An automated temperature and pressure distribution testing system and method for battery formation cabinets

Abstract

The application discloses an automatic temperature and pressure distribution test system and method for a battery formation cabinet, which comprises a mobile trolley, a suspension control mechanism, a suspension mechanism, a data acquisition mechanism and a mobile terminal. The suspension control mechanism is installed on the mobile trolley and drives the suspension mechanism to adjust the position through four supporting pillars and a lifting mechanism; the suspension mechanism drives the data acquisition mechanism containing a flexible temperature and pressure integrated sensor to the test station in the battery formation cabinet through a pulley motion electric cylinder. The application synchronously collects temperature and pressure data through an automatic system, not only evaluates the distribution uniformity, but also judges the relationship between pressure and temperature abnormalities through correlation analysis, so as to accurately diagnose the root cause of the fault. The system solves the problems of low efficiency, poor precision and inability to correlate and analyze temperature and pressure data in the traditional detection method, and significantly improves the quality control level of battery production.

Description

Technical Field

[0001] This application relates to the field of battery pressure testing, specifically to an automated temperature and pressure distribution testing system and method for battery formation cabinets. Background Technology

[0002] In the production of rechargeable batteries, formation is a crucial process. With the continuous development of the battery industry, the requirements for battery product quality are becoming increasingly stringent. The fixtures in the battery formation cabinet need to apply uniform mechanical pressure to the battery cells to ensure that the electrodes and separators inside the cells can fit tightly and evenly. This is an important prerequisite for ensuring the consistency of the formation reaction and is crucial for guaranteeing battery product quality. Uneven pressure distribution can lead to serious quality problems such as capacity decay, increased internal resistance, and localized bulging. Therefore, accurate detection, verification, and monitoring of the pressure distribution applied by the battery formation cabinet fixtures during production are particularly critical. This is of great significance for improving battery production efficiency and quality and promoting the development of the battery industry.

[0003] In existing technologies, pressure-sensitive paper technology is commonly used to detect the pressure distribution applied by the battery formation cabinet fixture. The specific operation involves placing the pressure-sensitive paper between the fixture and the battery cell. After pressure is applied, the pressure-sensitive paper qualitatively reflects the pressure magnitude and distribution through a color reaction. This method can help workers understand the pressure distribution to some extent and was widely used in early battery production testing. By observing the color development of the pressure-sensitive paper, workers can make a rough judgment on the pressure distribution, providing a certain basis for quality control during the battery production process.

[0004] However, this traditional pressure-sensitive paper technology has many drawbacks. First, pressure-sensitive paper is a disposable consumable, and for large-scale production lines, the long-term cost of consumables is very high. The process of manually placing, removing, photographing, and interpreting the pressure-sensitive paper is cumbersome and time-consuming, usually requiring a long time to complete a single test, which cannot meet the needs of fast-paced production. Second, the color development results of pressure-sensitive paper are greatly affected by ambient temperature and humidity, and the interpretation of results heavily relies on human experience, resulting in strong subjectivity and poor test accuracy and reliability. Furthermore, pressure-sensitive paper can only record the peak pressure during the pressure application process and cannot monitor the dynamic changes in pressure after it stabilizes in real time. At the same time, test results are mostly manually archived in the form of photos, making it difficult to conduct systematic data management and quality traceability. Moreover, this solution is purely offline manual operation and cannot be integrated with the factory's manufacturing execution system or other information systems, forming data silos, which is not conducive to modern intelligent manufacturing management. In addition, traditional formation cabinets can only heat the pressing plates during the hot pressing process. Each pressing plate has a single rigid temperature sensor built in, and it is impossible to monitor whether different areas of the pressing plate are heated evenly or whether abnormal regional temperatures affect the pressure distribution.

[0005] In addition, the existing technology has the following shortcomings: First, the detection process is a static single measurement, which cannot capture the dynamic characteristics of the temperature and pressure parameters evolving over time during the entire formation process, resulting in the inability to provide timely warnings of gradual pressure failure caused by the thermal expansion or mechanical creep of the fixture; Second, the existing sensor solutions lack the ability to adapt to different models of battery cells and fixtures, and it is often necessary to reconfigure or replace the hardware when changing product models; Third, there is a lack of effective integration between the detection data and the factory manufacturing execution system (MES), which makes it impossible to achieve automated production linkage control based on the detection results. Summary of the Invention

[0006] To address the technical problems in the prior art, this application provides an automated temperature and pressure distribution testing system and method for battery assembly cabinets.

[0007] This application provides an automated temperature and pressure distribution testing system for battery formation cabinets, comprising:

[0008] Mobile cart;

[0009] A suspension control mechanism, mounted on the mobile trolley, includes a suspension lifting mechanism, a suspension horizontal movement mechanism, and a suspension opening and closing adjustment mechanism, used to drive the suspension mechanism to perform multi-dimensional position adjustments; the suspension lifting mechanism includes four support pillars vertically mounted on the mobile trolley, a suspension lifting adjustment motor, a lifting screw, a nut, and a lifting platform, the nut being threaded onto the lifting screw and fixed to the lifting platform, and the lifting platform being slidably mounted on the support pillars;

[0010] The suspension mechanism, which is connected to the suspension control mechanism, includes two suspension struts, a pulley movement cylinder and a suspension pulley, and is configured to support the data acquisition mechanism and extend into the test station inside the battery formation cabinet;

[0011] The data acquisition mechanism includes several data acquisition units installed on the suspension mechanism. Each data acquisition unit is connected to a temperature and pressure sensing array. The temperature and pressure sensing array is a flexible integrated temperature and pressure sensor with a thickness of less than 0.3 mm, used to synchronously acquire temperature and pressure data between the battery formation cabinet fixture and the battery cell.

[0012] A manual control terminal, connected to the suspension control mechanism, is used to control the movement of the suspension mechanism and the displacement of the data acquisition device;

[0013] The mobile terminal is used to receive, analyze, and save the data collected by the data acquisition agency, and generate a visual report on temperature and pressure distribution.

[0014] Furthermore, the mobile terminal is also equipped with a multi-station data fusion module, which is used to register and align the temperature and pressure distribution data collected in the near and far areas of the same battery formation cabinet according to the station number and spatial coordinates, and synthesize them into an integrated temperature and pressure distribution detection report covering the complete number of channels; the mobile terminal can also perform horizontal comparison of temperature and pressure parameters between different stations, and automatically mark abnormal stations and their location coordinates where the deviation exceeds a preset threshold.

[0015] Furthermore, the data acquisition mechanism also includes an array reconfiguration controller, which is communicatively connected to the mobile terminal. The mobile terminal has a pre-stored database of geometric parameters for various types of battery formation cabinet fixtures. Before the test begins, the mobile terminal retrieves the corresponding fixture size and cell layout parameters from the geometric parameter database based on the model information of the battery formation cabinet under test, and sends a sensor activation command to the array reconfiguration controller accordingly. Based on the activation command, the array reconfiguration controller selectively activates a subset of sensor nodes corresponding to the current cell coverage area in the temperature and pressure sensor array, and blocks invalid nodes located in the area obstructed by the fixture structure, thereby achieving adaptive matching detection of different types of cells and fixtures.

[0016] Furthermore, the mobile terminal is also equipped with a data cloud and manufacturing execution system (MES) integration interface, which is used to automatically upload the temperature and pressure distribution test report generated after each test, along with relevant information, to the cloud quality management server, and realize the closed-loop linkage between test data and production control system.

[0017] This application also provides an automated temperature and pressure distribution testing method for battery formation cabinets, applicable to the above-mentioned system, and includes the following steps:

[0018] The suspension mechanism, which includes the data acquisition mechanism, is moved to the target area of ​​the battery formation cabinet by a mobile trolley, and the suspension support is deployed to the test station in the battery formation cabinet by the suspension control mechanism, so that the temperature and pressure sensing array is located between the formation fixture and the cell in the battery formation cabinet.

[0019] The battery formation cabinet inputs the total pressure and formation temperature, the clamps clamp the battery cells, and the temperature and pressure data between the clamps and the battery cells are obtained through the temperature and pressure sensor array.

[0020] The temperature and pressure data of the temperature and pressure sensor array are collected synchronously by the data acquisition device.

[0021] The temperature and pressure data are analyzed and saved using a mobile terminal to evaluate the uniformity of temperature and pressure applied to the battery cells by the battery formation cabinet, and to generate a visual test report on temperature and pressure distribution.

[0022] Furthermore, the testing method also includes a dynamic time-series temperature-pressure coupling analysis step, which includes: continuously triggering the data acquisition device to perform multiple rounds of synchronous temperature and pressure acquisition at preset time intervals at different time nodes in the formation process to form a time-stamped temperature-pressure time-series dataset; calculating the temperature change rate and pressure change rate of each measuring point between adjacent time nodes; when the cross-correlation coefficient between the temperature change rate and pressure change rate of a certain spatial region exceeds a preset coupling threshold, determining that there is a dynamic temperature-pressure coupling anomaly in that region, and recording the first occurrence time and duration of the coupling anomaly for use in optimizing formation process parameters and predictive maintenance of equipment.

[0023] Furthermore, the testing method also includes a fixture mechanical deformation auxiliary diagnosis step, which includes: extracting the pressure gradient distribution on the four edge lines of the battery cell from the pressure distribution data of the temperature and pressure sensing array; fitting and comparing the edge pressure gradient with a preset ideal uniform pressure baseline to calculate the deformation deviation at each edge; when the deformation deviation at a certain edge exceeds a preset mechanical tolerance threshold, and the deviation shows a monotonically increasing or decreasing gradient trend, it is determined that the flatness of the fixture in the corresponding direction is abnormal, and a fixture deformation diagnosis report including the deformation direction, estimated deviation amplitude, and suggested repair parts is output.

[0024] Furthermore, the testing method also includes a pressure decay prediction step for the formation process. This pressure decay prediction step includes: extracting the time sequence data of pressure changes at each measuring point based on the temperature and pressure time series dataset; fitting the pressure time series data using a preset pressure decay prediction model to calculate the pressure decay rate at each measuring point and the remaining time to predict the lower pressure limit; and issuing a warning to the operator when the predicted remaining time for a certain area is lower than the remaining time of the current formation process, indicating that the pressure in that area may fail before the formation is completed, and suggesting that the pressure compensation mechanism be checked or its parameters adjusted.

[0025] In summary, this application includes at least one of the following beneficial technical effects:

[0026] 1. This application adopts an automated architecture with four-column support and pulley electric cylinder drive, which realizes high-precision positioning and automatic forward and backward movement of the temperature and pressure sensor array, and solves the problems of low efficiency, poor accuracy and lack of data traceability of traditional manual sticker detection;

[0027] 2. A flexible integrated temperature and pressure sensor was adopted, and a temperature-pressure correlation analysis method was proposed. The system not only independently detects temperature and pressure, but also intelligently diagnoses whether the root cause of a fault is a mechanical fixture problem or an electrical temperature control problem by analyzing the correlation between the two, thus improving the targeting and efficiency of formation cabinet maintenance;

[0028] 3. A dynamic time-series temperature-pressure coupling analysis method is proposed, which can capture the dynamic evolution characteristics of temperature and pressure parameters throughout the entire process of transformation, realizing the leap from static single measurement to online monitoring of the entire process, and supporting early warning of progressive pressure failure;

[0029] 4. A pressure gradient-based auxiliary diagnostic method for clamp mechanical deformation is proposed, which can automatically identify the direction and magnitude of clamp flatness abnormalities, providing accurate quantitative basis for equipment maintenance;

[0030] 5. An adaptive sensor array reconfiguration mechanism was proposed, which enables the same set of hardware devices to be adapted to different models of battery cells and fixtures by defining the activation range of sensor nodes in software, thus significantly reducing the threshold for use and maintenance costs of the equipment.

[0031] 6. It has achieved deep integration between the inspection system and the manufacturing execution system (MES), and completed the transformation of inspection data from isolated information to a closed loop of production control, supporting the construction of a modern intelligent manufacturing management system. Attached Figure Description

[0032] Figure 1 This is a usage status reference diagram of an automated temperature and pressure distribution testing system for a battery formation cabinet provided in an embodiment of this application;

[0033] Figure 2 yes Figure 1 A three-dimensional structural diagram of an automated temperature and pressure distribution testing system used in battery formation cabinets;

[0034] Figure 3 This is a schematic diagram of the front view structure of the mobile vehicle in one embodiment of this application;

[0035] Figure 4 This is a rear view schematic diagram of the mobile vehicle in one embodiment of this application;

[0036] Figure 5 This is a partial structural schematic diagram of the suspension control mechanism and the suspension mechanism in one embodiment of this application;

[0037] Figure 6 This is a schematic diagram of the planar structure of a flexible temperature and pressure integrated sensor in one embodiment of this application;

[0038] Figure 7 This is a flowchart illustrating an automated temperature and pressure distribution testing method for a battery formation cabinet provided in one embodiment of this application.

[0039] Figure 8 This is a flowchart illustrating a dynamic time-series temperature-pressure coupling analysis method in one embodiment of this application;

[0040] Figure 9This is a schematic diagram of a fixture mechanical deformation auxiliary diagnosis method in one embodiment of this application;

[0041] Figure 10 This is a schematic diagram of an adaptive sensor array reconstruction mechanism in one embodiment of this application;

[0042] Explanation of reference numerals in the attached diagram: 1. Mobile trolley; 11. Push handle; 12. Self-locking caster wheel; 13. Power supply and display module; 14. Electrical control and communication module; 15. Balance weight module; 16. Ventilation and heat dissipation module; 17. Charging module; 18. Openable cabinet door; 2. Suspension control mechanism; 21. Suspension lifting mechanism; 211. Support column; 212. Suspension lifting adjustment motor; 213. Lifting screw; 214. Nut; 215. Lifting platform; 22. Suspension horizontal movement mechanism; 23. Suspension opening and closing distance adjustment mechanism; 3. Suspension mechanism; 31. Suspension support rod; 32. Pulley movement cylinder; 33. Suspension pulley; 4. Data acquisition mechanism; 41. Data acquisition device; 42. Temperature and pressure sensor array; 5. Manual control terminal; 6. Mobile terminal; 7. Battery formation cabinet; 71. Fixture. Detailed Implementation

[0043] The technical solutions in the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. The described embodiments are only possible technical implementations of the present invention, but are not limited thereto. Other embodiments obtained by those skilled in the art in conjunction with the embodiments of the present invention without creative effort are also within the protection scope of the present invention.

[0044] Please refer to Figures 1 to 7 This application mainly uses an automated system and method to detect the temperature and pressure distribution of the battery formation cabinet, achieving high precision, high efficiency, traceability, and the ability to monitor pressure changes. The following is a further detailed description of this application.

[0045] Example 1

[0046] This application provides an automated temperature and pressure distribution testing system for a battery formation cabinet. Its main structure includes a mobile trolley 1, a suspension control mechanism 2, a suspension mechanism 3, a data acquisition mechanism 4, a manual control terminal 5, and a mobile terminal 6. The mobile trolley 1, serving as the mobile foundation of the entire system, adopts a box-like structure design. Its bottom is equipped with self-locking casters 12 for flexible movement and parking positioning. A push handle 11 is provided on the outside of the box for easy manual pushing. An openable cabinet door 18 and a ventilation and heat dissipation module 16 are provided on the side of the box to ensure the heat dissipation needs of the internal equipment. A power supply and display module 13 is integrated inside or on the surface of the mobile trolley 1 for providing power support and status display; an electrical control and communication module 14 for system logic control and data transmission; a balance counterweight module 15 for balancing the center of gravity when the suspension mechanism 3 is extended to prevent tipping; and a charging module 17 for supporting external power supply charging.

[0047] The suspension control mechanism 2 is mounted on the mobile trolley 1 and is used to drive the suspension mechanism 3 to perform multi-dimensional position adjustments. To ensure the smoothness and accuracy of lifting, the suspension lifting mechanism 21 in the suspension control mechanism 2 adopts a four-column structure, specifically including four vertically arranged support columns 211 on the mobile trolley 1, a suspension lifting adjustment motor 212, a lifting screw 213, a nut 214, and a lifting platform 215. The suspension lifting adjustment motor 212 is connected to and drives the lifting screw 213 to rotate. The nut 214 is threaded onto the lifting screw 213 and fixed to the lifting platform 215, thereby driving the lifting platform 215 to slide smoothly along the four support columns 211, realizing the height adjustment of the suspension mechanism 3. In addition, the suspension control mechanism 2 also includes a suspension horizontal movement mechanism 22 and a suspension opening and closing adjustment mechanism 23. The suspension horizontal movement mechanism 22 is used to drive the suspension mechanism 3 to move left and right in the horizontal direction as a whole, so as to align with different storage positions; the suspension opening and closing adjustment mechanism 23 is used to drive the two suspension rods 31 in the suspension mechanism 3 to move relative to each other, so as to adjust the opening and closing distance between the two suspension rods 31 to adapt to the spacing of battery formation cabinet clamps 71 of different widths.

[0048] The suspension mechanism 3 is connected to the suspension control mechanism 2 and is configured to support the data acquisition mechanism and extend into the test station inside the battery formation cabinet. The suspension mechanism 3 mainly includes two suspension rods 31, a pulley movement cylinder 32, and suspension pulleys 33. The data acquisition mechanism 4 is slidably mounted on the left and right suspension rods 31 via the suspension pulleys 33. The pulley movement cylinder 32 drives each suspension pulley 33 to move, thereby enabling the data acquisition mechanism 4 to move forward and backward on the suspension rods 31, ensuring that the sensor can automatically extend into the cabinet. The manual control terminal 5 is connected to the suspension control mechanism 2 and serves as a human-machine interface for controlling the movement of the suspension mechanism 3 and the displacement of the data acquisition device 41.

[0049] In terms of sensing and acquisition, the data acquisition mechanism 4 includes several data acquisition units 41 mounted on the suspension mechanism 3. These data acquisition units 41 are connected to a temperature and pressure sensor array 42. The temperature and pressure sensor array 42 used in this system is a thin-film flexible integrated temperature and pressure sensor with a thickness controlled within 0.3mm. Its size can be customized according to requirements to ensure that the insertion gap does not affect the normal operating conditions. The data acquisition units 41 have high-performance acquisition capabilities, with a sampling frequency of not less than 100Hz, a temperature channel number of not less than 64 channels, and a pressure array specification of not less than 256 rows and 256 columns, with a total of 65,536 points, thereby ensuring the accuracy and real-time performance of the data.

[0050] Based on the above system, this application also provides an automated temperature and pressure distribution testing method for a battery formation cabinet. The testing process begins by moving the suspension mechanism 3, which includes the data acquisition mechanism 4, to the target area of ​​the battery formation cabinet using a mobile trolley 1. Next, the temperature and pressure sensor array 42 is aligned with the test station by adjusting the lifting, horizontal movement, and opening / closing of the suspension control mechanism 2. Subsequently, the temperature and pressure sensor array 42 is precisely deployed to the test station within the battery formation cabinet using a pulley-driven electric cylinder 32, positioning it between the clamp 71 and the battery cell. Once the sensor is in place, the battery formation cabinet inputs the set total pressure and formation temperature, and the clamp 71 clamps the battery cell. At this point, the temperature and pressure sensor array 42 begins to sense the temperature and pressure data between the clamp 71 and the battery cell, and collects this data synchronously through the data acquisition device 41.

[0051] To obtain more comprehensive data, the testing method also includes repeatedly performing the aforementioned mobile deployment and data acquisition steps to obtain temperature and pressure distribution data for both the near and far ends of the battery formation cabinet. In subsequent analysis and processing steps, the system will synthesize the multiple collected temperature and pressure data into a complete 64-channel temperature and pressure distribution test report for the formation cabinet. After acquisition, the mobile terminal 6 will perform in-depth analysis and storage of the data, evaluate the uniformity of temperature and pressure applied to the cells by the battery formation cabinet, and generate a visualized test report.

[0052] When assessing uniformity, the mobile terminal 6 identifies and calculates the temperature and pressure parameters of the central and edge regions of the battery cell. The specific assessment logic is based on a comprehensive judgment of the upper and lower limits of temperature and pressure in the central region of the battery cell, the proportion of effective points in the edge region, the overall proportion of effective points, and the temperature and pressure differences between different test stations. Specifically, the proportion of effective points in the edge region refers to the percentage of test points in the edge region where the temperature and pressure values ​​exceed a preset effective threshold, out of the total number of test points in that region. The overall proportion of effective points refers to the percentage of test points in all regions of the battery cell where the temperature and pressure values ​​exceed a preset effective threshold, out of the total number of test points.

[0053] Furthermore, a core innovation of this method lies in correlation analysis. The mobile terminal 6 is configured to perform correlation analysis on the pressure and temperature distribution data acquired by the data acquisition unit 41 to determine abnormal pressure and temperature states of the battery cell during the formation process, and the degree of correlation between the two. The specific correlation analysis steps include: first, identifying and locating abnormal temperature regions in the temperature and pressure distribution data; then, extracting the pressure value at the corresponding spatial location of the abnormal temperature region in the pressure distribution data. If the pressure value is lower than a preset lower limit of normal pressure or higher than a preset upper limit of normal pressure, the system determines that the abnormal temperature event is strongly correlated with uneven pressure application. Based on this correlation determination, the system further provides a fault diagnosis conclusion: when a strong correlation is determined between abnormal temperature and uneven pressure, the root cause of the abnormal temperature event is diagnosed as abnormal pressure in the clamp 71 of the battery formation cabinet (e.g., heat transfer obstruction due to poor mechanical contact); conversely, when the pressure value corresponding to the abnormal temperature region is within the preset normal pressure range, indicating good contact, the system diagnoses the root cause of the abnormal temperature event as an abnormality in the heating mechanism or temperature control system of the battery formation cabinet. This automated, interconnected diagnostics greatly improves the efficiency and accuracy of equipment maintenance.

[0054] Example 2

[0055] This embodiment provides an automated pressure distribution testing system and method for battery formation cabinets, primarily for independently detecting the uniformity of mechanical pressure during the battery formation process. Its main hardware structure is consistent with that of Embodiment 1, including a mobile trolley 1, a suspension control mechanism 2, a suspension mechanism 3, a data acquisition mechanism 4, a manual control terminal 5, and a mobile terminal 6. The suspension control mechanism 2 also employs a four-post structure to drive the suspension mechanism 3 for lifting, horizontal movement, and opening / closing adjustments. A pulley-driven electric cylinder 32 drives the data acquisition mechanism 4 to move forward and backward on the suspension support rod 31, achieving automated deployment.

[0056] In terms of sensing and acquisition, the difference in this embodiment lies in the sensing component connected to the data acquisition mechanism 4. The data acquisition unit 41 is connected to a pressure sensing array (i.e., the temperature and pressure sensing array 42 in Embodiment 1 is replaced by a pressure sensing array). This pressure sensing array is a flexible thin-film pressure sensor with a thickness controlled within 0.3 mm, and its size is customized according to requirements. The data acquisition unit 41 is optimized for pressure signals, with a sampling frequency of not less than 100 Hz, and the pressure array has a specification of not less than 256 rows and 256 columns, with a total of 65,536 points, to ensure high-precision gridded capture of the pressure distribution.

[0057] The testing method based on this system is as follows: First, the suspension mechanism 3, which includes a pressure sensor array, is deployed to the test station inside the battery formation cabinet via a mobile trolley 1 and a suspension control mechanism 2, positioning it between the clamp 71 and the battery cell. Once the sensors are in place, the battery formation cabinet inputs the set total pressure, and the clamp 71 clamps the battery cell. At this time, the pressure sensor array senses the pressure distribution data applied to the surface of the battery cell by the clamp 71, and collects it through a data acquisition unit 41. The testing process also supports repeated data acquisition of near-end and far-end areas, and synthesizes a complete channel pressure distribution report.

[0058] During the data analysis phase, mobile terminal 6 receives and saves pressure data to assess the uniformity of pressure applied to the battery cells by the battery formation cabinet. The evaluation logic mainly identifies and calculates the pressure parameters of the central and edge regions of the battery cells. The system makes a comprehensive judgment based on the upper and lower pressure limits of the central region of the battery cell, the proportion of effective pressure points in the edge region, the overall proportion of effective pressure points, and the pressure difference between different test stations. Among them, the proportion of effective points in the edge region is the proportion of the number of test points with pressure values ​​higher than a preset effective threshold in the edge region of the battery cell to the total number of test points in that region. Through the above analysis, a visualized pressure distribution heat map and test report are generated, thereby independently diagnosing whether the fixture 71 has purely mechanical faults such as poor mechanical flatness, spring failure, or structural deformation.

[0059] Example 3

[0060] This embodiment provides an automated temperature distribution testing system and method for battery formation cabinets, mainly for independently detecting the thermal field uniformity during the battery formation process. The mechanical execution part of the system includes a mobile trolley 1, a suspension control mechanism 2, a suspension mechanism 3, and a manual control terminal 5. Its structure and operation logic are completely consistent with those of Embodiment 1, and all of them use automated control to send the testing mechanism into the deep work position of the battery formation cabinet.

[0061] In terms of sensing and acquisition configuration, the data acquisition mechanism 4 in this embodiment is connected to a temperature sensing array (i.e., the temperature and pressure sensing array 42 in embodiment 1 is replaced by a temperature sensing array). This temperature sensing array is a flexible thin-film temperature sensor with a thickness of less than 0.3 mm, which can be tightly attached between the battery cell and the clamp 71 without interfering with heat transfer. The data acquisition unit 41 is configured in a high-precision temperature acquisition mode, with a sampling frequency of not less than 100 Hz and a temperature channel count of not less than 64 channels, which can cover key temperature measurement points on the surface of the battery cell and realize real-time monitoring of the formation temperature field.

[0062] The testing method is executed as follows: After positioning using a mobile trolley 1, the temperature sensor array is automatically moved into the test station within the battery formation cabinet via a suspension control mechanism 2 and a pulley-driven electric cylinder 32. Subsequently, the battery formation cabinet fixture 71 clamps the battery cell and initiates the heating program, inputting the set formation temperature. The temperature sensor array senses the temperature distribution data of the contact surface between the fixture 71 and the battery cell in real time, and the data acquisition unit 41 simultaneously records the data. To obtain the temperature field of the entire channel, the system can repeatedly execute the movement and acquisition steps to acquire temperature data from the near and far ends and synthesize them.

[0063] In the analysis and evaluation phase, mobile terminal 6 processes the collected temperature data to assess the uniformity of the heating system in the battery formation cabinet. The evaluation method includes identifying temperature parameters in the central and edge regions of the battery cells, and making judgments based on preset upper and lower temperature limits, temperature consistency within the region, and temperature differences between different workstations. The system calculates the proportion of measurement points whose temperature values ​​are within the valid range in both the edge and overall regions. If excessively high or low temperatures are found in localized areas, mobile terminal 6 generates a temperature anomaly distribution report. This embodiment is primarily used to diagnose thermal system problems in the battery formation cabinet, such as heating plate malfunctions, blocked temperature control channels, or uneven heating power, without involving pressure-level correlation analysis.

[0064] Example 4

[0065] Based on the system and testing method of Example 1, this embodiment further proposes a dynamic time-series temperature-pressure coupling analysis method to capture the dynamic evolution characteristics of temperature and pressure parameters over time during the entire formation process, thereby enabling early warning of progressive pressure failure and optimization of process parameters.

[0066] Please refer to Figure 8 After completing the basic temperature and pressure distribution test described in Example 1, this example further performs the following steps: First, at different time points in the formation process, the data acquisition device 41 is continuously triggered to perform multiple rounds of synchronous temperature and pressure acquisition at preset time intervals (e.g., every 5 minutes). The temperature and pressure distribution data obtained in each round of acquisition is appended with the current timestamp to form a temperature and pressure time-series dataset with a time dimension. This dataset can be represented as T(x,y,t) and P(x,y,t), where x and y are the spatial coordinates of each measuring point in the sensor array, and t is the acquisition time.

[0067] During the data analysis phase, the mobile terminal 6 calculates the temperature change rate ΔT / Δt and pressure change rate ΔP / Δt at each measuring point between adjacent time points. For each spatial location (x, y), the system calculates the cross-correlation coefficient R(x, y) between its temperature change rate time series and pressure change rate time series. When the cross-correlation coefficient R(x, y) of a certain spatial region exceeds a preset coupling threshold (e.g., |R|>0.8), the system determines that there is a significant dynamic temperature-pressure coupling anomaly in that region during that time period.

[0068] Physically, positive coupling (R close to +1) usually means that an increase in temperature leads to thermal expansion of the fixture, resulting in a synchronous increase in contact pressure; negative coupling (R close to -1) may mean that due to creep or a decrease in the elastic modulus of the fixture at high temperatures, an increase in temperature actually leads to a decrease in contact pressure. The system will record the first occurrence and duration of this coupling anomaly and present the dynamic coupling coefficient distribution in the form of a heatmap in the visualization report.

[0069] Regarding pressure decay prediction during the formation process, the system further extracts the pressure P(x,y,t) change sequence over time at each measuring point based on the aforementioned temperature and pressure time-series dataset. Using a preset pressure decay prediction model (e.g., a fitting model based on an exponential decay function or linear regression), the system fits the pressure time-series data, calculating the pressure decay rate v(x,y) at each measuring point and the predicted remaining time T_remain(x,y) to reach the preset lower pressure limit P_min. When T_remain(x,y) for a certain region is lower than the remaining time T_left of the current formation process, the system immediately issues a warning to the operator, indicating that the pressure in that region may fail before formation is complete, and recommends checking the pressure replenishment mechanism or adjusting the formation parameters to ensure pressure consistency throughout the formation process and avoid battery quality problems caused by insufficient pressure.

[0070] The dynamic time-series temperature-pressure coupling analysis method proposed in this embodiment improves temperature and pressure detection from traditional single static measurement to continuous dynamic monitoring of the entire formation process. It can capture the progressive pressure failure of the fixture caused by thermal expansion, creep and other effects during the formation thermal cycle, thereby realizing predictive maintenance and significantly reducing the battery formation defect rate caused by pressure failure.

[0071] Example 5

[0072] Based on the system in Example 1, this embodiment further proposes an adaptive sensor array reconfiguration mechanism and a deep integration scheme with the Manufacturing Execution System (MES), which solves the problems of lack of model compatibility and disconnect between detection data and production control in the existing technology.

[0073] Please refer to Figure 10Regarding adaptive sensor array reconstruction, in this embodiment, the data acquisition mechanism 4 further includes an array reconstruction controller 43, which is connected to the mobile terminal 6 via a high-speed data bus. The mobile terminal 6 has a pre-stored database of geometric parameters for various types of battery formation cabinet fixtures. The database records the effective pressure area size, cell arrangement coordinates, structural component obstruction areas, and corresponding sensor node coordinate mapping relationships for each type of fixture.

[0074] Before the test begins, the operator inputs the model information of the battery formation cabinet under test via manual control terminal 5. Based on this, mobile terminal 6 retrieves the corresponding fixture dimensions and cell layout parameters from the geometric parameter database and generates a sensor node activation mask. This mask identifies which sensor nodes in the temperature and pressure sensor array 42 are located in the effective cell coverage area (activated) and which nodes are located in the area blocked by the metal structure of the fixture (shielded). Mobile terminal 6 sends the mask as an activation command to array reconfiguration controller 43. The controller then selectively activates the corresponding subset of sensor nodes in the temperature and pressure sensor array 42 and puts the nodes in the shielded area into a low-power sleep state.

[0075] Through the aforementioned adaptive mechanism, the same set of temperature and pressure sensor array 42 hardware can quickly adapt and switch to different models of battery cells (such as square, soft-pack, and other different sizes and specifications) and different structural fixtures without any physical modifications, significantly reducing equipment preparation time and usage costs when crossing product models.

[0076] Regarding deep integration with the Manufacturing Execution System (MES), in this embodiment, the mobile terminal 6 is equipped with a data upload and MES integration interface. After each test, the mobile terminal 6 automatically uploads the generated temperature and pressure distribution test report, along with the timestamp of this test, battery formation cabinet number, operator employee number, and current cell batch number, to the cloud quality management server via an encrypted industrial Ethernet or Wi-Fi channel, realizing paperless archiving and historical traceability of test data.

[0077] In terms of reverse communication, mobile terminal 6 receives test task instructions from the Manufacturing Execution System (MES) via the MES integration interface. These instructions include the test cabinet number, test priority, and process parameter requirements. After receiving the instructions, mobile terminal 6 automatically plans the motion path and data acquisition sequence of the suspension control mechanism 2 and drives the system to execute the corresponding test tasks, thereby achieving remote scheduling and automation of the testing process.

[0078] Regarding abnormal linkage, when the inspection report generated by mobile terminal 6 contains temperature and pressure anomalies exceeding the preset quality threshold, mobile terminal 6 automatically pushes structured alarm information containing the anomaly type, location coordinates, and severity to the manufacturing execution system. After receiving the alarm information, the manufacturing execution system can automatically trigger the corresponding battery formation cabinet production stop command according to the preset linkage rules and notify maintenance personnel for handling, thereby realizing closed-loop control of the entire process from "detection of problems" to "automatic line stop protection", effectively preventing the outflow of non-conforming products.

[0079] Example 6

[0080] Based on the correlation analysis method described in the previous embodiments, this embodiment further proposes an auxiliary diagnostic method for the mechanical deformation of fixtures. This method is used to quantitatively identify fixture flatness abnormalities and their deformation directions through detailed analysis of pressure distribution data without disassembling the equipment, thus providing a quantitative basis for precise equipment maintenance.

[0081] Please refer to Figure 9 After completing the standard temperature and pressure distribution test described in Example 1 and obtaining high-resolution pressure distribution data P(x,y), the following fixture mechanical deformation auxiliary diagnosis steps are performed:

[0082] First, in the pressure distribution data P(x,y) of the temperature and pressure sensing array 42, the pressure values ​​of each measuring point on the four edge lines (upper edge, lower edge, left edge, and right edge) of the battery cell are extracted to form four edge pressure distribution curves.

[0083] Next, each edge pressure distribution curve is fitted and compared with a preset ideal uniform pressure baseline. The ideal uniform pressure baseline is a reference edge pressure curve collected and stored when the equipment leaves the factory with the fixture in good condition. By performing point-by-point difference between the measured curve and the baseline curve, the deformation deviation D(s) at each measuring point on each edge is calculated, where s is the coordinate along the edge direction.

[0084] Then, a trend analysis is performed on the calculated deformation deviation D(s). If the deformation deviation D(s) at a certain edge exceeds the preset mechanical tolerance threshold (e.g., ±5% of the rated pressure), and D(s) shows a monotonically increasing or monotonically decreasing gradient trend along the edge direction (i.e., the deviation value continuously increases or decreases from one end of the edge to the other), the system determines that the fixture has a flatness abnormality in the corresponding direction of that edge (e.g., the deviation at the upper edge indicates that the upper part of the fixture is warped).

[0085] Finally, the system outputs a structured fixture deformation diagnosis report, which includes: the edge direction of the abnormal deformation (up / down / left / right), the estimated maximum deviation (expressed as a percentage of rated pressure or absolute pressure value), the type of deformation trend (warping, collapse or torsion), and the fixture parts that are recommended for key inspection or replacement (such as the spring assembly, guide rail or clamping plate structure on the corresponding side).

[0086] The pressure gradient-based clamp mechanical deformation auxiliary diagnosis method proposed in this embodiment can automatically complete the quantitative assessment of clamp flatness using only the pressure distribution data collected in the normal testing process without disassembling the equipment. This improves the maintenance decision-making from qualitative judgment based on human experience to quantitative diagnosis based on data, significantly improving the accuracy and efficiency of equipment maintenance.

[0087] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. An automated temperature and pressure distribution testing system for battery formation cabinets, characterized in that, include: Mobile cart (1); The suspension control mechanism (2) is installed on the mobile trolley (1) and includes a suspension lifting mechanism (21), a suspension horizontal movement mechanism (22) and a suspension opening and closing adjustment mechanism (23), which is used to drive the suspension mechanism (3) to perform multi-dimensional position adjustment; the suspension lifting mechanism (21) includes four support pillars (211) vertically arranged on the mobile trolley (1), a suspension lifting adjustment motor (212), a lifting screw (213), a nut (214) and a lifting platform (215), the nut (214) is threaded onto the lifting screw (213) and fixed to the lifting platform (215), and the lifting platform (215) is slidably arranged on the support pillars (211); The suspension mechanism (3) is connected to the suspension control mechanism (2) and includes two suspension rods (31), a pulley movement cylinder (32) and a suspension pulley (33). It is configured to carry the data acquisition mechanism (4) and extend into the test station inside the battery formation cabinet. The data acquisition mechanism (4) includes several data acquisition units (41) installed on the suspension mechanism (3). The data acquisition units (41) are connected to a temperature and pressure sensor array (42). The temperature and pressure sensor array (42) is a flexible temperature and pressure integrated sensor with a thickness of less than 0.3 mm, used to synchronously acquire temperature and pressure data between the battery formation cabinet fixture and the battery cell. The manual control terminal (5) is connected to the suspension control mechanism (2) and is used to control the movement of the suspension mechanism and the displacement of the data acquisition device; The mobile terminal (6) is used to receive, analyze and save the data collected by the data acquisition agency (4) and generate a visual report on temperature and pressure distribution.

2. An automated temperature and pressure distribution testing method for battery formation cabinets, characterized in that, The system applicable to claim 1 includes the following steps: The suspension mechanism (3) containing the data acquisition mechanism (4) is moved to the target area of ​​the battery formation cabinet (7) by the mobile trolley (1), and the suspension support (31) is deployed to the test station in the battery formation cabinet (7) by the suspension control mechanism (2), so that the temperature and pressure sensing array (42) is located between the formation fixture (71) and the battery cell in the battery formation cabinet (7); The battery formation cabinet (7) inputs the total pressure and formation temperature, the clamp (71) clamps the battery cell, and the temperature and pressure data between the clamp (71) and the battery cell are obtained through the temperature and pressure sensor array (42); The temperature and pressure data of the temperature and pressure sensor array (42) are collected synchronously by the data acquisition unit (41); The temperature and pressure data are analyzed and saved by the mobile terminal (6), the uniformity of temperature and pressure applied to the battery cell by the battery formation cabinet (7) is evaluated, and a visual test report of temperature and pressure distribution is generated.

3. The automated temperature and pressure distribution testing method for battery formation cabinet according to claim 2, characterized in that, Methods for evaluating the uniformity of temperature and pressure applied to the cells by the battery formation cabinet (7) include: Identify and calculate the temperature and pressure parameters of the central and edge regions of the battery cell; The uniformity of temperature and pressure applied to the battery cell by the battery formation cabinet (7) is evaluated based on the upper and lower limits of temperature and pressure in the central area of ​​the battery cell, the proportion of effective points in the edge area, the proportion of effective points in the overall area, and the temperature and pressure difference between different test stations. The proportion of effective points in the edge area is the proportion of the number of test points in the edge area of ​​the battery cell whose temperature and pressure values ​​are higher than the preset effective threshold to the total number of test points in that area. The proportion of effective points in the overall area is the proportion of the number of test points in all areas of the battery cell whose temperature and pressure values ​​are higher than the preset effective threshold to the total number of test points.

4. The automated temperature and pressure distribution testing method for battery formation cabinet according to claim 2, characterized in that, It also includes a step of correlation analysis of the collected pressure distribution data and temperature distribution data, specifically: Identify and locate temperature anomaly regions in temperature and pressure distribution data; Extract the pressure value of the corresponding spatial location in the pressure distribution data for the temperature anomaly region; When the pressure value is lower than the preset lower limit of normal pressure or higher than the preset upper limit of normal pressure, it is determined that the abnormal temperature event is strongly correlated with the uneven pressure application, and the root cause is diagnosed as abnormal pressure of the clamp (71) of the battery formation cabinet (7). When the pressure value corresponding to the abnormal temperature area is within the preset normal pressure range, the root cause will be diagnosed as an abnormality in the heating mechanism or temperature control system of the battery formation cabinet (7).

5. The automated temperature and pressure distribution testing system for battery formation cabinet according to claim 1, characterized in that, The mobile terminal (6) is also equipped with a multi-station data fusion module, which is used to register and align the temperature and pressure distribution data collected in the near and far regions of the same battery formation cabinet (7) according to the station number and spatial coordinates, and synthesize them into an integrated temperature and pressure distribution detection report covering the complete number of channels; the mobile terminal (6) can also make a horizontal comparison of the temperature and pressure parameters between different stations, and automatically mark the abnormal stations and their location coordinates where the deviation exceeds the preset threshold.

6. The automated temperature and pressure distribution testing method for battery formation cabinet according to claim 2, characterized in that, It also includes a dynamic time-series temperature-pressure coupling analysis step, which includes: At different time points in the formation process, the data acquisition device (41) is continuously triggered at preset time intervals to perform multiple rounds of synchronous temperature and pressure acquisition, forming a temperature and pressure time series dataset with timestamps; Calculate the rate of temperature change and rate of pressure change at each measuring point between adjacent time points; When the cross-correlation coefficient between the rate of temperature change and the rate of pressure change in a certain spatial region exceeds the preset coupling threshold, it is determined that there is a dynamic temperature-pressure coupling anomaly in that region, and the first occurrence time and duration of the coupling anomaly are recorded for use in optimizing the formation process parameters and predictive maintenance of equipment.

7. The automated temperature and pressure distribution testing system for battery formation cabinet according to claim 1, characterized in that, The data acquisition mechanism (4) further includes an array reconstruction controller, which is communicatively connected to the mobile terminal (6); The mobile terminal (6) has a database of geometric parameters of various battery formation cabinet fixtures. Before the test begins, the mobile terminal (6) retrieves the corresponding fixture size and cell layout parameters from the geometric parameter database according to the model information of the battery formation cabinet to be tested, and sends a sensor activation command to the array reconfiguration controller accordingly. According to the activation command, the array reconfiguration controller selectively activates a subset of sensing nodes in the temperature and pressure sensing array (42) that correspond to the current cell coverage area, and shields invalid nodes located in the area blocked by the fixture structure, thereby achieving adaptive matching detection of different cell models and fixtures without replacing the sensor hardware.

8. The automated temperature and pressure distribution testing method for battery formation cabinet according to claim 4, characterized in that, The correlation analysis step further includes a fixture mechanical deformation auxiliary diagnosis step, which includes: From the pressure distribution data of the temperature and pressure sensing array (42), the pressure gradient distribution on the four edge lines of the battery cell is extracted; The edge pressure gradient is fitted and compared with a preset ideal uniform pressure baseline, and the deformation deviation at each edge is calculated. When the deformation deviation at a certain edge exceeds the preset mechanical tolerance threshold, and the deviation shows a monotonically increasing or decreasing gradient trend, it is determined that the flatness of the fixture in the corresponding direction is abnormal, and a fixture deformation diagnosis report containing the deformation direction, estimated deviation range, and suggested repair parts is output.

9. The automated temperature and pressure distribution testing system for battery formation cabinet according to claim 1, characterized in that, The mobile terminal (6) is also equipped with an interface for data uploading to the cloud and integration with the manufacturing execution system, used for: After each test, the temperature and pressure distribution test report generated, along with the test time, battery formation cabinet number, operator information, and cell batch number, will be automatically uploaded to the cloud quality management server through an encrypted channel. Receive test task instructions from the manufacturing execution system and automatically plan the motion path and data acquisition sequence of the suspension control mechanism (2) according to the instructions; When the test report contains abnormal temperature and pressure records that exceed the preset quality threshold, the mobile terminal (6) automatically pushes alarm information to the manufacturing execution system, triggering the production suspension command of the corresponding battery formation cabinet (7), thereby realizing the closed-loop linkage between the test data and the production control system.

10. The automated temperature and pressure distribution testing method for battery formation cabinet according to claim 6, characterized in that, It also includes a formation process pressure decay prediction step, which includes: Based on the aforementioned temperature and pressure time series dataset, extract the sequence data of pressure changes over time at each measuring point; Using a preset pressure decay prediction model, the pressure time series data is fitted to calculate the pressure decay rate at each measuring point and the predicted remaining time to reach the lower pressure limit. When the predicted remaining time in a certain area is lower than the remaining time of the current formation process, an early warning is issued to the operator, indicating that the pressure in that area may fail before the formation is completed, and it is recommended to check or adjust the pressure replenishment mechanism of the battery formation cabinet (7) to ensure the pressure consistency throughout the formation process.

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