An internal short circuit detection method, device, storage medium and equipment

Abstract

The application provides an internal short circuit detection method and device, a storage medium and equipment. In the method, the differential capacity curve of each battery cell in the battery pack to be detected is constructed according to the differential capacity curve data of each battery cell. The difference between the highest peak heights of the differential capacity curves of each battery cell is determined, and the highest peak heights of the differential capacity curves of each battery cell are compared with the highest peak height of the differential capacity curve of a reference battery cell to determine the battery cell suspected of internal short circuit. Then, the internal short circuit battery cell is determined by combining the determination results of the two determination methods, and the warning information for the internal short circuit battery cell is generated. In this way, the result accuracy of the battery cell internal short circuit detection is effectively improved by using the double-algorithm interactive verification method, thereby effectively improving the warning accuracy.

Description

Technical Field

[0001] This application relates to the field of battery safety early warning technology, and more specifically, to an internal short circuit detection method, apparatus, storage medium, and device. Background Technology

[0002] An internal short circuit refers to a short circuit between the positive and negative plates within the electrode group of a single battery. Internal short circuits can easily lead to reduced charging and discharging efficiency, decreased capacity retention, and in extreme cases, thermal runaway. Therefore, detecting internal short circuits is crucial for ensuring battery life and safety.

[0003] In related technologies, the presence of an internal short circuit in a battery is typically determined by observing changes in the battery pack voltage and observing whether the voltage drops abnormally. However, this method relies on empirically established internal short circuit thresholds, resulting in relatively low detection accuracy. Summary of the Invention

[0004] The purpose of this application is to provide an internal short circuit detection method, apparatus, storage medium, and device, aiming to solve the problem of low detection accuracy in related technologies for battery internal short circuit detection.

[0005] In a first aspect, this application provides an internal short-circuit detection method, comprising: acquiring differential capacity curve data of each cell in a battery pack under test; constructing a corresponding differential capacity curve based on the differential capacity curve data; the differential capacity curve data being data characterizing the capacity change of the cell under unit voltage; determining the cell with an internal short circuit and classifying it into a first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell; and determining the cell with an internal short circuit and classifying it into a second candidate group by comparing the highest peak height of the differential capacity curves of each cell with the highest peak height of the differential capacity curve of a reference cell; determining the cell with an internal short circuit based on the first candidate group and the second candidate group, and generating a warning message for the cell with the internal short circuit.

[0006] In the above implementation process, based on the differential capacity curve data of each cell in the battery pack under test, corresponding differential capacity curves are constructed. Cells suspected of internal short circuits are identified by comparing the difference between the peak heights of the differential capacity curves of each cell and by comparing the peak heights of the differential capacity curves of each cell with those of a reference cell. Then, the results of both identification methods are combined to determine the cell with the internal short circuit, and a warning message is generated for that cell. In this way, the accuracy of the internal short circuit detection results is effectively improved by using a dual-algorithm interactive verification method, thereby effectively enhancing the warning accuracy.

[0007] Furthermore, in some examples, the step of determining the cell with an internal short circuit and classifying it into the first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell includes: determining the minimum value among the highest peak heights of the differential capacity curves of each cell as a reference value; calculating the difference between the highest peak height of the differential capacity curves of each cell and the reference value, and determining the calculated difference as the highest peak height difference of the corresponding cell; determining the suspected internal short-circuited cell based on the highest peak height difference, and classifying the suspected internal short-circuited cell into the first candidate group.

[0008] In the above implementation process, the minimum peak height is determined from the maximum peak height of the differential capacity curve of each cell, and then the cell suspected of having an internal short circuit is initially identified based on the difference between the maximum peak height of the differential capacity curve of other cells and the minimum peak height.

[0009] Furthermore, in some examples, determining the suspected internal short-circuit cell based on the highest peak height difference includes: if the highest peak height difference of any cell is greater than a preset proportion of the reference value, the cell is determined to be a suspected internal short-circuit cell.

[0010] In the above implementation process, a specific method for judging candidate internally short-circuited cells is provided.

[0011] Furthermore, in some examples, the differential capacity curve of the reference cell is obtained based on the following method: An initial differential capacity curve of the reference cell is obtained through laboratory operating condition data; the laboratory operating condition data is data characterizing the relationship between the capacity change and voltage of the reference cell under laboratory operating conditions; correction coefficients for different temperatures, different charging rates, and different cycle numbers on the cell's differential capacity curve are calculated based on the dataset and actual operating condition data; the dataset is obtained by processing the actual vehicle operation data of the battery pack under test through a big data platform; the actual operating condition data is data characterizing the relationship between the capacity change and voltage of each cell in the battery pack under test under actual operating conditions; based on the correction coefficients, the initial differential capacity curve is updated to obtain the differential capacity curve of the reference cell.

[0012] In the above implementation process, the differential capacity curve of the reference cell is obtained under laboratory conditions, and feature parameters are extracted and updated in real time based on the real vehicle big data database. This can improve the accuracy of internal short circuit detection.

[0013] Furthermore, in some examples, the step of determining the cells with internal short circuits and classifying them into the second candidate group by comparing the highest peak height of the differential capacity curve of each cell with the highest peak height of the differential capacity curve of the reference cell includes: calculating the difference between the highest peak height of the differential capacity curve of each cell and the highest peak height of the differential capacity curve of the reference cell, and determining the calculated difference as the highest peak height difference of the corresponding cell; determining the suspected internal short circuit cells based on the highest peak height difference, and classifying the suspected internal short circuit cells into the second candidate group.

[0014] In the above implementation process, the difference between the highest peak height of the differential capacity curve of each cell and the highest peak height of the differential capacity curve of the reference cell is calculated, and then the cells suspected of internal short circuits are preliminarily identified based on the difference.

[0015] Furthermore, in some examples, determining the suspected internally short-circuited cell based on the highest peak height difference includes: if the highest peak height difference of any cell is greater than a preset proportion of the highest peak height of the differential capacity curve of the reference cell, the cell is determined to be a suspected internally short-circuited cell.

[0016] In the above implementation process, a specific method for judging candidate internally short-circuited cells is provided.

[0017] Furthermore, in some examples, the step of determining the internally short-circuited battery cell based on the first candidate group and the second candidate group, and generating warning information for the internally short-circuited battery cell, includes: calculating the intersection of the first candidate group and the second candidate group, determining the intersection as the internally short-circuited battery cell; using the average internally short-circuited current and average internally short-circuited resistance of the internally short-circuited battery cell as risk values, generating warning information based on the risk values, and outputting the warning information to the vehicle operation system.

[0018] In the above implementation process, the intersection of the judgment results of the two internal short-circuit cell judgment methods is determined as the internal short-circuit cell. Its average internal short-circuit current and average internal short-circuit resistance are calculated and used as risk values ​​to generate internal short-circuit warning information. This allows the vehicle operation system to judge whether there is a deterioration trend based on the risk value, thereby effectively ensuring vehicle safety.

[0019] Secondly, this application provides an internal short-circuit detection device, comprising: a construction module, configured to acquire differential capacity curve data of each cell in a battery pack under test, and construct a corresponding differential capacity curve based on the differential capacity curve data; the differential capacity curve data is data characterizing the capacity change of the cell under unit voltage; a judgment module, configured to determine the cell with internal short circuit and classify it into a first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell, and to determine the cell with internal short circuit and classify it into a second candidate group by comparing the highest peak height of the differential capacity curves of each cell with the highest peak height of the differential capacity curve of a reference cell; and a determination module, configured to determine the cell with internal short circuit based on the first candidate group and the second candidate group, and generate warning information for the cell with internal short circuit.

[0020] Thirdly, this application provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method described in any of the first aspects.

[0021] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described in any of the first aspects.

[0022] Fifthly, this application provides a computer program product that, when run on a computer, causes the computer to perform the method described in any of the first aspects.

[0023] Other features and advantages disclosed in this application will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the above-described technology disclosed in this application.

[0024] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A flowchart illustrating an internal short-circuit detection method provided in this application embodiment;

[0027] Figure 2 A schematic diagram illustrating the workflow of a big data-based intra-cell short-circuit early warning scheme provided in this application embodiment;

[0028] Figure 3 A schematic diagram illustrating a logic for obtaining a self-discharge rate-sensitive voltage range based on a differential capacity curve, provided in an embodiment of this application;

[0029] Figure 4 A schematic diagram showing the comparison results of the highest peak height of each cell in the battery pack under test relative to the minimum highest peak height provided in the embodiments of this application;

[0030] Figure 5 A schematic diagram showing the comparison results of the highest peak height of each cell in the battery pack under test provided in this application embodiment with the highest peak height of a reference cell;

[0031] Figure 6 A hardware structure diagram of a computer device containing an internal short-circuit detection device provided in an embodiment of this application;

[0032] Figure 7 This is a block diagram of an internal short-circuit detection device provided in an embodiment of this application. Detailed Implementation

[0033] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0034] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0035] As described in the background section, existing battery short-circuit detection methods suffer from low detection accuracy. Therefore, this application provides a cell-level short-circuit detection solution to address these issues.

[0036] The embodiments of this application will be described below:

[0037] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for detecting internal short circuits in a battery cell, as provided in an embodiment of this application. The method can be applied to a vehicle management platform. The method includes:

[0038] In step 101, the differential capacity curve data of each cell in the battery pack under test is obtained, and the corresponding differential capacity curve is constructed based on the differential capacity curve data; the differential capacity curve data is data characterizing the amount of capacity change of the cell under unit voltage.

[0039] The battery pack under test mentioned in this step can be a power battery in a vehicle that needs to implement an internal short-circuit warning function, which can be formed by several cells connected in series. In order to realize the internal short-circuit diagnosis of the battery pack under test, the solution in this embodiment acquires the differential capacity curve data of the battery pack under test in real time to construct the corresponding differential capacity curve, laying the foundation for subsequent judgment steps. The differential capacity curve data here is the data associated with the differential capacity curve, which can also be called the capacity increment curve. It is a curve that can intuitively reflect the electrochemical change characteristics inside the battery. In implementation, the platform can collect the cell voltage value, capacity value, etc. of the vehicle battery under constant current charging or discharging conditions, and use it as differential capacity curve data. After obtaining the differential capacity curve data, the platform can obtain the terminal voltage-capacity (VQ) curve of each cell through curve fitting, and then obtain the terminal voltage-capacity change rate (V-dQ / dV) curve of each cell by taking the first derivative of the curve, that is, the differential capacity curve of each cell.

[0040] In step 102, based on the difference between the highest peak heights of the differential capacity curves of each cell, cells with internal short circuits are identified and assigned to the first candidate group. By comparing the highest peak heights of the differential capacity curves of each cell with the highest peak heights of the differential capacity curves of the reference cell, cells with internal short circuits are identified and assigned to the second candidate group.

[0041] In this embodiment, two methods are used to determine internal short circuits. One method is to determine the short circuit based on the difference between the highest peak heights of the differential capacity curves of each cell. The other method is to determine the short circuit by comparing the highest peak heights of the capacity increment curves of the actual cell and the reference cell. This achieves dual-algorithm interactive verification, thereby effectively improving the accuracy of internal short circuit detection and enhancing detection precision.

[0042] Specifically, in some embodiments, the step of determining the cell with an internal short circuit and classifying it into the first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell may include: determining the minimum value among the highest peak heights of the differential capacity curves of each cell as a reference value; calculating the difference between the highest peak height of the differential capacity curves of each cell and the reference value, and determining the calculated difference as the highest peak height difference of the corresponding cell; determining the suspected internal short-circuited cell based on the highest peak height difference, and classifying the suspected internal short-circuited cell into the first candidate group.

[0043] A differential capacity curve may have multiple characteristic peaks and valleys. The characteristic peak with the highest peak is the highest peak of the differential capacity curve, also known as the main peak. The slope of the highest peak of the differential capacity curve reflects the speed at which the battery enters the phase transition, and the voltage range of the highest peak is also the voltage range most sensitive to self-discharge, making it more suitable for screening self-discharge rates caused by internal short circuits. When an internal short circuit occurs in a battery, due to the presence of the short-circuit current, more charge is required to raise the voltage to the same value, resulting in a larger highest peak in the short-circuited battery. Based on this, in this embodiment, the minimum maximum peak height is determined from the highest peak heights of the differential capacity curves of each cell. Then, based on the difference between the highest peak heights of the differential capacity curves of other cells and this minimum maximum peak height, cells suspected of having internal short circuits are preliminarily identified.

[0044] Furthermore, in some embodiments, the aforementioned determination of suspected internally short-circuited cells based on the peak height difference may include: if the peak height difference of any cell is greater than a preset proportion of the benchmark value, the cell is identified as a suspected internally short-circuited cell. Taking a preset proportion of 80% as an example, assuming the battery pack under test is formed by multiple cells connected in series, the minimum peak height among the differential capacity curves of these cells is H. peak_min Then, when the peak height H of the differential capacity curve of the i-th cell is... peak_i Satisfy (H) peak_i -H peak_min >80% H prak_min If the cell is suspected of having an internal short circuit, it is included in the first candidate group. This allows for accurate and rapid preliminary detection of cells with internal short circuits. Of course, in other embodiments, this preset ratio can be set differently according to the specific needs of the scenario, and this application does not impose any limitations on it.

[0045] To overcome the limitations of relying on empirically established internal short-circuit thresholds, this embodiment combines two methods to determine internal short-circuit cells: one method does not consider a reference cell, while the other does. This improves the reliability of the test results. The reference cell refers to a healthy cell of the same type as the cells in the battery pack under test, without any abnormalities such as capacity decay or internal short circuits. Similarly, when an internal short circuit occurs, the presence of the short-circuit current causes a greater amount of charge to be required to raise the voltage to the same value. Therefore, the peak height of the differential capacity curve of the short-circuited battery is relatively greater than that of the reference cell. Based on this, comparing the peak heights of the two methods allows for a preliminary assessment of the internally short-circuited cell.

[0046] In some embodiments, the differential capacity curve of the reference cell can be obtained as follows: An initial differential capacity curve of the reference cell is obtained using laboratory operating condition data; the laboratory operating condition data is data characterizing the relationship between the capacity change and voltage of the reference cell under laboratory operating conditions; correction coefficients are calculated based on the dataset and actual operating condition data to adjust the differential capacity curve for different temperatures, charging rates, and cycle numbers; the dataset is obtained by processing real-vehicle operating data of the battery pack under test using a big data platform; the actual operating condition data is data characterizing the relationship between the capacity change and voltage of each cell in the battery pack under test under actual operating conditions; the initial differential capacity curve is updated based on the correction coefficients to obtain the differential capacity curve of the reference cell. In other words, the differential capacity curve of the reference cell is obtained under laboratory operating conditions and its feature parameters are extracted and updated in real time using a real-vehicle big data database, thus improving the accuracy of internal short-circuit detection.

[0047] The laboratory operating condition data here refers to the data measured during the factory inspection of the battery pack under test, which can be obtained from the vehicle's VIN (Vehicle Identification Number). By extracting relevant data from the laboratory operating condition data and performing curve fitting, the initial differential capacity curve of the reference cell can be obtained. The real vehicle operation data here refers to the operation data of the vehicle where the battery pack under test is located. After the platform collects the real vehicle operation data, it is uploaded to the big data platform through the vehicle network. The big data platform integrates the discrete real vehicle operation data into continuous vehicle data, divides it into different segment types according to the vehicle's operating status and charging status, and extracts the corresponding cumulative mileage, segment start time, segment end time, state of charge, voltage, and current data items to obtain the data set. The actual operating condition data here refers to the data measured during the actual road condition test of the battery pack under test, which can be collected each time the vehicle returns to the depot for charging through a pre-set BMS strategy. By combining this dataset with the actual operating condition data, correction coefficients for the differential capacity curve of the battery cell under different temperatures, different charging rates, and different cycle counts can be calculated. Then, based on these three correction coefficients, the initial differential capacity curve can be verified and updated in real time to obtain the differential capacity curve of the reference battery cell.

[0048] In some embodiments, the step of determining whether a cell has an internal short circuit and classifying it into the second candidate group by comparing the highest peak height of the differential capacity curve of each cell with the highest peak height of the differential capacity curve of the reference cell may include: calculating the difference between the highest peak height of the differential capacity curve of each cell and the highest peak height of the differential capacity curve of the reference cell, and determining the calculated difference as the highest peak height difference of the corresponding cell; determining the suspected internal short circuit cell based on the highest peak height difference, and classifying the suspected internal short circuit cell into the second candidate group. In other words, in implementation, the platform can calculate the difference between the highest peak height of the differential capacity curve of each cell and the highest peak height of the differential capacity curve of the reference cell, and then preliminarily determine the suspected internal short circuit cell based on this difference.

[0049] Furthermore, in some embodiments, the aforementioned determination of suspected internally short-circuited cells based on the peak height difference may include: if the peak height difference of any cell is greater than a preset proportion of the peak height of the differential capacity curve of the reference cell, then the cell is identified as a suspected internally short-circuited cell. Continuing with the previous example, assume the peak height of the differential capacity curve of the reference cell is H. peak_bm Then, when the peak height H of the differential capacity curve of the i-th cell is... peak_i Satisfy (H) peak_i -H peak_bm >80% H peak_bm If the cell is suspected of having an internal short circuit, it is included in the second candidate group. This allows for accurate and rapid preliminary detection of cells with internal short circuits. Similarly, this preset ratio can be set differently according to the specific needs of the scenario; this application does not impose any restrictions on this.

[0050] In step 103, based on the first candidate group and the second candidate group, the internally short-circuited cell is determined, and a warning message for the internally short-circuited cell is generated.

[0051] In this embodiment, the difference between the peak heights of the differential capacity curves of each cell is used to identify cells suspected of internal short circuits, forming a first candidate group. By comparing the peak heights of the differential capacity curves of each cell with the peak height of the differential capacity curve of the reference cell, cells suspected of internal short circuits are identified as forming a second candidate group. By combining the results of the two methods, the cells experiencing internal short circuits can be determined, and corresponding internal short circuit warning information can be generated so that vehicle owners can address the internal short circuit cells in a timely manner, thereby reducing the safety risk of thermal runaway.

[0052] Furthermore, in some embodiments, this step may include: calculating the intersection of the first candidate group and the second candidate group, identifying the intersection as the internally short-circuited cell; using the average internal short-circuit current and average internal short-circuit resistance of the internally short-circuited cell as a risk value, generating warning information based on the risk value, and outputting the warning information to the vehicle operation system. Taking a battery pack formed by 50 lithium iron phosphate cells connected in series as an example, where these cells are numbered 1 to 50, if the first candidate group consists of cells numbered 11, 34, and 35, and the second candidate group consists of cells numbered 34, 35, and 41, then their intersection, i.e., cells numbered 34 and 35, is identified as the internally short-circuited cell. The average internal short-circuit current and average internal short-circuit resistance of these two internally short-circuited cells are then calculated and used as the risk value. This risk value is carried in the warning information and input into the vehicle operation system for a warning reminder. The vehicle operation system can then determine whether there is a deterioration trend based on this risk value, and if the determination result is yes, lock the vehicle and contact maintenance personnel for on-site handling. This effectively ensures vehicle safety.

[0053] Among them, the average internal short-circuit current of the battery cell The average internal short-circuit resistance of the battery cell Here ΔQ leak This refers to the internal short-circuit leakage current of the battery cell during the process of its charging voltage increasing from a first voltage value to a second voltage value. It can be based on the cumulative charging amount Q of the battery cell during this charging process as its voltage increases from the first voltage value to the second voltage value. charge Subtract the average charge amount Q accumulated during the multiple historical charging cycles as the voltage rises from the first voltage value to the second voltage value. mul_charge And thus we obtain ΔQ lea( =Q charge -Q mul_charge ;ΔT v This refers to the time it takes for the voltage to rise from the first voltage value to the second voltage value during this charging process. The voltage is the average voltage corresponding to the voltage rise from a first voltage value to a second voltage value during this charging process. The first and second voltage values ​​can be set according to the needs of specific scenarios, and this application does not impose any restrictions on them.

[0054] In this embodiment, based on the differential capacity curve data of each cell in the battery pack under test, corresponding differential capacity curves are constructed. Cells suspected of internal short circuits are identified by the difference between the peak heights of the differential capacity curves of each cell, and by comparing the peak heights of the differential capacity curves of each cell with those of a reference cell. Then, the results of both identification methods are combined to determine the cell with the internal short circuit, and a warning message is generated for that cell. Thus, by using a dual-algorithm interactive verification method, the accuracy of the cell internal short circuit detection results is effectively improved, thereby significantly enhancing the warning precision.

[0055] To provide a more detailed explanation of the solution in this application, a specific embodiment is described below:

[0056] This embodiment provides a cell-level short-circuit early warning scheme based on big data. The workflow of this embodiment is as follows: Figure 2 As shown, it includes:

[0057] S201. Obtain characteristic data such as terminal voltage and capacity of the battery pack under test under constant current charging or discharging conditions.

[0058] S202. Perform curve fitting on the battery pack under test based on the differential capacity curve, and determine the voltage range that is most sensitive to the self-discharge rate.

[0059] Specifically, using eigenvalue data, the differential capacity curves of each cell in the battery pack under test are obtained through curve fitting. After determining the location of the peak of the highest peak of the differential capacity curve, ΔV is selected on both the left and right sides of the peak, with that location as the center. reg The voltage range of / 2 is taken as the peak range, that is, the voltage range that is most sensitive to self-discharge. Figure 3 As shown, Figure 3 This is a schematic diagram of a logic for obtaining a self-discharge rate-sensitive voltage range based on a differential capacity curve, provided in an embodiment of this application. Curve 31 is the QV curve, curve 32 is the dQ / dV curve, and the circled area 33 in the diagram represents the voltage range most sensitive to the self-discharge rate [V]. t1 V t2 ], where V t1 =V peak -ΔV reg / 2,V t2 =V peak +ΔV reg / 2, In this embodiment, the battery pack under test is formed by 116 lithium iron phosphate cells connected in series, V peak =3.3620V, ΔV reg =31.7mV;

[0060] S203. The internal short-circuit cell is determined by the highest peak height of the differential capacity curve, and the result is the first candidate group.

[0061] Specifically, the 116 cells in the battery pack under test are numbered sequentially from 1 to 116. The comparison results of the highest peak height of these cells relative to the minimum peak height are as follows: Figure 4As shown in the figure, the minimum peak height of the battery cell in the battery pack under test is 23119.48. The differences between the peak height of the actual vehicle battery cells numbered 4, 30, 36, 41, and 69 and this minimum peak height are 20818.09, 18872.25, 20122.57, 19288.26, and 18996.35, respectively, all exceeding 80% of the minimum peak height. Therefore, battery cells numbered 4, 30, 36, 41, and 69 are included in the suspected internal short-circuit battery cells and recorded as the first candidate group.

[0062] S204. By comparing the difference in the highest peak height of the capacity increment curves of the actual cell and the reference cell, the internal short-circuit cell is determined, and the result is the second candidate group.

[0063] Specifically, the comparison results of the peak heights of these cells relative to the peak heights of the reference cell are as follows: Figure 5 As shown in the figure, the highest peak height of the reference cell is 23121.01. The differences between the highest peak heights of the actual vehicle cells numbered 4, 30, 36, 41, and 69 and the highest peak height of the reference cell are 20816.57, 18870.73, 20121.05, 19286.74, and 18994.83, respectively. All of these exceed 80% of the highest peak height of the reference cell. Therefore, cells numbered 4, 30, 36, 41, and 69 are included in the suspected internal short-circuit cells and recorded as the second candidate group.

[0064] S205. Calculate the intersection of the first candidate group and the second candidate group, and determine the intersection as the internal short-circuit cell.

[0065] S206. Calculate the risk value of the internal short-circuit cell, which includes the average internal short-circuit current and the average internal short-circuit resistance.

[0066] S207. Output internal short circuit warning information based on the risk value;

[0067] Specifically, the cells at the intersection of the first and second candidate groups, namely cells numbered 4, 30, 36, 41, and 69, do indeed have internal short circuits. Therefore, an internal short circuit warning message is output so that the vehicle operation system can perform maintenance and repair as soon as possible and quickly specify the BMS retirement strategy online.

[0068] This embodiment overcomes the limitations of relying on empirically established internal short-circuit thresholds by establishing a highly reliable internal short-circuit model based on dual-algorithm interactive verification. This improves the scenario coverage and versatility of the internal short-circuit detection method, while also enhancing the accuracy of the detection results.

[0069] Corresponding to the embodiments of the aforementioned methods, this application also provides embodiments of an internal short-circuit detection device and a terminal thereof:

[0070] Embodiments of the internal short-circuit detection device of this application can be applied to computer devices, such as servers or terminal devices. The device embodiments can be implemented through software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by its processor reading the corresponding computer program instructions from non-volatile memory into memory and executing them. From a hardware perspective, such as... Figure 6 The diagram shown is a hardware structure diagram of a computer device containing the short-circuit detection device in an embodiment of this application. Except for... Figure 6 In addition to the processor 610, memory 630, network interface 620, and non-volatile memory 640 shown, the server or electronic device where the internal short-circuit detection device 631 is located in the embodiment may also include other hardware depending on the actual function of the computer device, which will not be described in detail here.

[0071] Accordingly, this application also provides a computer storage medium storing a program that, when executed by a processor, implements the method in any of the above embodiments.

[0072] Accordingly, this application also provides a computer device, the electronic device including a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the method in any of the above embodiments when executing the instructions.

[0073] The embodiments of this application may take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information may be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0074] like Figure 7 As shown, Figure 7 This is a block diagram of an internal short-circuit detection device provided in an embodiment of this application. The device includes:

[0075] The construction module 71 is used to acquire the differential capacity curve data of each cell in the battery pack under test, and construct the corresponding differential capacity curve based on the differential capacity curve data; the differential capacity curve data is data characterizing the amount of capacity change of the cell under unit voltage.

[0076] The judgment module 72 is used to determine the cells with internal short circuits and classify them into the first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell, and to determine the cells with internal short circuits and classify them into the second candidate group by comparing the highest peak heights of the differential capacity curves of each cell with the highest peak heights of the differential capacity curves of the reference cell.

[0077] The determination module 73 is used to determine the internally short-circuited cell based on the first candidate group and the second candidate group, and generate early warning information for the internally short-circuited cell.

[0078] The specific implementation process of the functions and roles of each module in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0079] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0080] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention filed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not claimed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0082] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

[0083] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for detecting internal short circuits, characterized in that, include: Obtain the differential capacity curve data of each cell in the battery pack under test, and construct the corresponding differential capacity curve based on the differential capacity curve data; The differential capacity curve data is data that characterizes the change in capacity of the battery cell under unit voltage when it is charged or discharged. Based on the difference between the highest peak heights of the differential capacity curves of each cell, cells with internal short circuits are identified and assigned to the first candidate group. By comparing the highest peak heights of the differential capacity curves of each cell with the highest peak heights of the differential capacity curves of the reference cell, cells with internal short circuits are identified and assigned to the second candidate group. Based on the first candidate group and the second candidate group, the internally short-circuited cell is identified, and a warning message is generated for the internally short-circuited cell. The step of determining the internally short-circuited cell based on the first candidate group and the second candidate group includes: Calculate the intersection of the first candidate group and the second candidate group, and determine the intersection as the internally short-circuited cell; The highest peak height is the height corresponding to the characteristic peak with the largest peak height in the voltage range most sensitive to self-discharge in the differential capacity curve.

2. The method according to claim 1, characterized in that, The step of determining which cells have internal short circuits and classifying them into the first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell includes: The minimum value among the highest peak heights of the differential capacity curves of each cell is determined as the benchmark value; Calculate the difference between the highest peak height of the differential capacity curve of each cell and the reference value, and determine the calculated difference as the highest peak height difference of the corresponding cell. Based on the difference in the highest peak height, suspected internally short-circuited cells are identified and classified into the first candidate group.

3. The method according to claim 2, characterized in that, The step of identifying suspected internally short-circuited cells based on the height difference of the highest peak includes: If the difference in the highest peak height of any cell is greater than a preset proportion of the benchmark value, the cell is identified as a suspected internal short-circuit cell.

4. The method according to claim 1, characterized in that, The differential capacity curve of the reference cell was obtained based on the following method: The initial differential capacity curve of the reference cell is obtained by using laboratory operating condition data; the laboratory operating condition data is data characterizing the relationship between the capacity change and voltage of the reference cell under laboratory operating conditions. Based on the dataset and actual operating data, correction coefficients are calculated for different temperatures, charging rates, and cycle counts on the differential capacity curve of the battery cell; the dataset is obtained by processing the actual vehicle operating data of the battery pack under test through a big data platform. The actual operating condition data is data that characterizes the relationship between the capacity change and voltage of each cell in the battery pack under test under actual operating conditions. Based on the correction coefficient, the initial differential capacity curve is updated to obtain the differential capacity curve of the reference cell.

5. The method according to claim 4, characterized in that, The step of comparing the peak height of the differential capacity curve of each cell with the peak height of the differential capacity curve of the reference cell to determine the cells with internal short circuits and classify them into the second candidate group includes: Calculate the difference between the highest peak height of the differential capacity curve of each cell and the highest peak height of the differential capacity curve of the reference cell, and determine the calculated difference as the highest peak height difference of the corresponding cell. Based on the height difference of the highest peak, suspected internally short-circuited cells are identified and classified into the second candidate group.

6. The method according to claim 5, characterized in that, The step of identifying suspected internally short-circuited cells based on the height difference of the highest peak includes: If the difference in the highest peak height of any cell is greater than a preset proportion of the highest peak height of the differential capacity curve of the reference cell, the cell is identified as a suspected internal short-circuit cell.

7. The method according to claim 1, characterized in that, The generation of early warning information for the internally short-circuited battery cell includes: The average internal short-circuit current and average internal short-circuit resistance of the internal short-circuit cell are used as risk values. Early warning information is generated based on the risk values ​​and then output to the vehicle operation system.

8. An internal short-circuit detection device, characterized in that, include: The module is used to acquire the differential capacity curve data of each cell in the battery pack under test, and to construct the corresponding differential capacity curve based on the differential capacity curve data. The differential capacity curve data is data that characterizes the change in capacity of the battery cell under unit voltage when it is charged or discharged. The judgment module is used to determine the cells with internal short circuits and classify them into the first candidate group based on the difference between the highest peak heights of the differential capacity curves of each cell, and to determine the cells with internal short circuits and classify them into the second candidate group by comparing the highest peak heights of the differential capacity curves of each cell with the highest peak heights of the differential capacity curves of the reference cell. The determination module is used to determine the internally short-circuited battery cell based on the first candidate group and the second candidate group, and generate early warning information for the internally short-circuited battery cell; The determining module is specifically used to: calculate the intersection of the first candidate group and the second candidate group, and determine the intersection as an internally short-circuited cell; The highest peak height is the height corresponding to the characteristic peak with the largest peak height in the voltage range most sensitive to self-discharge in the differential capacity curve.

9. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any one of claims 1 to 7.

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