Method for determining abnormal monomers, electronic device, and storage medium

Abstract

The application provides a method for determining abnormal monomers, an electronic device and a storage medium, and relates to the technical field of new energy. The method comprises the following steps: collecting monomer voltage values before and after charging by using the time when the battery system enters the charging mode to determine the risk monomers in the current charging process, and if the determination frequency of the risk monomers reaches a first preset value for the same monomer after the first preset charging of the branch, the risk monomers are determined as abnormal monomers, so that the abnormal monomers with potential liquid leakage risks can be accurately identified before the monomers are irreversibly damaged, and effective early warning is realized.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a method for determining abnormal cells, an electronic device, and a storage medium. Background Technology

[0002] In recent years, with the rapid development of new energy, battery systems, as the core energy storage component of a vehicle, directly affect the vehicle's lifespan and user safety in terms of safety and reliability. Battery systems typically consist of multiple individual cells (also known as single cells or individual units). During long-term charge-discharge cycles, individual cells may degrade in performance due to reasons such as leakage, affecting the safety and reliability of the battery system.

[0003] Currently, battery management systems (BMS) typically use fault alarm mechanisms to detect individual cells. When parameters such as voltage and temperature exceed preset safety thresholds, a fault alarm is triggered. However, this mechanism has significant drawbacks: firstly, some cells may temporarily recover after a fault alarm by being powered on again, masking the fault; secondly, when a fault is actually triggered, the cell has often already suffered irreversible damage, even leading to serious safety incidents such as thermal runaway, thus failing to achieve early identification of cells with potential leakage risks. Summary of the Invention

[0004] This application provides a method, electronic device, and storage medium for identifying abnormal cells, in order to solve the problem that "on the one hand, some cells may temporarily return to normal after a fault alarm is triggered by power-on, thus masking the fault; on the other hand, when the fault is actually triggered, the cell has often already suffered irreversible damage, or even caused serious safety accidents such as thermal runaway, thus making it impossible to identify cells with potential leakage risks in the early stages." Therefore, it can accurately identify cells with potential leakage risks before irreversible damage occurs, thus achieving effective early warning.

[0005] In a first aspect, this application provides a method for determining abnormal cells, applied to a battery system, the battery system including at least one branch, the branch including at least one battery pack, the battery pack including multiple cells, the method comprising: Record the first voltage value of each cell in the branch before charging; After charging with the first charging current for a first duration, the second voltage value of each of the cells in the branch is recorded; Based on the first voltage value and the second voltage value of each of the individual cells in the branch, the risky individual cells in the branch are determined; After the branch is charged for the first preset number of times, if the frequency of determining the risky cell reaches a first preset value for the same cell, then the risky cell is determined to be an abnormal cell.

[0006] In one possible design, determining the at-risk cell in the branch based on the first voltage value and the second voltage value of each cell in the branch includes: Based on the first voltage value and the second voltage value of each cell in the branch, the cell voltage difference of each cell in the branch and the average voltage difference of the branch are obtained; The risky cells in the branch are determined based on the cell pressure difference of each cell in the branch and the average pressure difference of the branch.

[0007] In one possible design, obtaining the individual voltage difference of each cell in the branch and the average voltage difference of the branch based on the first voltage value and the second voltage value of each cell in the branch includes: The difference between the second voltage value and the first voltage value of each of the said cells is determined as the cell voltage difference of each of the said cells; The average pressure difference of each individual cell in the branch is determined as the average pressure difference of the branch.

[0008] In one possible design, determining the risky cells in the branch based on the cell pressure differential of each cell in the branch and the average pressure differential of the branch includes: For a battery pack in the branch, calculate the average voltage difference of the battery pack, and determine the first number of initial cells with the largest individual voltage differences from the cells in the battery pack whose individual cell voltage differences are greater than k times the average voltage difference of the battery pack; where k is greater than 1; Calculate the ratio of the differential pressure of each initial cell to the average differential pressure of the branch; The second number of initial monomers with the largest ratio are identified as the risky monomers in the branch.

[0009] In one possible design, determining the risky cells in the branch based on the cell pressure differential of each cell in the branch and the average pressure differential of the branch includes: Calculate the ratio of the differential pressure of each cell in the branch to the average differential pressure of the branch; The third number of units with the largest ratio are identified as the risk units in the branch.

[0010] In one possible design, after identifying the anomalous monomer, the method further includes: Record early warning information; the early warning information includes the number of each abnormal unit, the ratio of the differential pressure of each abnormal unit to the average differential pressure of the branch, and the early warning information is used to warn the user that there is a risk of leakage in the abnormal unit.

[0011] In one possible design, the method further includes: When it is determined that the battery system has entered the charging mode, under the condition that the state of charge (SOC) of the battery system meets the first preset condition and the temperature of the battery system meets the second preset condition, the first voltage value of each cell in the branch before charging is recorded. The first preset condition includes: the SOC is less than 75%; The second preset condition includes: the temperature of the lowest-temperature cell in the battery system is greater than or equal to 5°C, and the absolute value of the temperature difference between the lowest-temperature cell in the battery system and the highest-temperature cell in the battery system is less than or equal to 5°C.

[0012] In one possible design, the method further includes: Real-time monitoring of the battery management system (BMS) charging wake-up signal and the battery system charging connection confirmation signal; When the BMS charging wake-up signal and the charging connection confirmation signal are both valid, the battery system is determined to enter charging mode.

[0013] Using the method provided in the first aspect, for each branch, the first voltage value of each cell in the branch is recorded; after charging continuously for a first duration with the first charging current, the second voltage value of each cell in the branch is recorded, thereby enabling the acquisition of the voltage changes of the cells during the charging process. This allows for the identification of cells with abnormal changes in internal resistance by comparing the voltage changes of each cell before and after charging. Based on the first and second voltage values ​​of the cells in the branch, risk cells in the branch are identified. Thus, during a single entry into the charging mode and charging process, risk cells in the branch are identified, allowing for cross-cycle comparison of the risk cells identified in each charging cycle during subsequent charging processes. After the branch has undergone a first preset number of charging cycles, if the frequency of risk cell identification for the same cell reaches a first preset value, the risk cell is identified as an abnormal cell. This accurately identifies abnormal cells with potential leakage risks before irreversible damage occurs, enabling effective early warning.

[0014] In a second aspect, this application provides an apparatus for determining an abnormal individual, comprising: a module for performing the method for determining an abnormal individual in the first aspect and any possible design of the first aspect.

[0015] The beneficial effects of the apparatus provided in the second aspect and the various possible designs of the second aspect can be found in the first aspect and the various possible implementations of the first aspect, and will not be repeated here.

[0016] Thirdly, this application provides an electronic device including a first processor, wherein the first processor executes a computer-executable program or instructions in a memory to implement a method for determining an abnormal entity in any possible design of the first aspect.

[0017] Fourthly, this application provides an electronic device including at least one memory and at least one second processor. The memory stores a computer-executable program or instructions, and the second processor, when executing the computer-executable program or instructions, implements a method for determining abnormal entities as described in the first aspect and any possible design of the first aspect.

[0018] Fifthly, this application provides a computer-readable storage medium storing a computer-executable program or instructions, which, when executed by a processor, implements the method for determining abnormal entities as described in the first aspect and any possible design of the first aspect.

[0019] Sixthly, this application provides a computer program product comprising: execution instructions stored in a readable storage medium, at least one processor of an electronic device being able to read the execution instructions from the readable storage medium, and the at least one processor executing the execution instructions causing the electronic device to implement the method for determining abnormal entities as described in the first aspect and any possible design of the first aspect.

[0020] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of a battery system provided in an embodiment of this application.

[0022] Figure 2 This is a flowchart of a method for determining an abnormal monomer provided in an embodiment of this application.

[0023] Figure 3 This is a flowchart illustrating a method for determining risky cells in a branch, as provided in an embodiment of this application.

[0024] Figure 4 A flowchart of another method for determining abnormal monomers provided in an embodiment of this application.

[0025] Figure 5 This is a flowchart illustrating a method for determining risky monomers according to an embodiment of this application.

[0026] Figure 6 A flowchart illustrating another method for determining risky monomers provided in an embodiment of this application.

[0027] Figure 7 This is a schematic diagram of a device for determining an abnormal monomer provided in an embodiment of this application.

[0028] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 1 .

[0029] Figure 9 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 2 . Detailed Implementation

[0030] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c alone can mean: a alone, b alone, c alone, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0031] The terms “center,” “longitudinal,” “lateral,” “up,” “down,” “left,” “right,” “front,” and “rear,” etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0032] The terms "connected" and "connected" should be interpreted broadly. For example, in circuit structures, "connected" or "connected" can refer not only to physical connections but also to electrical or signal connections. This could be a direct connection (physical connection) or an indirect connection via at least one intermediate component, as long as the circuit is connected. It could also refer to the internal connection between two components. Similarly, a signal connection can refer to a connection via a circuit or a medium, such as radio waves. Those skilled in the art will understand the specific meaning of these terms in this application based on the specific circumstances.

[0033] For example, this application provides a method, electronic device, and storage medium for determining abnormal cells. By utilizing the timing when the battery system enters the charging mode, the voltage values ​​of individual cells before and after charging are collected to determine the risk cells during the current charging process. Furthermore, for the same individual cell, if the frequency of determining the risk cells reaches a first preset value, the risk cell is determined to be an abnormal cell. Thus, before the cell suffers irreversible damage, abnormal cells with potential leakage risks can be accurately identified, achieving effective early warning.

[0034] The method for determining abnormal individual in this application can be performed by an electronic device or by a device for determining abnormal individual in an electronic device (hereinafter referred to as the determining device).

[0035] Among them, electronic devices can be servers, desktop computers, mobile phones, tablets, laptops, wearable devices, in-vehicle devices, or augmented reality (AR) / virtual reality (VR) devices, etc.

[0036] The determining device can be implemented through a combination of software and / or hardware. For example, the determining device can be a BMS, or an application (APP), webpage, or public account, etc.

[0037] To simplify the explanation, the embodiments of this application will be described using the example of a determined device.

[0038] Below, in conjunction with Figure 1 This describes the application scenarios of the embodiments of this application.

[0039] Please see Figure 1 , Figure 1 This is a schematic diagram of a battery system provided in one embodiment of this application. Figure 1 As shown, the battery system includes at least one branch, which includes at least one battery pack, and the battery pack includes multiple cells. Figure 1The illustration shows a battery system comprising two branches, each branch comprising two battery packs, and each battery pack comprising three individual cells. However, this embodiment is not limited to this. In practical applications, the number of branches, battery packs, and individual cells can be flexibly configured according to the capacity and layout requirements of the battery system.

[0040] In a battery system, a cell, also known as a single cell or simply a cell, is the basic, indivisible electrochemical unit. Each cell independently stores and releases electrical energy. Each cell is assigned a number to distinguish it from other cells in the battery system. Cells can be prismatic aluminum-cased cells, cylindrical cells, or pouch cells, etc.

[0041] The battery pack is an intermediate layer in the battery system. Each battery pack can include multiple cells connected in series and parallel, and encapsulated in the same housing to form an independent unit. The battery pack may also have independent data acquisition harnesses and heat dissipation structures.

[0042] In some examples, multiple cells can be combined in series and parallel to form a higher capacity cell group. A battery pack can include multiple cell groups.

[0043] In this context, a branch is the highest-level structure of the battery system, referring to an independent path in the battery system that is connected in parallel with each other in terms of high-voltage electrical connections. Each branch can include multiple battery packs connected in series, and the multiple battery packs electrically form a complete high-voltage circuit.

[0044] The battery system may include multiple parallel-connected branches that work together to provide power to the entire vehicle.

[0045] Below, in Figure 1 Based on the battery system shown, combined with Figures 2 to 6 The method for determining abnormal monomers provided in the embodiments of this application will be described in detail.

[0046] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for determining an abnormal monomer according to an embodiment of this application. Figure 2 As shown, the method includes: S101, The device records the first voltage value of each cell in the branch before charging.

[0047] The determining device can, when determining that the battery system has entered the charging mode, record the first voltage value of each cell in the branch before charging, provided that the state of charge (SOC) of the battery system meets the first preset condition and the temperature of the battery system meets the second preset condition.

[0048] When the battery system is determined to enter charging mode, the device activates the identification of abnormal cells to ensure that the voltage changes of individual cells can be obtained before and after charging in order to identify abnormal cells.

[0049] The determining device can determine whether the battery system has entered charging mode through communication handshake detection, charging status notification detection, or charging-related signal detection.

[0050] As a feasible implementation, the device monitors the BMS charging wake-up signal and the charging connection confirmation signal of the battery system in real time; when the BMS charging wake-up signal and the charging connection confirmation signal are both valid, the battery system is determined to enter the charging mode.

[0051] When the BMS charging wake-up signal or the charging connection confirmation signal is determined to be invalid, the determining device determines that the battery system has not entered the charging mode, and the determining device can continue to monitor the BMS charging wake-up signal and the charging connection confirmation signal.

[0052] Among them, the BMS charging wake-up signal refers to the signal generated when the charging gun is connected to the battery system and wakes up the BMS of the battery system when charging is required.

[0053] A valid BMS charging wake-up signal indicates that the charging gun and the battery system have completed a handshake communication, and the battery system's BMS has been woken up. An invalid BMS charging wake-up signal indicates that the charging gun and the battery system have not established a valid handshake communication, and the battery system's BMS has not been woken up.

[0054] The BMS charging wake-up signal is, for example, the ChargeKey signal or the signal between the A+ and A- pins.

[0055] The charging connection confirmation signal is the signal generated after the charging gun is fully connected to the battery system and locked.

[0056] A valid charging connection confirmation signal indicates that the charging gun is fully connected to the battery system and locked, and charging can begin. An invalid charging connection confirmation signal indicates that the charging gun is not connected to the battery system and charging cannot begin.

[0057] The charging connection confirmation signal is, for example, the CC2 signal.

[0058] Considering that when the SOC of the battery system is too high, the charging process will quickly reach full charge, which cannot provide enough time window to complete the identification of abnormal cells, the device needs to determine the SOC state of the battery system. If the SOC meets the first preset condition, it can determine whether abnormal cells can be identified.

[0059] The determination device can obtain the SOC of the battery system from the BMS.

[0060] In some examples, the first preset condition includes: SOC less than 75%.

[0061] Furthermore, considering that temperature affects the performance of the battery system, such as low temperature affecting the internal resistance of individual cells and temperature difference affecting the consistency of individual cells, the determination device also needs to determine the temperature of the battery system and determine whether abnormal cells can be identified when the temperature meets the second preset condition.

[0062] The device can obtain the temperature of the battery system from the BMS or from a temperature sensor installed in the battery system.

[0063] In addition, due to sensor failure or signal interference, the determination device may obtain invalid temperature data. For example, "-40℃" is the default feedback value in the BMS when the temperature sensor is open-circuited or disconnected. Therefore, when the determination device obtains the battery system temperature as -40℃, -40℃ can be regarded as invalid data and discarded, and will not be included in the temperature condition judgment, thereby avoiding false triggering caused by sensor failure.

[0064] In some examples, the second preset condition includes: The temperature of the lowest-temperature cell in the battery system is greater than or equal to 5°C, and the absolute value of the temperature difference between the lowest-temperature cell and the highest-temperature cell in the battery system is less than or equal to 5°C.

[0065] Specifically, a temperature of 5°C or higher for each individual cell can prevent artificially high internal resistance due to low temperature, thus avoiding affecting the accuracy of the acquired voltage values ​​and preventing normal cells from being misidentified. A temperature difference of less than or equal to 5°C between individual cells ensures that each cell operates under similar temperature conditions, so that differences in cell voltage differentials primarily reflect differences in internal resistance rather than differences caused by temperature unevenness, thereby ensuring the accuracy and reliability of identifying abnormal cells.

[0066] When the SOC is greater than or equal to 75%, the temperature of the lowest-temperature cell in the battery system is less than 5°C, or the absolute value of the temperature difference between the lowest-temperature cell and the highest-temperature cell in the battery system is greater than 5°C, the device will not identify abnormal cells when the battery system enters charging mode this time, and the device can wait for the next time the battery system enters charging mode.

[0067] Therefore, when the battery system is determined to enter the charging mode, the device detects the SOC and temperature of the battery system. Only when the SOC meets the first preset condition and the temperature meets the second preset condition will the identification of abnormal cells be initiated. This ensures that the voltage changes of individual cells can be obtained during the charging process under conditions of stable current and suitable battery status, eliminating data distortion caused by environmental factors and helping to ensure the accuracy and reliability of abnormal cell identification.

[0068] For a single cell, according to Ohm's law, under stable charging current conditions, the change in cell voltage is directly proportional to the cell's DC internal resistance. Therefore, by comparing the voltage changes of each cell before and after charging, cells with abnormal internal resistance changes can be identified. Cells with abnormal internal resistance changes may be abnormal cells with potential leakage risks.

[0069] Based on this, under the conditions described above, the device records the first voltage value of each cell in the branch before charging.

[0070] Here, "before charging" refers to the moment before the charging current flows into the battery system; that is, the first voltage value is the open-circuit voltage of a single cell.

[0071] Specifically, the determining device can read the voltage value of each individual cell one by one, and associate the collected first voltage value with the number of each individual cell to store it, thereby obtaining the first voltage value of each individual cell in the branch.

[0072] Thus, the device can obtain the reference voltage value of each cell before charging, so as to identify abnormal cells by the voltage changes of the cells before and after charging.

[0073] At the same time, the BMS sends a battery charging parameter (BCP) message to the charging pile. The charging pile adjusts its output capacity according to the BCP message to match the battery system. After the matching is completed, the BMS controls the relay to close, and the charging pile begins to charge the battery system.

[0074] S102. After charging for a first duration with the first charging current, the determining device records the second voltage value of each cell in the branch.

[0075] The first charging current refers to the charging current output by the charging pile to the battery system. This application does not limit the specific value of the first charging current, but considering the accuracy of subsequent calculations, the first charging current should have a sufficient amplitude. When the charging current is large enough, the voltage change generated by the current flowing through the cell can be effectively identified, avoiding the inability to accurately collect data due to the voltage change being too small, thus failing to meet the requirements for abnormal cell identification.

[0076] For example, the absolute value of the first charging current can be set to be greater than 50A.

[0077] The first duration refers to the time from the start of charging to the recording of the second voltage value. This application does not limit the specific value of the first duration, but in order to ensure that the charging state enters a stable stage, the first duration should be sufficiently long so that the current tends to stabilize and the battery enters a steady state, thereby improving the accuracy of the collected second voltage value.

[0078] For example, the first duration can be 40 seconds.

[0079] Based on this, after charging continuously for a first duration with the first charging current, the device records the second voltage value of each cell in the branch.

[0080] Specifically, the determining device can read the voltage value of each individual cell one by one, and associate the collected first voltage value with the number of each individual cell to obtain the second voltage value of each individual cell in the branch.

[0081] Thus, the determining device can know the voltage value of each cell after a period of charging, so as to identify abnormal cells by the voltage changes of cells before and after charging.

[0082] S103. The determining device determines the risky cells in the branch based on the first voltage value and the second voltage value of each cell in the branch.

[0083] Based on this, during the process of entering the charging mode and charging, the device identifies the risky cells in the branch, so that in subsequent charging processes, the risky cells identified in each charging cycle can be compared across cycles to identify abnormal cells.

[0084] S104. After the first preset charging of the branch, if the frequency of determining the risky cell for the same cell reaches the first preset value, then the risky cell is determined to be an abnormal cell.

[0085] The "determined frequency" refers to the number of times the same cell is identified as a risk cell during the first preset charging process.

[0086] Among them, an abnormal single unit refers to a single unit whose frequency of being identified as a risky single unit reaches a first preset value. In other words, a single unit that has been identified as a risky single unit the number of times after entering the charging mode and charging multiple times has reached the first preset value.

[0087] The higher the detection frequency, the more accurate the identification of abnormal cells; the lower the detection frequency, the faster the response. The first preset value can be configured according to factors such as the battery system's safety level, usage frequency, and maintenance strategy.

[0088] In some examples, the first preset value can be set to 3, which means that the same cell must be identified as a risk cell in each of the three times it enters the charging mode and charges before it is finally identified as an abnormal cell.

[0089] It should be noted that this application does not specifically limit the counting method for determining the frequency; a continuous counting method can be used, meaning that no unidentified cases are allowed in the middle. When a single cell exhibits a persistent abnormality, it indicates that an irreversible physical change may have occurred inside the cell, such as leakage, rather than an occasional interference. In the continuous counting method, the first preset value is equal to the first preset number of occurrences. By using continuous counting, interference can be filtered out, improving the accuracy of the determination.

[0090] Of course, a cumulative counting method can also be used, where a certain number of charges is accumulated within a certain number of charging cycles. In the cumulative counting method, the first preset value is less than the first preset number of charges. The appropriate method can be chosen based on specific needs in practical applications.

[0091] Continuity here refers to temporal continuity, meaning each charging process must be completed sequentially without interruption or skipping. If a risk cell verification operation is not performed during a charging process due to unmet SOC or temperature conditions, this charging session will not be counted in the determination frequency. Specifically, the determination device can skip charging events that do not meet the conditions and only count charging processes that have performed risk cell verification operations in the determination frequency, thereby ensuring the effectiveness of risk cell identification. Of course, the determination device can also restart the accumulation of determination frequencies when a charging event that does not meet the conditions occurs, thereby improving the accuracy of abnormal cell identification.

[0092] For example, when using a continuous counting method, the first preset value is 3. This means that if a cell is identified as a risk cell in each of the three consecutive charging cycles, the determining device will classify that cell as an abnormal cell. If a cell is identified as a risk cell in the first and second charging cycles, but not in the third charging cycle, then that cell is not an abnormal cell.

[0093] In this embodiment, the determining device records the first voltage value of each cell in each branch; after charging continuously for a first duration with the first charging current, it records the second voltage value of each cell in the branch. This allows the device to acquire the voltage changes of the cells during charging, enabling the identification of cells with abnormal internal resistance changes by comparing the voltage changes of each cell before and after charging. Based on the first and second voltage values ​​of the cells in the branch, the device identifies the risk cells in the branch. Thus, during each charging cycle, the determining device identifies the risk cells in the branch, allowing for cross-cycle comparison of the risk cells identified in each subsequent charging cycle. After the branch has undergone a first preset number of charging cycles, if the frequency of risk cell identification reaches a first preset value for the same cell, the risk cell is identified as an abnormal cell. This accurately identifies abnormal cells with potential leakage risks before irreversible damage occurs, facilitating effective early warning.

[0094] Based on the above exemplary description, the determining device can be achieved through, for example... Figure 3 The method shown is used to identify risky individual units in the branch.

[0095] Please see Figure 3 , Figure 3 This is a flowchart illustrating a method for determining risky cells in a branch, as provided in one embodiment of this application. Figure 3 As shown, the method includes: S201. The determining device obtains the individual voltage difference of each cell in the branch and the average voltage difference of the branch based on the first voltage value and the second voltage value of each cell in the branch.

[0096] Among them, the single-cell voltage difference is the voltage change of the same single cell at two different times before and after charging.

[0097] In some examples, the determining device determines the differential voltage of each cell by the difference between the second voltage value of each cell and the first voltage value of the cell.

[0098] The average voltage difference of a branch can reflect the average internal resistance level of all cells in that branch. Since the cells in the same branch flow with the same charging current, the average voltage difference of a branch can reflect the overall health status of the cells in that branch.

[0099] In some examples, the determining device determines the average differential pressure of the branch as the average differential pressure of each cell in the branch.

[0100] The device can store the calculated differential pressure between individual cells and the average differential pressure between branches in a preset storage space, and record them in association with information such as cell number and acquisition time. For battery systems with multiple branches, the device independently maintains the data for each branch.

[0101] S202. The determining device determines the risky cells in the branch based on the cell pressure difference of each cell in the branch and the average pressure difference of the branch.

[0102] Among them, the risky cell refers to the cell whose differential pressure is significantly different from the average differential pressure of the branch during this charging process.

[0103] The determination device can identify risky individual units in a branch in a variety of ways.

[0104] As a feasible implementation method, the device calculates the ratio of the differential pressure of each individual cell to the average differential pressure of the branch, and identifies a preset number of cells with the largest ratio as risk cells. This method is simple to calculate and saves computational resources.

[0105] As another feasible implementation, the device identifies risky cells as those whose individual pressure differential is greater than a certain multiple of the branch's average pressure differential. For example, if the multiple is set to 1.1, then cells whose individual pressure differential is greater than 1.1 times the branch's average pressure differential are considered risky cells. This method allows for dynamic adjustment of the multiple to adapt to the needs of different safety levels.

[0106] As another feasible approach, the determination device can dynamically identify risky cells using statistical methods. Specifically, the device calculates the standard pressure difference of a branch, which is equal to the standard deviation of the cell pressure difference of each cell within that branch. Based on the standard pressure difference and the average pressure difference of the branch, and under the assumption of a normal distribution, cells whose pressure differences deviate from the average value by more than a certain multiple of the standard deviation are identified as risky cells. This method can adapt to the data distribution characteristics of different branches, thereby improving the accuracy of risky cell identification.

[0107] Based on the above exemplary description, after S104, the determining device can also provide an early warning.

[0108] Please see Figure 4 , Figure 4 A flowchart illustrating another method for determining abnormal monomers provided in an embodiment of this application. Figure 4 As shown, after S104, the method further includes: S105. Determine if the device records the early warning information.

[0109] The early warning information includes the number of each abnormal cell and the ratio of the cell's differential pressure to the average differential pressure of the branch. This ratio reflects the degree to which the internal resistance of the abnormal cell deviates from the average level of the branch, thus providing a basis for users to maintain the abnormal cells and improving the user experience.

[0110] In addition, the warning information may also include the identifier of the branch where the abnormal cell is located, the identifier of the battery pack where the abnormal cell is located, and the number of times the abnormal cell has been identified as a risk cell, providing users with a comprehensive basis for fault analysis.

[0111] The early warning information is used to alert users that an abnormal cell may have a risk of leakage. This allows users to perform maintenance on the cell before serious malfunctions such as leakage occur, thus preventing safety accidents such as thermal runaway.

[0112] Based on the above exemplary description, the determining device can store the warning information in a preset storage space after each warning information is received; if a new abnormal unit is determined in the branch, the warning information in the preset storage space is replaced; if no new abnormal unit is determined in the branch, no operation is performed on the preset storage space; if a clearing command is received, the warning information in the preset storage space is cleared.

[0113] The preset storage space refers to a storage area within the device's memory used to store warning information. The size of the preset storage space can be configured based on the number of branches and individual cells in the battery system.

[0114] Here, a new abnormal unit refers to a unit that is different from the abnormal units already recorded in the preset storage space. For example, if unit number 3 of branch 1 is recorded as an abnormal unit in the preset storage space, and unit number 5 of branch 1 is subsequently confirmed as an abnormal unit during charging, the determining device will update the unit number in the warning information in the preset storage space to unit number 5.

[0115] The clear command can be a command sent by the user to the determining device after maintaining the abnormal unit.

[0116] Based on this, warning information is stored in a preset storage space so that users can maintain the battery system according to the warning information, providing users with a basis for maintenance and improving user experience.

[0117] Based on the above exemplary description, the determining device can identify risky individual units in a branch in various ways. The following, in conjunction with... Figure 5 and Figure 6 This explains the method for identifying risky entities.

[0118] Please see Figure 5 , Figure 5 This is a flowchart illustrating a method for determining risky monomers according to an embodiment of this application. Figure 5 As shown, the method includes: S301. For a battery pack in a branch, the determining device calculates the average pressure difference of the battery pack and determines the first number of initial cells with the largest individual pressure difference from the cells whose individual cell pressure difference is greater than k times the average pressure difference of the battery pack.

[0119] Where k is greater than 1.

[0120] Considering that the voltage values ​​of individual cells in the battery system may fluctuate due to factors such as measurement errors and environmental noise, k needs to be greater than 1 to avoid false alarms and improve the accuracy of abnormal cell identification. If k equals 1, any cell with a voltage difference greater than the average voltage difference may be identified as an abnormal cell, resulting in a false alarm.

[0121] The first quantity can be 1, 2, or 3, etc.

[0122] S302. The determination device calculates the ratio of the differential pressure of each initial unit to the average differential pressure of the branch.

[0123] In some examples, when calculating ratios, the ratio can be multiplied by 100 to retain the decimal part and improve calculation accuracy.

[0124] S303. The determining device identifies the second number of initial units with the largest ratio as the risk units in the branch.

[0125] The second quantity can be 1, 2, or 3, etc.

[0126] It should be noted that if the quantity is less than the first quantity / second quantity, all monomers that meet the conditions will be identified as initial monomers / risk monomers.

[0127] The following is a specific example to illustrate this.

[0128] k is 1.1, the first quantity is 1, the second quantity is 1, branch 1 includes battery pack A and battery pack B. Battery pack A includes cells A1, A2, A3, and A4, and battery pack B includes cells B1, B2, B3, and B4. The differential pressure of each cell is shown in Table 1 below: Table 1

[0129] As shown in Table 1, the average voltage difference of battery pack A is 17, the average voltage difference of battery pack B is 18.5, and the average voltage difference of branch 1 is 17.75.

[0130] In battery pack A, the cell with a differential pressure greater than 1.1 times the average differential pressure of battery pack A is cell A3. In battery pack B, the cell with a differential pressure greater than 1.1 times the average differential pressure of battery pack B is cell B2. Therefore, the initial cells include cells A3 and B2.

[0131] The ratio of the differential pressure of unit A3 to the average differential pressure of branch 1 is calculated to be 1.070, and the ratio of the differential pressure of unit B2 to the average differential pressure of branch 1 is calculated to be 1.183. Since 1.183 > 1.070, the determination device identifies unit B2 as a high-risk unit.

[0132] Based on this, the identification device identifies risk cells by performing initial screening within the battery pack and then secondary screening within the branches. This ensures that all potentially abnormal cells within each battery pack can enter the candidate pool of risk cells, preventing abnormal cells within the battery pack from being missed and improving the accuracy of risk cell identification.

[0133] Please see Figure 6 , Figure 6 A flowchart illustrating another method for determining risky monomers provided in an embodiment of this application. Figure 6 As shown, the method includes: S401. Determine the ratio of the differential pressure of each unit in the branch to the average differential pressure of the branch.

[0134] S402. The device determines the third number of units with the largest ratio as the risk units in the branch.

[0135] The third quantity can be 1, 2, or 3, etc.

[0136] It should be noted that if the number is less than the third number, all monomers that meet the conditions will be identified as risk monomers.

[0137] Below, based on the examples in Table 1, we will use a specific example to illustrate the point.

[0138] Based on Table 1, the ratio of the pressure difference of each individual cell in branch 1 to the average pressure difference of branch 1 is shown in Table 2 below: Table 2

[0139] If the third quantity is 1, then the determining device can determine that the risky single entity in branch 1 is: single entity B2.

[0140] Based on this, the device described above can quickly and easily identify risky cells, making it suitable for scenarios with a small number of battery packs and similar health conditions among them, and it has high real-time performance and efficiency.

[0141] Below, during the process of identifying abnormal units, an exemplary data triggering and transmission method is provided, with the specific message as follows: 1. Host computer request message: Message Name: B2P_Req; Baud Rate: Follows external network; ID: 0x10000000 Data length: 8 bytes; Period: Trigger sending node: BMS; The message rules are shown in Table 3 below: Table 3

[0142] Message Name: B2P_Req2; Baud Rate: Follows external network; ID: 0x10000010 Data length: 8 bytes; Period: Trigger sending node: BMS; The message rules are shown in Table 4 below: Table 4

[0143] 2. BMS feedback message Message Name: B2P_Fdback; Baud Rate: Follows external network; ID: 0x10000001 Data length: 8 bytes; Period: trigger (each time 0x10000000 is received, the first byte = 0x01 is sent, and information from branch 1 and 2 is sent); (Each time 0x10000000 is received, the first byte = 0x02, and information from branches 3 and 4 is sent). Sending node: BMS; The message rules are shown in Table 5 below: Table 5

[0144] Message Name: B2P_Fdback2 Baud Rate: Follows external network; ID: 0x10000011 Data length: 8 bytes; Period: trigger (each time 0x10000000 is received, the first byte = 0x01 is sent, and information from branch 1 and 2 is sent); (Each time 0x10000000 is received, the first byte = 0x02, and information from branches 3 and 4 is sent). Sending node: BMS; The message rules are shown in Table 6 below: Table 6

[0145] The following examples, A, B, and C, illustrate the message sending mechanism: A. When the message 0x10000000 0x01 00 00 00 00 00 00 00 is sent, the following message will be received: 0x100000010x01 02 73 74 05 00 72 00 0x100000110x00 00 00 00 00 00 00 6E This message contains the warning information for branch 1 and branch 2. It indicates that the most severe abnormal individual in branch 1 is numbered 01 with a ratio of 1.15; the second most severe abnormal individual is numbered 05 with a ratio of 1.14. The most severe abnormal individual in branch 2 is numbered 02 with a ratio of 1.16, and there are no other abnormal individuals. k is 1.10.

[0146] B. When the message 0x10000000 0x02 00 00 00 00 00 00 00 is sent, the following message will be received: 0x100000010x02 03 74 73 07 00 6E 00 0x100000110x00 00 00 00 00 00 00 6E This message contains the warning information for branches 3 and 4. It indicates that the most severe abnormal individual in branch 3 is numbered 02 with a ratio of 1.16; the second most severe abnormal individual is numbered 07 with a ratio of 1.10. The most severe abnormal individual in branch 4 is numbered 03 with a ratio of 1.15, and there are no other abnormal individuals. k is 1.10.

[0147] C. Sending the message 0x10000000 0x01 01 00 00 00 00 00 will clear the warning information.

[0148] For example, this application provides an apparatus for determining an abnormal individual.

[0149] Figure 7 This is a schematic diagram of a device for determining abnormal monomers according to an embodiment of this application. Figure 7 As shown, the device includes: a first recording module 101, a second recording module 102, and a determination module 103.

[0150] The first recording module 101 is used to record the first voltage value of each cell in the branch before charging; The second recording module 102 is used to record the second voltage value of each cell in the branch after charging for a first time with the first charging current. The determination module 103 is used to determine the risky cells in the branch based on the first voltage value and the second voltage value of each cell in the branch; After the first preset charging of the branch, if the frequency of determining the risky cell reaches the first preset value for the same cell, then the risky cell is determined to be an abnormal cell.

[0151] It should be noted that the device for determining abnormal entities in this application embodiment can be used to execute the technical solutions of the above method embodiments, and its implementation principle and technical effect are similar, so it will not be repeated here.

[0152] In some examples, module 103 is identified as being used specifically for: Based on the first and second voltage values ​​of each cell in the branch, the individual cell voltage difference and the average voltage difference of the branch are obtained. The risky cells in the branch are determined based on the pressure difference of each cell in the branch and the average pressure difference of the branch.

[0153] In some examples, module 103 is identified as being used specifically for: The difference between the second voltage value and the first voltage value of each cell is determined as the cell voltage difference for each cell. The average pressure difference of each cell in the branch is determined as the average pressure difference of the branch.

[0154] In some examples, module 103 is identified as being used specifically for: For a battery pack in a branch, calculate the average voltage difference of the battery pack, and determine the first number of initial cells with the largest individual voltage difference from the cells whose individual cell voltage difference is greater than k times the average voltage difference of the battery pack; where k is greater than 1. Calculate the ratio of the individual pressure differential of each initial cell to the average pressure differential of the branch; The second-largest number of initial monomers with the largest ratios are identified as the risky monomers in the branch.

[0155] In some examples, module 103 is identified as being used specifically for: Calculate the ratio of the pressure difference of each cell in the branch to the average pressure difference of the branch; The third-largest number of units with the largest ratio are identified as the risk units in the branch.

[0156] In some examples, the device also includes: a warning module; The early warning module is used to record early warning information. The early warning information includes the number of each abnormal unit and the ratio of the differential pressure of each abnormal unit to the average differential pressure of the branch. The early warning information is used to warn users that there is a risk of leakage in the abnormal unit.

[0157] In some examples, the first recording module 101 is also used to record the first voltage value of each cell in the branch before charging when it is determined that the battery system has entered the charging mode, provided that the state of charge (SOC) of the battery system meets the first preset condition and the temperature of the battery system meets the second preset condition. The first preset condition includes: SOC less than 75%; The second preset condition includes: the temperature of the lowest-temperature cell in the battery system is greater than or equal to 5°C, and the absolute value of the temperature difference between the lowest-temperature cell in the battery system and the highest-temperature cell in the battery system is less than or equal to 5°C.

[0158] In some examples, the device also includes: a monitoring module; The monitoring module is used to monitor the battery management system (BMS) charging wake-up signal and the battery system charging connection confirmation signal in real time. When the BMS charging wake-up signal and the charging connection confirmation signal are both valid, the battery system is determined to enter charging mode.

[0159] By way of example, this application also provides an electronic device.

[0160] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 1 .like Figure 8 As shown, the electronic device may include a first processor 201, which, when executing a computer-executable program or instruction stored in a memory, implements the embodiments of this application. Figures 2 to 6 The method for identifying abnormal monomers is shown.

[0161] The electronic device can be used to perform the various steps and / or processes corresponding to the electronic devices in the above method embodiments.

[0162] Figure 9 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 2 .like Figure 9 As shown, the electronic device may include a second processor 301 and a memory 302. The memory 302 stores a computer program. When the second processor 301 executes the computer program, it implements the embodiments of this application. Figures 2 to 6 The method for identifying abnormal monomers is shown.

[0163] The electronic device can be used to perform the various steps and / or processes corresponding to the electronic devices in the above method embodiments.

[0164] The electronic device of this application can be used to execute the technical solutions of the method embodiments described above. Its implementation principle and technical effects are similar. The operations implemented by each module can be further referred to the relevant descriptions of the method embodiments, which will not be repeated here. The modules here can also be replaced by components or circuits.

[0165] This application can divide electronic devices into functional modules based on the above method examples. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0166] Another embodiment of this application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the embodiments of this application. Figures 2 to 6 The method for identifying abnormal monomers is shown.

[0167] This application also provides a program product including executable instructions stored in a computer-readable storage medium. At least one processor of an electronic device can read the executable instructions from the computer-readable storage medium, and the at least one processor executes the executable instructions to cause the electronic device to implement embodiments of this application. Figures 2 to 6 The method for identifying abnormal monomers is shown.

[0168] This application also provides a chip that is connected to a memory, or a chip that integrates a memory. When a software program stored in the memory is executed, it implements the embodiments of this application. Figures 2 to 6 The method for identifying abnormal monomers is shown.

[0169] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0170] Those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0171] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for determining an abnormal monomer, characterized in that, Applied to a battery system, the battery system including at least one branch, the branch including at least one battery pack, the battery pack including multiple cells, the method comprising: Record the first voltage value of each cell in the branch before charging; After charging with the first charging current for a first duration, the second voltage value of each of the cells in the branch is recorded; Based on the first voltage value and the second voltage value of each of the individual cells in the branch, the risky individual cells in the branch are determined; After the branch is charged for the first preset number of times, if the frequency of determining the risky cell reaches a first preset value for the same cell, then the risky cell is determined to be an abnormal cell.

2. The method according to claim 1, characterized in that, The step of determining the risky cells in the branch based on the first voltage value and the second voltage value of each cell in the branch includes: Based on the first voltage value and the second voltage value of each cell in the branch, the cell voltage difference of each cell in the branch and the average voltage difference of the branch are obtained; The risky cells in the branch are determined based on the cell pressure difference of each cell in the branch and the average pressure difference of the branch.

3. The method according to claim 2, characterized in that, The step of obtaining the individual voltage difference of each cell in the branch and the average voltage difference of the branch based on the first voltage value and the second voltage value of each cell in the branch includes: The difference between the second voltage value and the first voltage value of each of the said cells is determined as the cell voltage difference of each of the said cells; The average pressure difference of each individual cell in the branch is determined as the average pressure difference of the branch.

4. The method according to claim 2, characterized in that, The step of determining the risky cells in the branch based on the cell pressure difference of each cell in the branch and the average pressure difference of the branch includes: For a battery pack in the branch, calculate the average voltage difference of the battery pack, and determine the first number of initial cells with the largest individual voltage differences from the cells in the battery pack whose individual cell voltage differences are greater than k times the average voltage difference of the battery pack; where k is greater than 1; Calculate the ratio of the differential pressure of each initial cell to the average differential pressure of the branch; The second number of initial monomers with the largest ratio are identified as the risky monomers in the branch.

5. The method according to claim 2, characterized in that, The step of determining the risky cells in the branch based on the cell pressure difference of each cell in the branch and the average pressure difference of the branch includes: Calculate the ratio of the differential pressure of each cell in the branch to the average differential pressure of the branch; The third number of units with the largest ratio are identified as the risk units in the branch.

6. The method according to any one of claims 1 to 5, characterized in that, After identifying the anomalous monomer, the method further includes: Record early warning information; the early warning information includes the number of each abnormal unit, the ratio of the differential pressure of each abnormal unit to the average differential pressure of the branch, and the early warning information is used to warn the user that there is a risk of leakage in the abnormal unit.

7. The method according to any one of claims 1 to 5, characterized in that, The method further includes: When it is determined that the battery system has entered the charging mode, under the condition that the state of charge (SOC) of the battery system meets the first preset condition and the temperature of the battery system meets the second preset condition, the first voltage value of each cell in the branch before charging is recorded. The first preset condition includes: the SOC is less than 75%; The second preset condition includes: the temperature of the lowest-temperature cell in the battery system is greater than or equal to 5°C, and the absolute value of the temperature difference between the lowest-temperature cell in the battery system and the highest-temperature cell in the battery system is less than or equal to 5°C.

8. The method according to claim 7, characterized in that, The method further includes: Real-time monitoring of the battery management system (BMS) charging wake-up signal and the battery system charging connection confirmation signal; When the BMS charging wake-up signal and the charging connection confirmation signal are both valid, the battery system is determined to enter charging mode.

9. An electronic device, characterized in that, include: First processor; The first processor is configured to execute a computer-executable program or instructions in memory, causing the electronic device to perform the method for determining an abnormal entity as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-executable program or instructions configured to perform the method for determining an abnormal entity as described in any one of claims 1 to 8.

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