it in the titration cup of the automatic titration stage, and add neutral ethanol solvent; the automatic burette, driven by a stepper motor, adds standard sodium hydroxide solution to the cup in a preset step volume; the composite electrode senses the solution potential in real time, and the embedded algorithm processing platform calculates the second derivative of the potential curve. When the second derivative reaches an extreme point, it is determined to be the titration endpoint; the processor calculates the hydrofluoric acid content in the electrolyte based on the volume of alkali solution consumed and the stoichiometric relationship.

[0083] S5. Trace Moisture Determination Procedure: The Karl Fischer coulometric method is used. The sample is injected into the Karl Fischer electrolytic cell through a sealed injection pad. Iodine is generated at the anode in the electrolytic cell. The iodine reacts quantitatively with the water in the sample and the sulfur dioxide, alkali, and solvent in the electrolyte. The completeness of the moisture reaction is detected by measuring the polarization voltage between the auxiliary electrodes. The embedded algorithm processing platform integrates the electrolytic current over time and converts the electrical quantity into the mass of water according to Faraday's law of electrolysis.

[0084] S6. Closed-Loop Feedback and Control Process: The data visualization terminal displays the calculated component content, hydrofluoric acid content, and moisture content on the screen in the form of a structured report. If the content of a key component, such as the additive fluoroethylene carbonate, is lower than the preset process lower limit, the feedback control area of ​​the embedded algorithm processing platform immediately generates a control pulse, driving the precision metering pump in the feeding actuator to start. Based on the missing mass difference, the metering pump extracts a precise volume of material from the additive storage tank and replenishes it to the main circulation tank of the production line. During the feeding process, the system continuously monitors the content changes until the component returns to the standard range, thus completing the closed-loop management from detection to automatic correction.

[0085] In specific application scenarios, such as on a continuous production line for high-performance power battery electrolytes, the system is installed at the bypass sampling point of the mixing tank. When the humidity of the production environment fluctuates, the water and oxygen sensor detects the rise in the environmental dew point and transmits the signal to the processor. When calculating the correction factor in step S3, the processor automatically increases the compensation weight for hydrolysis by-products. At the same time, the sampling robot, in its high-frequency sampling cycle, uses the rapid cooling function of the low-temperature constant temperature bath to ensure that each batch of samples is in the same thermodynamic initial state before analysis. The physical linkage between the gas chromatograph and the tandem mass spectrometer enables the system to identify the extremely low content of overcharge protection additives and their degradation products in the electrolyte. The inductively coupled plasma atomic emission spectrometer monitors the content of magnetic impurity ions in the electrolyte in real time. Once the concentration of iron, nickel, or other ions exceeds the preset threshold, the red abnormal alarm indicator on the data visualization terminal will flash immediately and lock the batch of products.

[0086] The system's physical connections not only ensure the airtightness of sample transmission but also guarantee the real-time performance of signal transmission. The vaporization chamber and splitter of the gas chromatograph are sealed with graphite gaskets, enabling it to withstand frequent pressure switching at high temperatures. The embedded algorithm processing platform interacts with various detection instruments via a high-speed bus, and its internal non-volatile memory chip records the baseline formulations for different production batches. When changing production models, the operator only needs to select the corresponding product code on the data visualization terminal, and the system will automatically load the appropriate relative correction factor. This embodiment effectively solves the analytical bias caused by environmental interference and solvent loss through a highly integrated hardware layout and dynamic correction algorithm, significantly improving the accuracy and stability of lithium battery electrolyte component analysis. It also incorporates a volatile rate coefficient database.

[0087] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principles of this invention are further supplemented below with a specific application scenario.

[0088] In the quality monitoring scenario of an electrolyte production workshop, when it is necessary to perform full-component accuracy verification on the finished electrolyte containing highly active lithium salts such as LiPF6 and thermosensitive additives such as lithium difluorophosphate, the specific operating principle is as follows:

[0089] Step 1: Sample Stabilization and Environmental Isolation Operation Principle: First, the environmental parameters inside the inert gas protective shield are monitored in real time by a water-oxygen sensor. When the dew point temperature exceeds the set threshold, the embedded algorithm processing platform drives the circulating purification device to accelerate the replacement of high-purity argon gas. The chemical inertness of the inert gas blocks the contact between water and lithium hexafluorophosphate in the electrolyte at the molecular level. At the same time, the sampling robot quickly embeds the grasped sampling bottle into the cooling hole of the low-temperature constant temperature bath according to the preset coordinate path. During this process, the low-temperature constant temperature bath forcibly locks the sample temperature at around -20℃ through the semiconductor cooling effect. The Arrhenius equation principle is used to reduce the rate constant of the hydrolysis reaction, thereby freezing the chemical composition state of the sample before entering the analysis process at the physical level, ensuring that the hydrofluoric acid content in the test solution will not be artificially increased due to environmental fluctuations during the sampling process.

[0090] Step 2: Principle of Synchronous Triggering and Transmission of Multidimensional Signal Chains: During the detection task, the sample is automatically diluted and sent to the multidimensional signal acquisition unit. The vaporization chamber of the gas chromatograph instantly vaporizes the liquid components, using carrier gas pressure to drive the components to migrate kinetically within the capillary column. Simultaneously, the ion source interface of the tandem mass spectrometer receives the effluent from the column via a constant-temperature transfer line, using high-energy electron bombardment to convert neutral molecules into charged ion fragments. During this period, the embedded algorithm processing platform sends synchronous sampling pulses to the inductively coupled plasma atomic emission spectrometer, ensuring that the inorganic analysis flow path driven by the peristaltic pump and the organic chromatographic flow path are aligned at the same time origin. This physical-level synchronous triggering mechanism allows organic solvent data and metal cation data from the same batch of samples to be correlated based on the same physical timestamp, eliminating the risk of data asynchrony caused by instrument startup delays.

[0091] Step 3: Dynamic Physical Property Compensation and Quantization Correction Principle: In the signal processing stage, the embedded algorithm processing platform retrieves the degradation correction model from step S3 for calculation; at this time, the processor reads the pressure sensor values ​​inside the gas chromatograph in real time via the bus. and the ambient temperature fed back by the water and oxygen sensor Because the carbonate solvents in the electrolyte are volatile, their vapor pressure varies with temperature. Increases with rising pressure Decrease and increase; the processor calculates Factors were used to quantitatively assess the concentration effect of solvent loss on solute concentration at the moment the sampling bottle was opened and during dilution; furthermore, dynamic viscosity change characteristic values ​​were obtained by monitoring pump pressure fluctuations in the injection system. This is used to correct minor deviations in sample volume caused by differences in electrolyte viscosity; this real-time compensation based on fluid dynamics and thermodynamic parameters ensures that the final output component mass fraction is accurate. It can eliminate physical environmental interference and restore the true concentration of electrolyte in closed production pipelines.

[0092] Step 4: Closed-Loop Feedback Execution and Process Control Principle: When the data visualization terminal displays analysis results deviating from the standard formula range, the feedback control loop of the embedded algorithm processing platform immediately enters the activation state. If a moisture content triggers an alarm, the processor outputs a control level to the feeding actuator through a logic gate circuit, driving the precision metering pump to open and inject a specific proportion of dehydrating agent into the mixing tank or execute a molecular sieve circulation filtration program. If the hydrofluoric acid content is too high, the system automatically calculates the required amount of deacidifying additive and drives the stepper motor to control the opening stroke of the feeding valve. This achieves a physical closed loop from controlled sampling and high-precision detection to automatic process feedback. Through the precise manipulation of the hardware actuator by the algorithm, the component consistency and chemical stability in the lithium battery electrolyte production process are significantly improved.

[0093] All contents not described in detail in the specification are existing technologies known to those skilled in the art, and the model parameters of each electrical appliance are not specifically limited; conventional equipment can be used. Electrical control components not mentioned in this technical solution are not shown in the figures because they are existing technologies, and will not be described here.

[0094] The foregoing has shown and described 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 embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing lithium battery electrolyte, characterized in that, Includes the following steps: Step S1: Collect lithium battery electrolyte samples under an inert atmosphere and pre-treat the samples to obtain the diluent to be tested; S11: Place the collected electrolyte sample in a low-temperature environment and let it stand. S12: Add anhydrous organic diluent to the settled sample. The anhydrous organic diluent is specifically anhydrous acetonitrile. The volume ratio of the anhydrous organic diluent to the sample is (5-10):

1. S13: Add internal standard solution; the internal standard is selected from any one of di-n-propyl carbonate, adiponitrile, and sulfolane. Step S2: Inject the diluent to be tested into the analysis and detection system to obtain the characteristic response signals of each component in the lithium battery electrolyte; S21: Use gas chromatography to separate organic solvent components, set the initial temperature of the chromatographic column to 40℃, and increase the temperature to 220℃ at a rate of 5-8℃ / min. S22: Use a mass spectrometer detector to scan the separated components and obtain the mass-to-charge ratio and corresponding ion current intensity of each component; Step S3: Based on a preset quantitative analysis model, calculate the content of the target component using the characteristic response signal; the quantitative analysis model incorporates a solvent degradation correction factor. The calculation formula is as follows: ； in, The mass fraction of the target component. The characteristic peak area of ​​the target component. For the mass of the internal standard, The characteristic peak area of ​​the internal standard. For sample quality, This is a relative correction factor. This is a solvent degradation correction factor; The solvent degradation correction factor The calculation method is as follows: ； in, For the first The volatility coefficient of each solvent component, This represents the change in viscosity of the component during the analysis process. To analyze the absolute temperature of the environment, To analyze the real-time pressure within the system; Step S4: Detect the hydrofluoric acid content in the electrolyte; Step S5: Detect trace amounts of moisture in the electrolyte; Step S6: Data feedback and evaluation.

2. The method according to claim 1, characterized in that, S11 specifically involves placing the collected electrolyte sample in a low-temperature environment of -20℃ to -10℃ for 10 to 15 minutes; S13 specifically involves adding an internal standard solution with a mass concentration of 0.5% to 1.2%, shaking to mix, and then passing the solution through a 0.22... An organic filter membrane was used to obtain the diluted solution to be tested.

3. The method according to claim 1, characterized in that, The step S2 of obtaining the characteristic response signal also includes the following steps: S23: Simultaneously detect the intensity of metal cations in the sample using an inductively coupled plasma atomic emission spectrometer.

4. The method according to claim 1, characterized in that, The sub-steps for calculating the content of the target component in step S3 include: S31: Extract the area of ​​characteristic peaks and the peak area of ​​the internal standard The relative correction factor is determined based on the standard curve in S32. ; S32: Establish a linear regression equation based on standard samples of known concentrations. The linear correlation coefficient of the linear regression equation is: ; S33: Substitute the characteristic response signal into the quantitative analysis model to calculate the percentage content of each solvent component and additive.

5. The method according to claim 1, characterized in that, Step S4 specifically includes: S41: Take 5 mL of the test solution and add neutral ethanol solvent for secondary dilution; S42: Potentiometric titration was performed using bromothymol blue as an indicator and a 0.01 mol / L sodium hydroxide standard solution. S43: Calculate the mass percentage of hydrofluoric acid based on the abrupt jump point at the titration endpoint.

6. The method according to claim 1, characterized in that, Step S5 specifically includes: S51: The Karl Fischer coulometric analyzer is used, and the injection volume is set to 0.5 g to 1.0 g; S52: The amount of electricity consumed is measured by the redox reaction between iodine generated by electrolysis and water in the sample; S53: Calculate the water content in the sample based on the product of electrolysis current and time; the detection limit should not exceed 1. .

7. The method according to claim 1, characterized in that, The chromatographic column is a capillary column with polyethylene glycol stationary phase, with a length of 30 m to 60 m, an inner diameter of 0.25 mm to 0.32 mm, and a film thickness of 0.25 mm. Up to 0.5 .

8. The method according to claim 1, characterized in that, Step S6 specifically includes: S61: Compare the calculated component content with the preset standard component range; S62: If the deviation exceeds ±2%, an abnormal alarm will be triggered and the electrolyte batch will be either replenished or discarded.

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