A cell processing method and system based on hierarchical screening

Abstract

The application discloses a kind of based on hierarchical screening battery processing method and system, belong to lithium ion battery manufacturing technical field.It includes: to the battery that completes injection and standing, synchronous exertion low-frequency pulse ultrasonic excitation and multi-frequency point alternating current micro-current excitation, by collecting ultrasonic response signal and alternating current impedance spectrum signal, respectively extract the characteristic parameters reflecting physical filling state and electrochemical interface formation state, and calculate the synergy index on time series.Based on synergy index, battery is divided into qualified product, can be reworked product and defective product and so on multiple grades, and the defect root type of can be reworked product is further analyzed, and corresponding directional rework strategy is matched and executed.After rework, battery is rechecked, and the manufacturing closed loop of detection-diagnosis-treatment-recheck is formed.The application upgrades traditional binary quality control to fine classification and intelligent rework, significantly improves yield, reduces scrap cost, and the accumulated process data can provide basis for front-end process optimization.

Description

Technical Field

[0001] This invention relates to a cell processing method and system based on graded screening, belonging to the field of lithium-ion battery manufacturing technology. Background Technology

[0002] Electrolyte wetting is a critical step in lithium-ion battery manufacturing. Its uniformity and adequacy directly determine the quality of the subsequent solid electrolyte interphase (SEI) film formation, thus affecting the battery's initial efficiency, cycle life, rate performance, and safety. Currently, the industry commonly uses a passive process of "electrolyte injection - long-term settling," which has the following prominent drawbacks: 1. Unknown process: The wetting process is a black box. Relying solely on a fixed settling time makes it impossible to determine whether the internal wetting is uniform, especially failing to detect risk points prone to localized dryness, such as the core center and tab roots. 2. Delayed and crude quality assessment: All quality defects are only exposed after formation, capacity testing, or even cycle testing. By this time, the entire manufacturing cost of the cell has already been added, leaving only two options: pass or scrap, resulting in poor economic efficiency. 3. Lack of corrective measures: Even if insufficient wetting is suspected in a batch of cells, there is a lack of reliable online testing data to support decisions such as extending the settling period or re-injecting electrolyte, and it is impossible to perform targeted repairs for different types of wetting defects. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a cell processing method and system based on graded screening.

[0004] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution.

[0005] In a first aspect, the present invention discloses a cell processing method based on graded screening, comprising:

[0006] S1: For the battery cells that have completed liquid injection and settling, low-frequency pulsed ultrasonic excitation and multi-frequency AC microcurrent excitation are applied simultaneously, and ultrasonic response signals and AC impedance spectrum signals are collected.

[0007] S2: Extract a first characteristic parameter characterizing the physical filling dynamics from the ultrasonic response signal, and extract a second characteristic parameter characterizing the electrochemical interface formation dynamics from the AC impedance spectroscopy signal;

[0008] S3: Calculate the coordination index of the first feature parameter and the second feature parameter in the time series. The coordination index is used to quantify the degree of matching and synchronization between the physical filling process and the interface formation process.

[0009] S4: Based on the coordination index and the preset threshold, the battery cells are divided into several grades, including qualified products, reworkable products, and defective products.

[0010] S5: For cells classified as reworkable, compare the deviation patterns of the first characteristic parameter and the second characteristic parameter of the reworkable cell to determine the root cause type of the wetting defect, and match and execute the corresponding targeted rework strategy according to the root cause type; after rework is completed, the cell is returned to step S1 for re-inspection.

[0011] The above technical solution, by accurately classifying the wetting quality before formation, upgrades the traditional binary judgment of qualified / scrap to refined control of qualified, reworkable, and defective, and opens up a rework channel, significantly improving the overall yield and reducing production costs.

[0012] Furthermore, the first characteristic parameter includes the time T_U for the ultrasonic propagation speed to reach a stable state; the second characteristic parameter includes the trend of the interface double layer capacitance Cdl(t) and charge transfer resistance Rct(t) as a function of time t, which are obtained by fitting the equivalent circuit from the AC impedance spectrum.

[0013] The above technical solution, by analyzing the synergy between ultrasonic signals (physical process) and impedance signals (electrochemical process), can not only determine whether wetting has occurred, but also diagnose why wetting was not done well, thus achieving precise localization of the root cause of the defect.

[0014] Further, calculating the co-exponent of the first feature parameter and the second feature parameter on the time series includes:

[0015] The Co-operation Index (CSI) is calculated based on the time T_U for the ultrasonic propagation velocity to reach stability and the values ​​of the interface double-layer capacitance Cdl(t) and charge transfer resistance Rct(t) at characteristic moments.

[0016] The above technical solution can quantify the degree of matching and synchronization between the physical filling process and the interface formation process through the calculated synergy index.

[0017] Furthermore, the formula for calculating the Coordination Index (CSI) is as follows:

[0018] CSI = α * (Cdl(t) / Cdl_target) / (T_U / T_U_target) + β * (Rct_target / Rct(t)) / (T_U / T_U_target);

[0019] In the formula, α and β are weighting coefficients, α + β = 1; Cdl_target, Rct_target and T_U_target are the target values ​​of interface double layer capacitance, charge transfer resistance and time to stabilize ultrasonic propagation speed obtained by statistical analysis of data from multiple qualified battery cells.

[0020] The above technical solution, by comparing the ratio of the completion degree of the electrochemical process to that of the physical process, can achieve a comprehensive evaluation of the synergistic level of the two processes.

[0021] Further, the deviation pattern between the first characteristic parameter and the second characteristic parameter of the reworkable cell is compared to determine the root cause type of the wetting defect, and a corresponding targeted rework strategy is matched and executed according to the root cause type, including:

[0022] If the time T_U for the ultrasonic propagation speed to reach stability is greater than the first multiple of the target value T_U_target for the time T_U for the ultrasonic propagation speed to reach stability, and the interface double layer capacitance Cdl(t) and charge transfer resistance Rct(t) are normal, it is determined that the electrolyte is insufficient in whole or in part, and it is identified as a deviation mode of physical filling lag. In order to implement a directional rework strategy of sending the cell to the stationary position and extending the first stationary time;

[0023] If the ultrasonic propagation speed reaches a stable time T_U and is normal, but the interfacial double layer capacitance Cdl(t) is less than the second multiple of the target value Cdl_target and / or the charge transfer resistance Rct(t) is greater than the third multiple of the target value Rct_target, it is determined that although the electrolyte has been filled, the interfacial contact is poor. This is identified as a deviation mode of poor interfacial contact, and a directional rework strategy of sending the cell to the electrolyte replenishment station to replenish a quantitative amount of electrolyte is implemented.

[0024] If the ultrasonic propagation velocity reaches a stable value T_U_target (a multiple of the first time T_U), and the interfacial double layer capacitance Cdl(t) is less than the second time T_target and / or the charge transfer resistance Rct(t) is greater than the third time Rct_target, it is determined that there is a local dry area or pore blockage, and it is identified as a local defect type. In this case, a targeted rework strategy is implemented: the cell is sent to the settling station, the second settling time is extended, and then it is sent to the electrolyte replenishment station to replenish the electrolyte and re-inspected. Cells that fail the re-inspection are scrapped. The second settling time is longer than the first settling time.

[0025] The above technical solution can automatically match and execute the optimal rework strategy based on the diagnostic results and realize the re-inspection closed loop, transforming intelligent judgment into direct process action, which greatly improves the autonomy and intelligence level of the manufacturing process.

[0026] Furthermore, the cell is divided into several grades based on the synergy index and a preset threshold, including:

[0027] If CSI ≥ a and the synergy index curve is smooth, it is classified as a qualified product;

[0028] If b≤CSI<a, it is classified as a reworkable item;

[0029] If CSI < b or the co-existence curve is severely distorted, it is classified as a defective product.

[0030] Wherein, CSI is the synergy index, a is the first preset threshold, b is the second preset threshold, and 0 < b < a ≤ 1.

[0031] The above technical solution compares the calculated CSI with a preset threshold to distinguish between good and poor synergy, thereby automatically classifying the cell grades.

[0032] Furthermore, it also includes: recording the occurrence rate of each deviation mode within a set time period, and sending an early warning when the proportion of any deviation mode exceeds the standard continuously to prompt checking the quality of the previous injection or electrolyte batch.

[0033] The above technical solution can accumulate data such as the proportion of each grade and the distribution of defect types, which can be fed back to the previous coating, rolling and liquid injection processes in real time, providing a direct basis for the continuous optimization of process parameters and improving the consistency of product quality from the source.

[0034] In a second aspect, the present invention also discloses a cell processing system for implementing the method described in the first aspect, comprising:

[0035] The multimodal testing station is used to simultaneously apply low-frequency pulsed ultrasonic excitation and multi-frequency AC micro-current excitation to the battery cell and acquire the response signal;

[0036] The intelligent decision-making unit, connected to the multimodal detection station, is used to process response signals, calculate the coordination index, classify cell grades, and generate rework decision instructions.

[0037] The material sorting mechanism, connected to the intelligent decision-making unit, is used to distribute battery cells of different grades to different flow directions;

[0038] The targeted rework module is connected to the intelligent decision-making unit and the material sorting mechanism, and is used to receive reworkable battery cells and execute the rework decision instructions.

[0039] The above technical solution forms a manufacturing closed loop of detection-diagnosis-treatment-re-inspection, which can automatically match and execute the optimal rework strategy based on the diagnostic results and realize the re-inspection closed loop, transforming intelligent judgment into direct process action, which greatly improves the autonomy and intelligence level of the manufacturing process.

[0040] Furthermore, the multimodal detection station integrates an ultrasonic transducer and an AC impedance measurement unit.

[0041] The above technical solution can achieve multi-angle measurement during the cell rotation process, ensuring signal representativeness.

[0042] Furthermore, the directional rework module includes a controllable settling station for controlling the temperature and time of the battery cell during settling and a precision electrolyte replenishment station for injecting a quantitative amount of electrolyte into the battery cell.

[0043] The above technical solution allows for programmable control of temperature and time at the controllable static station, while the precision electrolyte replenishment station can inject a fixed amount of electrolyte via a precision injection pump, thereby improving product quality consistency.

[0044] The beneficial effects achieved by this invention are as follows:

[0045] The method of this invention, by accurately classifying the wetting quality before formation, upgrades the traditional binary judgment of qualified / scrap to refined control of qualified, reworkable, and defective, and opens up a rework channel, significantly improving the overall yield and reducing production costs.

[0046] The system of this invention forms a manufacturing closed loop of detection-diagnosis-treatment-re-inspection. It can automatically match and execute the optimal rework strategy based on the diagnostic results and realize the re-inspection closed loop, transforming intelligent judgment into direct process action, which greatly improves the autonomy and intelligence level of the manufacturing process. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the overall architecture of the system described in an embodiment of the present invention;

[0048] Figure 2 This is a flowchart illustrating the method described in an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram illustrating the decision-making logic of hierarchical screening and targeted rework in an embodiment of the present invention;

[0050] Figure 4 This is a schematic diagram of the acoustic-electric characteristic parameter coupling curves of an ideal battery cell and battery cells with different types of defects.

[0051] In the diagram: 10 - Multimodal testing station; 20 - Intelligent decision-making unit; 30 - Material sorting mechanism; 40 - Directional rework module; 41 - Controllable static station; 42 - Precision liquid replenishment station. Detailed Implementation

[0052] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0053] Example 1

[0054] This embodiment introduces a cell processing method based on graded screening, including:

[0055] S1: For the battery cells that have completed liquid injection and settling, low-frequency pulsed ultrasonic excitation and multi-frequency AC microcurrent excitation are applied simultaneously, and ultrasonic response signals and AC impedance spectrum signals are collected.

[0056] S2: Extract a first characteristic parameter characterizing the physical filling dynamics from the ultrasonic response signal, and extract a second characteristic parameter characterizing the electrochemical interface formation dynamics from the AC impedance spectroscopy signal;

[0057] S3: Calculate the coordination index of the first feature parameter and the second feature parameter in the time series. The coordination index is used to quantify the degree of matching and synchronization between the physical filling process and the interface formation process.

[0058] S4: Based on the coordination index and the preset threshold, the battery cells are divided into several grades, including qualified products, reworkable products, and defective products.

[0059] S5: For cells classified as reworkable, compare the deviation patterns of the first characteristic parameter and the second characteristic parameter of the reworkable cell to determine the root cause type of the wetting defect, and match and execute the corresponding targeted rework strategy according to the root cause type; after rework is completed, the cell is returned to step S1 for re-inspection.

[0060] By accurately classifying the wetting quality before formation, the traditional binary judgment of qualified / scrap is upgraded to refined control of qualified, reworkable, and defective products, and a rework channel is opened, which significantly improves the overall yield and reduces production costs.

[0061] In this embodiment, the first characteristic parameter includes the time T_U for the ultrasonic propagation speed to reach a stable state; the second characteristic parameter includes the trend of the interfacial double-layer capacitance Cdl(t) and charge transfer resistance Rct(t) as a function of time t, which are obtained by fitting the equivalent circuit from the AC impedance spectrum. By analyzing the synergy between the ultrasonic signal (physical process) and the impedance signal (electrochemical process), it is possible not only to determine whether wetting has occurred, but also to diagnose why wetting was inadequate, thus achieving precise localization of the root cause of the defect.

[0062] In this embodiment, calculating the coordination index (CSI) of the first and second characteristic parameters over a time series includes: calculating the CSI based on the time T_U when the ultrasonic propagation velocity reaches stability and the values ​​of the interface double-layer capacitance Cdl(t) and charge transfer resistance Rct(t) at the characteristic time. The calculated CSI quantifies the degree of matching and synchronization between the physical filling process and the interface formation process.

[0063] In this embodiment, the formula for calculating the Collaborative Index (CSI) is as follows:

[0064] CSI = α * (Cdl(t) / Cdl_target) / (T_U / T_U_target) + β * (Rct_target / Rct(t)) / (T_U / T_U_target);

[0065] In the formula, α and β are weighting coefficients, α + β = 1; Cdl_target, Rct_target, and T_U_target are the target values ​​for the interfacial double-layer capacitance, charge transfer resistance, and the time to stabilize the ultrasonic propagation velocity, obtained through statistical analysis of data from multiple qualified battery cells. This formula, by comparing the ratio of the completion rate of the electrochemical process to the completion rate of the physical process, enables a comprehensive assessment of the synergistic level of the two processes.

[0066] In this embodiment, comparing the deviation patterns of the first and second characteristic parameters of the reworkable cell to determine the root cause type of the wetting defect, and matching and executing a corresponding targeted rework strategy based on the root cause type, includes:

[0067] If the time T_U for the ultrasonic propagation speed to reach stability is greater than the target value T_U_target for the time T_U for the first multiple of the ultrasonic propagation speed to reach stability, and the interface double layer capacitance Cdl(t) and charge transfer resistance Rct(t) are normal, it is judged that the electrolyte is insufficient in whole or in part, and it is determined to be a deviation mode of physical filling lag. In order to implement a directional rework strategy of sending the cell to the stationary position and extending the stationary time;

[0068] If the ultrasonic propagation speed reaches a stable time T_U and is normal, but the interfacial double layer capacitance Cdl(t) is less than the second multiple of the target value Cdl_target and / or the charge transfer resistance Rct(t) is greater than the third multiple of the target value Rct_target, it is determined that although the electrolyte has been filled, the interfacial contact is poor. This is identified as a deviation mode of poor interfacial contact, and a directional rework strategy of sending the cell to the electrolyte replenishment station to replenish a quantitative amount of electrolyte is implemented.

[0069] If the ultrasonic propagation velocity reaches a stable value T_U_target (a multiple of the first time T_U), and the interfacial double layer capacitance Cdl(t) is less than the second time T_target and / or the charge transfer resistance Rct(t) is greater than the third time Rct_target, it is determined that there is a local dry area or pore blockage, and it is identified as a local defect type. In this case, a targeted rework strategy is implemented: the cell is sent to the settling station, the second settling time is extended, and then it is sent to the electrolyte replenishment station to replenish the electrolyte and re-inspected. Cells that fail the re-inspection are scrapped. The second settling time is longer than the first settling time.

[0070] It can automatically match and execute the optimal rework strategy based on the diagnostic results and realize the re-inspection closed loop, transforming intelligent judgment into direct process action, which greatly improves the autonomy and intelligence level of the manufacturing process.

[0071] In this embodiment, the cell is classified into several grades based on the coordination index and a preset threshold, including: if CSI ≥ a and the coordination index curve is smooth, it is classified as a qualified product; if b ≤ CSI < a, it is classified as a reworkable product; if CSI < b or the coordination index curve is severely distorted, it is classified as a defective product; wherein, CSI is the coordination index, a is the first preset threshold, b is the second preset threshold, and 0 < b < a ≤ 1. By comparing the calculated CSI with the preset threshold, the distinction between good and poor coordination is achieved, thereby automatically classifying the cell grades.

[0072] This embodiment also includes: recording the occurrence rate of each deviation mode within a set time period; and sending an early warning when the proportion of any deviation mode continuously exceeds the standard to prompt inspection of the batch quality of the upstream liquid injection or electrolyte. It can accumulate data such as the proportion of each level and the distribution of defect types, and can provide real-time feedback to upstream processes such as coating, rolling, and liquid injection, providing direct basis for continuous optimization of process parameters and improving product quality consistency from the source.

[0073] Example 2

[0074] Based on the same inventive concept as Embodiment 1, this embodiment introduces a cell processing system, such as... Figure 1 As shown, it includes: a multimodal testing station 10, an intelligent decision-making unit 20, a material sorting mechanism 30, and a directional rework module 40. The multimodal testing station 10 is installed on the production line after the liquid injection and preliminary settling processes and before the formation process.

[0075] The multimodal testing station 10 includes a sealed cavity with a precision rotating fixture inside, capable of holding cylindrical or prismatic battery cells. The fixture integrates a 500kHz ultrasonic transducer and an impedance measurement probe, enabling multi-angle measurements during cell rotation to ensure signal representativeness.

[0076] The intelligent decision-making unit 20 is an industrial computer with built-in signal processing and machine learning algorithms.

[0077] The material sorting mechanism 30 includes a high-speed conveyor belt and a robotic arm, which can sort the battery cells to the formation line, rework line or scrap bin according to decision instructions.

[0078] The directional rework module 40 includes a controllable static station 41 and a precision electrolyte replenishment station 42. The controllable static station 41 is programmable and controls the temperature and time, while the precision electrolyte replenishment station 42 is equipped with a precision injection pump that can inject a fixed amount of electrolyte.

[0079] like Figure 2 and Figure 3 As shown, the system in this embodiment executes the following steps:

[0080] Step 1: Online detection.

[0081] The battery cell flows into the multimodal testing station 10, where the clamps are tightened and good contact is ensured. The system simultaneously initiates a 10-second ultrasonic pulse sequence and an impedance sweep measurement from 0.1 Hz to 5 kHz.

[0082] Step 2: Feature extraction.

[0083] The intelligent decision-making unit 20 processes the signal and extracts the ultrasonic propagation speed stabilization time T_U of the current cell, the charge transfer resistance at 120 seconds, and the estimated interface capacitance Cdl_120s at 120 seconds as the core feature parameters of this embodiment.

[0084] Step 3: Collaborative computing and hierarchical classification.

[0085] To quantify the synchronization between the physical filling process and the interface formation process, this embodiment defines the Comprehensive Synergy Index (CSI) as follows:

[0086] CSI = α * (Cdl_120s / Cdl_target) / (T_U / T_U_target) + β * (Rct_target / Rct_120s) / (T_U / T_U_target);

[0087] Where α and β are weighting coefficients, α + β = 1, and Cdl_target, Rct_target, and T_U_target are target values ​​obtained through statistical analysis of a large amount of high-quality battery cell data. This formula comprehensively evaluates the synergy between the two processes by comparing the ratio of the completion rate of the electrochemical process to the completion rate of the physical process: when both processes proceed synchronously at an ideal speed, both the numerator and denominator are close to 1, and the CSI value is also close to 1, indicating good synergy; if either process lags behind, the CSI value will deviate from 1, and the synergy will worsen.

[0088] If CSI ≥ 0.9 and the curve is smooth, it is classified as Grade A qualified product.

[0089] If 0.6 ≤ CSI < 0.9, it is classified as a B-grade reworkable product.

[0090] If CSI < 0.6 or the curve is severely distorted, it is classified as a defective product in grade D.

[0091] Step 4: Decision-making and execution of targeted rework.

[0092] Mode C1, or physical fill lag type: T_U is greater than 1.3 * T_U_target, while Cdl_120s and Rct_120s are relatively normal. This indicates insufficient electrolyte filling, either overall or locally. The instruction is to send the cell to the controllable settling station 41 and extend the settling time by 2-6 hours.

[0093] Mode C2, or poor interface contact type: T_U is normal, but Cdl_120s is less than 0.85 * Cdl_target and / or Rct_120s is greater than 1.15 * Rct_target. This indicates that although the electrolyte is filled, there is poor interface contact. The instruction is to send the cell to the precision electrolyte replenishment station 42 to replenish a fixed amount of electrolyte.

[0094] Mode C3, or local defect type, indicates that T_U is greater than 1.3 * T_U_target and Cdl_120s is less than 0.85 * Cdl_target or Rct_120s is greater than 1.15 * Rct_target, meaning both characteristic parameters are abnormal. This is determined to be due to the presence of local dry areas or pore blockage. The instruction is to sequentially extend the settling time of the cell by 4-8 hours at the controllable settling station 41, replenish the electrolyte at the precision electrolyte replenishment station 42, and then re-inspect. Cells that fail the re-inspection are scrapped.

[0095] Step 5: Closed-loop re-inspection and feedback.

[0096] All reworked battery cells are returned to the multi-modal testing station 10 for re-inspection. Those that pass the re-inspection are moved to grade B for further processing, while those that fail are downgraded to grade D and scrapped. At the same time, the system records the daily occurrence rate of each defect mode. When the proportion of a certain mode (such as C2) exceeds the standard continuously, an early warning is sent to the MES system, prompting an inspection of the upstream electrolyte filling or electrolyte batch quality.

[0097] This invention achieves fully automated closed-loop management from detection to action through rigorous logical judgment.

[0098] Example Results: After applying this system to a 21700 cylindrical battery production line, statistical data showed that the final scrap rate due to wetting issues decreased from 0.5% to 0.02%, with approximately 0.47% of the cells successfully reworked and meeting the qualification standards. Simultaneously, data feedback optimized the upstream rolling pressure, resulting in a 5% increase in the proportion of high-quality (Grade A) products.

[0099] Figure 4 In the graph, the horizontal axis represents time t (calculated from the start of detection), and the vertical axis represents the normalized feature parameter values ​​(0~1.0).

[0100] Figure 4 It includes eight curves, from curve one to curve eight, and their specific meanings include:

[0101] (a) Qualified products are ideal battery cells:

[0102] Curve 1: The first characteristic parameter curve of qualified products, U_ideal(t), shows that the ultrasonic propagation speed increases rapidly over time and then tends to stabilize.

[0103] Curve 2: The second characteristic parameter curve Z_ideal(t) of qualified products — the interface double layer capacitance increases rapidly over time and then tends to stabilize.

[0104] (ii) Physical filling lag type:

[0105] Curve 3: Physically filled lag type U(t) - rises slowly, T_U > 1.3×T_U_target, but eventually tends to stabilize.

[0106] Curve 4: Physically filled lag type Z(t) - the evolution is basically normal and close to the ideal curve.

[0107] (iii) Poor interface contact type:

[0108] Curve 5: U(t) with poor interface contact - evolution is basically normal.

[0109] Curve 6: Z(t) for poor interface contact type - slow rise, Cdl_120s < 0.85×Cdl_target or Rct_120s > 1.15×Rct_target.

[0110] (iv) Local defect type:

[0111] Curve 7: Local defect type U(t) - extremely slow rise, T_U deviates significantly from the target value, and the curve is distorted or fluctuates.

[0112] Curve 8: Z(t) with local defects - rises very slowly or without any upward trend, Cdl_120s and Rct_120s are both severely abnormal, and the curve shape is distorted.

[0113] By comparing the positional relationship and morphological differences of the two characteristic parameter curves of the four types of battery cells, the acoustic-electric synergistic characteristics of different wetting defect types are intuitively displayed, specifically:

[0114] Qualified product: The two curves basically overlap and rise synchronously, CSI ≥ 0.9;

[0115] Physical fill lag type: U(t) is shifted to the right relative to E(t) (physical process lag), CSI is low but still within the reworkable range;

[0116] Poor interface contact type: E(t) is shifted to the right relative to U(t) (lagging electrochemical process), CSI is low but still within the reworkable range;

[0117] Local defect type: U(t) and E(t) are both severely abnormal and asynchronous, the curves are distorted, CSI < 0.6, and it is judged as a defective product.

[0118] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0120] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0122] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A cell processing method based on graded screening, characterized in that, include: S1: For the battery cells that have completed liquid injection and settling, low-frequency pulsed ultrasonic excitation and multi-frequency AC microcurrent excitation are applied simultaneously, and ultrasonic response signals and AC impedance spectrum signals are collected. S2: Extract a first characteristic parameter characterizing the physical filling dynamics from the ultrasonic response signal, and extract a second characteristic parameter characterizing the electrochemical interface formation dynamics from the AC impedance spectroscopy signal; S3: Calculate the coordination index of the first feature parameter and the second feature parameter in the time series. The coordination index is used to quantify the degree of matching and synchronization between the physical filling process and the interface formation process. S4: Based on the coordination index and the preset threshold, the battery cells are divided into several grades, including qualified products, reworkable products, and defective products. S5: For cells classified as reworkable, compare the deviation patterns of the first characteristic parameter and the second characteristic parameter of the reworkable cell to determine the root cause type of the wetting defect, and match and execute the corresponding targeted rework strategy according to the root cause type; after rework is completed, the cell is returned to step S1 for re-inspection.

2. The cell processing method based on graded screening according to claim 1, characterized in that, The first characteristic parameter includes the time T_U for the ultrasonic propagation speed to reach a stable state; the second characteristic parameter includes the trend of the interface double layer capacitance Cdl(t) and charge transfer resistance Rct(t) as a function of time t, which are obtained by fitting the equivalent circuit from the AC impedance spectrum.

3. The cell processing method based on graded screening according to claim 2, characterized in that, The calculation of the coordination index between the first feature parameter and the second feature parameter on the time series includes: The Co-operation Index (CSI) is calculated based on the time T_U for the ultrasonic propagation velocity to reach stability and the values ​​of the interface double-layer capacitance Cdl(t) and charge transfer resistance Rct(t) at characteristic moments.

4. The cell processing method based on graded screening according to claim 3, characterized in that, The formula for calculating the Coordination Index (CSI) is as follows: CSI = α * (Cdl(t) / Cdl_target) / (T_U / T_U_target) + β * (Rct_target / Rct(t)) / (T_U / T_U_target); In the formula, α and β are weighting coefficients, α + β = 1; Cdl_target, Rct_target and T_U_target are the target values ​​of interface double layer capacitance, charge transfer resistance and time to stabilize ultrasonic propagation speed obtained by statistical analysis of data from multiple qualified battery cells.

5. The cell processing method based on graded screening according to claim 2, characterized in that, The deviation pattern between the first and second characteristic parameters of the reworkable battery cell is compared to determine the root cause type of the wetting defect, and a corresponding targeted rework strategy is matched and executed according to the root cause type, including: If the time T_U for the ultrasonic propagation speed to reach stability is greater than the first multiple of the target value T_U_target for the time T_U for the ultrasonic propagation speed to reach stability, and the interface double layer capacitance Cdl(t) and charge transfer resistance Rct(t) are normal, it is determined that the electrolyte is insufficient in whole or in part, and it is identified as a deviation mode of physical filling lag. In order to implement a directional rework strategy of sending the cell to the stationary position and extending the first stationary time; If the ultrasonic propagation speed reaches a stable time T_U and is normal, but the interfacial double layer capacitance Cdl(t) is less than the second multiple of the target value Cdl_target and / or the charge transfer resistance Rct(t) is greater than the third multiple of the target value Rct_target, it is determined that although the electrolyte has been filled, the interfacial contact is poor. This is identified as a deviation mode of poor interfacial contact, and a directional rework strategy of sending the cell to the electrolyte replenishment station to replenish a quantitative amount of electrolyte is implemented. If the ultrasonic propagation velocity reaches a stable value T_U_target (a multiple of the first time T_U), and the interfacial double layer capacitance Cdl(t) is less than the second time T_target and / or the charge transfer resistance Rct(t) is greater than the third time Rct_target, it is determined that there is a local dry area or pore blockage, and it is identified as a local defect type. In this case, a targeted rework strategy is implemented: the cell is sent to the settling station, the second settling time is extended, and then it is sent to the electrolyte replenishment station to replenish the electrolyte and re-inspected. Cells that fail the re-inspection are scrapped. The second settling time is longer than the first settling time.

6. The cell processing method based on graded screening according to claim 1, characterized in that, The battery cells are divided into several grades based on the synergy index and a preset threshold, including: If CSI ≥ a and the synergy index curve is smooth, it is classified as a qualified product; If b≤CSI<a, it is classified as a reworkable item; If CSI < b or the co-existence curve is severely distorted, it is classified as a defective product. Wherein, CSI is the synergy index, a is the first preset threshold, b is the second preset threshold, and 0 < b < a ≤ 1.

7. The cell processing method based on graded screening according to claim 1, characterized in that, Also includes: Record the occurrence rate of each deviation pattern within a set time period. When the proportion of any deviation pattern exceeds the standard continuously, send an alert to prompt you to check the quality of the previous injection or electrolyte batch.

8. A cell processing system for implementing the method according to any one of claims 1-7, characterized in that, include: The multimodal testing station is used to simultaneously apply low-frequency pulsed ultrasonic excitation and multi-frequency AC micro-current excitation to the battery cell and acquire the response signal; The intelligent decision-making unit, connected to the multimodal detection station, is used to process response signals, calculate the coordination index, classify cell grades, and generate rework decision instructions. The material sorting mechanism, connected to the intelligent decision-making unit, is used to distribute battery cells of different grades to different flow directions; The targeted rework module is connected to the intelligent decision-making unit and the material sorting mechanism, and is used to receive reworkable battery cells and execute the rework decision instructions.

9. The cell processing system according to claim 8, characterized in that, The multimodal testing station integrates an ultrasonic transducer and an AC impedance measurement unit.

10. The cell processing system according to claim 8, characterized in that, The directional rework module includes a controllable settling station for controlling the temperature and time of the battery cell during settling and a precision electrolyte replenishment station for injecting a quantitative amount of electrolyte into the battery cell.

Images