A portable battery cell self-discharge rapid test system

Abstract

The application relates to the technical field of battery cells, in particular to a portable battery cell self-discharge rapid test system, which is used for screening a batch of battery cells and comprises a test circuit, a first end and a second end of the test circuit are used for detachably connecting a battery cell to be tested, a high-precision source measurement unit is integrated in the test circuit and is used for applying a micro-current pulse excitation to the battery cell to be tested and monitoring a voltage response thereof, a controller is electrically connected with the high-precision source measurement unit and is configured to control the high-precision source measurement unit to perform a test operation, acquire multi-dimensional characteristic parameters of the battery cell to be tested, input the multi-dimensional characteristic parameters into a normalization scoring model based on batch statistics which is constructed in advance, acquire a quality score of the battery cell to be tested, and perform a grading screening on the battery cell to be tested according to the quality score of the battery cell to be tested in combination with a dynamic threshold of the battery cell, and finally acquire an evaluation result of the battery cell to be tested. The application solves the technical problems that the prior art is time-consuming and is easily affected by external environmental factors.

Description

Technical Field

[0001] This application relates to the field of battery cell technology, and in particular to a portable battery cell self-discharge rapid testing system. Background Technology

[0002] The internal resistance of a lithium-ion battery / cell is one of the intrinsic parameters of battery characteristics. If the internal resistance of the cell can be accurately measured, the characteristics and quality of the battery / cell, such as the self-discharge rate, can be quickly evaluated.

[0003] Due to the electrochemical characteristics of lithium-ion batteries / cells, the current method for measuring cell internal resistance or self-discharge rate is generally to measure open-circuit voltage (OVC) and then allow the cells to rest. This method is time-consuming, typically requiring 48 hours for a single measurement; furthermore, the measurement data is also affected by the resting environment.

[0004] Therefore, there is an urgent need for a portable rapid self-discharge testing system for battery cells. Summary of the Invention

[0005] (a) Technical problems to be solved In view of the above-mentioned shortcomings and deficiencies of the prior art, this application provides a portable battery cell self-discharge rapid testing system, which solves the technical problems of long measurement time and susceptibility to external environmental factors in the prior art.

[0006] (II) Technical Solution To achieve the above objectives, the main technical solutions adopted in this application include: This application provides a portable rapid self-discharge testing system for battery cells, used for screening batches of battery cells. The system includes: A test circuit, wherein the first and second terminals of the test circuit are used for detachably connecting to the battery cell under test; A high-precision source measurement unit, integrated in the test circuit, is used to apply bidirectional micro-current pulse excitation to the cell under test and monitor its voltage response; The controller, electrically connected to the high-precision source measurement unit, is configured as follows: The high-precision source measurement unit is controlled to perform test operations to obtain multi-dimensional characteristic parameters of the cell under test. The multi-dimensional characteristic parameters include at least the static voltage change integral difference characterizing the static self-discharge characteristics of the cell, the charging charge difference characterizing the dynamic charging polarization loss of the cell, and the discharge charge difference characterizing the dynamic discharge efficiency and internal consistency of the cell. The multidimensional feature parameters are input into a pre-constructed normalized scoring model based on batch statistics to obtain the quality score of the cell under test. The cell under test is then graded and screened based on the quality score and the cell dynamic threshold to obtain the final evaluation result of the cell under test.

[0007] Optionally, in some embodiments of this application, the controller is configured to: The test operation is performed on the pre-treated battery cell; wherein, the pre-treatment means that the battery cell under test has been discharged to 0% state of charge before being connected to the test system, and has been placed in an environment with a constant temperature of 25℃±1℃ for 8 hours.

[0008] Optionally, in some embodiments of this application, the controller controls the high-precision source measurement unit to apply bidirectional micro-current pulse excitation in the following manner: The frequency of the bidirectional microcurrent pulse is dynamically adjusted according to the relaxation time constant of the cell under test. When the change of the relaxation time constant is detected to exceed a threshold, the pulse frequency is adjusted inversely within the range of 50Hz-500Hz.

[0009] Optionally, in some embodiments of this application, the controller obtains the integral difference of the static voltage change in the following manner: Before and after applying bidirectional microcurrent pulse excitation, the high-precision source measurement unit is controlled to enter a first voltage monitoring period and a second voltage monitoring period, respectively. During the first voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a first open-circuit voltage matrix; during the second voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a second open-circuit voltage matrix. Obtain the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix, and use the difference between the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix as the static voltage change integral difference characterizing the static self-discharge characteristics of the battery cell.

[0010] Optionally, in some embodiments of this application, the controller obtains the difference in charging charge by means of: The high-precision source measurement unit is controlled to charge the battery cell under test to the first offset voltage in constant voltage mode, and the charging time and charging current are obtained. The first charging charge is obtained based on the charging time and charging current. After controlling the high-precision source measurement unit to discharge the cell under test to the open circuit voltage in constant voltage mode, the discharge time, discharge current and cell voltage are obtained. The first released charge is obtained based on the discharge time and discharge current. The above steps are repeated a certain number of times to obtain the arithmetic mean of the difference between the first charging charge and the first released charge as the charging charge difference value characterizing the dynamic charging polarization loss of the cell.

[0011] Optionally, in some embodiments of this application, the controller obtains the discharge charge difference in the following manner: The high-precision source measurement unit is controlled to discharge the cell under test to the second offset voltage in constant voltage mode, and the discharge time and discharge current are obtained. The second released charge is obtained based on the discharge time and discharge current. The high-precision source measurement unit is controlled to charge the cell under test to the open circuit voltage in constant voltage mode, and the charging time and charging current are obtained. The second charging charge is obtained based on the charging time and charging current. The above steps are repeated 12 times, and the arithmetic mean of the difference between the second charging charge and the second released charge is obtained as the discharge charge difference value characterizing the dynamic discharge efficiency and internal consistency of the cell.

[0012] Optionally, in some embodiments of this application, the controller is further configured to perform a consistency check during repeated operations, specifically including: The standard deviation of the charge difference obtained in each loop is obtained. When the standard deviation exceeds the preset stability threshold, the data of the current test operation is determined to be invalid and all test operations are automatically re-executed.

[0013] Optionally, in some embodiments of this application, the controller constructs the normalized scoring model based on batch statistics in the following manner: Obtain the multidimensional feature parameter dataset of all cells in the batch to which the cell under test belongs, and obtain the batch mean and standard deviation of each feature parameter; Based on the batch mean and standard deviation, Mahalanobis distance is used to obtain the degree of deviation between the characteristic parameters of the cell under test and the current batch distribution center, and the degree of deviation is normalized to a quality score of 0-100 using the sigmoid function to obtain the quality score of the cell under test.

[0014] Optionally, in some embodiments of this application, the controller performs graded screening of the cells under test based on the quality score of the cells under test combined with the cell dynamic threshold, and obtains the final evaluation result of the cells under test, including: A static grade threshold is set for initial classification; an adaptive pass threshold is calculated in real time based on the test data of the current batch of the cell under test; the initial classification result is cross-validated with the adaptive pass threshold; for cells that are initially rated as qualified but whose quality score is lower than the adaptive pass threshold, downgrading is implemented.

[0015] Optionally, in some embodiments of this application, the real-time calculation of the adaptive pass threshold based on the test data of the current batch of the battery cell under test specifically includes: A time-decrease-based weighted algorithm is used to calculate a weighted average of the quality scores of qualified cells in the current batch, arranged in chronological order of testing time, with cells tested more recently having a higher weight. Calculate the confidence interval of the weighted average, and use the lower limit of the confidence interval as the adaptive qualified threshold.

[0016] (III) Beneficial Effects The beneficial effects of this application are as follows: The portable cell self-discharge rapid testing system of this application adopts a high-precision source measurement unit that integrates bidirectional micro-current pulse excitation and voltage response monitoring functions. By acquiring multi-dimensional characteristic parameters such as static voltage change integral difference, charging charge difference, and discharging charge difference, and combining a batch-based statistical normalized scoring model and cell dynamic threshold for graded screening, compared with the prior art, it can get rid of the dependence on long-term storage, significantly shorten the testing cycle, and avoid the interference of the storage environment on the measurement data. It takes into account the comprehensive evaluation of the static self-discharge characteristics and dynamic performance of the cell, significantly improving the efficiency, accuracy and anti-interference ability of batch cell screening, and achieving the technical effect of rapid, accurate and stable screening of high-quality cells. Attached Figure Description

[0017] Figure 1 This is a structural diagram of a portable battery cell self-discharge rapid testing system according to an embodiment of this application; Figure 2 This is a controller configuration diagram of a portable battery cell self-discharge rapid testing system according to an embodiment of this application. Detailed Implementation

[0018] To better explain and facilitate understanding of this application, the following detailed description of the application is provided in conjunction with the accompanying drawings and specific embodiments.

[0019] In existing technologies, the internal resistance of lithium-ion batteries / cells is an intrinsic parameter of battery characteristics. Accurately measuring its value is key to quickly evaluating the characteristics and quality of batteries / cells (such as self-discharge rate). However, the current mainstream open-circuit voltage plus rest measurement method not only takes more than 72 hours, which is extremely time-consuming and cannot meet the needs of rapid sorting in production lines, but is also easily affected by factors such as ambient temperature and humidity and battery aging, resulting in insufficient accuracy of measurement results.

[0020] To address this technical pain point, the core technical problem this application aims to solve is to overcome the bottlenecks of existing methods, such as long processing time and weak anti-interference capabilities, and to achieve rapid, accurate, stable detection and graded screening of the self-discharge characteristics of batch battery cells.

[0021] To address this core issue, this application constructs a portable rapid self-discharge testing system for battery cells. The system connects to the battery cell under test via a detachable test circuit. After preprocessing, a bidirectional micro-current pulse excitation with dynamically adjustable frequency is applied using a high-precision source measurement unit integrated into the test circuit, and the voltage response is monitored. The controller acquires multi-dimensional characteristic parameters such as the integral difference of static voltage change, the difference in charging charge, and the difference in discharging charge. Combined with a normalized scoring model based on batch statistics and a dynamic adaptive pass threshold, the system completes the quality scoring and grading of the battery cell under test.

[0022] The above-mentioned solution can significantly shorten the testing cycle, eliminate environmental interference, take into account both the static self-discharge characteristics and dynamic performance evaluation of the battery cells, and significantly improve the efficiency, accuracy and stability of batch battery cell screening, thus meeting the rapid sorting requirements of the production line.

[0023] To better understand the above technical solutions, exemplary embodiments of this application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application can be understood more clearly and thoroughly, and that the scope of this application can be fully conveyed to those skilled in the art.

[0024] Example 1

[0025] Figure 1 This is a structural diagram of a portable battery cell self-discharge rapid testing system according to an embodiment of this application. Figure 1 As shown, this rapid testing system is used to screen battery cells in batches, including: The test circuit has a first and a second terminal for detachable connection to the battery cell under test.

[0026] The test circuit employs spring clips or probe interfaces at both ends for quick connection and disconnection of the battery cell under test, meeting the high throughput requirements of production lines. Furthermore, this test circuit is compatible with mainstream battery cell specifications such as 18650, 21700, and pouch cells, and features a low contact resistance of ≤10mΩ and a single insertion / removal life of ≥100,000 cycles. It also integrates a foolproof positioning structure to effectively prevent equipment damage or test failure caused by reversed battery cell polarity. To improve batch testing efficiency, the circuit adopts a matrix channel layout, with a single system supporting 8 / 16 / 32 channels for parallel testing (flexible expansion based on production line capacity). Each channel is independently isolated with crosstalk ≤-80dB, ensuring data does not interfere with each other when multiple cells are tested simultaneously.

[0027] A high-precision source measurement unit, integrated in the test circuit, is used to apply bidirectional micro-current pulse excitation to the cell under test and monitor its voltage response.

[0028] Specifically, the high-precision source measurement unit is the core component for realizing "bidirectional micro-current excitation-voltage transient response monitoring." It undertakes the critical task of applying controllable disturbance signals to the cell under test and accurately capturing its electrical response characteristics, and must meet the stringent requirements of batch screening for "accuracy, speed, and consistency." Its core functions integrate "micro-current excitation output," "voltage / current synchronous monitoring," and "mode adaptive switching," serving as a crucial hub connecting the test circuit and the data processing system, and efficiently matching static and dynamic testing processes.

[0029] In the specific implementation process, the high-precision source measurement unit is responsible for applying bidirectional micro-current pulse excitation to the cell under test. This pulse includes both charging and discharging directions, simulating the minute disturbances of the cell in a near-open-circuit state. The high-precision source measurement unit intelligently switches between constant current (CC) and constant voltage (CV) modes to control the amplitude and timing of current injection, while simultaneously monitoring the transient response of the cell's terminal voltage in real time. The voltage response data is collected and transmitted to the controller, where it is analyzed in conjunction with an equivalent circuit model to calculate the cell's self-discharge equivalent resistance and leakage current parameters. This allows for qualitative or semi-quantitative evaluation of a single cell within minutes, significantly improving screening efficiency. Furthermore, this solution also supports batch parallel testing. Through multiplexer expansion, it enables simultaneous excitation and monitoring of multiple cells, ensuring the consistency and reliability of the screening process.

[0030] In terms of hardware characteristics, the high-precision source measurement unit has an output current range of -100μA to +100μA and a current resolution of ≤1nA, which can avoid irreversible damage to the internal structure of the battery cell caused by large current; it supports square wave pulse output, the pulse width can be adjusted within 1ms to 100ms, and the rise / fall time is ≤50ns, ensuring the controllability and transient characteristics of the excitation signal; the switching response time between charging current and discharging current is ≤10μs, which can realize "charge-discharge-rest" cyclic excitation, perfectly adapting to dynamic testing requirements.

[0031] The controller is electrically connected to the high-precision source measurement unit; see [link / reference]. Figure 2 The controller is configured as follows: The high-precision source measurement unit is controlled to perform test operations to obtain multi-dimensional characteristic parameters of the battery cell under test. The multi-dimensional characteristic parameters include at least the static voltage change integral difference characterizing the static self-discharge characteristics of the battery cell, the charging charge difference characterizing the dynamic charging polarization loss of the battery cell, and the discharge charge difference characterizing the dynamic discharge efficiency and internal consistency of the battery cell.

[0032] The test operations include static test operations and dynamic test operations; In this embodiment, the controller controls the high-precision source measurement unit to apply bidirectional micro-current pulse excitation in the following manner: The frequency of the bidirectional micro-current pulse is dynamically adjusted according to the relaxation time constant of the cell under test. When the change in the relaxation time constant exceeds a threshold, the pulse frequency is adjusted inversely within the range of 50Hz-500Hz.

[0033] Specifically, the controller uses an adaptive frequency control algorithm to precisely manage the application of bidirectional micro-current pulse excitation by the high-precision source measurement unit. Its core lies in real-time feedback and optimization based on the dynamic response characteristics of the cell under test—namely, the relaxation time constant. The relaxation time constant is a key parameter that measures the time required for the cell's terminal voltage to recover to a steady state after the micro-current excitation is removed, directly reflecting the degree of polarization and charge migration rate within the cell.

[0034] The controller's execution logic begins with the initial frequency setting and the measurement of the reference relaxation time. The controller first applies a set of bidirectional micro-current pulses at a preset initial frequency, and during this process, uses a high-precision source measurement unit to monitor the cell's voltage transient response curve. An exponential fitting algorithm is then used to calculate the reference relaxation time constant for this state, which serves as the benchmark for subsequent comparisons. Subsequently, the system enters the real-time monitoring and threshold judgment phase. During continuous testing, the controller synchronously controls the high-precision source measurement unit to apply pulses and calculate the latest relaxation time constant, continuously calculating its relative deviation from the reference value. Once the system detects that the relative deviation exceeds a preset dynamic threshold, such as 10%, it determines that the cell's internal state has changed significantly.

[0035] Based on this, the controller immediately initiates an inverse proportional adaptive frequency adjustment mechanism. Its control law follows a clear mathematical relationship: the new pulse frequency is inversely proportional to the currently measured relaxation time constant. To ensure stability and reliability, frequency adjustment is strictly limited to an effective operating range of 50Hz to 500Hz. Specifically, when an increase in the relaxation time constant is detected (indicating slower cell response and increased polarization), the controller reduces the pulse frequency to provide more sufficient relaxation time for voltage recovery, thereby avoiding measurement distortion. Conversely, when the relaxation time constant decreases, the controller correspondingly increases the frequency, significantly improving test throughput efficiency while ensuring data accuracy. This dynamic adjustment mechanism ensures that the system can adapt to cells of different models, capacities, and aging states, always operating at the optimal excitation-relaxation balance point, ultimately achieving a balance between accuracy and efficiency.

[0036] This application makes the above-mentioned dynamic adjustments, which intelligently balance the test accuracy and efficiency by matching the polarization characteristics of the battery cell in real time. It avoids the measurement distortion caused by fixed high-frequency excitation and ensures the accuracy of the data. It also overcomes the inefficiency caused by fixed low-frequency excitation and significantly shortens the test time, thereby realizing the rapid, accurate and universal performance screening of diverse battery cells.

[0037] Furthermore, the controller is configured as follows: The test operation is performed on the pre-treated battery cell; wherein, the pre-treatment means that the battery cell under test has been discharged to 0% state of charge before being connected to the test system, and has been placed in an environment with a constant temperature of 25℃±1℃ for 8 hours.

[0038] Specifically, the pretreatment process aims to establish a unified initial benchmark for testing. First, the battery cell needs to be placed in a constant temperature environment of 25℃±1℃ until its overall temperature stabilizes. Then, under this constant temperature condition, an independent standard charge and discharge device (not this test system) is used to discharge the battery cell with a constant current to the cutoff voltage of 0% state of charge using a standard current. Finally, it is left to stand in the same constant temperature environment for 8 hours to ensure that the standing process can completely eliminate the polarization effect and internal stress of the battery cell, thereby providing a stable and comparable test object for subsequent high-precision microcurrent testing.

[0039] In the specific implementation process, the controller obtains the integral difference of static voltage change in the following way: Before and after applying bidirectional microcurrent pulse excitation, the high-precision source measurement unit is controlled to enter a first voltage monitoring period and a second voltage monitoring period, respectively. During the first voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a first open-circuit voltage matrix; during the second voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a second open-circuit voltage matrix. Obtain the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix, and use the difference between the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix as the static voltage change integral difference characterizing the static self-discharge characteristics of the battery cell.

[0040] In the specific implementation process, the controller obtains the high-precision integral difference of static voltage change through a precisely timed multi-stage operation. The core of this process lies in comparing the overall stability change of the open-circuit voltage of the battery cell before and after being subjected to micro-current pulse disturbances.

[0041] First, before applying any bidirectional micro-current pulse excitation, the controller initiates an initial voltage monitoring phase. During this phase, the controller sets the high-precision source measurement unit to a high-impedance voltage measurement mode, continuously monitoring the cell open-circuit voltage with extremely high input impedance, thereby avoiding any load effect on the cell. The controller continuously acquires multiple voltage data points and their corresponding timestamps at millisecond intervals, forming a set of initial voltage timing data to generate the first open-circuit voltage matrix. After completing the predetermined dynamic test, the controller immediately initiates a subsequent voltage monitoring phase of the same duration. Using the same high-impedance mode and millisecond-level sampling intervals, another set of voltage timing data is acquired as a record of the voltage state after disturbance, generating a second open-circuit voltage matrix. Finally, the areas of the first and second open-circuit voltage matrices are obtained, and the difference between the areas of the first and second open-circuit voltage matrices is used as the static voltage change integral difference characterizing the static self-discharge characteristics of the battery cell.

[0042] The above method, which uses the integral area difference, comprehensively reflects the overall drift trend and stability of the voltage throughout the monitoring period. Compared with a single instantaneous voltage comparison, it can more effectively suppress random noise interference, thus sensitively and reliably capturing voltage changes caused by minute self-discharge inside the cell, providing a stable and effective quantitative indicator for evaluating the static self-discharge characteristics of the cell.

[0043] Furthermore, the controller obtains the difference in charging charge in the following way: The high-precision source measurement unit is controlled to charge the cell under test to the first offset voltage in constant voltage mode, and the charging time and charging current are obtained. The first charging charge is obtained based on the charging time and charging current. After the high-precision source measurement unit controls the cell under test to discharge and restore it to the open circuit voltage in constant voltage mode, the discharge time, discharge current and cell voltage are obtained. The first released charge is obtained based on the discharge time and discharge current. The above steps are repeated 12 times, and the arithmetic mean of the difference between the first charging charge and the first released charge is obtained as the charging charge difference value characterizing the dynamic charging polarization loss of the cell.

[0044] Specifically, the controller first controls the high-precision source measurement unit to operate in constant voltage mode, precisely increasing the voltage of the cell under test from a stable open-circuit voltage value by an extremely small offset; this target voltage is the first offset voltage. Throughout the charging process, the controller synchronously and with high precision monitors and records the total charging time and the real-time changing charging current. Subsequently, the controller calculates the total charge injected into the cell to achieve this voltage offset by integrating the charging current at each moment with the corresponding time element; this is the first charging charge. This charge represents the total externally input energy.

[0045] Next, the controller maintains the source measurement unit in constant voltage mode, discharging the cell voltage from the first offset voltage to precisely restore it to the initial open-circuit voltage. During this discharge recovery process, the controller also records the discharge time, discharge current, and cell voltage. Through the same integration calculation, the total charge released from the cell, i.e., the first released charge, is calculated. In an ideal lossless cell, the released charge should equal the injected charge. However, in actual cells, due to polarization effects and slight self-discharge, the released charge will be slightly less than the injected amount.

[0046] To eliminate random errors and obtain reliable data, the controller repeats the complete "charge-discharge recovery" cycle 12 times. In each cycle, an instantaneous difference in charging charge is calculated (i.e., the first charging charge minus the first releasing charge in that cycle). After all cycles are completed, the controller performs statistical analysis on all valid instantaneous differences, eliminates possible outliers, and finally calculates the arithmetic mean of the remaining differences. This arithmetic mean represents the charging charge difference that characterizes the dynamic charging polarization loss of the battery cell. A positive value, and the larger the value, the greater the irreversible charge loss caused by polarization, internal micro-short circuits, and other effects during charging, resulting in poorer dynamic performance. Conversely, the closer the value is to zero, the higher the charge storage and release efficiency of the battery cell, and the more ideal the dynamic response. This precise measurement method enables the effective quantification of the microscopic polarization loss inside the battery cell.

[0047] Furthermore, the controller precisely acquires the discharge charge difference, which characterizes the dynamic discharge efficiency and internal consistency of the battery cell, through a discharge and charge compensation cycle symmetrical to the charging test. This process aims to quantify the energy loss and internal differences of the battery cell when discharging under minute negative voltage disturbances. Specifically, the controller acquires the discharge charge difference in the following ways: The high-precision source measurement unit is controlled to discharge the cell under test to the second offset voltage in constant voltage mode, and the discharge time and discharge current are obtained. The second released charge is obtained based on the discharge time and discharge current. The high-precision source measurement unit is controlled to charge the cell under test to the open circuit voltage in constant voltage mode, and the charging time and charging current are obtained. The second charging charge is obtained based on the charging time and charging current. The above steps are repeated a certain number of times, and the arithmetic mean of the difference between the second charging charge and the second released charge is obtained as the discharge charge difference value characterizing the dynamic discharge efficiency and internal consistency of the cell.

[0048] In practical implementation, the smaller the absolute value (closer to zero) of the difference between the dynamic discharge efficiency and the internal consistency of the battery cell, the less energy loss occurs during the discharge process, the higher the efficiency of charge release and compensation, the more consistent the electrochemical behavior of each internal part, and the better the dynamic performance. Together with the difference in charging charge, which characterizes the dynamic charging polarization loss of the battery cell, it reveals the dynamic response characteristics of the battery cell from different dimensions.

[0049] In addition, to ensure the reliability and repeatability of test data, the controller is configured to perform real-time consistency checks during the repeated calculation of charge difference. This check mechanism is a key step in ensuring measurement accuracy and result reliability. The check mechanism includes: The standard deviation of the charge difference obtained in each loop is obtained. When the standard deviation exceeds the preset stability threshold, the data of the current test operation is determined to be invalid and all test operations are automatically re-executed.

[0050] Specifically, in each complete test operation, such as the 12 "charge-discharge recovery" cycles performed to obtain the difference in charging charge, the controller not only calculates the final average value but also simultaneously acquires the instantaneous charge difference calculated for each independent cycle and calculates the standard deviation of this set of instantaneous differences. This standard deviation quantitatively describes the dispersion of a single measurement value around its average value and is a direct indicator for evaluating data volatility and the stability of the test process. The system in this application presets a stability threshold, which is a reasonable range set based on extensive prior experiments, equipment accuracy, and statistical regularities. During the test, the controller compares the standard deviation calculated in real time with this stability threshold.

[0051] If the calculated standard deviation does not exceed the preset stability threshold, it indicates that the data dispersion is small and the repeatability is good. The controller determines that the current test operation is valid and continues to execute subsequent average calculations and recordings. Conversely, if the standard deviation exceeds the stability threshold, it means that abnormal fluctuations or unacceptable dispersion have occurred in the multiple cycles of this test, which may be due to factors such as transient interference from the external environment, poor cell contact, or unstable equipment operation.

[0052] Once data is deemed invalid, the controller will automatically trigger a safety mechanism: first, discard all currently collected data; then, after a brief pause, the control test system will automatically re-execute all test operations, i.e., restart a new round of 12 cycles. This design endows the system with self-diagnosis and self-repair capabilities, effectively preventing the adoption of erroneous data caused by accidental factors, thereby ensuring that the final output charge difference result has high consistency and reliability, meeting the stringent requirements of high-precision quality screening on the production line.

[0053] In addition, the controller is also configured as follows: Multidimensional feature parameters are input into a pre-constructed batch statistics-based normalized scoring model to obtain the quality score of the cell under test. Based on the quality score of the cell under test and the cell dynamic threshold, the cell under test is graded and screened to obtain the final evaluation result of the cell under test.

[0054] The controller constructs a normalized scoring model based on batch statistics in the following way: Obtain the multidimensional feature parameter dataset of all cells in the batch to which the cell under test belongs, and obtain the batch mean and standard deviation of each feature parameter; Based on the batch mean and standard deviation, Mahalanobis distance is used to obtain the degree of deviation between the characteristic parameters of the cell under test and the current batch distribution center. The deviation degree is then normalized to a quality score of 0-100 using the sigmoid function to obtain the quality score of the cell under test.

[0055] The controller uses the quality score of the battery cell under test combined with the dynamic threshold of the cell to classify and screen the battery cells under test, and obtains the final evaluation results of the battery cells under test, including: A static grade threshold is set for initial classification; an adaptive pass threshold is calculated in real time based on the test data of the current batch of the cell under test; the initial classification results are cross-validated with the adaptive pass threshold; for cells that are initially rated as qualified but whose quality score is lower than the adaptive pass threshold, downgrading is implemented.

[0056] Specifically, the real-time calculation of the adaptive pass threshold based on the test data of the current batch of the battery cell under test includes: A time-decrease-based weighted algorithm is used to calculate a weighted average of the quality scores of qualified cells in the current batch, arranged in chronological order of testing time, with cells tested more recently having a higher weight. Calculate the confidence interval of the weighted average, and use the lower limit of the confidence interval as the adaptive qualified threshold.

[0057] In the above model construction process, Mahalanobis distance is used to obtain the deviation of the characteristic parameters of the tested cell from the current batch distribution center. Mahalanobis distance corrects the correlation between features through the "covariance matrix," and can more accurately quantify the "deviation" of a single cell relative to the overall batch distribution. Simply put, the larger the Mahalanobis distance, the more significant the difference between the characteristics of the cell and the majority of cells in the batch, which may indicate a risk of abnormal self-discharge. During calculation, the controller first constructs the covariance matrix of the three characteristic parameters, then inverts the covariance matrix, and then constructs the "deviation vector" by the difference between the three characteristic parameters of the tested cell and the corresponding batch mean. The Mahalanobis distance value is obtained through vector operation. For example, if the voltage change integral difference of a tested cell is 8.5 μV•s, the charging charge difference is 1.5 mC, and the discharging charge difference is -1.0 mC, the Mahalanobis distance calculated by combining the covariance matrix is ​​2.8, which means that the deviation of this cell from the batch distribution center is relatively large and requires special attention.

[0058] The deviation is then normalized to a quality score of 0-100 using the sigmoid function. The Mahalanobis distance can range from 0 to positive infinity. The sigmoid function maps any real number to the interval of 0-1, and then transforms it into a score of 0-100 through linear scaling. The scoring curve exhibits a characteristic of "flat in the middle and steep at both ends"—that is, when the deviation is small (Mahalanobis distance is close to 0), the score is close to 100 (high-quality cell); when the deviation is moderate, the score changes smoothly (most qualified cells are concentrated in this interval); when the deviation is extremely large (Mahalanobis distance is far beyond the normal range), the score drops rapidly to 0 (defective cell). This characteristic can effectively avoid the interference of extreme values ​​on the scoring of most cells, while highlighting the differences of defective cells.

[0059] Furthermore, after obtaining the quality score of the battery cell under test, the controller combines it with the cell's dynamic threshold to complete the grading and screening, obtaining the final evaluation result. Here, the dynamic threshold is not a fixed value, but is dynamically determined based on the quality score distribution of the current batch.

[0060] Specifically, the controller first sorts the quality scores of all valid cells in this batch, and then determines the quantile thresholds based on the production line's screening requirements. For example, if a batch contains 988 cells and requires 12% (approximately 119) to be grade A, then the score of the 119th cell after sorting is taken as the grade A threshold (i.e., the top 12% are grade A); if 75% (approximately 741) to be grade B, then the score of the 119th + 741st = 860th cell after sorting is taken as the grade B threshold (i.e., 12% to 87% are grade B), and the remaining 13% are grade C (it needs to be confirmed whether it meets the requirement of ≤10%, and if not, the proportion is fine-tuned). Optionally, if the batch scores follow a normal distribution, the threshold can also be determined by "batch score mean ± standard deviation": for example, grade A is "mean + 1.28 times the standard deviation" (corresponding to the 90th percentile), and grade B is "mean - 0.84 times the standard deviation" (corresponding to the 20th percentile). That is, a score ≥ mean + 1.28σ is grade A, a score between mean - 0.84σ and mean + 1.28σ is grade B, and a score < mean - 0.84σ is grade C, ensuring that the threshold is closely related to the batch distribution.

[0061] Furthermore, the controller will also conduct "sampling retesting" on Grade A cells—randomly select Grade A cells at a rate of 5% to 10% and re-execute static and dynamic tests. If the proportion of Grade A cells with scores ≥ 98% after retesting is still ≥ Grade A threshold, the batch screening results are deemed valid; if it is lower than 98%, the batch statistics and dynamic threshold are recalculated and the screening is conducted again to avoid misjudgment due to statistical deviations in the previous data.

[0062] This application discloses a portable rapid self-discharge testing system for battery cells. Through adaptive micro-current excitation technology with dynamic frequency adjustment, combined with a multi-parameter fusion evaluation model of static voltage integral difference and dynamic charge difference, it achieves high-precision and high-efficiency screening of battery cell self-discharge performance within minutes. Its batch-based Mahalanobis distance scoring mechanism and dynamic threshold grading strategy ensure the adaptability and high reliability of the screening results to batch characteristics, effectively improving the accuracy and consistency of production line sorting, and forming a fast, accurate, and universal quality control technology closed loop.

[0063] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0064] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0065] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first and second features are in direct contact, or that they are in indirect contact through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0066] In the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0067] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make modifications, alterations, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A portable rapid self-discharge testing system for battery cells, characterized in that, The system is used to screen battery cells in batches, including: A test circuit, wherein the first and second terminals of the test circuit are used for detachably connecting to the battery cell under test; A high-precision source measurement unit, integrated in the test circuit, is used to apply bidirectional micro-current pulse excitation to the cell under test and monitor its voltage response; The controller, electrically connected to the high-precision source measurement unit, is configured as follows: The high-precision source measurement unit is controlled to perform test operations to obtain multi-dimensional characteristic parameters of the cell under test. The multi-dimensional characteristic parameters include at least the static voltage change integral difference characterizing the static self-discharge characteristics of the cell, the charging charge difference characterizing the dynamic charging polarization loss of the cell, and the discharge charge difference characterizing the dynamic discharge efficiency and internal consistency of the cell. The multidimensional feature parameters are input into a pre-constructed normalized scoring model based on batch statistics to obtain the quality score of the cell under test. The cell under test is then graded and screened based on the quality score and the cell dynamic threshold to obtain the final evaluation result of the cell under test. The controller obtains the integral difference of static voltage change in the following manner: Before and after applying bidirectional microcurrent pulse excitation, the high-precision source measurement unit is controlled to enter a first voltage monitoring period and a second voltage monitoring period, respectively. During the first voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a first open-circuit voltage matrix; during the second voltage monitoring period, the open-circuit voltage of the cell under test is monitored to generate a second open-circuit voltage matrix. Obtain the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix, and use the difference between the areas of the first open-circuit voltage matrix and the second open-circuit voltage matrix as the static voltage change integral difference characterizing the static self-discharge characteristics of the battery cell.

2. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller is configured to: The test operation is performed on the pre-treated battery cell; wherein, the pre-treatment means that the battery cell under test has been discharged to 0% state of charge before being connected to the test system, and has been placed in an environment with a constant temperature of 25℃±1℃ for 8 hours.

3. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller controls the high-precision source measurement unit to apply bidirectional micro-current pulse excitation in the following manner: The frequency of the bidirectional microcurrent pulse is dynamically adjusted according to the relaxation time constant of the cell under test. When the change of the relaxation time constant is detected to exceed a threshold, the pulse frequency is adjusted inversely within the range of 50Hz-500Hz.

4. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller obtains the difference in charging charge through the following method: The high-precision source measurement unit is controlled to charge the battery cell under test to the first offset voltage in constant voltage mode, and the charging time and charging current are obtained. The first charging charge is obtained based on the charging time and charging current. After controlling the high-precision source measurement unit to discharge the cell under test to the open circuit voltage in constant voltage mode, the discharge time, discharge current and cell voltage are obtained, and the first released charge is obtained based on the discharge time and discharge current. Repeat the above steps a certain number of times to obtain the arithmetic mean of the difference between the first charging charge and the first releasing charge as the charging charge difference value characterizing the dynamic charging polarization loss of the battery cell.

5. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller obtains the difference in discharge charge in the following manner: The high-precision source measurement unit is controlled to discharge the cell under test to the second offset voltage in constant voltage mode, and the discharge time and discharge current are obtained. The second released charge is obtained based on the discharge time and discharge current. The high-precision source measurement unit is controlled to charge the cell under test to the open circuit voltage in constant voltage mode, and the charging time and charging current are obtained. The second charging charge is obtained based on the charging time and charging current. The above steps are repeated 12 times, and the arithmetic mean of the difference between the second charging charge and the second released charge is obtained as the discharge charge difference value characterizing the dynamic discharge efficiency and internal consistency of the cell.

6. The portable cell self-discharge rapid testing system according to claim 4 or 5, characterized in that, During repeated operations, the controller is also configured to perform consistency checks, specifically including: The standard deviation of the charge difference obtained in each loop is obtained. When the standard deviation exceeds the preset stability threshold, the data of the current test operation is determined to be invalid and all test operations are automatically re-executed.

7. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller constructs the normalized scoring model based on batch statistics in the following manner: Obtain the multidimensional feature parameter dataset of all cells in the batch to which the cell under test belongs, and obtain the batch mean and standard deviation of each feature parameter; Based on the batch mean and standard deviation, Mahalanobis distance is used to obtain the degree of deviation between the characteristic parameters of the cell under test and the current batch distribution center, and the degree of deviation is normalized to a quality score of 0-100 using the sigmoid function to obtain the quality score of the cell under test.

8. The portable cell self-discharge rapid testing system according to claim 1, characterized in that, The controller performs graded screening of the cells under test based on the quality score of the cells under test and the cell dynamic threshold, and obtains the final evaluation result of the cells under test, including: A static grade threshold is set for initial classification; an adaptive pass threshold is calculated in real time based on the test data of the current batch of the cell under test; the initial classification result is cross-validated with the adaptive pass threshold; for cells that are initially rated as qualified but whose quality score is lower than the adaptive pass threshold, downgrading is implemented.

9. The portable cell self-discharge rapid testing system according to claim 8, characterized in that, The adaptive pass threshold is calculated in real time based on the test data of the current batch of the battery cell under test, specifically including: A time-decrease-based weighted algorithm is used to calculate a weighted average of the quality scores of qualified cells in the current batch, arranged in chronological order of testing time, with cells tested more recently having a higher weight. Calculate the confidence interval of the weighted average, and use the lower limit of the confidence interval as the adaptive qualified threshold.

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