A battery internal short circuit detection method, device, equipment and medium

Abstract

This application relates to the field of battery safety technology and discloses a method, apparatus, device, and medium for detecting internal short circuits in batteries. The method includes: collecting historical charging process data of a rechargeable battery over a historical time period starting from the current moment; filtering target charging process data for each target time period from the historical charging process data; obtaining the remaining rechargeable capacity of each cell of the rechargeable battery at a reference time within the corresponding target time period based on the target charging process data; for each cell, calculating the time interval between two reference times corresponding to two adjacent target time periods, and the difference between the remaining rechargeable capacity of the cell at the corresponding two reference times; and calculating the average internal short-circuit current of the cell based on the time interval and the difference between the cells. Using the method of this application can effectively improve the real-time performance and accuracy of internal short-circuit detection of rechargeable batteries.

Description

Technical Field

[0001] This application relates to the field of battery safety technology, and in particular to a method, apparatus, device and medium for detecting short circuits inside a battery. Background Technology

[0002] Internal short circuits in lithium batteries are one of the main causes of serious safety accidents such as thermal runaway, fires, and explosions. Real-time and accurate detection of these short circuits is crucial for ensuring the safe operation of battery systems. Currently, commonly used methods for detecting internal short circuits in the industry mainly include the static voltage method and the cell SOC (state of charge) estimation method, but these methods have all revealed significant shortcomings in practical applications.

[0003] The internal short-circuit detection method based on the static voltage method calculates the internal short-circuit current by measuring the voltage change of the battery under prolonged static conditions. This method places stringent requirements on battery operating conditions, requiring the battery to be in a static state for an extended period, typically no less than one hour. Particularly for lithium iron phosphate batteries, it further requires the battery to be in a static state with a state of charge below 30% in order to complete the internal short-circuit current calculation. This limitation directly results in extremely low efficiency in internal short-circuit current calculation, frequently leading to prolonged calculation failures and detection interruptions, making it difficult to meet the needs of real-time monitoring.

[0004] Internal short-circuit detection methods based on cell SOC estimation rely on high-precision estimation of the state of charge to calculate the internal short-circuit current. To ensure detection accuracy, the relative error of SOC is typically required to be controlled within 0.1%. However, in practical engineering applications, due to various factors such as temperature fluctuations, battery aging, and changes in charge / discharge rates, it is difficult for SOC estimation to consistently achieve this accuracy standard. This results in a large error in the calculation of the internal short-circuit current, and the detection accuracy cannot be effectively guaranteed. In summary, existing methods for detecting short circuits within rechargeable batteries suffer from poor accuracy and real-time performance. Summary of the Invention

[0005] To address the technical problems of poor real-time performance and low accuracy in existing short-circuit detection methods for rechargeable batteries, this application provides technical solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for detecting short circuits within a battery, comprising: Collect historical charging process data of the rechargeable battery within a historical time period starting from the current moment; Target charging process data for each target time period is selected from the historical charging process data; Based on the target charging process data, obtain the remaining rechargeable capacity of each cell of the rechargeable battery at a reference time in the corresponding target time period; For each of the battery cells, the time interval between two reference times corresponding to two adjacent target time periods is calculated, as well as the difference between the remaining rechargeable capacity of the battery cell at the corresponding two reference times; the average internal short-circuit current of the battery cell is calculated based on the time interval and the difference of the battery cell.

[0007] In some embodiments, the historical charging process data includes the charging status, charging current, and voltage of each cell at the corresponding historical sampling time; the step of filtering target charging process data for each target time period from the historical charging process data includes: According to preset filtering conditions, target charging process data for each target time period are filtered from the historical charging process data of the historical time period. The preset filtering conditions are: the corresponding time period is in a continuous charging state and the charging current is greater than a preset current threshold, and the highest cell voltage at the end of the corresponding time period reaches the full charge determination threshold.

[0008] In some embodiments, the reference time is the charging end time of the corresponding time period or the time when the highest cell voltage reaches the full charge determination threshold, and obtaining the remaining rechargeable capacity of each cell of the rechargeable battery at the reference time in the corresponding target time period includes: For any given cell, obtain the cumulative charge-voltage curve of the cell with the highest voltage during the target time period, and the first voltage of the given cell at the reference time. Based on the cumulative charge-voltage curve and the first voltage, the first cumulative charge of any cell at the reference time is obtained using the linear difference method; based on the cumulative charge-voltage curve and the reference voltage, the second cumulative charge corresponding to the reference voltage is obtained using the linear difference method. The difference between the second accumulated power and the first accumulated power is taken as the remaining rechargeable power of any cell at the reference time.

[0009] In some embodiments, the historical charging process data further includes the cumulative charge of the cell with the highest voltage at the corresponding historical sampling time, and obtaining the cumulative charge-voltage curve of the cell with the highest voltage during the continuous charging period includes: The cumulative charge and voltage of the battery cell with the highest voltage at each sampling time during the continuous charging period are fitted to obtain the cumulative charge-voltage curve.

[0010] In some embodiments, calculating the average internal short-circuit current of the battery cell based on the time interval and the difference between the battery cells includes: dividing the difference between the battery cells by the time interval to obtain the average internal short-circuit current of the battery cell.

[0011] In some embodiments, the method further includes: for each of the battery cells, selecting the maximum average internal short-circuit current among the average internal short-circuit currents within the historical time period; The largest maximum average internal short-circuit current is selected from the maximum average internal short-circuit current of each of the cells as the strongest internal short-circuit current, and the strongest internal short-circuit current is compared with the preset warning threshold and the preset alarm threshold. If the strongest internal short-circuit current is greater than the warning threshold but less than the alarm threshold, the rechargeable battery is determined to be at level one risk. If the strongest internal short-circuit current is greater than or equal to the alarm threshold, the rechargeable battery is determined to be at level two risk.

[0012] In some embodiments, the method further includes: sorting the average internal short-circuit currents of each of the battery cells in the historical time period according to time order, and determining whether the average internal short-circuit current gradually increases over time based on the sorting result. If the average internal short-circuit current of at least one of the cells gradually increases over time, and the cumulative increase is greater than a preset increase threshold, and the strongest internal short-circuit current is greater than or equal to the alarm threshold, then the rechargeable battery is determined to be at level three risk.

[0013] In a second aspect, the present invention provides a battery internal short circuit detection device, comprising: The data acquisition module is used to collect historical charging process data of the rechargeable battery within a historical time period starting from the current moment; The data filtering module is used to filter out target charging process data for each target time period from the historical charging process data; The power calculation module is used to obtain the remaining rechargeable power of each cell of the rechargeable battery at a reference time in the corresponding target time period based on the target charging process data. The current calculation module is used to calculate the time interval between two corresponding reference times and the difference between the remaining rechargeable capacity of the battery cell at the corresponding two reference times for two adjacent target time periods; and to calculate the average internal short-circuit current of each battery cell based on the time interval and the difference of each battery cell.

[0014] In a third aspect, the present invention provides a computer device including a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the battery internal short circuit detection method of the present invention.

[0015] In a fourth aspect, the present invention provides a computer storage medium storing a computer program that, when executed on a processor, implements the battery internal short-circuit detection method of the present invention.

[0016] The embodiments of this application have the following beneficial effects: This application's method collects historical charging process data and filters target time periods. It then calculates the average internal short-circuit current of each cell by utilizing the change in remaining rechargeable capacity at a reference time within the target time period and the time interval between adjacent time periods. Compared to existing static voltage methods, this method eliminates the need for prolonged battery resting and does not rely on specific state of charge (SOC) ranges. Internal short-circuit current calculation can be completed during normal charging, significantly improving the real-time performance and continuity of detection, and avoiding calculation interruptions due to unmet resting conditions. Compared to existing methods that rely on high-precision SOC estimation, this method avoids the problem of large errors in SOC estimation caused by temperature, aging, and charge / discharge rates. By calculating the internal short-circuit current based on changes in remaining rechargeable capacity, it significantly improves the accuracy of the detection results. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and therefore should not be considered as a limitation on the scope of protection of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 The flowchart of the battery internal short circuit detection method according to an embodiment of this application is shown. Figure 1 ; Figure 2 A schematic diagram showing the reference time and remaining rechargeable power of an embodiment of this application is provided. Figure 3 The flowchart of the battery internal short circuit detection method according to an embodiment of this application is shown. Figure 2 ; Figure 4 A schematic diagram of the structure of a battery internal short circuit detection device according to an embodiment of this application is shown; Figure 5 A schematic diagram of the computer device structure according to an embodiment of this application is shown. Detailed Implementation

[0019] The technical solutions in 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.

[0020] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0021] In the following, the terms “comprising,” “having,” and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0022] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0023] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0024] Existing methods for detecting internal short circuits in lithium batteries suffer from poor real-time performance and low accuracy. This application improves the real-time performance, continuity, and accuracy of internal short circuit detection by collecting historical charging process data and filtering charging process data for a target time period. It uses the change in remaining rechargeable capacity at a reference time within the target time period and the time interval between adjacent time periods to calculate the average internal short circuit current of each cell.

[0025] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0026] Example 1: like Figure 1As shown, this application provides a method for detecting short circuits within a battery, including: S101. Collect historical charging process data of the rechargeable battery within a historical time period starting from the current moment; In this embodiment, the historical charging process data includes the charging status at the corresponding historical sampling time, the charging current, the voltage of each cell, and the cumulative charge of the cell with the highest voltage; in other embodiments, the historical charging process data may also include the battery pack identifier, the temperature of each cell, and the SOC (i.e., the remaining charge percentage) of each cell.

[0027] After collecting historical charging process data of the rechargeable battery, the historical charging process data of each sampling point can be sorted according to the sampling time.

[0028] In this embodiment, historical charging process data of the battery within a historical time period can be collected through the battery management system, the vehicle-mounted T-Box (i.e., the vehicle-mounted remote information processing terminal), or the energy storage gateway.

[0029] The historical time period can be the past 24 hours from the current moment or other suitable time periods.

[0030] S102. Filter out the target charging process data for each target time period from the historical charging process data; In this embodiment, selecting target charging process data for each target time period from the historical charging process data includes: selecting target charging process data for each target time period from the historical charging process data of the historical time period according to preset filtering conditions; in this embodiment, the filtering conditions include: the corresponding time period is in a continuous charging state and the charging current is greater than a preset current threshold, and the highest cell voltage at the end of the corresponding time period reaches the full charge determination threshold. In other embodiments, the filtering conditions may further include: the charging rate of the corresponding time period is less than 1C.

[0031] By setting filtering conditions, requiring that each sampling moment within the target time period be in a charging state, the charging current be greater than a preset current threshold, and the highest cell voltage at the end of the period reach the full charge determination threshold, invalid data segments such as charging interruptions, low-current charging, and incomplete charging can be effectively eliminated. This ensures that the target charging process data used correspond to a stable charging and reliable operating condition close to full charge. This provides a high-quality data foundation for the accurate calculation of remaining rechargeable capacity, further guaranteeing the accuracy and consistency of internal short-circuit current detection and avoiding detection errors introduced by fluctuations in operating conditions.

[0032] S103. Based on the target charging process data, obtain the remaining rechargeable capacity of each cell of the charging battery at a reference time in the corresponding target time period; In this embodiment, the reference time is either the end time of charging within the corresponding time period or the time when the highest cell voltage reaches the full charge determination threshold. In other embodiments, other suitable times can be selected as the reference time.

[0033] In this embodiment, by setting the reference time to the end of charging within the corresponding time period or the moment when the highest cell voltage reaches the full charge threshold, the calculation time for the remaining rechargeable capacity uniformly corresponds to the battery being close to full charge. In this state, the voltage is sensitive to changes in capacity, more accurately reflecting the remaining capacity of each cell before it is fully charged. This improves the accuracy of the remaining rechargeable capacity calculation, and the average internal short-circuit current obtained based on its changes more accurately reflects the internal short-circuit loss, thus improving the accuracy of detection.

[0034] Obtaining the remaining rechargeable capacity of each cell of the rechargeable battery at a reference time within the corresponding target time period includes: (1) For any cell, obtain the cumulative charge-voltage curve of the cell with the highest voltage during the target time period, and the first voltage of the cell at the reference time. The method for obtaining the cumulative charge-voltage curve of the battery cell with the highest voltage during the target time period is as follows: the cumulative charge and voltage of the battery cell with the highest voltage at each sampling time during the continuous charging time period are fitted to obtain the cumulative charge-voltage curve.

[0035] (2) Based on the cumulative charge-voltage curve and the first voltage, the first cumulative charge of any cell at the reference time is obtained using the linear difference method; based on the cumulative charge-voltage curve and the reference voltage, the second cumulative charge corresponding to the reference voltage is obtained using the linear difference method. In this embodiment, the method of obtaining the first cumulative charge of a target cell at a reference time using the linear interpolation method is as follows: find two voltage sampling points adjacent to the first voltage of the target cell on the cumulative charge-voltage curve, and interpolate the voltage and cumulative charge of the two sampling points to obtain the cumulative charge corresponding to the voltage of the target cell when the voltage reaches the specified voltage.

[0036] Similarly, find two voltage sampling points adjacent to the reference voltage on the cumulative charge-voltage curve, and interpolate based on the voltage and cumulative charge of these two sampling points to obtain the second cumulative charge corresponding to when the voltage of the target cell reaches the reference voltage.

[0037] In this embodiment, the reference voltage can be the full charge determination voltage threshold of the battery cell.

[0038] (3) The difference between the second accumulated power and the first accumulated power is taken as the remaining rechargeable power of any cell at the reference time.

[0039] By utilizing the cumulative charge-voltage curve of the cell with the highest voltage during the target time period, combined with the first voltage and reference voltage of the cell under test at the reference time, the first and second cumulative charges are obtained through linear interpolation, and the difference between the two is taken as the remaining rechargeable charge of the cell. This method only needs to obtain the cumulative charge-voltage characteristics of the highest voltage cell to uniformly calculate the remaining rechargeable charge of each cell. It does not rely on the difficult-to-accurate SOC estimation, nor does it require complex modeling of each cell individually. This simplifies the calculation and effectively overcomes the technical problem of inaccurate internal short-circuit current calculation results due to excessive errors in traditional SOC estimation methods.

[0040] S104. Calculate the average internal short-circuit current of each cell, specifically: for each cell, calculate the time interval between two reference times corresponding to two adjacent target time periods, and the difference between the remaining rechargeable capacity of the cell at the corresponding two reference times; calculate the average internal short-circuit current of the cell based on the time interval and the difference of the cell.

[0041] In this embodiment, when calculating the average internal short-circuit current of the battery cell, the average internal short-circuit current can be positively correlated with the corresponding difference and negatively correlated with the corresponding time interval. In one embodiment, the difference can be divided by the time interval between the two corresponding reference times to obtain the average internal short-circuit current corresponding to each pair of adjacent continuous charging time periods.

[0042] For example: Suppose that the two adjacent target time periods in the j-th group are the m-th target time period and the n-th target time period, the reference time of the m-th target time period is the m-th reference time, and the reference time of the n-th target time period is the n-th reference time, then the corresponding calculation expression is: ; In the formula, This represents the average internal short-circuit current of the i-th cell corresponding to each pair of adjacent target time periods in the j-th group. This represents the difference between the remaining rechargeable capacity of the i-th cell at reference time m and reference time n, expressed in Ah. This represents the time interval between the m-th and n-th reference times, expressed in hours. The calculated average internal short-circuit current is expressed in amperes (A); to output mA, multiply the result by 1000.

[0043] like Figure 2 As shown, assuming the m-th reference time is T1 and the n-th reference time is T2, the remaining rechargeable capacity of the i-th cell at the m-th reference time is... The remaining rechargeable capacity of the i-th cell at the n-th reference time is The corresponding difference The value is and The difference, the time interval between the m-th reference time and the n-th reference time. The value is the time interval between T1 and T2.

[0044] This application's method collects historical charging process data and filters target time periods. It then calculates the average internal short-circuit current of each cell by utilizing the change in remaining rechargeable capacity at a reference time within the target time period and the time interval between adjacent time periods. Compared to existing static voltage methods, this method eliminates the need for prolonged battery resting and does not rely on specific state of charge (SOC) ranges. Internal short-circuit current calculation can be completed during normal charging, significantly improving the real-time performance and continuity of detection, and avoiding calculation interruptions due to unmet resting conditions. Compared to existing methods that rely on high-precision SOC estimation, this method avoids the problem of large errors in SOC estimation caused by temperature, aging, and charge / discharge rates. By calculating the internal short-circuit current based on changes in remaining rechargeable capacity, it significantly improves the accuracy of the detection results.

[0045] Furthermore, existing deep learning-based internal short circuit detection methods suffer from core data bottlenecks and limitations in generalization ability. Due to the extremely low actual occurrence rate of internal short circuits in lithium batteries, labeled data related to internal short circuits is extremely scarce, resulting in a lack of sufficient effective samples to support model training. Simultaneously, these methods exhibit poor generalization performance; when battery models are changed, operating conditions are altered, or batteries enter different aging stages, the trained models directly fail, making them unsuitable for complex real-world application scenarios. In contrast, the method in this application does not rely on prior models based on battery model, aging state, or specific operating conditions, avoiding the data scarcity and poor generalization capabilities inherent in deep learning methods. Stable detection can be achieved solely through charging data.

[0046] In another embodiment, such as Figure 3 As shown, the battery internal short circuit detection method also includes: S201. For each of the battery cells, select the maximum average internal short-circuit current among the average internal short-circuit currents in the historical time period. S202. Select the largest maximum average internal short-circuit current from the maximum average internal short-circuit current of each of the cells as the strongest internal short-circuit current, and compare the strongest internal short-circuit current with the preset warning threshold and the preset alarm threshold. In this embodiment, preset warning thresholds and preset alarm thresholds can be calibrated through accelerated aging tests of the battery cells and internal short-circuit simulations. The warning threshold is the critical value for leakage current during a minor internal short circuit in the battery cell, and the alarm threshold is the critical value for leakage current during a severe internal short circuit in the battery cell.

[0047] S203. If the strongest internal short-circuit current is greater than the warning threshold and less than the alarm threshold, then the rechargeable battery is determined to be at level one risk. S204. If the strongest internal short-circuit current is greater than or equal to the alarm threshold, the rechargeable battery is determined to be at level two risk.

[0048] By extracting the maximum average internal short-circuit current from the historical average internal short-circuit current of each cell, and comparing the strongest internal short-circuit current with the warning threshold and alarm threshold, internal short-circuit risks can be classified into Level 1 and Level 2 risks. This solution, based on online detection of internal short-circuit current, further provides a graded early warning mechanism, enabling timely detection of potential safety hazards and differentiation of severity without the need for prolonged static storage and complex SOC estimation, thereby improving the operational safety of rechargeable batteries.

[0049] In another embodiment, the battery internal short circuit detection method further includes: S301. For each of the battery cells, sort the average internal short-circuit currents in the historical time period according to the time sequence, and determine whether the average internal short-circuit current gradually increases over time based on the sorting result. S302. If the average internal short-circuit current of at least one of the cells gradually increases over time, and the cumulative increase is greater than a preset increase threshold, and the strongest internal short-circuit current is greater than or equal to the alarm threshold, then the rechargeable battery is determined to be at level three risk.

[0050] The preset increase threshold can be a preset percentage (e.g., 20%) of the minimum internal short-circuit current of the target cell within a historical time period.

[0051] By sorting the average internal short-circuit current of each cell over a historical period and determining whether it shows a gradual increasing trend and whether the cumulative increase exceeds a preset increase threshold, and combining this with whether the strongest internal short-circuit current reaches an alarm threshold, a dangerous evolution pattern of continuously deteriorating internal short-circuit severity can be identified and classified as a level three risk. This method can detect the trend of escalating internal short circuits earlier, providing a higher level of warning at a stage that traditional methods cannot detect due to detection interruptions or excessive errors, further improving the early identification capability of thermal runaway risk and the effectiveness of safety control.

[0052] In another embodiment, the battery short-circuit detection method further includes: if the rechargeable battery is classified as a Level 1 risk, issuing at least one instruction to the corresponding device of the rechargeable battery, including increasing the cell voltage / current sampling frequency, actively initiating cell balancing, and real-time encrypted monitoring of cell status. The corresponding device of the rechargeable battery can be at least one of a battery management system, an on-board charging device, and a cloud-based operation and maintenance platform. It is understood that actively initiating cell balancing or real-time encrypted monitoring of cell status can eliminate the potential for minor inconsistencies.

[0053] If the rechargeable battery is classified as a level 2 risk, then at least one instruction is issued to the corresponding device for the rechargeable battery, including limiting charging current, limiting charging power, lowering the charging cutoff SOC / charging cutoff voltage, and prohibiting fast charging. It is understood that constraining charging conditions can slow down the rate of cell degradation.

[0054] If the rechargeable battery is classified as a Level 3 risk, then at least one instruction is issued to the corresponding device for the rechargeable battery: suspend charging, generate an offline maintenance work order, or isolate the battery pack to which the faulty cell belongs. It can be understood that isolating the battery pack to which the faulty cell belongs can cut off the input of dangerous operating conditions, isolate the source of the fault, and avoid the safety risk of thermal runaway.

[0055] This embodiment achieves a complete safety closed loop from accurate detection to intelligent response by executing differentiated control commands for each level. When a level 1 risk is determined, commands are issued to at least one device among the battery management system, on-board charging equipment, or cloud-based operation and maintenance platform to increase the sampling frequency of cell voltage / current, actively initiate cell balancing, and monitor cell status in real time with encrypted settings. This can enhance the perception density of cell status in the early stages of a risk, suppress the expansion of cell inconsistencies through active balancing, and thus more sensitively capture the evolution trend of internal short circuits, delay or block the degradation process of internal short circuits, and effectively prevent serious failures due to monitoring lag.

[0056] When a risk level is determined to be Level 2, proactive intervention measures such as limiting charging current, limiting charging power, lowering the charging cutoff SOC / charging cutoff voltage, and prohibiting fast charging can significantly reduce electrochemical stress and heat accumulation during the charging process, mitigate the degree of internal short circuits, and reduce the probability of thermal runaway, thus achieving a balance between safety and availability, while ensuring that the battery can still maintain basic use.

[0057] When a level three risk is identified, indicating that the internal short circuit is accelerating, emergency commands such as suspending charging, generating offline maintenance work orders, and isolating the battery pack containing the faulty cell can be issued to immediately cut off energy input and initiate manual maintenance procedures. Simultaneously, the faulty unit is physically isolated, completely interrupting the thermal runaway chain reaction at its source and preventing major safety accidents such as fires and explosions. This tiered control strategy, combined with the aforementioned internal short-circuit current detection method that does not rely on long-term static storage and high-precision SOC estimation, overcomes the technical shortcomings of existing technologies that cannot effectively prevent safety accidents due to inaccurate detection and control lag. This significantly improves the real-time safety protection capability and overall lifecycle operational safety of the rechargeable battery system.

[0058] Example 2: like Figure 4 As shown, this application provides a battery internal short circuit detection device 100, comprising: Data acquisition module 110 is used to collect historical charging process data of rechargeable batteries within a historical time period starting from the current moment; The data filtering module 120 is used to filter out target charging process data for each target time period from the historical charging process data; The power calculation module 130 is used to obtain the remaining rechargeable power of each cell of the rechargeable battery at a reference time in the corresponding target time period based on the target charging process data. The current calculation module 140 is used to calculate the time interval between two corresponding reference times and the difference between the remaining rechargeable capacity of the battery cell at the corresponding two reference times for two adjacent target time periods; and to calculate the average internal short-circuit current of each battery cell based on the time interval and the difference of each battery cell.

[0059] In some embodiments, when the current calculation module 140 calculates the average internal short-circuit current of each of the cells based on the time interval and the difference between each of the cells, the average internal short-circuit current may be positively correlated with the corresponding difference and negatively correlated with the corresponding time interval.

[0060] In some embodiments, the reference time can be the end time of charging in the corresponding time period or the time when the highest cell voltage reaches the full charge determination threshold.

[0061] In some embodiments, the historical charging process data includes the charging status, charging current, and voltage of each cell at the corresponding historical sampling time. The data filtering module 120 filters the target charging process data for each target time period from the historical charging process data by filtering the target charging process data for each target time period from the historical charging process data of the historical time period according to preset filtering conditions. The preset filtering conditions are: the corresponding time period is in a continuous charging state and the charging current is greater than a preset current threshold, and the highest cell voltage at the end of the corresponding time period reaches the full charge determination threshold.

[0062] In some embodiments, the remaining rechargeable capacity calculation module 130 includes a cumulative capacity-voltage curve acquisition unit, a cumulative capacity acquisition unit, and a remaining rechargeable capacity acquisition unit; wherein, the cumulative capacity-voltage curve acquisition unit is used to acquire, for any given cell, the cumulative capacity-voltage curve of the cell with the highest voltage during the target time period, and the first voltage of the given cell at a reference time; the cumulative capacity acquisition unit is used to obtain the first cumulative capacity of the given cell at the reference time using a linear difference method based on the cumulative capacity-voltage curve and the first voltage; and to obtain the second cumulative capacity corresponding to the reference voltage using a linear difference method based on the cumulative capacity-voltage curve and the reference voltage; the remaining rechargeable capacity acquisition unit is used to calculate the difference between the second cumulative capacity and the first cumulative capacity, and use it as the remaining rechargeable capacity of the given cell at the reference time.

[0063] In some embodiments, the historical charging process data further includes the cumulative charge of the battery cell with the highest voltage at the corresponding historical sampling time. The cumulative charge-voltage curve acquisition unit acquires the cumulative charge-voltage curve of the battery cell with the highest voltage in the target time period by fitting the cumulative charge and voltage of the battery cell with the highest voltage at each sampling time in the target time period to obtain the cumulative charge-voltage curve.

[0064] In some embodiments, the battery internal short circuit detection device 100 further includes: an average internal short circuit current screening module, a comparison module, and a risk level determination module. The average internal short circuit current screening module is used to screen out the maximum average internal short circuit current among the average internal short circuit currents within the historical time period for each of the battery cells. The comparison module is used to screen out the largest maximum average internal short circuit current from the maximum average internal short circuit currents of each of the battery cells as the strongest internal short circuit current, and compare the strongest internal short circuit current with a preset warning threshold and a preset alarm threshold. The risk level determination module is used to determine that the rechargeable battery is at level one risk if the strongest internal short circuit current is greater than the warning threshold but less than the alarm threshold; and to determine that the rechargeable battery is at level two risk if the strongest internal short circuit current is greater than or equal to the alarm threshold.

[0065] In some embodiments, the battery internal short circuit detection device 100 further includes a sorting module, which is used to sort the average internal short circuit currents of each of the battery cells in the historical time period according to the time order, and determine whether the average internal short circuit current gradually increases over time based on the sorting result; the risk level determination module is further used to determine that the rechargeable battery is at level three risk if the average internal short circuit current of at least one of the battery cells gradually increases over time and the cumulative increase is greater than a preset increase threshold, and the maximum internal short circuit current is greater than or equal to the alarm threshold.

[0066] The battery internal short-circuit detection device provided in this application utilizes a charging process data acquisition module to acquire charging process data of the rechargeable battery over a historical time period. A charging process data filtering module then filters the charging data for each target time period. A remaining rechargeable capacity calculation module determines the remaining rechargeable capacity of each cell at a reference time within the corresponding target time period. Based on this, an average internal short-circuit current calculation module directly calculates the average internal short-circuit current of each cell for two adjacent target time periods, according to the difference in remaining rechargeable capacity at the corresponding reference time and the time interval between the two reference times. Thus, the entire detection process can be completed using only historical data under battery charging conditions, without requiring the battery to be in a long-term static state or a low-charge state. This completely breaks through the stringent limitations of existing static voltage methods on static time and state of charge, significantly improving the continuity and real-time performance of internal short-circuit current detection, enabling continuous online monitoring and avoiding calculation interruptions. Meanwhile, this scheme characterizes the abnormal power decay caused by internal short circuit by the difference in remaining rechargeable power, and obtains the internal short circuit current by dividing the difference by the time interval. This avoids the requirement for ultra-high precision estimation of the absolute value of state of charge (SOC), effectively overcoming the problem of large deviations in SOC estimation caused by factors such as temperature, aging, and charge / discharge rate, which in turn leads to large errors in the calculation of internal short circuit current. This significantly improves the accuracy and engineering applicability of the detection results, thereby reliably ensuring the safe operation of the rechargeable battery system.

[0067] It is understood that the battery internal short circuit detection device in this embodiment corresponds to the battery internal short circuit detection method in the above embodiment. The options in the above embodiment are also applicable to this embodiment, so they will not be described again here.

[0068] Example 3: like Figure 5 As shown, this application also provides a computer device, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to enable the computer device to perform the functions of the various modules in the above-described battery internal short circuit detection method or the above-described battery internal short circuit detection device.

[0069] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0070] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0071] Example 4: This application also provides a computer storage medium for storing the computer program used in the aforementioned computer device. The computer storage medium can be a readable storage medium, a non-volatile storage medium, or a volatile storage medium. For example, the computer storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0072] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0073] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0074] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a 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 part 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 smartphone, 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.

[0075] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for detecting internal short circuits in a battery, characterized in that, include: Collect historical charging process data of the rechargeable battery within a historical time period starting from the current moment; Target charging process data for each target time period is selected from the historical charging process data; Based on the target charging process data, obtain the remaining rechargeable capacity of each cell of the rechargeable battery at a reference time in the corresponding target time period; For each of the battery cells, the time interval between two reference times corresponding to two adjacent target time periods is calculated, as well as the difference between the remaining rechargeable capacity of the battery cell at the corresponding two reference times; the average internal short-circuit current of the battery cell is calculated based on the time interval and the difference of the battery cell.

2. The battery internal short circuit detection method according to claim 1, characterized in that, The historical charging process data includes the charging status, charging current, and voltage of each cell at the corresponding historical sampling time; the process of filtering target charging process data for each target time period from the historical charging process data includes: According to preset filtering conditions, target charging process data for each target time period are filtered from the historical charging process data of the historical time period. The preset filtering conditions are: the corresponding time period is in a continuous charging state and the charging current is greater than a preset current threshold, and the highest cell voltage at the end of the corresponding time period reaches the full charge determination threshold.

3. The battery internal short circuit detection method according to claim 2, characterized in that, The reference time is the charging end time of the corresponding time period or the time when the highest cell voltage reaches the full charge determination threshold; obtaining the remaining rechargeable capacity of each cell of the rechargeable battery at the reference time in the corresponding target time period includes: For any given cell, obtain the cumulative charge-voltage curve of the cell with the highest voltage during the target time period, and the first voltage of the given cell at the reference time. Based on the cumulative charge-voltage curve and the first voltage, the first cumulative charge of any cell at the reference time is obtained using the linear difference method; based on the cumulative charge-voltage curve and the reference voltage, the second cumulative charge corresponding to the reference voltage is obtained using the linear difference method. The difference between the second accumulated power and the first accumulated power is taken as the remaining rechargeable power of any cell at the reference time.

4. The battery internal short circuit detection method according to claim 3, characterized in that, The historical charging process data also includes the cumulative charge of the battery cell with the highest voltage at the corresponding historical sampling time. Obtaining the cumulative charge-voltage curve of the battery cell with the highest voltage within the target time period includes: The cumulative charge and voltage of the battery cell with the highest voltage at each sampling time within the target time period are fitted to obtain the cumulative charge-voltage curve.

5. The battery internal short circuit detection method according to claim 1, characterized in that, The step of calculating the average internal short-circuit current of the battery cell based on the time interval and the difference between the battery cells includes: dividing the difference between the battery cells by the time interval to obtain the average internal short-circuit current of the battery cell.

6. The battery internal short circuit detection method according to any one of claims 1 to 5, characterized in that, Also includes: For each of the aforementioned cells, the maximum average internal short-circuit current is selected from the average internal short-circuit currents within the aforementioned historical time period. The largest maximum average internal short-circuit current is selected from the maximum average internal short-circuit current of each of the cells as the strongest internal short-circuit current, and the strongest internal short-circuit current is compared with the preset warning threshold and the preset alarm threshold. If the strongest internal short-circuit current is greater than the warning threshold but less than the alarm threshold, the rechargeable battery is determined to be at level one risk. If the strongest internal short-circuit current is greater than or equal to the alarm threshold, the rechargeable battery is determined to be at level two risk.

7. The battery internal short circuit detection method according to claim 6, characterized in that, Also includes: For each of the aforementioned cells, the average internal short-circuit currents within the historical time period are sorted in chronological order, and the sorting results are used to determine whether the average internal short-circuit current gradually increases over time. If the average internal short-circuit current of at least one of the cells gradually increases over time, and the cumulative increase is greater than a preset increase threshold, and the strongest internal short-circuit current is greater than or equal to the alarm threshold, then the rechargeable battery is determined to be at level three risk.

8. A battery internal short circuit detection device, characterized in that, include: The data acquisition module is used to collect historical charging process data of the rechargeable battery within a historical time period starting from the current moment; The data filtering module is used to filter out target charging process data for each target time period from the historical charging process data; The power calculation module is used to obtain the remaining rechargeable power of each cell of the rechargeable battery at a reference time in the corresponding target time period based on the target charging process data. The current calculation module is used to calculate the time interval between two corresponding reference times and the difference between the remaining rechargeable capacity of the battery cell at the corresponding two reference times for two adjacent target time periods; and to calculate the average internal short-circuit current of each battery cell based on the time interval and the difference of each battery cell.

9. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the battery internal short circuit detection method according to any one of claims 1-7.

10. A computer storage medium, characterized in that, It stores a computer program, which, when executed on a processor, implements the battery internal short circuit detection method according to any one of claims 1-7.

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