Lithium ion battery self-discharge detection method and system
By analyzing the dQ/dV curve characteristics of lithium-ion batteries, determining the self-discharge test point and calculating the self-discharge coefficient K, the problem of the inability to effectively identify self-discharge anomalies in existing technologies is solved, efficient self-discharge detection is achieved, and product quality and reliability are improved.
Patent Information
- Application Number
- CN202511074638.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-31
- Publication Date
- 2025-10-10
AI Technical Summary
Existing lithium-ion battery self-discharge detection methods are unable to effectively identify cells with abnormally high self-discharge rates, resulting in defective products entering the customer end, increasing customer complaints and after-sales costs.
By analyzing the dQ/dV curve characteristics of lithium-ion batteries, the continuous SOC region where the absolute value of dQ/dV is less than the preset threshold is determined. Self-discharge test points are set within this region, the self-discharge coefficient K is calculated, and the outlier rate is calculated using the box plot method, 3σ criterion or Mahalanobis distance method to determine the battery quality.
The detection rate of abnormal self-discharge products has been improved, customer complaints and after-sales costs caused by CIM problems have been reduced, market competitiveness and customer satisfaction have been enhanced, and product quality control capabilities have been ensured.
Smart Images
Figure CN120761855A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of lithium-ion battery detection, and in particular to a lithium-ion battery self-discharge detection method and system based on dQ / dV curve characteristics. Background Art
[0002] With the rapid development of lithium-ion battery technology, its energy density has increased significantly, while the thickness of the separator has gradually decreased. In multi-series and parallel applications such as laptop computers, the problem of CIM (cell imbalance) has become increasingly prominent due to poor control of cell self-discharge consistency.
[0003] Currently, lithium-ion battery self-discharge performance is primarily screened based on factory-tested SOC (State of Charge), typically at a fixed 30% or 60% SOC. However, this method has significant limitations and cannot effectively identify cells with abnormally high self-discharge rates. As a result, some defective products successfully escape and reach end-users, leading to increased customer complaints and higher after-sales costs.
[0004] The main existing testing method involves fully charging a lithium battery, leaving it in a high-temperature environment of 40-60°C, and calculating the self-discharge rate by measuring the difference in open-circuit voltage before and after the battery is fully charged. This method uses a fixed fully charged state for testing and fails to optimize testing conditions based on the battery's electrochemical characteristics.
[0005] Therefore, there is an urgent need for a lithium-ion battery self-discharge detection method and system to improve the detection rate of abnormal self-discharge in lithium-ion cells, so as to ensure the quality and reliability of lithium-ion batteries and meet market demand. Summary of the Invention
[0006] The purpose of the present invention is to provide a lithium-ion battery self-discharge detection method and system to improve the detection rate of abnormal self-discharge products and significantly reduce the frequency of CIM problems on the client side.
[0007] To achieve this object, the present invention adopts the following technical solutions:
[0008] In a first aspect, the present invention provides a method for detecting self-discharge of a lithium-ion battery, comprising the following steps:
[0009] S1. Discharging the lithium-ion battery to be tested with a small current to obtain a dQ / dV curve of the lithium-ion battery to be tested;
[0010] S2. Analyze the characteristics of the dQ / dV curve to determine continuous SOC regions where the absolute value of dQ / dV is less than a preset threshold;
[0011] S3, setting a self-discharge test point within the determined SOC region;
[0012] S4, detecting self-discharge of each lithium ion battery of the same batch as the lithium ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium ion battery;
[0013] S5, calculating an outlier rate of the current batch of lithium ion batteries according to the self-discharge coefficient K of each lithium ion battery;
[0014] S6, judging the quality of the current batch of lithium ion batteries according to the outlier rate of the current batch of lithium ion batteries.
[0015] Preferably, the step S4 specifically comprises:
[0016] S41, adjusting each lithium ion battery of the same batch as the lithium ion battery to be tested to an SOC state corresponding to the self-discharge test point;
[0017] S42, detecting self-discharge of each lithium ion battery of the same batch at the self-discharge test point to obtain a self-discharge parameter of each lithium ion battery, the self-discharge parameter comprising a test time difference dt and a voltage change value dV of a self-discharge process;
[0018] S43, calculating a self-discharge coefficient K of each lithium ion battery according to the formula K = dV / dt. dt
[0019] Specifically, the step S42 specifically comprises:
[0020] S421, testing a first open circuit voltage V1 of each lithium ion battery of the current batch after the lithium ion battery is left at a preset temperature for a first preset time at the self-discharge test point, and testing a second open circuit voltage V2 of each lithium ion battery of the current batch after the lithium ion battery is left at the preset temperature for a second preset time;
[0021] S422, calculating an absolute value of a difference between the second open circuit voltage V2 and the first open circuit voltage V1 of each lithium ion battery to obtain the voltage change value dV of each lithium ion battery, and calculating an absolute value of a difference between the second preset time and the first preset time to obtain the test time difference dt.
[0022] Specifically, the preset temperature is 20-60°C, the first preset time is 48-72 hours, and the second preset time is 48-168 hours.
[0023] Preferably, the preset threshold value is 1-10%, and the current size of the small current discharge is 0.01C-0.2C.
[0024] Preferably, the step S5 specifically comprises:
[0025] The self-discharge coefficient K of all lithium-ion batteries in the current batch is calculated by using the box plot method, the 3σ criterion or the Mahalanobis distance method to obtain the outlier rate of the lithium-ion batteries in the current batch.
[0026] Preferably, the step S6 specifically includes:
[0027] If the outlier rate of the current batch of lithium-ion batteries is less than or equal to the preset outlier rate, the current batch of lithium-ion batteries is good; otherwise, the current batch of lithium-ion batteries is defective.
[0028] Preferably, the step S1 specifically includes:
[0029] S11, discharging the lithium-ion battery to be tested at a low current for a third preset time;
[0030] S12, obtaining the charge change dQ, voltage change dV and SOC value of the lithium-ion battery to be tested at each moment;
[0031] S13. Draw a dQ / dV curve of the lithium-ion battery to be tested, with the SOC value at each moment as the horizontal coordinate and the absolute value of the ratio of the charge change dQ to the voltage change dV at the same moment as the vertical coordinate.
[0032] In a second aspect, the present invention provides a lithium-ion battery self-discharge detection system, comprising:
[0033] The first execution unit is configured to perform a low-current discharge on the lithium-ion battery to be tested to obtain a dQ / dV curve of the lithium-ion battery to be tested;
[0034] a second execution unit, configured to analyze the characteristics of the dQ / dV curve and determine a continuous SOC region where the absolute value of dQ / dV is less than a preset threshold;
[0035] a third execution unit, configured to set a self-discharge test point within the determined SOC region;
[0036] a fourth execution unit, configured to perform a self-discharge test on each lithium-ion battery of the same model and the same batch as the lithium-ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium-ion battery;
[0037] a fifth execution unit, configured to calculate an outlier rate of lithium-ion batteries in a current batch according to a self-discharge coefficient K of each lithium-ion battery;
[0038] The sixth execution unit is configured to determine the quality of the current batch of lithium-ion batteries according to the outlier rate of the current batch of lithium-ion batteries.
[0039] Preferably, the lithium-ion battery self-discharge detection system further includes a temperature control unit for controlling the ambient temperature during the self-discharge detection process.
[0040] Compared with the prior art, the present invention has the following beneficial effects:
[0041] By analyzing the dQ / dV curve characteristics of the specific chemical system of lithium-ion batteries, the SOC area with relatively low dQ / dV values is found to define the SOC point of the self-discharge test, thereby improving the detection rate of abnormal self-discharge products. It is more scientific and reasonable. Testing at this SOC point can amplify the K value, thereby improving the recognition rate of self-discharge anomalies, effectively reducing customer complaints and after-sales costs caused by CIM problems, enhancing market competitiveness and customer satisfaction, and effectively avoiding the risk of batch outflow of defective products due to unscientific testing methods under traditional conditions of using thin diaphragms. It fundamentally strengthens product quality control capabilities and provides a solid guarantee for the safe and reliable application of lithium-ion batteries in the era of high energy density.
[0042] The present invention has other features and advantages that will be apparent from or will be described in detail in the accompanying drawings and the following detailed description incorporated herein, which together serve to explain certain principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS
[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0044] Figure 1 This is a flow chart of a lithium-ion battery self-discharge detection method provided by an embodiment of the present invention.
[0045] Figure 2 This is a graph of the outlier rate data of the dQ / dV curve at different SOC points obtained by discharging a type of lithium-ion battery at 0.2C at 25°C.
[0046] Figure 3 This is a voltage change data chart of a batch of lithium-ion batteries that were tested as good products by this method at 30% SOC and 5% SOC and were fully charged and stored for a long time.
[0047] Figure 4 This is the dQ / dV curve obtained at 0.2C discharge capacity.
[0048] Figure 5This is a system block diagram of a lithium-ion battery self-discharge detection system provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0049] In order to explain in detail the possible application scenarios, technical principles, specific solutions that can be implemented, and the purpose and effects of this application, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of this application and are therefore only examples and are not intended to limit the scope of protection of this application.
[0050] The existing technology uses the time interval from the production to the use of the battery cell to calculate the self-discharge rate through the OCV-SOC relationship. Although this method involves the SOC concept, it does not disclose the selection of the optimal test SOC point through dQ / dV curve characteristic analysis.
[0051] Example 1:
[0052] See also Figure 1 The lithium-ion battery self-discharge detection method of this embodiment includes the following steps:
[0053] S1. Discharge the lithium-ion battery to be tested at a low current to obtain a dQ / dV curve of the lithium-ion battery to be tested.
[0054] Preferably, step S1 is specifically as follows:
[0055] S11 , discharging the lithium-ion battery to be tested at a low current for a third preset time.
[0056] The third preset time is determined according to the battery capacity, and is typically 5 to 100 hours. The current of the low-current discharge is 0.01C to 0.2C, preferably 0.05C, to ensure accurate acquisition of the electrochemical characteristics of the battery.
[0057] During the discharge process, S12 obtains the charge change dQ, voltage change dV, and SOC value of the lithium-ion battery under test at each moment. In theory, the smaller the data collection interval, the higher the data accuracy. In practice, the data collection interval is generally 1-30 seconds, preferably 10 seconds, to obtain sufficiently accurate curve data.
[0058] For example, first take the system battery cell to be tested, fully charge it according to the standard method, and then discharge it at a constant current of ≤0.2C to obtain the discharge capacity and voltage data. Then, calculate the SOC state during the discharge process based on the actual discharge capacity of the battery cell.
[0059] S13. Draw a dQ / dV curve of the lithium-ion battery to be tested, with the SOC value at each moment as the horizontal axis and the absolute value of the ratio of the charge change dQ to the voltage change dV at the same moment as the vertical axis.
[0060] It is understood that low-current discharge of a lithium-ion battery under test is typically performed directly by connecting to an external charge-discharge device, such as a battery tester, to analyze and obtain data such as the dQ / dV curve of the lithium-ion battery under test. The absolute value of the ratio of the charge change dQ to the voltage change dV at the same time can be calculated using the SLOPE formula. The number of charge change dQ to voltage change dV ratios selected is determined based on actual needs.
[0061] S2. Analyze the characteristics of the dQ / dV curve to determine continuous SOC regions where the absolute value of dQ / dV is less than a preset threshold.
[0062] It is understandable that the dQ / dV curve reflects the electrochemical characteristics of lithium-ion batteries. Since dQ / dV = (dQ / dt) / (dV / dt), during low-current discharge, dQ / dt represents the change in charge per unit time (i.e., leakage current I), and dV / dt represents the change in voltage per unit time. Within a fixed test time, the leakage current I can be considered constant, that is, dQ / dt can be regarded as a constant. Assuming K = dV / dt, then dQ / dV = I / K. The smaller the absolute value of dQ / dV, the larger the corresponding K value, which can amplify the differences between lithium-ion batteries, thereby improving the recognition rate of self-discharge anomalies.
[0063] Preferably, the preset threshold value ranges from 1% to 10%. The specific value of the preset threshold value needs to be determined according to the electrochemical system characteristics of the lithium-ion battery. The SOC range of conventional lithium-ion batteries is generally selected between 0% and 5%. Figure 4 The dQ / dV curve of the 0.2C discharge capacity is shown, where the circled SOC interval is between 0% and 5%.
[0064] S3. Setting a self-discharge test point within the determined SOC region.
[0065] Within the SOC region determined in step S2 , any point can be selected as a self-discharge test point, and a middle point of the region is generally selected.
[0066] Since the preset threshold value ranges from 1% to 10%, a test point is selected within the SOC region where the absolute value of dQ / dV is less than the preset threshold. Taking a certain battery system as an example, the SOC range corresponding to this region is 3%-8%. The middle point of 5% SOC is selected as the self-discharge test point, which is different from the traditional self-discharge test points of 30% SOC and 60% SOC.
[0067] S4. Perform a self-discharge test on each lithium-ion battery of the same model and batch as the lithium-ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium-ion battery.
[0068] Preferably, the step S4 specifically includes:
[0069] S41: Adjust each lithium-ion battery of the same model and batch as the lithium-ion battery to be tested to the SOC state corresponding to the self-discharge test point. The SOC state adjustment method can adopt constant current charging or constant current discharging, and the current size is preferably 0.1C to 0.5C, such as 0.2C.
[0070] S42, performing a self-discharge test on each lithium-ion battery of the same batch at the self-discharge test point to obtain self-discharge parameters of each lithium-ion battery, wherein the self-discharge parameters include a test time difference dt and a voltage change value dV during the self-discharge process;
[0071] S43. Calculate the self-discharge coefficient K of each lithium-ion battery according to the formula K=dV / dt.
[0072] Similarly, in step S1 , each lithium-ion battery is connected to an external charging and discharging device such as a battery tester for direct analysis to obtain data such as self-discharge parameters of each lithium-ion battery, thereby calculating the self-discharge coefficient K of each lithium-ion battery.
[0073] Specifically, the step S42 includes:
[0074] S421, at the self-discharge test point, after each lithium-ion battery in the current batch is allowed to stand at a preset temperature for a first preset time, measuring a first open circuit voltage V1 of each lithium-ion battery; and after each lithium-ion battery in the current batch is allowed to stand at the preset temperature for a second preset time, measuring a second open circuit voltage V2 of each lithium-ion battery;
[0075] S422: Calculate the absolute value of the difference between the second open-circuit voltage V2 and the first open-circuit voltage V1 of each lithium-ion battery to obtain the voltage change value dV of each lithium-ion battery, and calculate the absolute value of the difference between the second preset time and the first preset time to obtain the test time difference dt.
[0076] Preferably, the preset temperature is 20° C. to 60° C., such as the commonly used 25° C., to accelerate the self-discharge process and improve detection efficiency. The first preset time is 48 hours to 72 hours, such as 72 hours, and the second preset time is 48 hours to 168 hours, such as 72 hours.
[0077] S5. Calculate the outlier rate of the current batch of lithium-ion batteries based on the self-discharge coefficient K of each lithium-ion battery.
[0078] Specifically, outlier rate = (number of outlier lithium-ion batteries / total number of lithium-ion batteries) × 100%. The outlier rate represents the proportion of lithium-ion batteries with abnormal self-discharge. By limiting the outlier rate, the yield rate of lithium-ion batteries in a batch can be guaranteed.
[0079] Preferably, this embodiment can perform statistical analysis on the self-discharge coefficient K of all lithium-ion batteries in the current batch by using the box plot method, the 3σ criterion or the Mahalanobis distance method, identify abnormal values, and calculate the outlier rate of the lithium-ion batteries in the current batch.
[0080] As an extension, the core principle of the boxplot method is to identify data points that are beyond the upper quartile + 1.5 times the interquartile range or below the lower quartile - 1.5 times the interquartile range as outliers. The core principle of the 3σ criterion is to identify data points that are more than 3 standard deviations away from the mean as outliers. The core principle of the Mahalanobis distance method is to calculate the Mahalanobis distance of each data point and identify points whose distance exceeds the threshold as outliers.
[0081] S6. Determine the quality of the current batch of lithium-ion batteries based on the outlier rate of the current batch of lithium-ion batteries.
[0082] If the outlier rate of the current batch of lithium-ion batteries is less than or equal to the preset outlier rate, the current batch of lithium-ion batteries is good; if the outlier rate is greater than the preset outlier rate, the current batch of lithium-ion batteries is defective.
[0083] It is understandable that the preset outlier rate is determined according to the yield rate requirement, and is usually 0.01% to 0.05%, preferably 0.03%.
[0084] In order to better illustrate the effectiveness of the lithium-ion battery self-discharge detection method of this embodiment, Figure 2 The dQ / dV curves of a type of lithium-ion battery obtained by 0.2C discharge at 25°C are shown, and the corresponding outlier rates are counted for 5% SOC, 30% SOC, 60% SOC and 100% SOC. Figure 2 It is clearly shown that in the area where the SOC is around 5%, the dQ / dV value is relatively low and the maximum outlier rate is obtained, which can detect more defective products. This SOC area can be used as the optimal self-discharge test area.
[0085] In addition, this embodiment also provides voltage change data of a batch of lithium-ion batteries tested as good products by this method at 30% SOC and 5% SOC during long-term storage. To simplify the description, Figure 3 The batch of lithium-ion batteries tested as good products by this method is simplified to have a K value of OK. Figure 3This clearly shows that batches of lithium-ion batteries tested as good at 30% SOC exhibited a high number of outlier cells after long-term storage, resulting in greater voltage dispersion and a low interception rate for abnormal cells. In contrast, batches of lithium-ion batteries tested as good at 5% SOC exhibited a more concentrated overall voltage after the same period of long-term storage, with fewer abnormal cells. This demonstrates that scientific analysis of the dQ / dV curve and testing the self-discharge coefficient K at SOC conditions corresponding to lower dQ / dV values can effectively improve the detection rate of self-discharge anomalies.
[0086] It is understandable that this embodiment significantly reduces the risk of batch outflow of defective products due to unscientific detection methods when using thin diaphragms by optimizing the self-discharge detection method. The self-discharge detection SOC point used in this embodiment is not simply set according to the shipping state SOC, but is derived after in-depth analysis of the characteristics of the specific chemical system, and is therefore more scientific and reasonable. This improvement not only improves the accuracy of the test results, but also fundamentally strengthens the product quality control capability, providing a solid guarantee for the safe and reliable application of lithium-ion batteries in the era of high energy density.
[0087] Example 2
[0088] See also Figure 5 , the lithium-ion battery self-discharge detection system of this embodiment includes:
[0089] The first execution unit 10 is configured to discharge the lithium-ion battery under test at a low current and obtain a dQ / dV curve of the lithium-ion battery under test. For example, the dQ / dV curve of the lithium-ion battery under test can be calculated and obtained by collecting voltage, current, and time data in real time. The first execution unit 10 may include a charge and discharge device, a current sensor, and a data acquisition module.
[0090] The second execution unit 20 is configured to analyze the characteristics of the dQ / dV curve and determine continuous SOC regions where the absolute value of dQ / dV is less than a preset threshold. The second execution unit 20 may include a data processing module and a curve analysis algorithm.
[0091] The third execution unit 30 is configured to automatically or manually set a self-discharge test point within the determined SOC region and generate a test parameter configuration. The third execution unit 30 may include a parameter setting module.
[0092] The fourth execution unit 40 is configured to perform a self-discharge test on each lithium-ion battery of the same model and batch as the lithium-ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium-ion battery. The fourth execution unit 40 may include automated testing equipment, a temperature control system, and a multi-channel data acquisition system.
[0093] The fifth execution unit 50 is configured to calculate the outlier rate of the current batch of lithium-ion batteries based on the self-discharge coefficient K of each lithium-ion battery. The fifth execution unit 50 may include a statistical analysis module having built-in statistical algorithms such as box plot method, 3σ criterion, and Mahalanobis distance method.
[0094] The sixth execution unit 60 is configured to determine the quality of the current batch of lithium-ion batteries based on the outlier rate of the current batch of lithium-ion batteries and generate a test report. The sixth execution unit 60 may include a quality determination module and a result output module.
[0095] The temperature control unit 70 is used to accurately control the ambient temperature during the self-discharge detection process to ensure the consistency and accuracy of the test conditions. The temperature control unit 70 may include a constant temperature box, a temperature sensor, and a temperature controller.
[0096] This lithium-ion battery self-discharge detection system, through the configuration of highly automated hardware equipment and intelligent software algorithms, realizes efficient and accurate detection of lithium-ion battery self-discharge performance, significantly improving production efficiency and product quality control level.
[0097] Combine Figure 1-Figure 5 , the present invention has the following beneficial effects:
[0098] By analyzing the dQ / dV curve characteristics of the specific chemical system of lithium-ion batteries, the SOC area with relatively low dQ / dV values is found to define the SOC point of the self-discharge test, thereby improving the detection rate of abnormal self-discharge products. It is more scientific and reasonable. Testing at this SOC point can amplify the K value, thereby improving the recognition rate of self-discharge anomalies, effectively reducing customer complaints and after-sales costs caused by CIM problems, enhancing market competitiveness and customer satisfaction, and effectively avoiding the risk of batch outflow of defective products due to unscientific testing methods under traditional conditions of using thin diaphragms. It fundamentally strengthens product quality control capabilities and provides a solid guarantee for the safe and reliable application of lithium-ion batteries in the era of high energy density.
[0099] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A lithium-ion battery self-discharge detection method, characterized in that: The following steps are involved: Discharging the lithium-ion battery to be tested with a small current to obtain a dQ / dV curve of the lithium-ion battery to be tested; Analyzing characteristics of the dQ / dV curve to determine continuous SOC regions where the absolute value of dQ / dV is less than a preset threshold; Setting a self-discharge test point within the determined SOC region; Performing a self-discharge test on each lithium-ion battery of the same model and the same batch as the lithium-ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium-ion battery; Calculate the outlier rate of the current batch of lithium-ion batteries based on the self-discharge coefficient K of each lithium-ion battery; The quality of the current batch of lithium-ion batteries is judged according to the outlier rate of the current batch of lithium-ion batteries.
2. The lithium-ion battery self-discharge detection method according to claim 1, wherein: The self-discharge test is performed on each lithium-ion battery of the same model and the same batch as the lithium-ion battery to be tested at the self-discharge test point to obtain the self-discharge coefficient K of each lithium-ion battery, specifically including: Adjusting each lithium-ion battery of the same model and the same batch as the lithium-ion battery to be tested to the SOC state corresponding to the self-discharge test point; Performing a self-discharge test on each lithium-ion battery of the same batch at the self-discharge test point to obtain self-discharge parameters of each lithium-ion battery, wherein the self-discharge parameters include a test time difference dt and a voltage change value dV during the self-discharge process; The self-discharge coefficient K of each lithium-ion battery is calculated according to the formula K=dV / dt.
3. The lithium-ion battery self-discharge detection method according to claim 2, wherein: The self-discharge test is performed on each lithium-ion battery of the same batch at the self-discharge test point to obtain the self-discharge parameter of each lithium-ion battery, specifically including: At the self-discharge test point, each lithium-ion battery in the current batch is left at a preset temperature for a first preset time, and then a first open circuit voltage V1 of each lithium-ion battery is measured. Then, each lithium-ion battery in the current batch is left at a preset temperature for a second preset time, and then a second open circuit voltage V2 of each lithium-ion battery is measured. The absolute value of the difference between the second open circuit voltage V2 and the first open circuit voltage V1 of each lithium ion battery is calculated to obtain the voltage change value dV of each lithium ion battery, and the absolute value of the difference between the second preset time and the first preset time is calculated to obtain the test time difference dt.
4. The lithium-ion battery self-discharge detection method according to claim 3, wherein: The preset temperature is 20° C. to 60° C., the first preset time is 48 hours to 72 hours, and the second preset time is 48 hours to 168 hours.
5. The lithium-ion battery self-discharge detection method according to claim 1, wherein: The preset threshold is 1% to 10%, and the current of the small current discharge is 0.01C to 0.2C.
6. The lithium-ion battery self-discharge detection method according to claim 1, wherein: The outlier rate of the lithium-ion batteries in the current batch is calculated based on the self-discharge coefficient K of each lithium-ion battery, specifically including: The self-discharge coefficient K of all lithium-ion batteries in the current batch is calculated by using the box plot method, the 3σ criterion or the Mahalanobis distance method to obtain the outlier rate of the lithium-ion batteries in the current batch.
7. The lithium-ion battery self-discharge detection method according to claim 1, wherein: The determining of the quality of the current batch of lithium-ion batteries based on the outlier rate of the current batch of lithium-ion batteries specifically includes: If the outlier rate of the current batch of lithium-ion batteries is less than or equal to the preset outlier rate, the current batch of lithium-ion batteries is good; otherwise, the current batch of lithium-ion batteries is defective.
8. The lithium-ion battery self-discharge detection method according to claim 1, wherein: The step of discharging the lithium-ion battery to be tested at a low current to obtain a dQ / dV curve of the lithium-ion battery to be tested specifically includes: Discharging the lithium-ion battery under test at a low current for a third preset time; Obtaining the charge change dQ, voltage change dV and SOC value of the lithium-ion battery to be tested at each moment; The dQ / dV curve of the lithium-ion battery to be tested is drawn with the SOC value at each moment as the horizontal axis and the absolute value of the ratio of the charge change dQ to the voltage change dV at the same moment as the vertical axis.
9. A lithium-ion battery self-discharge detection system, characterized in that: include: The first execution unit is configured to perform a low-current discharge on the lithium-ion battery to be tested to obtain a dQ / dV curve of the lithium-ion battery to be tested; a second execution unit, configured to analyze the characteristics of the dQ / dV curve and determine a continuous SOC region where the absolute value of dQ / dV is less than a preset threshold; a third execution unit, configured to set a self-discharge test point within the determined SOC region; a fourth execution unit, configured to perform a self-discharge test on each lithium-ion battery of the same model and the same batch as the lithium-ion battery to be tested at the self-discharge test point to obtain a self-discharge coefficient K of each lithium-ion battery; a fifth execution unit, configured to calculate an outlier rate of lithium-ion batteries in a current batch according to a self-discharge coefficient K of each lithium-ion battery; The sixth execution unit is configured to determine the quality of the current batch of lithium-ion batteries according to the outlier rate of the current batch of lithium-ion batteries.
10. The lithium-ion battery self-discharge detection system according to claim 9, wherein: A temperature control unit is also included for controlling the ambient temperature during the self-discharge detection process.