A method and apparatus for identifying abnormal battery cells based on active balancing technology

Abstract

This application provides a method and apparatus for identifying abnormal battery cells based on active balancing technology. The method includes: determining the operating condition of the power battery, which includes either a resting time exceeding a time threshold or a resting time not exceeding a time threshold; and identifying abnormal battery cells based on abnormal identification conditions corresponding to the aforementioned power battery operating condition. The technical solution provided by this application distinguishes different power battery operating conditions and sets two scenarios: a resting time exceeding a time threshold or a resting time not exceeding a time threshold. Corresponding abnormal identification conditions are set for each power battery operating condition, and then abnormal battery cells are identified based on these conditions, thereby achieving effective identification of abnormal battery cells based on active balancing technology.

Description

Technical Field

[0001] This application relates to the field of power battery technology, and in particular to an abnormal cell identification method and device based on active balancing technology. Background Technology

[0002] Currently, most power battery balancing strategies on the market are based on passive balancing technology. This means that when a low-voltage cell is detected, the excess power of all other high-voltage cells is dissipated as heat through balancing resistors. Based on this passive balancing technology, by judging the voltage difference range and the rate of increase between cells, abnormal cells can be identified relatively accurately, thereby providing early warnings and implementing relevant handling measures for the power battery.

[0003] Another power battery balancing strategy is based on active balancing technology. When a low-voltage cell is identified, the voltage difference is compensated by actively replenishing the cell. Active balancing technology can replenish the low-voltage cell in real time, and the voltage difference will be continuously equalized within a controllable range, without continuous increase. Therefore, judging the voltage difference range and the rate of increase between cells is no longer sufficient for identifying abnormal cells based on active balancing technology. Currently, there is no method for identifying abnormal cells based on active balancing technology. Summary of the Invention

[0004] This application provides a method and apparatus for identifying abnormal battery cells based on active balancing technology, which solves the problem that there is no suitable method in the prior art to identify abnormal battery cells based on active balancing technology, and realizes effective identification of abnormal battery cells of power batteries based on active balancing technology under different operating conditions.

[0005] This application provides a method for identifying abnormal battery cells based on active balancing technology, including the following steps: Determine the operating condition of the power battery, which includes whether the resting time exceeds a time threshold or the resting time does not exceed a time threshold. Abnormal cells are identified based on the abnormal identification conditions corresponding to the operating conditions of the power battery.

[0006] In some embodiments, if the power battery operating condition includes a resting time exceeding a time threshold, the abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes at least one of the following: If the resting time of the power battery exceeds the first time threshold, the abnormal cell is determined by judging whether the voltage difference between any two cells collected at the first moment meets the first preset condition, or by judging whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition. If the resting time after a slow full charge of the power battery exceeds the second time threshold, the abnormal cell is identified based on whether the expected and actual charging time of the cell during the active balancing process meets the third preset condition.

[0007] In some embodiments, the first time point is a preset time point after the thermal runaway inspection timed wake-up ends, and the interval between any two adjacent first time points is the same.

[0008] In some embodiments, determining the abnormal battery cell by judging whether the change in the voltage difference between any two battery cells between two adjacent first moments satisfies a second preset condition includes: The abnormal cell is determined by judging whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition, and whether the voltage difference in the latter first moment between two adjacent first moments meets the fourth preset condition.

[0009] In some embodiments, determining abnormal cells based on whether the expected and actual charging times of the cells during active balancing charging meet a third preset condition includes: The replenishment voltage value of the replenishment cell is obtained based on the voltage of the replenishment cell during the active equalization replenishment process and the average voltage of other cells in the power battery. Based on the correspondence between the charging voltage and the charging duration in the charging duration table, the expected charging duration of the charging cell is determined according to the charging voltage of the charging cell and the charging voltage table. The charging voltage table stores the correspondence between the charging voltage value and the expected charging duration. Obtain the actual charging time of the charging cell during the active balancing charging process; Based on the expected charging time and the actual charging time, it is determined whether the charging cell is an abnormal cell.

[0010] In some embodiments, determining whether the battery cell being charged is an abnormal cell based on the expected charging time and the actual charging time includes: Determine the difference between the expected power replenishment time and the actual power replenishment time; Divide the difference by the actual charging time to obtain the increase ratio of the equalization time of the charging cell; If the increase in the equalization duration is greater than the first duration increase threshold, the battery cell being replenished is identified as an abnormal battery cell.

[0011] In some embodiments, if the power battery operating condition includes a resting time that does not exceed a time threshold, the abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes: Obtain the percentage of replenished power of the battery cell in at least two capacity cycles, wherein the percentage of replenished power of the battery cell is the ratio of the replenished power of the battery cell to the rated capacity of the battery cell in each capacity cycle; An abnormal cell is identified by determining whether the percentage of the replenished power of the replenished cell in at least two capacity cycles meets the fifth preset condition.

[0012] In some embodiments, determining the abnormal cell based on whether the percentage of the replenished capacity of the replenished cell in at least two capacity cycles meets a fourth or fifth preset condition includes: Based on the percentage of replenished power of the replenished battery cell in at least two capacity cycles, determine the average percentage of replenished power of the replenished battery cell in at least two capacity cycles, and the growth rate of the percentage of replenished power of the replenished battery cell in at least two capacity cycles. If the average percentage of the replenished power of the replenished battery cell is greater than or equal to a first threshold for the percentage of the replenished power, and / or if the growth rate of the percentage of the replenished power of the replenished battery cell is greater than or equal to a growth rate threshold, the replenished battery cell is determined to be an abnormal battery cell.

[0013] This application also provides an abnormal battery cell identification device based on active balancing technology, comprising the following modules: The operating condition determination module is used to determine the operating condition of the power battery, which includes whether the resting time exceeds a time threshold or the resting time does not exceed a time threshold. The identification module is used to identify abnormal cells based on abnormal identification conditions corresponding to the operating conditions of the power battery.

[0014] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the abnormal cell identification method based on active balancing technology as described above.

[0015] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the abnormal cell identification method based on active balancing technology as described above.

[0016] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the abnormal cell identification method based on active balancing technology as described above.

[0017] The abnormal cell identification method and apparatus based on active balancing technology provided in this application distinguishes different power battery operating conditions and sets two conditions: the resting time exceeds a time threshold or the resting time does not exceed a time threshold. Corresponding abnormal identification conditions are set for each power battery operating condition. Then, abnormal cells are identified in the power battery according to the above-mentioned abnormal identification conditions, thereby realizing the effective identification of abnormal cells based on active balancing technology. Furthermore, by setting different abnormal identification conditions according to different power battery operating conditions, more targeted abnormal cell identification can be achieved for different operating conditions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of an active balancing technology in an embodiment of this application.

[0020] Figure 2 This is a flowchart illustrating the abnormal cell identification method based on active balancing technology provided in this application.

[0021] Figure 3 This is a schematic diagram of the abnormal cell identification device based on active balancing technology provided in this application.

[0022] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] The following is combined with Figures 1-4 The technical solution of this application is described.

[0025] Based on extensive aftermarket data analysis, most power battery differential voltage failures are often due to voltage deviations in a single cell. Passive balancing technology requires consuming the power of other cells to achieve balancing, while active balancing technology only needs to replenish the power of a single cell to achieve balancing. In some embodiments, a bus-isolated unidirectional fixed-point active balancing technology can be used, replenishing only a single cell at a time to achieve active balancing, and then identifying the next cell location for active balancing after replenishment. Furthermore, the balancing circuit has a unidirectional structure, meaning it can only perform replenishment operations on cells from the replenishing power source.

[0026] like Figure 1 The diagram shown is a schematic of an active balancing technology in an embodiment of this application. For multiple battery cells (cell1, cell2, cell3...celln-1 and celln), when the voltage of celln-1 is low, voltage balancing can be achieved by individually replenishing the voltage of celln-1. This active balancing technology identifies the state of charge (SOC) of a single battery cell, determines the location of the cell requiring replenishment, and then activates the active balancing control switch of the corresponding cell. This control switch can be a MOS switch, transferring the replenishing power to the corresponding cell. For example, the balancing duty cycle can be 50%, and the balancing current can be adjustable within 2A.

[0027] Based on the technical solution provided in this application, the identification of abnormal battery cells can be divided into several different power battery operating conditions and processed separately. Corresponding abnormal identification conditions are set for each power battery operating condition, enabling the identification of abnormal battery cells based on these conditions. If the corresponding abnormal identification conditions are met, the abnormal battery cell is determined. It is understood that the power battery in this application embodiment can be applied to vehicles; therefore, the aforementioned power battery operating conditions can also be referred to as vehicle operating conditions.

[0028] Figure 2 A flowchart illustrating the abnormal cell identification method based on active balancing technology provided in this application is shown below. Figure 2 The steps shown may include the following: Step 201: Determine the operating condition of the power battery. The operating condition of the power battery may include two conditions: the resting time exceeds the time threshold or the resting time does not exceed the time threshold. This step primarily considers that if the resting time of the power battery exceeds a certain time threshold, i.e., meets the long-term resting condition, a stable operating condition can be reached. At this point, cell anomaly identification can be based on this stable operating condition. However, if the resting time does not exceed the certain time threshold, the long-term resting condition is not met, and cell anomaly identification cannot be achieved through a stable operating condition. Therefore, other methods can be considered, such as identifying abnormal cells during the dynamic process of active balancing and charging operations. In this embodiment, corresponding anomaly identification conditions can be set for the two different power battery operating conditions mentioned above.

[0029] Step 202: Identify abnormal cells based on the abnormal identification conditions corresponding to the operating conditions of the power battery.

[0030] After setting corresponding anomaly identification conditions for two different operating conditions of the power battery, abnormal cells can be identified based on the anomaly identification conditions corresponding to the actual determined operating conditions of the power battery.

[0031] The technical solution provided in this application distinguishes different power battery operating conditions and sets the above-mentioned power battery operating conditions to include two types of operating conditions: the resting time exceeds the time threshold or the resting time does not exceed the time threshold. Corresponding abnormal identification conditions are set for each power battery operating condition. Then, based on the above-mentioned abnormal identification conditions, abnormal cells of the power battery are identified, thereby realizing the effective identification of abnormal cells based on active balancing technology. Furthermore, by setting different abnormal identification conditions according to different power battery operating conditions, more targeted abnormal cell identification can be achieved for different operating conditions.

[0032] In some embodiments, the above-mentioned power battery operating conditions, including the resting time exceeding a time threshold, can also be divided into two cases, and abnormal cells can be identified separately. For example, the first case may be: the resting time of the power battery exceeds the first time threshold T1; the second case may be: the resting time of the power battery after slow charging exceeds the second time threshold T2.

[0033] In some embodiments, the resting time of the power battery and the resting time after slow charging can both be calculated in real time by the MCU chip unit of the controller, and the first time threshold T1 and the second time threshold T2 can be obtained through calibration tests.

[0034] In a specific embodiment of this application, for the first case described above, when the resting time of the power battery exceeds the first time threshold T1, the abnormal cell can be identified by determining whether the voltage difference between any two cells collected at the first moment meets the first preset condition; and / or by determining whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition.

[0035] In the above embodiments, if the resting time of the power battery exceeds the first time threshold T1, it means that the power battery meets the long-term resting condition. At this time, abnormal cells can be detected by measuring the self-discharge rate and self-discharge capacity of each cell. That is, in this embodiment, the indicators that can be of interest include at least one of the cell voltage difference and voltage difference change between different cells. For example, corresponding thresholds can be set for the voltage difference and voltage difference change, that is, voltage difference threshold and cell voltage difference change threshold can be set respectively, and the first preset condition and the second preset condition can be generated according to the two thresholds respectively.

[0036] When the voltage difference is large, it indicates that the self-discharge rate of the corresponding cell is too high and the cell has generated a large internal resistance, which can be identified as an abnormal cell. The unit of voltage difference can be mV. The change in voltage difference can refer to the increase in voltage difference. A large increase in voltage difference means that the internal resistance of the cell is increasing rapidly and the cell condition is deteriorating sharply. Therefore, it can also be identified as an abnormal cell. The unit of change in voltage difference can be mV / day.

[0037] In this embodiment, when acquiring the voltage difference and its increase, the voltage of each cell can be sampled at multiple fixed first moments, and the voltage difference between different cells at each first moment can be calculated. Simultaneously, the change in the voltage difference between adjacent first moments can also be calculated. Furthermore, the first moment can be a preset time after the thermal runaway inspection wake-up of the power battery has ended; and the interval between adjacent first moments can be the same, meaning that sampling the voltage of each cell is performed at equal intervals. For example, if sampling the voltage of each cell is performed once a day, then the interval between any two adjacent first moments is 24 hours.

[0038] In some embodiments, determining the abnormal cell by judging whether the change in the voltage difference between any two cells between two adjacent first moments satisfies the second preset condition may specifically include: Abnormal cells are identified by determining whether the change in voltage difference between any two cells between two adjacent first moments satisfies the second preset condition, and whether the voltage difference in the latter first moment between two adjacent first moments satisfies the fourth preset condition.

[0039] As described in the above embodiments, the voltage difference can characterize whether the internal resistance of each cell has increased, i.e., whether there is an increase in internal resistance. The change in voltage difference can also be the increase in voltage difference, which can characterize the rate at which the internal resistance of each cell increases. Considering that the rate of change of the internal resistance of the cell is relatively fast, it can also be confirmed at the same time that the internal resistance of the cell is also large before the cell is determined to be an abnormal cell. Whether the voltage difference of the latter first moment in the above two adjacent first moments satisfies the fourth preset condition, wherein the fourth preset condition can also be a voltage difference threshold, and the voltage difference threshold can be the same as the voltage difference threshold corresponding to the first preset condition, or the voltage difference threshold can also be less than the voltage difference threshold corresponding to the first preset condition.

[0040] In some embodiments, determining abnormal cells by judging whether the voltage difference between any two cells collected at a first moment meets a first preset condition may include steps A1 to A3 as shown below: Step A1: At a certain moment after the thermal runaway inspection timed wake-up ends, record the wake-up voltage value of different cells.

[0041] Step A2: Determine the first voltage difference between any two cells at the first moment based on the wake-up voltage value; wherein, the first voltage difference is the voltage difference between a specific cell and another cell.

[0042] Step A3: If the first voltage difference is greater than a preset first voltage threshold, the cell with the lower voltage value among the two cells constituting the first voltage difference is identified as an abnormal cell.

[0043] In steps A1 to A3 above, after the thermal runaway detection timed wake-up is completed, the voltage values ​​of each cell are recorded and stored to obtain the voltage difference between any two cells. Thermal runaway detection is an existing battery control technology and is performed during the battery's resting period; for example, if the battery's resting time has reached 24 hours, the thermal runaway detection could be a task performed 6 hours before reaching 24 hours.

[0044] When the cumulative deep dormancy time of the power battery, i.e., the resting time, reaches 24 hours, it can be woken up again by the system base chip (SBC) at a timed interval, the voltage value of each cell can be collected, and the voltage difference V between any two cells can be obtained. nIn this embodiment, all timing is implemented by the controller chip of the Battery Management System (BMS), and the chip has a global timing function. The above example of reaching the first moment after a 24-hour rest period is for illustration and is not limited in this embodiment. Deep sleep refers to a standby state in which the controller code does not run and does not send or receive messages.

[0045] When a certain first voltage difference V n Once the voltage exceeds the first voltage threshold V1, the corresponding battery cell can be identified, thus forming the aforementioned first voltage difference V. n Of the two battery cells, the cell with the smaller voltage value has an excessively high self-discharge rate, resulting in a large internal resistance. It is impossible to meet the usage requirements by actively balancing the voltage value. This indicates that the battery cell is abnormal and a failure warning can be issued for that cell.

[0046] It is understood that the thresholds in the embodiments of this application can be determined through calibration experiments, and the specific values ​​can eventually be written into the calibrable code area of ​​the software.

[0047] In some embodiments, at the first voltage difference V mentioned above n If the voltage is not greater than the first voltage threshold V1, it can be further determined that after the next resting time, when the next first moment is reached, the voltage difference between each cell is obtained, and the abnormal cell is identified based on the voltage difference between each cell. Specifically, this can include steps B1 to B2: Step B1: At the next first moment, obtain the second voltage difference between each cell, and if the second voltage difference is greater than or equal to a preset first voltage threshold, determine the cell with the lower voltage value among the two cells constituting the second voltage difference as an abnormal cell.

[0048] Step B2: If any second voltage difference is not greater than the first voltage threshold, it can be further determined whether there is a second voltage difference greater than the second voltage threshold. If it can be further determined that the difference between the second voltage difference and the first voltage difference is greater than or equal to the third voltage threshold, the cell with the lower voltage value among the two cells constituting the second voltage difference is identified as an abnormal cell.

[0049] In steps B1 to B2 above, when the first voltage difference Vn does not exceed the first voltage threshold V1, the first voltage difference V between each cell at this time is recorded and stored. n The battery pack contains multiple cells. The voltage difference mentioned above refers to the voltage difference between any cell number n and any other cell number m, where n and m are different integers.

[0050] If the cumulative deep sleep time, i.e. the inactivity time, reaches 24 hours again, it can be woken up again via SBC to obtain and compare the second voltage difference V between each cell. n+1 When there is a second voltage difference V between two battery cells n+1 When the voltage exceeds the first voltage threshold V1, the voltage difference V that constitutes the second voltage difference mentioned above is... n+1 Of the two battery cells, the cell with the lower voltage value issues a failure warning, indicating that the cell is abnormal. When any second voltage difference V... n+1 None of them exceeded the first voltage threshold V1, but there was a second voltage difference V. n+1 When the voltage exceeds the second voltage threshold V2, if the second voltage difference V n+1 The relationship between the time of the corresponding first voltage difference and V satisfies n+1 -V n If the voltage is ≥V3, where V3 is the third voltage threshold, then for the two cells that constitute the second voltage difference mentioned above, the cell with the lower voltage value will be reported as having a failure warning and the cell will be determined to be abnormal.

[0051] If neither of the above two scenarios occurs in the second first moment, the second voltage difference V between the individual cells can be recorded and stored. n+1 The above steps are repeated to identify the abnormal battery cell.

[0052] In this embodiment, for the second scenario described above, if the resting time after a slow full charge of the power battery exceeds the second time threshold T2, abnormal cells can be identified based on whether the expected and actual charging times of the charging cells during the active balancing process meet a third preset condition. In this second scenario, the abnormal cell identification process no longer determines the abnormal cells based on the voltage difference between cells or the change in voltage difference between adjacent first moments, but rather by determining whether the actual charging time of each charging cell during the active balancing process matches the expected charging time.

[0053] In some embodiments, the process of determining abnormal cells by whether the actual charging time of each charging cell during the active balancing process is consistent with the expected charging time may include steps C1 to C4: Step C1: Calculate the replenishment voltage value of the replenishment cell based on the voltage of the replenishment cell during the active balancing process and the average voltage of other cells in the power battery.

[0054] Step C2: Determine the expected charging time of the battery cell based on the charging voltage value and the charging voltage table. The charging voltage table stores the correspondence between the charging voltage value and the expected charging time.

[0055] Step C3: Obtain the actual charging time of the charging cell during the active balancing charging process.

[0056] Step C4: Based on the expected and actual charging times, determine whether the charging cell is an abnormal cell. Specifically, an abnormal cell can be identified if the actual charging time significantly exceeds the expected charging time.

[0057] In some embodiments, the difference between the expected charging time and the actual charging time can be determined first, and then the difference can be divided by the expected charging time to obtain the equalization time increase ratio of the charging cell. If the equalization time increase ratio is greater than the first time increase threshold, the cell can be identified as an abnormal cell.

[0058] In steps C1 to C4 above, for the second scenario, if the resting time after a slow full charge of the power battery exceeds the second time threshold T2, the charge and discharge characteristics of the cells tend to stabilize. At this point, the voltage difference between the cells can be used to identify whether any cell meets the active balancing charging threshold V4. If none does, the BMS remains dormant; if it does, the BMS is woken up to perform active balancing charging. During the active balancing charging process, abnormal cells are identified and judged according to the above strategy. The power battery pack contains multiple cells, and the voltage difference refers to the voltage difference between any n-th cell and any m-th cell, where n and m are distinct positive integers.

[0059] In some specific embodiments, the voltage Vi of the battery cell that needs to be recharged, and the average voltage Vavrg of the remaining cells excluding the recharged cell, can be recorded to obtain the required recharge voltage Via for the recharged cell. Then, based on the Vi and Via mentioned above, and by looking up the recharge duration table, the expected recharge duration T4 is obtained. Simultaneously, the actual recharge duration is recorded during the actual active equalization recharge process. For example, the time T5 taken to raise the corresponding cell voltage to the predetermined level when performing active equalization recharge with 2A and a 50% duty cycle. The equalization duration increase ratio N = (T5-T4) / T4 can be calculated. If N exceeds the first duration increase threshold, it is determined that the internal resistance of the recharged cell exceeds the safety threshold, and a failure warning is issued for the recharged cell, i.e., the recharged cell is abnormal. If N does not exceed the first duration increase threshold, the BMS can continue to sleep after equalization is completed. In some cases, if the voltage difference between all cells is less than the active balancing threshold V4, it means that the voltage consistency of all cells is good and active balancing is not required.

[0060] For the first and second scenarios mentioned above, both address situations where the resting time of the power battery exceeds a time threshold. In this embodiment, for the third scenario where the resting time of the power battery does not exceed the time threshold, the aforementioned abnormal cell identification based on abnormal identification conditions corresponding to the power battery's operating conditions may include: Step D1: Obtain the percentage of the replenished capacity of the battery cell in at least two capacity cycles. The percentage of the replenished capacity of the battery cell is the ratio of the replenished capacity of the battery cell to the rated capacity of the battery cell in each capacity cycle. Step D2: Based on whether the percentage of the replenished power of the replenished cell in at least two capacity cycles meets the fifth preset condition, determine the abnormal cell.

[0061] In some embodiments, obtaining the percentage of charge replenished by the battery cell in at least two capacity cycles in step D1 may specifically include the following steps: Step D11: In each capacity cycle, calculate the amount of electricity to be charged by the battery cell in each capacity cycle based on the charging current, charging duty cycle and charging execution duration.

[0062] Step D12: For a preset number of consecutive capacity cycles, for each capacity cycle, calculate the percentage of the replenishment capacity of the replenishment cell in each capacity cycle based on the charging capacity of the power battery pack, the discharging capacity of the power battery pack, the rated capacity of the power battery pack, and the replenishment capacity of the replenishment cell.

[0063] Furthermore, the step D2 above, which determines abnormal cells based on whether the percentage of charge replenished by the cells in at least two capacity cycles meets the fifth preset condition, may also include the following steps: Step D21: Based on the percentage of replenished energy of the replenished cells in at least two consecutive capacity cycles, determine the average percentage of replenished energy of the replenished cells in at least two capacity cycles, and the growth rate of the percentage of replenished energy of the replenished cells in each capacity cycle in the aforementioned at least two capacity cycles.

[0064] Step D22: If the average percentage of the replenished power of the replenished cell is greater than or equal to the threshold for the percentage of the replenished power, and / or the growth rate of the percentage of the replenished power of the replenished cell is greater than or equal to the growth rate threshold, the replenished cell shall be identified as an abnormal cell.

[0065] Steps D1 and D2 above pertain to the third scenario in this application's embodiments. Since the power battery does not meet the long-term resting conditions, abnormal cells cannot be identified through a stable operating condition. Therefore, it is necessary to make a judgment during the dynamic process of active balancing and charging. If the first or second scenario occurs during this dynamic process, the recorded value of the dynamic process is reset and accumulation restarts. The first or second scenario represents a situation after sufficient resting, where the internal characteristics of each cell are stable. The third scenario represents the incompletely stable characteristics of the cells within the power battery. Considering that the transition from stability to incomplete stability is a new process, recalculation is required.

[0066] In this embodiment of the application, for the third situation described above, the following key information needs to be obtained during the execution process: the position n of the charging cell in the battery pack of the power battery, the charging current A of the charging cell, the charging duty cycle per of the charging cell, and the charging execution time t. Based on obtaining the above key information, the charging capacity Q of the charging cell n can be further obtained. n : In addition, the cumulative charging capacity / cumulative discharging capacity of the power battery can be calculated simultaneously. When the cumulative charging capacity / cumulative discharging capacity reaches a full capacity cycle, the proportion of the charging capacity d of the charging cell is compared, i.e., d=Q. n / Q a This represents the ratio of the replenished capacity of the battery cell to its rated capacity. The battery pack bus current Ipack for the replenished battery cell can be obtained from the BMS. The cumulative charging capacity Q can be obtained by accumulating the current in both the positive and negative directions. c and cumulative discharge capacity Q d Assuming the rated capacity of the battery cell is Q, a complete charge-discharge cycle can be considered when the cumulative discharge capacity reaches Q and the cumulative charge capacity also reaches Q.

[0067] When Ipack < 0, the cumulative charging capacity Q c It can be expressed by the following formula: ; When Ipack > 0, the cumulative discharge capacity Q d It can be expressed by the following formula: ; In this embodiment of the application, the rated capacity of each cell in the battery pack of the power battery is Q. a When the cumulative charging capacity Q c and cumulative discharge capacity Q d Each reaches the rated capacity Q aAt that time, the proportion of the charge replenishment capacity d of the cell n can be calculated; at the same time, the accumulated charge capacity Q can be cleared. c and cumulative discharge capacity Q d And the amount of electricity replenished, Q n Then restart the next capacity cycle calculation. The calculation process for the above-mentioned replenishment power ratio can also be shown in the following code: If Q c >=Q a &&Q d >=Q a / / Determine the cumulative charging capacity Q c and cumulative discharge capacity Q d All are greater than or equal to the rated capacity Q a ; / / Calculate the percentage of electricity used for replenishment.

[0068] The above formula can be used to calculate the proportion of replenished power for any cell in one capacity cycle. This proportion reflects the percentage of time a cell needs replenishment in one capacity cycle, in addition to normal charging. A higher proportion of replenishment indicates frequent replenishment and may also suggest that the cell has a higher internal resistance, potentially indicating an abnormal cell. In some embodiments, to avoid the influence of random factors and improve the accuracy of abnormal cell prediction, the average proportion of replenished power over multiple capacity cycles can be calculated. For example, after three capacity cycles, the proportions of replenished power are d1 / d2 / d3, and the average proportion of replenished power for the cell, da, can be calculated, satisfying: The aforementioned average percentage of replenished power can more accurately reflect the internal resistance of the battery cell at a given time period and can avoid the influence of some accidental factors. Therefore, the average percentage of replenished power d can be set as described above. a Greater than or equal to the threshold d c1 In such cases, the battery cell is identified as abnormal.

[0069] Furthermore, the growth rate d of the replenishment capacity can be calculated based on the replenishment capacity percentages d1 / d2 / d3 obtained in the three capacity cycles mentioned above. z , the d z This can be expressed by the following formula: The growth rate of the proportion of supplementary power generation d z A large value indicates a significant difference in the amount of charge replenished by the cell across different capacity cycles, potentially reflecting a drastic change in cell performance. Therefore, a growth rate d for the proportion of charge replenished can be set as described above. zIf the value is greater than or equal to the threshold dc2, the cell is determined to be abnormal.

[0070] For the average percentage d of the above-mentioned replenishment power... a and the growth rate of the proportion of supplementary power generation d z It can be set to determine a cell malfunction only when only one condition is met; in another case, it can be set to determine a cell malfunction only when both conditions are met, i.e., only when condition d is met. a Greater than or equal to the threshold d c1， And d z Greater than or equal to the threshold d c2 If the battery cell is frequently recharged and the recharge amount varies too much, it can be determined that the battery cell is abnormal and an early warning can be issued for the battery cell.

[0071] Compared to existing technologies that lack specific strategies for identifying abnormal cells using active balancing technology, the technical solutions provided in this application offer corresponding solutions for the three operating conditions of power batteries, thereby enabling accurate identification of the actual state of cells under different operating conditions and identifying abnormal cells in the power battery. In the specific implementation process, the stable characteristics of the battery when it is stationary are also fully utilized for the effective identification of abnormal cells.

[0072] The abnormal cell identification device based on active balancing technology provided in this application is described below. The abnormal cell identification device based on active balancing technology described below can be referred to in correspondence with the abnormal cell identification method based on active balancing technology described above.

[0073] Figure 3 This is a schematic diagram of the abnormal cell identification device based on active balancing technology provided in this application, as shown below. Figure 3 As shown, the device includes the following: The operating condition determination module 301 is used to determine the operating condition of the power battery, which includes whether the resting time exceeds a time threshold or the resting time does not exceed a time threshold. Abnormal cell identification module 302 is used to identify abnormal cells based on abnormal identification conditions corresponding to the operating conditions of the power battery.

[0074] In some embodiments, if the power battery operating condition includes a resting time exceeding a time threshold, the above-mentioned abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes at least one of the following: If the resting time of the power battery exceeds the first time threshold, the abnormal cell is determined by judging whether the voltage difference between any two cells collected at the first moment meets the first preset condition, or by judging whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition. If the resting time after a slow full charge of the power battery exceeds the second time threshold, the abnormal cell is identified based on whether the expected and actual charging time of the cell during the active balancing process meets the third preset condition.

[0075] In some embodiments, the first time point is a preset time point after the thermal runaway inspection timed wake-up ends, and the interval between any two adjacent first time points is the same.

[0076] In some embodiments, determining the abnormal battery cell by judging whether the change in the voltage difference between any two battery cells between two adjacent first moments satisfies a second preset condition includes: The abnormal cell is determined by judging whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition, and whether the voltage difference in the latter first moment between two adjacent first moments meets the fourth preset condition.

[0077] In some embodiments, determining abnormal cells based on whether the expected and actual charging times of the cells during active balancing meet a third preset condition includes: The replenishment voltage value of the replenishment cell is obtained based on the voltage of the replenishment cell during the active balancing process and the average voltage of other cells in the power battery. Based on the correspondence between the charging voltage and the charging duration in the charging duration table, the expected charging duration of the charging cell is determined according to the charging voltage value of the charging cell and the charging duration table. The charging duration table stores the correspondence between the charging voltage value and the charging duration. Obtain the actual charging time of the charging cell during the active balancing charging process; Based on the expected charging time and the actual charging time, it is determined whether the charging cell is an abnormal cell.

[0078] In some embodiments, determining whether the battery cell being charged is an abnormal cell based on the expected charging time and the actual charging time includes: Determine the difference between the expected power replenishment time and the actual power replenishment time; Divide the difference by the actual charging time to obtain the increase ratio of the equalization time of the charging cell; If the increase in the equalization duration is greater than the first duration increase threshold, the battery cell being replenished is identified as an abnormal battery cell.

[0079] In some embodiments, if the power battery operating condition includes a resting time that does not exceed a time threshold, the abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes: Obtain the percentage of replenished power of the battery cell in at least two capacity cycles, wherein the percentage of replenished power of the battery cell is the ratio of the replenished power of the battery cell to the rated capacity of the battery cell in each capacity cycle; An abnormal cell is identified by determining whether the percentage of the replenished power of the replenished cell in at least two capacity cycles meets the fifth preset condition.

[0080] In some embodiments, the above-mentioned determination of abnormal cells based on whether the proportion of the replenished capacity of the replenished cell in at least two capacity cycles meets the fourth and fifth preset conditions includes: Based on the percentage of replenished power of the replenished battery cell in at least two capacity cycles, determine the average percentage of replenished power of the replenished battery cell in at least two capacity cycles, and the growth rate of the percentage of replenished power of the replenished battery cell in at least two capacity cycles. If the average percentage of the replenished power of the replenished battery cell is greater than or equal to a first threshold for the percentage of the replenished power, and / or if the growth rate of the percentage of the replenished power of the replenished battery cell is greater than or equal to a growth rate threshold, the replenished battery cell is determined to be an abnormal battery cell.

[0081] Optionally, the first anomaly determination module 301 includes: Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include a processor 810, a communications interface 820, a memory 830, and a communication bus 840. The processor 810, communications interface 820, and memory 830 communicate with each other via the communication bus 840. The processor 810 can call logic instructions from the memory 830 to execute an abnormal cell identification method based on active balancing technology.

[0082] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the abnormal cell identification method based on active balancing technology provided by the above methods.

[0084] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the abnormal cell identification method based on active balancing technology provided by the above methods.

[0085] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0086] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0087] Finally, it should be noted that the above 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 identifying abnormal battery cells based on active balancing technology, characterized in that, include: Determine the operating condition of the power battery, which includes whether the resting time exceeds a time threshold or the resting time does not exceed a time threshold. Abnormal cells are identified based on the abnormal identification conditions corresponding to the operating conditions of the power battery.

2. The abnormal cell identification method based on active balancing technology according to claim 1, characterized in that, If the power battery operating condition includes a resting time exceeding a time threshold, the abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes at least one of the following: If the resting time of the power battery exceeds the first time threshold, the abnormal cell is determined by judging whether the voltage difference between any two cells collected at the first moment meets the first preset condition, or by judging whether the change in the voltage difference between any two cells between two adjacent first moments meets the second preset condition. If the resting time after a slow full charge of the power battery exceeds the second time threshold, the abnormal cell is identified based on whether the expected and actual charging time of the cell during the active balancing process meets the third preset condition.

3. The abnormal cell identification method based on active balancing technology according to claim 2, characterized in that, The first moment is the preset moment after the thermal runaway inspection timed wake-up ends, and the interval between any two adjacent first moments is the same.

4. The method according to claim 2, characterized in that, The step of determining abnormal cells by judging whether the change in voltage difference between any two cells between two adjacent first moments meets a second preset condition includes: Abnormal cells are identified by determining whether the change in voltage difference between any two cells between two adjacent first moments satisfies the second preset condition, and whether the voltage difference in the latter first moment between two adjacent first moments satisfies the fourth preset condition.

5. The abnormal cell identification method based on active balancing technology according to claim 2, characterized in that, The step of determining abnormal cells based on whether the expected and actual charging times of the cells during active balancing meet a third preset condition includes: The replenishment voltage value of the replenishment cell is obtained based on the voltage of the replenishment cell during the active balancing process and the average voltage of other cells in the power battery. Based on the charging voltage value of the charging cell and the charging voltage table, the expected charging time of the charging cell is determined. The charging voltage table stores the correspondence between the charging voltage value and the expected charging time. Obtain the actual charging time of the charging cell during the active balancing charging process; Based on the expected charging time and the actual charging time, it is determined whether the charging cell is an abnormal cell.

6. The abnormal cell identification method based on active balancing technology according to claim 5, characterized in that, The step of determining whether the battery cell being recharged is an abnormal battery cell based on the expected recharge duration and the actual recharge duration includes: Determine the difference between the expected power replenishment time and the actual power replenishment time; Divide the difference by the actual charging time to obtain the increase ratio of the equalization time of the charging cell; If the increase in the equalization duration is greater than the first duration increase threshold, the battery cell being charged will be identified as an abnormal battery cell.

7. The abnormal cell identification method based on active balancing technology according to claim 1, characterized in that, If the power battery operating condition includes a resting time that does not exceed a time threshold, the abnormal cell identification based on the abnormal identification conditions corresponding to the power battery operating condition includes: Obtain the percentage of replenished power of the battery cell in at least two capacity cycles, wherein the percentage of replenished power of the battery cell is the ratio of the replenished power of the battery cell to the rated capacity of the battery cell in each capacity cycle; Abnormal cells are identified by determining whether the percentage of charge replenished by the cells in at least two capacity cycles meets the fifth preset condition.

8. The abnormal cell identification method based on active balancing technology according to claim 7, characterized in that, The step of determining abnormal cells by judging whether the proportion of the replenished capacity of the replenished cells in at least two capacity cycles meets the fifth preset condition includes: Based on the percentage of the replenished battery cell's replenished capacity in at least two capacity cycles, determine the average percentage of the replenished battery cell's replenished capacity in at least two capacity cycles, and the growth rate of the percentage of the replenished battery cell's replenished capacity in at least two capacity cycles. If the average percentage of the replenished power of the replenished battery cell is greater than or equal to the threshold for the percentage of the replenished power, and / or if the growth rate of the percentage of the replenished power of the replenished battery cell is greater than or equal to the growth rate threshold, the replenished battery cell is determined to be an abnormal battery cell.

9. An abnormal battery cell identification device based on active balancing technology, characterized in that, include: The operating condition determination module is used to determine the operating condition of the power battery, which includes whether the resting time exceeds a time threshold or the resting time does not exceed a time threshold. The identification module is used to identify abnormal cells based on abnormal identification conditions corresponding to the operating conditions of the power battery.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the abnormal cell identification method based on active balancing technology as described in any one of claims 1 to 8.

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