Method, device and equipment for determining energy storage battery pack (PACK) air tightness leak point type and medium

Abstract

The application provides a method, device, equipment and medium for determining the type of a leakage point of a storage battery PACK, including: filling nitrogen into a box of a measured storage battery PACK to a preset test pressure, entering a pressure maintaining stage after closing the filling valve, continuously collecting pressure values in the box at a preset sampling frequency, and obtaining a pressure-time data sequence; preprocessing the pressure-time data sequence and calculating pressure drop curve characteristic parameters; wherein the pressure drop curve characteristic parameters at least include a segmented pressure drop rate, a pressure drop rate attenuation coefficient, a pressure drop rate variation coefficient, and a pressure drop acceleration rate; matching the pressure drop curve characteristic parameters with a preset leakage point determination rule to determine the type of the leakage point; and outputting at least one of a pressure-time curve, a segmented pressure drop rate, a determined leakage point type, and a maintenance troubleshooting path. The type of the leakage point is quickly and accurately determined, subjective differences in manual experience judgment are eliminated, and the determination standard is clear, reproducible, and traceable.

Description

Technical Field

[0001] This application relates to the field of airtightness testing technology for energy storage systems, and in particular to methods, apparatus, equipment and media for determining the type of airtightness leaks in energy storage battery packs. Background Technology

[0002] With the rapid development of the energy storage industry, battery packs, as the core component of energy storage systems, directly affect insulation performance, operational safety, and service life due to their airtightness. If a pack housing leaks, external moisture and dust can penetrate, potentially leading to electrical short circuits, insulation failure, and corrosion of metal parts, and in severe cases, even thermal runaway. Therefore, packs typically undergo airtightness testing before leaving the factory. Current technologies generally employ a "fill-hold-voltage drop determination" method for airtightness testing of energy storage battery packs. However, existing technologies have the following shortcomings: First, current airtightness tests only provide a binary conclusion of "pass / fail," without identifying the type and specific location of the leak. Second, existing methods have low utilization of pressure-time data. Third, traditional leak determination methods are mainly for metal packs and are not applicable to industrial plastic packs. Fourth, existing determination methods rely on human experience, leading to significant subjective differences. Different testers may have different understandings and judgments of the same voltage drop curve, lacking a unified, quantifiable, and reproducible judgment standard, resulting in unstable leak type predictions and making it difficult to establish standardized maintenance procedures. Therefore, accurately and quickly determining the type of airtightness leak in an energy storage battery pack has become a significant technical challenge. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a method, apparatus, equipment and medium for determining the type of airtightness leaks in energy storage battery packs. By directly using existing pressure-time data to determine the characteristic parameters of the pressure drop curve after the airtightness test, the type of leak can be quickly and accurately determined by using the characteristic parameters of the pressure drop curve and the preset leak judgment rules. This eliminates the subjective difference of human experience judgment and makes the judgment criteria clear, reproducible and traceable.

[0004] This application provides a method for determining the type of airtightness leakage in an energy storage battery pack, the method comprising: Nitrogen gas is filled into the test chamber of the energy storage battery PACK to the preset test pressure. After the filling valve is closed, the pressure holding stage is entered. The pressure value inside the chamber is continuously collected at the preset sampling frequency to obtain the pressure and time data sequence. The pressure and time data sequence is preprocessed and the characteristic parameters of the pressure drop curve are calculated; wherein, the characteristic parameters of the pressure drop curve include at least the segmented pressure drop rate, the pressure drop rate attenuation coefficient, the pressure drop rate variation coefficient, and the pressure drop acceleration rate. The characteristic parameters of the pressure drop curve are matched with preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type; At least one of the following: output pressure versus time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

[0005] In one possible implementation, preprocessing the pressure and time data series and calculating characteristic parameters of the pressure drop curve includes: The pressure and time data sequence is subjected to moving average filtering and temperature compensation correction to determine the preprocessed pressure and time data sequence; The pressure holding stage is divided into multiple segments, and the average pressure drop rate in each segment is calculated to determine the segmented pressure drop rate. The voltage drop rate attenuation coefficient is determined based on the ratio of the first segment voltage drop rate to the last segment voltage drop rate. The coefficient of variation of the voltage drop rate is determined based on the standard deviation and mean of the multiple segmented voltage drop rates; The pressure drop acceleration rate is determined by taking the second derivative of pressure with respect to time.

[0006] In one possible implementation, when the leak type is the large leak type, the preset leak determination rule is: When the voltage drop rate of the first segment is greater than the first rate threshold, the voltage drop rate attenuation coefficient is greater than the first attenuation threshold, and the voltage drop rate of the last segment is less than the second rate threshold, the voltage drop curve of the large-leak type exhibits a steep-then-flat shape; wherein, the first rate threshold is greater than the second rate threshold.

[0007] In one possible implementation, when the leak type is the micro-leak type, the preset leak determination rule is: When the coefficient of variation of the voltage drop rate is less than the first variation threshold, the coefficient of decay of the voltage drop rate is less than the second decay threshold, and the average value of the segmented voltage drop rates is less than the third rate threshold, the voltage drop curve of the micro-leakage type exhibits a slow and uniform shape; wherein, the second decay threshold is less than the first decay coefficient threshold, and the third rate threshold is between the first rate threshold and the second rate threshold.

[0008] In one possible implementation, matching the characteristic parameters of the pressure drop curve with a preset leak detection rule to determine the leak type includes: When the leak type is the gap type, the preset leak determination rule is that the coefficient of variation of the pressure drop rate is greater than the second variation threshold, the positive step change or the positive spike is greater than the preset threshold, and the average value of the segmented pressure drop rate is in the first rate range. When the leak type is the variant, the preset leak determination rule is that the first segment voltage drop rate is greater than the fourth rate threshold, and the voltage drop rate attenuation coefficient is greater than the third attenuation threshold; wherein, the third attenuation threshold is higher than the first attenuation threshold. When the leak type is the crack type, the preset leak determination rule is that the average value of the segmented pressure drop rate falls into the second rate interval, the pressure drop rate attenuation coefficient is within the preset range, and the preset condition that characterizes the leakage rate as increasing instead of decreasing is met.

[0009] In one possible implementation, the leak type also includes a composite type. When the extracted characteristic parameters of the pressure drop curve simultaneously satisfy the judgment rules of two or more leak types, a composite type prediction signal is output.

[0010] In one possible implementation, after at least one of the output pressure versus time curve, segmented pressure drop rate, determined leak type, and troubleshooting path, the determination method further includes: Receive the repair and retest results after maintenance personnel conduct targeted troubleshooting according to the repair and troubleshooting path, and update and optimize the thresholds in the preset leak point judgment rules based on the repair and retest results.

[0011] This application embodiment also provides a device for determining the type of airtightness leakage point of an energy storage battery PACK, the device comprising: The data acquisition module is used to fill the box of the energy storage battery PACK under test with nitrogen to the preset test pressure. After closing the filling valve, it enters the pressure holding stage and continuously collects the pressure value inside the box at a preset sampling frequency to obtain the pressure and time data sequence. The feature extraction module is used to preprocess the pressure and time data sequence and calculate the pressure drop curve feature parameters; wherein, the pressure drop curve feature parameters include at least the segmented pressure drop rate, pressure drop rate attenuation coefficient, pressure drop rate variation coefficient, and pressure drop acceleration rate. The rule determination module is used to match the characteristic parameters of the pressure drop curve with preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type; The output module is used to output at least one of the following: pressure-time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

[0012] This application also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the method for determining the airtightness leakage type of the energy storage battery PACK as described above are performed.

[0013] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method for determining the type of airtightness leaks in an energy storage battery PACK as described above.

[0014] The present application provides a method, apparatus, equipment, and medium for determining the airtightness leak type of an energy storage battery pack. The determination method includes: filling the battery pack under test with nitrogen to a preset test pressure, closing the filling valve, and entering a pressure holding stage; continuously collecting pressure values ​​inside the pack at a preset sampling frequency to obtain a pressure and time data sequence; preprocessing the pressure and time data sequence and calculating pressure drop curve characteristic parameters; wherein the pressure drop curve characteristic parameters include at least segmented pressure drop rate, pressure drop rate attenuation coefficient, pressure drop rate variation coefficient, and pressure drop acceleration rate; matching the pressure drop curve characteristic parameters with preset leak determination rules to determine the leak type; wherein the leak type includes at least large leak, micro leak, gap leak, deformation leak, and crack leak; and outputting at least one of the following: pressure and time curve, segmented pressure drop rate, determined leak type, and maintenance troubleshooting path. By directly using existing pressure-time data to determine the characteristic parameters of the pressure drop curve after the airtightness test, and using the characteristic parameters of the pressure drop curve and the preset leak point judgment rules, the type of leak can be quickly and accurately determined, eliminating the subjective difference of human experience judgment, and making the judgment criteria clear, reproducible and traceable.

[0015] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of a method for determining the type of airtightness leaks in an energy storage battery PACK, provided as an embodiment of this application; Figure 2 One of the structural schematic diagrams of a device for determining the airtightness leakage type of an energy storage battery PACK provided in an embodiment of this application; Figure 3 A second schematic diagram of a device for determining the type of airtightness leaks in an energy storage battery PACK, provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0019] First, the applicable application scenarios of this application are introduced. This application can be applied to the field of airtightness testing technology for energy storage systems.

[0020] Research has revealed the following shortcomings in existing technologies: First, current airtightness tests only provide a binary "pass / fail" conclusion, failing to identify the type and specific location of leaks. Second, existing methods have low utilization of pressure-time data. Third, traditional leak detection methods are primarily designed for metal PACKs and are not applicable to industrial plastic PACKs. Fourth, existing methods rely on human experience, leading to significant subjective differences. Different testers may interpret and judge the same pressure drop curve differently, lacking a unified, quantifiable, and reproducible standard, resulting in unstable leak type predictions and hindering the development of standardized maintenance procedures. Therefore, accurately and quickly determining the type of airtightness leak in energy storage battery PACKs has become a significant technical challenge.

[0021] Based on this, the present application provides a method for determining the type of airtightness leak in an energy storage battery PACK. By directly using existing pressure-time data to determine the characteristic parameters of the pressure drop curve after the airtightness test, the leak type can be quickly and accurately determined using the characteristic parameters of the pressure drop curve and preset leak judgment rules. This eliminates the subjective differences of human experience judgment and makes the judgment criteria clear, reproducible and traceable.

[0022] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for determining the type of airtightness leak in an energy storage battery pack, as provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, the determination method includes: S101: Nitrogen gas is filled into the test chamber of the energy storage battery PACK to the preset test pressure. After the filling valve is closed, the pressure holding stage is entered. The pressure value inside the chamber is continuously collected at the preset sampling frequency to obtain the pressure and time data sequence.

[0023] In this step, gas is filled into the PACK box under test to the preset test pressure. After the gas filling valve is closed, the pressure holding stage is entered. Pressure change data over time during the pressure holding stage is collected at a preset sampling frequency to obtain a pressure-time data sequence (pressure drop curve).

[0024] S102: Preprocess the pressure and time data sequence and calculate the characteristic parameters of the pressure drop curve; wherein, the characteristic parameters of the pressure drop curve include at least the segmented pressure drop rate, the pressure drop rate attenuation coefficient, the pressure drop rate variation coefficient, and the pressure drop acceleration rate.

[0025] In this step, the pressure-time data series is preprocessed, and the characteristic parameters of the pressure drop curve are calculated. These characteristic parameters include: the segmented pressure drop rate v_j obtained by dividing the pressure holding phase into M equal segments, the pressure drop rate attenuation coefficient α, the pressure drop rate variation coefficient CV, and the pressure drop acceleration rate. A .

[0026] In one possible implementation, preprocessing the pressure and time data series and calculating characteristic parameters of the pressure drop curve includes: A: The pressure and time data sequence is subjected to moving average filtering and temperature compensation correction to determine the preprocessed pressure and time data sequence.

[0027] Here, the collected pressure-time data series are filtered by moving average, and when the absolute value of temperature change during the pressure holding stage exceeds the preset temperature threshold, the pressure-time data series are corrected by temperature compensation.

[0028] B: Divide the pressure holding stage into multiple segments and calculate the average pressure drop rate within each segment to determine the segmented pressure drop rate; determine the pressure drop rate attenuation coefficient based on the ratio of the first segmented pressure drop rate to the last segmented pressure drop rate; determine the pressure drop rate variation coefficient based on the standard deviation and mean of multiple segmented pressure drop rates; determine the pressure drop acceleration rate by taking the second derivative of the pressure data with respect to the time data.

[0029] Here, the pressure holding phase is divided into M=5 segments (each segment 24 seconds) according to time, and the average pressure drop rate v_j (j=1,2,...,5) of each segment is calculated. The pressure drop rate attenuation coefficient α=v_1 / v_5 (v_1 is the pressure drop rate of the first segment, and v_5 is the pressure drop rate of the last segment) is calculated. The pressure drop rate variation coefficient CV=σ(v_1~v_5) / mean(v_1~v_5) is calculated. The pressure drop acceleration sequence A(t_i)=[V(t_i)-V(t_{i-1})] / Δt is calculated. Where V(t_i) is the pressure drop rate, Δt is the sampling time interval, σ(v_1~v_5) is the standard deviation of v_1~v_5, and mean(v_1~v_5) is the arithmetic mean of v_1~v_5.

[0030] S103: Match the characteristic parameters of the pressure drop curve with the preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type.

[0031] In this step, the characteristic parameters of the pressure drop curve are matched with the preset leak detection rules to determine the leak type.

[0032] It should be noted that the total pressure drop ΔP = P(t_0) - P(t_N) is calculated. If ΔP ≤ the allowable threshold ΔP_th = 80Pa, the airtightness is directly determined to be qualified and the process ends; otherwise, the characteristic parameters of the pressure drop curve are matched with the preset leak point judgment rules to determine the leak point type.

[0033] Here, the pressure drop curve morphology information from the airtightness test is converted into a leak type prediction signal. At the end of the test, the system automatically provides the leak type: large leaks correspond to leaks on the cover sealing surface; micro leaks correspond to leaks due to micropores or weld lines in the injection molding; gap leaks correspond to leaks at the insert interface or connector seal; deformation leaks correspond to intermittent leaks on the sealing surface caused by slight deformation of the housing under pressure; cracked leaks correspond to leaks due to plastic cracking at bolt holes; and composite leaks correspond to mixed leaks that do not meet a single rule or simultaneously meet multiple rules. Based on this, the system outputs a targeted maintenance and troubleshooting path corresponding to the leak type, eliminating the need for maintenance personnel to blindly check the cover sealing surface, housing, bolt holes, insert interfaces, connectors, and injection molding defect areas one by one, thus improving the efficiency of location.

[0034] In one possible implementation, when the leak type is the large leak type, the preset leak determination rule is: When the voltage drop rate of the first segment is greater than the first rate threshold, the voltage drop rate attenuation coefficient is greater than the first attenuation threshold, and the voltage drop rate of the last segment is less than the second rate threshold, the voltage drop curve of the large-leak type exhibits a steep-then-flat shape; wherein, the first rate threshold is greater than the second rate threshold.

[0035] The first rate threshold is 500 Pa / min, the first attenuation threshold is 3.0, and the second rate threshold is 100 Pa / min.

[0036] Here, when v_1>500Pa / min, α>3.0 and v_5<100Pa / min are satisfied, it is determined to be a large leakage caused by leakage of the cover sealing surface. The pressure drop curve of the large leakage type is steep at first and then flat.

[0037] In one possible implementation, when the leak type is the micro-leak type, the preset leak determination rule is: When the coefficient of variation of the voltage drop rate is less than the first variation threshold, the coefficient of decay of the voltage drop rate is less than the second decay threshold, and the average value of the segmented voltage drop rates is less than the third rate threshold, the voltage drop curve of the micro-leakage type exhibits a slow and uniform shape; wherein, the second decay threshold is less than the first decay coefficient threshold, and the third rate threshold is between the first rate threshold and the second rate threshold.

[0038] The first variation threshold is 0.15, the second decay threshold is 0.15, and the third rate threshold is 300 Pa / min.

[0039] Here, when CV < 0.15, α < 1.5 and v_avg < 300 Pa / min, it is determined to be a micro-leakage caused by micropores or weld lines in the injection molding; the pressure drop curve of the micro-leakage is slow and uniform.

[0040] In one possible implementation, matching the characteristic parameters of the pressure drop curve with a preset leak detection rule to determine the leak type includes: (1): When the leak type is the gap type, the preset leak determination rule is that the coefficient of variation of the pressure drop rate is greater than the second variation threshold, the positive step change or the positive spike is greater than the preset threshold, and the average value of the segmented pressure drop rate is in the first rate range.

[0041] Here, the second variation threshold is 0.25, the preset threshold is 100 Pa / min², and the first rate range is [100, 500] Pa / min.

[0042] Among them, when CV>0.25, positive step change or positive spike>100Pa / min² and v_avg∈[100,500]Pa / min, it is determined to be a gap type caused by leakage of insert interface or connector seal. The gap type corresponds to intermittent flow, and the pressure drop curve shows a stepped fluctuation shape.

[0043] (2): When the leakage point type is the variant type, the preset leakage point determination rule is that the first segment voltage drop rate is greater than the fourth rate threshold, and the voltage drop rate attenuation coefficient is greater than the third attenuation threshold; wherein, the third attenuation threshold is higher than the first attenuation threshold.

[0044] Here, the fourth rate threshold is 200 Pa / min, and the third decay threshold is 4.0.

[0045] Among them, when v_1>200Pa / min, α>4.0 and the absolute value of the initial negative acceleration rate>200Pa / min², it is determined to be a deformation type caused by intermittent leakage of the sealing surface due to micro-deformation of the shell under pressure; the deformation type corresponds to the elastic deformation dependent flow A(P)=A0+k_elas·P, where A0 is the initial effective area of ​​the leak point at the beginning of pressure holding, and k_elas is the elastic deformation coefficient; and the deformation type is distinguished from the large leakage type α>3.0 in Rule 1 by α>4.0.

[0046] (3): When the leak type is the crack type, the preset leak determination rule is that the average value of the segmented pressure drop rate falls into the second rate interval, the pressure drop rate attenuation coefficient is within the preset range, and the preset condition that characterizes the leakage rate to increase instead of decrease is met.

[0047] Here, the second rate interval is [80, 400] Pa / min, the preset range is [0.7, 1.3], and the preset condition is CV∈[0.10, 0.30], which is stable cracking or the condition α<1.0 and CV<0.10 and the second half of v_j is monotonically increasing, which is extended cracking.

[0048] Among them, when v_avg∈[80,400]Pa / min, α∈[0.7,1.3], and satisfies condition A: stable cracking with CV∈[0.10,0.30], or satisfies condition B: α<1.0, CV<0.10 and the latter half of v_j is monotonically increasing, it is determined to be a cracking type caused by plastic cracking and leakage at the bolt hole; the cracking type corresponds to the creep driving flow A(t)=A0+ΔA_creep(t), where ΔA_creep(t) is the area increment caused by creep expansion, and α<1.0 indicates that the crack continues to expand during the pressure holding process.

[0049] The instruction manual requires that the judgment threshold be adaptively adjusted according to the PACK box volume. When the PACK box volume is >200L, the rate threshold is reduced to 0.8 times. The method is applicable to 314Ah cell PACKs with volumes of 80L to 250L, with a test pressure P_max=4kPa, a holding time of 2 minutes, and an allowable voltage drop of 80Pa.

[0050] In one possible implementation, the leak type also includes a composite type. When the extracted characteristic parameters of the pressure drop curve simultaneously satisfy the judgment rules of two or more leak types, a composite type prediction signal is output.

[0051] Here, if any one of the rules is not met, or multiple rules are met simultaneously, it is judged as a composite type; the priority of targeted maintenance and troubleshooting for composite types is: cover sealing surface → shell micro-deformation → bolt hole cracking → insert interface / connector → injection molding defect micropores.

[0052] In this application, the segmented voltage drop rate v_j, attenuation coefficient α, coefficient of variation CV, and acceleration rate are used. A The system constructs judgment rules based on characteristic parameters and thresholds, with clear judgment standards that do not rely on personal experience. Test results are consistent across different personnel, batches, and equipment, facilitating standardized operations and quality traceability.

[0053] S104: At least one of the following: output pressure versus time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

[0054] Here, the output includes at least one of the following: pressure-time curve, pressure drop rate bar chart for each time period, leak type prediction conclusion, and targeted maintenance and troubleshooting path suggestion.

[0055] In one possible implementation, after at least one of the output pressure versus time curve, segmented pressure drop rate, determined leak type, and maintenance troubleshooting path, the determination method further includes: receiving the repair and retest results after maintenance personnel have conducted targeted troubleshooting according to the maintenance troubleshooting path, and updating and optimizing the threshold in the preset leak determination rules based on the repair and retest results.

[0056] In a specific embodiment, the test conditions were as follows: nitrogen was introduced to P_max = 4 kPa, the pressure was maintained for 2 minutes after the charging valve was closed, the sampling frequency was 10 Hz, and the allowable pressure drop threshold ΔP_th = 80 Pa. After the test, data preprocessing and feature parameter extraction were performed, and the leak type was matched according to the preset leak point judgment rules. The following are some typical embodiments. For large leaks: the airtightness test of the tested energy storage battery PACK was performed, and the average pressure drop rate of 5 segments was extracted as: v_j = {675, 275, 155, 105, 65} Pa / min. The attenuation coefficient α = v_1 / v_5 = 10.4 was calculated, and the total pressure drop ΔP = 510 Pa. This result satisfies rule one: v_1 > 500 Pa / min, α > 3.0, v_5 < 100 Pa / min, and is judged to be a large leak, with the leak type predicted to be a leak at the cover sealing surface. The cover sealing surface was checked according to the targeted maintenance troubleshooting path, and it was found that the torque of the corner bolt of the upper cover was insufficient. For the micro-leak type: v_j={50,52,48,44,42}Pa / min, the calculated attenuation coefficient α=1.19, coefficient of variation CV=0.082, and total pressure drop ΔP=94Pa. This result satisfies rule two: CV<0.15, α<1.5, v_avg<300Pa / min, classifying it as a micro-leak. The predicted leak type is injection molding defect micropores or weld line leakage. Following the directional maintenance troubleshooting path, a 0.5mm shrinkage cavity was found at the weld line on the side wall of the housing. For the gap type: v_j={65,160,72,185,88}Pa / min, the calculated coefficient of variation CV=0.44, positive peak +113Pa / min², total pressure drop ΔP=228Pa, and v_avg=114Pa / min. The result satisfies rule three: CV>0.25, positive step change or positive spike>100Pa / min², v_avg∈[100,500]Pa / min, classifying it as a gap type, with the predicted leak type being insert interface or connector seal leakage. For the deformation type: v_j={420,225,105,52,28}Pa / min, the calculated attenuation coefficient α=15.0, and the total pressure drop ΔP=332Pa. This result satisfies rule four: v_1>200Pa / min, α>4.0, and the absolute value of the initial negative acceleration rate>200Pa / min², classifying it as a deformation type, with the predicted leak type being intermittent leakage at the sealing surface caused by micro-deformation of the housing under pressure. For the cracked type: v_j={145,142,150,155,163}Pa / min, the calculated attenuation coefficient α=0.89, the total pressure drop ΔP=302Pa, v_avg=151Pa / min, and CV≈0.055.The result satisfies rule 5: v_avg∈[80,400]Pa / min, α∈[0.7,1.3], and also satisfies condition ③B: α<1.0, CV<0.10, and the second half of v_j is monotonically increasing. It is determined to be an extended type of cracking, and the leak point type is predicted to be plastic cracking leakage at the bolt hole.

[0057] This application provides a method for determining the type of airtight leak in an energy storage battery pack. The method includes: filling the battery pack under test with nitrogen to a preset test pressure, closing the filling valve and entering a pressure holding stage; continuously collecting pressure values ​​inside the pack at a preset sampling frequency to obtain a pressure and time data sequence; preprocessing the pressure and time data sequence and calculating pressure drop curve characteristic parameters; wherein the pressure drop curve characteristic parameters include at least segmented pressure drop rate, pressure drop rate attenuation coefficient, pressure drop rate variation coefficient, and pressure drop acceleration rate; matching the pressure drop curve characteristic parameters with preset leak determination rules to determine the leak type; wherein the leak type includes at least large leak, micro leak, gap leak, deformation leak, and crack leak; and outputting at least one of the following: pressure and time curve, segmented pressure drop rate, determined leak type, and maintenance troubleshooting path. By directly using existing pressure-time data to determine the characteristic parameters of the pressure drop curve after the airtightness test, and using the characteristic parameters of the pressure drop curve and the preset leak point judgment rules, the type of leak can be quickly and accurately determined, eliminating the subjective difference of human experience judgment, and making the judgment criteria clear, reproducible and traceable.

[0058] Please see Figure 2 , Figure 3 , Figure 2 One of the structural schematic diagrams of a device for determining the airtightness leakage type of an energy storage battery PACK provided in an embodiment of this application; Figure 3 This is a second schematic diagram of a device for determining the type of airtightness leaks in an energy storage battery pack, provided as an embodiment of this application. Figure 2 As shown, the device 200 for determining the type of airtightness leaks in the energy storage battery pack includes: The data acquisition module 210 is used to fill the box of the energy storage battery PACK under test with nitrogen to the preset test pressure. After closing the filling valve, it enters the pressure holding stage and continuously collects the pressure value inside the box at a preset sampling frequency to obtain the pressure and time data sequence. The feature extraction module 220 is used to preprocess the pressure and time data sequence and calculate the pressure drop curve feature parameters; wherein, the pressure drop curve feature parameters include at least the segmented pressure drop rate, the pressure drop rate attenuation coefficient, the pressure drop rate variation coefficient, and the pressure drop acceleration rate. The rule determination module 230 is used to match the characteristic parameters of the pressure drop curve with preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type; Output module 240 is used to output at least one of the following: pressure-time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

[0059] Furthermore, the pressure and time data series are preprocessed and the characteristic parameters of the pressure drop curve are calculated, including: The pressure and time data sequence is subjected to moving average filtering and temperature compensation correction to determine the preprocessed pressure and time data sequence; The pressure holding stage is divided into multiple segments, and the average pressure drop rate in each segment is calculated to determine the segmented pressure drop rate. The voltage drop rate attenuation coefficient is determined based on the ratio of the first segment voltage drop rate to the last segment voltage drop rate. The coefficient of variation of the voltage drop rate is determined based on the standard deviation and mean of the multiple segmented voltage drop rates; The pressure drop acceleration rate is determined by taking the second derivative of the pressure data with respect to the time data.

[0060] Furthermore, when the leak type is the large leak type, the preset leak determination rule is: When the voltage drop rate of the first segment is greater than the first rate threshold, the voltage drop rate attenuation coefficient is greater than the first attenuation threshold, and the voltage drop rate of the last segment is less than the second rate threshold, the voltage drop curve of the large-leak type exhibits a steep-then-flat shape; wherein, the first rate threshold is greater than the second rate threshold.

[0061] Furthermore, when the leak type is the micro-leak type, the preset leak determination rule is: When the coefficient of variation of the voltage drop rate is less than the first variation threshold, the coefficient of decay of the voltage drop rate is less than the second decay threshold, and the average value of the segmented voltage drop rates is less than the third rate threshold, the voltage drop curve of the micro-leakage type exhibits a slow and uniform shape; wherein, the second decay threshold is less than the first decay coefficient threshold, and the third rate threshold is between the first rate threshold and the second rate threshold.

[0062] Furthermore, the step of matching the characteristic parameters of the pressure drop curve with preset leak detection rules to determine the leak type includes: When the leak type is the gap type, the preset leak determination rule is that the coefficient of variation of the pressure drop rate is greater than the second variation threshold, the positive step change or the positive spike is greater than the preset threshold, and the average value of the segmented pressure drop rate is in the first rate range. When the leak type is the variant, the preset leak determination rule is that the first segment voltage drop rate is greater than the fourth rate threshold, and the voltage drop rate attenuation coefficient is greater than the third attenuation threshold; wherein, the third attenuation threshold is higher than the first attenuation threshold. When the leak type is the crack type, the preset leak determination rule is that the average value of the segmented pressure drop rate falls into the second rate interval, the pressure drop rate attenuation coefficient is within the preset range, and the preset condition that characterizes the leakage rate as increasing instead of decreasing is met.

[0063] Furthermore, the leakage type also includes a composite type. When the extracted characteristic parameters of the pressure drop curve simultaneously meet the judgment rules of two or more leakage types, a composite type prediction signal is output.

[0064] Furthermore, such as Figure 3 As shown, the device 200 for determining the type of airtightness leaks in an energy storage battery pack also includes a threshold update module 350, which is used for: Receive the repair and retest results after maintenance personnel conduct targeted troubleshooting according to the repair and troubleshooting path, and update and optimize the thresholds in the preset leak point judgment rules based on the repair and retest results.

[0065] This application provides a device for determining the type of airtightness leak in an energy storage battery pack. The device includes: a data acquisition module for filling the battery pack under test with nitrogen to a preset test pressure, closing the filling valve, and entering a pressure holding stage, continuously acquiring the pressure value inside the pack at a preset sampling frequency to obtain a pressure and time data sequence; a feature extraction module for preprocessing the pressure and time data sequence and calculating pressure drop curve feature parameters; wherein the pressure drop curve feature parameters include at least segmented pressure drop rate, pressure drop rate attenuation coefficient, pressure drop rate variation coefficient, and pressure drop acceleration rate; a rule determination module for matching the pressure drop curve feature parameters with preset leak determination rules to determine the leak type; wherein the leak type includes at least large leak, micro leak, gap leak, deformation leak, and crack leak; and an output module for outputting at least one of the following: pressure and time curve, segmented pressure drop rate, determined leak type, and repair and troubleshooting path. By directly using existing pressure-time data to determine the characteristic parameters of the pressure drop curve after the airtightness test, and using the characteristic parameters of the pressure drop curve and the preset leak point judgment rules, the type of leak can be quickly and accurately determined, eliminating the subjective difference of human experience judgment, and making the judgment criteria clear, reproducible and traceable.

[0066] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4As shown, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.

[0067] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, they can perform the operations described above. Figure 1 The steps of the method for determining the airtightness leakage type of the energy storage battery PACK in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0068] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 The steps of the method for determining the airtightness leakage type of the energy storage battery PACK in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0069] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0070] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0071] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0072] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0073] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining the type of airtightness leakage point in an energy storage battery pack, characterized in that, The determination method includes: Nitrogen gas is filled into the test chamber of the energy storage battery PACK to the preset test pressure. After the filling valve is closed, the pressure holding stage is entered. The pressure value inside the chamber is continuously collected at the preset sampling frequency to obtain the pressure and time data sequence. The pressure and time data sequence is preprocessed and the characteristic parameters of the pressure drop curve are calculated; wherein, the characteristic parameters of the pressure drop curve include at least the segmented pressure drop rate, the pressure drop rate attenuation coefficient, the pressure drop rate variation coefficient, and the pressure drop acceleration rate. The characteristic parameters of the pressure drop curve are matched with preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type; At least one of the following: output pressure versus time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

2. The determination method according to claim 1, characterized in that, The pressure and time data series are preprocessed and the characteristic parameters of the pressure drop curve are calculated, including: The pressure and time data sequence is subjected to moving average filtering and temperature compensation correction to determine the preprocessed pressure and time data sequence; The pressure holding stage is divided into multiple segments, and the average pressure drop rate in each segment is calculated to determine the segmented pressure drop rate. The voltage drop rate attenuation coefficient is determined based on the ratio of the first segment voltage drop rate to the last segment voltage drop rate. The coefficient of variation of the voltage drop rate is determined based on the standard deviation and mean of the multiple segmented voltage drop rates; The pressure drop acceleration rate is determined by taking the second derivative of the pressure data with respect to the time data.

3. The determination method according to claim 1, characterized in that, When the leak type is the large leak type, the preset leak determination rule is: When the voltage drop rate of the first segment is greater than the first rate threshold, the voltage drop rate attenuation coefficient is greater than the first attenuation threshold, and the voltage drop rate of the last segment is less than the second rate threshold, the voltage drop curve of the large-leak type exhibits a steep-then-flat shape; wherein, the first rate threshold is greater than the second rate threshold.

4. The determination method according to claim 1, characterized in that, When the leak type is the micro-leak type, the preset leak determination rule is: When the coefficient of variation of the voltage drop rate is less than the first variation threshold, the coefficient of decay of the voltage drop rate is less than the second decay threshold, and the average value of the segmented voltage drop rates is less than the third rate threshold, the voltage drop curve of the micro-leakage type exhibits a slow and uniform shape; wherein, the second decay threshold is less than the first decay coefficient threshold, and the third rate threshold is between the first rate threshold and the second rate threshold.

5. The determination method according to claim 1, characterized in that, The step of matching the characteristic parameters of the pressure drop curve with preset leak detection rules to determine the leak type includes: When the leak type is the gap type, the preset leak determination rule is that the coefficient of variation of the pressure drop rate is greater than the second variation threshold, the positive step change or the positive spike is greater than the preset threshold, and the average value of the segmented pressure drop rate is in the first rate range. When the leak type is the variant, the preset leak determination rule is that the first segment voltage drop rate is greater than the fourth rate threshold, and the voltage drop rate attenuation coefficient is greater than the third attenuation threshold; wherein, the third attenuation threshold is higher than the first attenuation threshold. When the leak type is the crack type, the preset leak determination rule is that the average value of the segmented pressure drop rate falls into the second rate interval, the pressure drop rate attenuation coefficient is within the preset range, and the preset condition that characterizes the leakage rate as increasing instead of decreasing is met.

6. The determination method according to claim 1, characterized in that, The leak type also includes a composite type. When the extracted pressure drop curve feature parameters simultaneously meet the judgment rules of two or more leak types, a composite type prediction signal is output.

7. The determination method according to claim 1, characterized in that, After at least one of the output pressure versus time curve, segmented pressure drop rate, determined leak type, and troubleshooting path, the determination method further includes: Receive the repair and retest results after maintenance personnel conduct targeted troubleshooting according to the repair and troubleshooting path, and update and optimize the thresholds in the preset leak point judgment rules based on the repair and retest results.

8. A device for determining the type of airtightness leakage point in an energy storage battery pack, characterized in that, The determining device includes: The data acquisition module is used to fill the box of the energy storage battery PACK under test with nitrogen to the preset test pressure. After closing the filling valve, it enters the pressure holding stage and continuously collects the pressure value inside the box at a preset sampling frequency to obtain the pressure and time data sequence. The feature extraction module is used to preprocess the pressure and time data sequence and calculate the pressure drop curve feature parameters; wherein, the pressure drop curve feature parameters include at least the segmented pressure drop rate, pressure drop rate attenuation coefficient, pressure drop rate variation coefficient, and pressure drop acceleration rate. The rule determination module is used to match the characteristic parameters of the pressure drop curve with preset leak point determination rules to determine the leak point type; wherein, the leak point type includes at least large leak type, micro leak type, gap type, deformation type and crack type; The output module is used to output at least one of the following: pressure-time curve, segmented pressure drop rate, identified leak type, and troubleshooting path.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the method for determining the airtightness leakage type of the energy storage battery PACK as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method for determining the type of airtightness leaks in an energy storage battery PACK as described in any one of claims 1 to 7.

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