Battery cell leveling equipment and method and energy storage system

Abstract

The embodiment of the invention provides battery cell leveling equipment, a battery cell leveling method and an energy storage system, the battery cell leveling equipment is applied to the energy storage system, the energy storage system comprises a plurality of battery cells, and the battery cell leveling equipment comprises a data acquisition module used for acquiring state data of the plurality of battery cells; the feature analysis module is used for determining an abnormal battery cell according to the state data; the parameter generation module is used for determining a leveling parameter according to the state data of the abnormal battery cell and a preset state data change curve corresponding to the abnormal battery cell; and the leveling module is connected with a plurality of battery cells of the energy storage system and is used for leveling the abnormal battery cells according to the leveling parameters. Through the feature analysis module, the parameter generation module and the leveling module, the battery cell leveling equipment realizes the positioning and leveling functions of the abnormal battery cell, can perform online leveling, improves the leveling efficiency, and ensures the normal use of the energy storage system.

Description

Technical Field

[0001] This application relates to the field of energy storage system technology, and in particular to a cell leveling device, method and energy storage system. Background Technology

[0002] Energy storage systems consist of multiple battery cells, which form the core unit of the system. However, during operation, inconsistencies in the battery cell conditions may arise due to manufacturing differences, aging rates, or other factors. If these inconsistencies are not addressed promptly, continued operation will lead to a decline in system performance, such as reduced capacity and shortened cycle life. More seriously, it may even trigger safety issues like thermal runaway.

[0003] Currently, the common method for leveling inconsistent battery cells is to disassemble the cells and perform the leveling using laboratory equipment. This method cannot achieve online leveling, and leveling during this process will affect the normal operation of the energy storage system. Furthermore, the disassembly and installation of the cells is time-consuming, resulting in low leveling efficiency. Summary of the Invention

[0004] This application provides a battery cell leveling device, method, and energy storage system. By setting a feature analysis module, a parameter generation module, and a leveling module on the leveling device, the battery cell leveling device can locate and level abnormal battery cells, realizing leveling during battery cell use without disassembling abnormal battery cells, ensuring the normal use of the energy storage system, and improving leveling efficiency.

[0005] In a first aspect, embodiments of this application provide a battery cell leveling device applied to an energy storage system. The energy storage system includes multiple battery cells. The leveling device includes: a data acquisition module for acquiring state data of the multiple battery cells; a feature analysis module for identifying abnormal battery cells based on the state data; a parameter generation module for determining leveling parameters based on the state data of the abnormal battery cells and a preset state data change curve corresponding to the abnormal battery cells; and a leveling module connected to the multiple battery cells of the energy storage system for leveling the abnormal battery cells according to the leveling parameters.

[0006] In one possible implementation, the preset state data change curve is a preset relationship curve between the state of charge and the open-circuit voltage; the state data includes voltage; the parameter generation module is specifically used for: reading the reference state of charge corresponding to the voltage of the abnormal cell from the preset state data change curve; determining the target voltage based on the voltage of other cells, and reading the target state of charge corresponding to the target voltage from the preset state data change curve; and determining the balancing parameters based on the difference between the reference state of charge and the target state of charge.

[0007] In one possible implementation, the balancing parameters include balancing current and balancing time; the balancing parameters are determined based on the difference between the reference state of charge and the target state of charge, including: determining the balancing current according to the range of the balancing current; calculating the ratio of the product of the difference between the reference state of charge and the target state of charge and the nominal capacity of the abnormal cell to the product of the balancing current and the efficiency coefficient, and determining the ratio as the balancing time.

[0008] In one possible implementation, the parameter generation module is further configured to: acquire multiple state data of the abnormal cell during the balancing process collected by the data acquisition module; calculate the convergence speed of the state data of the abnormal cell based on the multiple state data during the balancing process; and if the convergence speed is lower than the speed threshold, increase the balancing current to perform balancing based on the increased balancing current.

[0009] In one possible implementation, the balancing module includes a DC-DC converter connected to a programmable load; the programmable load is used to adjust the output current of the DC-DC converter according to the balancing current, so as to balance the abnormal battery cell through the output current.

[0010] In one possible implementation, the DC-DC converter includes a fuse protector; the fuse protector is configured to: blow when the current of the DC-DC converter exceeds a preset fuse current, thereby cutting off the corresponding branch of the DC-DC converter.

[0011] In one possible implementation, the status data includes voltage; the feature analysis module is specifically used to: for each cell, calculate the voltage change rate of the cell in the current cycle based on the collected voltage of the cell in the current cycle; and determine whether the cell is an abnormal cell based on the voltage change rate of multiple consecutive cycles.

[0012] In one possible implementation, the parameter generation module is further configured to: if there is no preset state data change curve corresponding to the abnormal cell, generate the preset state data change curve corresponding to the abnormal cell by performing a pulse test on a cell of the same model as the abnormal cell.

[0013] Secondly, embodiments of this application provide a cell balancing method applied to an energy storage system, the energy storage system including multiple cells, the method including: collecting state data of multiple cells; identifying abnormal cells based on the state data of multiple cells; determining balancing parameters based on the state data of the abnormal cells and a preset state data change curve corresponding to the abnormal cells; and balancing the abnormal cells according to the balancing parameters.

[0014] Thirdly, embodiments of this application provide an energy storage system including multiple battery cells and the battery cell leveling device provided in the first aspect above.

[0015] The battery cell leveling device, method, and energy storage system provided in this application embodiment enable online detection and leveling of battery cells in the energy storage system. Specifically, the feature analysis module identifies inconsistent abnormal battery cells based on the state data of multiple battery cells collected by the data acquisition module, achieving rapid location of abnormal battery cells and enabling the battery cell leveling device to perform online detection of multiple battery cells. For abnormal battery cells, the parameter generation module determines the leveling parameters required for leveling the abnormal battery cells based on the state data of the abnormal battery cells and preset state data change curves. Then, the leveling module levels the abnormal battery cells according to the leveling parameters, achieving online leveling of battery cells, avoiding disassembly of abnormal battery cells, significantly reducing leveling time, and improving leveling efficiency. At the same time, by determining the leveling parameters through preset state data change curves, the leveling parameters are more adapted to abnormal battery cells, optimizing the leveling parameters and making them more accurate, thereby further improving leveling efficiency. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0018] Figure 2 This is a schematic diagram of the structure of a battery cell leveling device provided in an embodiment of this application;

[0019] Figure 3 This is a schematic diagram of another cell leveling device provided in an embodiment of this application;

[0020] Figure 4 A schematic flowchart of a cell leveling method provided in an embodiment of this application;

[0021] Figure 5 This is a schematic diagram of an energy storage system provided in an embodiment of this application.

[0022] Figure label:

[0023] 100 - Energy storage system; 110 - Battery cell;

[0024] 200-Cell leveling equipment;

[0025] 210 - Data Acquisition Module; 220 - Feature Analysis Module; 230 - Parameter Generation Module; 240 - Leveling Module; 250 - Backup Power Module; 260 - Security Protection Module; 270 - Gateway Module; 280 - Cloud Platform; 290 - Display Module.

[0026] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0028] Figure 1 This diagram illustrates an application scenario provided by an embodiment of this application. The specific application scenario is the detection and leveling of abnormalities in battery cells within an energy storage system, specifically applicable to energy storage systems such as power storage, new energy vehicles, and industrial battery packs. Figure 1 As shown, the above-mentioned energy storage system typically has multiple battery cells, which are connected in series, parallel or mixed to meet the higher demands of the energy storage system, such as providing larger capacity, stronger power and higher voltage.

[0029] However, when multiple cells are connected, especially in series, inconsistencies in cell condition may occur due to manufacturing differences, aging rates, or other factors. Inconsistent cell condition refers to differences in the status data (such as voltage, capacity, internal resistance, etc.) of multiple cells, leading to performance degradation or safety risks in the entire energy storage system. Figure 1 The remaining capacities of the multiple battery cells shown are inconsistent (the gray area represents the remaining capacity). When multiple cells are charging, the cell with the higher remaining capacity will be fully charged first, while the other cells are not yet fully charged and continue charging, potentially leading to overcharging of the cell with the higher remaining capacity. Similarly, when multiple cells are discharging, the cell with the lower capacity may be over-discharged. Therefore, during the operation of the energy storage system, it is necessary to monitor the consistency of the cell states and promptly adjust any inconsistent cells to ensure that the states of all cells are consistent, thereby guaranteeing the healthy operation of the energy storage system.

[0030] Leveling refers to the proactive elimination of state differences in detected abnormal cells (i.e., inconsistent cells) through hardware or software methods to ensure that all cells in the energy storage system are in a consistent state. Currently, the typical method for leveling abnormal cells is to manually disassemble them after locating them, which generally takes 2-4 hours. Furthermore, due to limited on-site testing conditions and weak leveling capabilities, leveling requires laboratory equipment after disassembly. This method leads to prolonged interruptions in the energy storage system during leveling, affecting its normal operation. Additionally, both cell disassembly and installation are time-consuming, resulting in high labor costs and low leveling efficiency.

[0031] The battery cell leveling device provided in this application realizes online detection and online leveling functions. Specifically, the feature analysis module analyzes the status data of each battery cell collected by the data acquisition module to identify inconsistent abnormal cells, thus realizing online detection of inconsistent cells. Then, the parameter generation module determines the leveling parameters adapted to the abnormal cells based on the status data of the abnormal cells and the preset status data change curves. The leveling parameters are more accurate, thereby improving the efficiency of subsequent leveling. Finally, according to the leveling parameters, the leveling module connects to the abnormal cells to level them, realizing online leveling, avoiding the need to disassemble the abnormal cells, and improving leveling efficiency.

[0032] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0033] Figure 2 This is a schematic diagram of the structure of a battery cell leveling device provided in an embodiment of this application, as shown below. Figure 2 As shown, the cell leveling device 200 provided in this application is applied to an energy storage system 100, which includes multiple battery cells 110. The cell leveling device 200 includes a data acquisition module 210, a feature analysis module 220, a parameter generation module 230, and a leveling module 240.

[0034] The data acquisition module 210 is used to acquire the status data of multiple battery cells 110; the feature analysis module 220 is used to identify abnormal battery cells based on the status data; the parameter generation module 230 is used to determine the leveling parameters based on the status data of the abnormal battery cells and the preset status data change curves corresponding to the abnormal battery cells; the leveling module 240 is connected to the multiple battery cells 110 of the energy storage system 100 and is used to level the abnormal battery cells according to the leveling parameters.

[0035] Status data are indicators reflecting the current performance of cell 110, including voltage, temperature, and current.

[0036] An abnormal cell is a cell whose status data is inconsistent with that of other cells.

[0037] The preset state data change curve corresponding to cell 110 is a pre-set curve showing the state data of cell 110 changing with other data. Generally, the preset state data change curves of cells 110 of the same model are basically the same, so the preset state data change curve can also be a pre-set curve showing the state data of cell 110 corresponding to that model changing with other data. The preset state data change curve can be pre-stored in the parameter generation module 230.

[0038] For example, the preset state data change curve can be a pre-set curve showing the change of open-circuit voltage of each cell 110 with its state of charge. The state of charge (SOC) is the percentage of the remaining capacity of the cell 110.

[0039] For example, the preset state change curve can also be a preset curve showing the change of open circuit voltage of each cell 110 with the state of charge at different temperatures; or it can be a preset curve showing the change of output current with the state of charge.

[0040] Leveling parameters are the relevant parameters used to level abnormal battery cells, including but not limited to leveling voltage, leveling current, and leveling time.

[0041] The data acquisition module 210 is connected to multiple cells 110 in the energy storage system 100, and the data acquisition module 210 is equipped with multiple sensors, such as voltage sensors, current sensors and temperature sensors, which are used to acquire the status data of each cell 110.

[0042] In some embodiments, the energy storage system 100 further includes a battery management system (BMS). The battery management system is used to monitor, protect, and optimize the operating state of the battery pack. The battery management system has multiple channels, each connected to each battery cell 110, and can collect status data of each connected battery cell 110. The data acquisition module 210 is communicatively connected to the battery management system to obtain the status data of each battery cell 110 collected by the battery management system.

[0043] For example, the data acquisition module 210 can be connected via an adapter that matches the acquisition cable of the battery management system and a 0.5mm... 2 The shielded wire is connected to the battery management system within the energy storage system 100 to obtain the status data of each cell 110 collected by the battery management system.

[0044] The data acquisition module 210 can acquire status data from multiple battery cells 110 at a preset frequency (e.g., 1Hz). After acquiring the status data, it performs noise reduction to improve the data quality. For example, wavelet transform, such as the dB5 basis function, can be used to filter out noise, and then the noise-reduced status data can be further processed. Experimental tests show that the signal-to-noise ratio of the status data can be improved after wavelet transform.

[0045] The feature analysis module 220 is connected to the data acquisition module 210 to receive the status data of multiple battery cells 110 collected by the data acquisition module 210, and to analyze the status data to locate abnormal battery cells.

[0046] The feature analysis module 220 can be a main control chip, such as a microcontroller unit (MCU), digital signal processor (DSP), or application-specific integrated circuit (ASIC); or it can be a field-programmable gate array (FPGA).

[0047] In some embodiments, the feature analysis module 220 can be connected to the data acquisition module 210 via a PCIe (Peripheral Component Interconnect Express) bus. The PCIe bus is a widely used interface standard for high-speed data transmission.

[0048] In other embodiments, the feature analysis module 220 can be connected to the data acquisition module 210 via an opto-isolator, enabling the data acquisition module 210 to send status data to the feature analysis module 220 via optical communication. The opto-isolator can convert electrical signals into optical signals for transmission. Since optical signals are far less susceptible to electromagnetic interference than electrical signals, this embodiment effectively avoids introducing noise during transmission, thereby improving signal transmission quality.

[0049] After receiving the status data of multiple battery cells 110 collected by the data acquisition module 210, the feature analysis module 220 can compare the status data of multiple battery cells 110, identify the battery cells with inconsistent status, and identify the battery cells with inconsistent status as abnormal battery cells.

[0050] For example, if the status data includes voltage, the voltages of multiple cells 110 are compared, and cells whose difference from a reference value is greater than or equal to a preset difference are identified as abnormal cells. The reference value can be the average voltage of the multiple cells 110, or the median voltage of the multiple cells 110; or it can be other statistical values ​​of the voltages of the multiple cells 110.

[0051] In some embodiments, the feature analysis module 220 may also calculate the rate of change of the state data of each cell 110 after receiving the state data of multiple cells 110 collected by the data acquisition module 210, and determine the cells with inconsistent states based on the comparison results of the rate of change of the state data of multiple cells 110.

[0052] The parameter generation module 230 is connected to the data acquisition module 210 and the feature analysis module 220. For example, the parameter generation module 230 is connected to the data acquisition module 210 and the feature analysis module 220 via a PCIe bus.

[0053] The parameter generation module 230 can be a main control chip or a field programmable gate array.

[0054] After determining the presence of an abnormal battery cell, the feature analysis module 220 generates a parameter generation command and sends it to the parameter generation module 230. Responding to the parameter generation command, the parameter generation module 230 identifies the abnormal battery cell indicated by the command and obtains the abnormal battery cell's status data and the corresponding preset status data change curve from the data acquisition module 210. Based on the abnormal battery cell's status data and the corresponding preset status data change curve, the parameter generation module 230 determines the required leveling parameters.

[0055] Among them, obtaining the preset state data change curve corresponding to the abnormal battery cell can be done by querying the preset state data change curve corresponding to the model of the abnormal battery cell in the local parameter library.

[0056] Based on the state data of the abnormal battery cell and the corresponding preset state data change curve, the required leveling parameters are determined. This can be done by determining the target state data to be leveled based on the state data of the abnormal battery cell and the corresponding preset state data change curve; and by determining the leveling parameters required to change the state data of the abnormal battery cell from the current state data to the target state data based on the current state data and the target state data.

[0057] The parameter generation module 230 is connected to the leveling module 240, for example, via a PCIe bus. After determining the leveling parameters, the parameter generation module 230 generates control commands and sends them to the leveling module 240.

[0058] The balancing module 240 is connected to multiple cells 110 of the energy storage system 100 to balance abnormal cells according to the balancing parameters indicated by the control command after responding to the control command.

[0059] In some embodiments, the leveling module 240 may include multiple channels, each channel being connected to multiple cells 110 of the energy storage system 100. In actual operation, only the channel corresponding to the abnormal cell is selected, so that the leveling module 240 only connects to the abnormal cell.

[0060] In other embodiments, the balancing module 240 can also be connected to the battery management system of the energy storage system 100 to send abnormal cells to the battery management system. The battery management system selects the channel corresponding to the abnormal cell to realize the connection between the balancing module 240 and the abnormal cell.

[0061] In this embodiment, the balancing module 240 can use a DC-DC converter for balancing. Specifically, based on the balancing parameters, the output voltage, output circuit, and operating time of the DC-DC converter are configured to match the state data of the DC-DC converter with the balancing parameters. Ultimately, the DC-DC converter transfers energy to or consumes the energy of the abnormal battery cell, thereby achieving the balancing of the abnormal battery cell.

[0062] The cell leveling device 200 provided in this application embodiment enables online detection and leveling of the cells 110 in the energy storage system 100. Specifically, the feature analysis module 220 identifies inconsistent abnormal cells based on the state data of multiple cells 110 collected by the data acquisition module 210, achieving rapid location of abnormal cells and enabling the cell leveling device 200 to perform online detection of multiple cells 110. For abnormal cells, the parameter generation module 230 determines the leveling parameters required for leveling the abnormal cells based on the state data of the abnormal cells and preset state data change curves. Then, the leveling module 240 levels the abnormal cells according to the leveling parameters, achieving online leveling of the cells 110, avoiding disassembly of abnormal cells, significantly reducing leveling time, and improving leveling efficiency. At the same time, by determining the leveling parameters through preset state data change curves, the leveling parameters are more adapted to abnormal cells, optimizing the leveling parameters and making them more accurate, thereby further improving leveling efficiency.

[0063] In one possible implementation, the feature analysis module 220 can be used to calculate the rate of change of the state data of each cell 110, and to determine the cells with inconsistent states based on the comparison of the rate of change of the state data of multiple cells 110.

[0064] Specifically, the status data includes voltage; the feature analysis module 220 is specifically used to: for each cell 110, calculate the voltage change rate of the cell 110 in the current cycle based on the collected voltage of the cell 110 in the current cycle; and determine whether the cell 110 is an abnormal cell based on the voltage change rate of multiple consecutive cycles.

[0065] The voltage is the voltage across the terminals of cell 110. The voltage change rate is a physical quantity representing the change in voltage over time within a preset time period. The period can be a pre-set configurable parameter, such as 30 seconds.

[0066] In this embodiment, the feature analysis module 220 can calculate the voltage change rate of each cell 110 in the current cycle based on the collected voltage of each cell 110 in the current cycle, and determine that the cell 110 is an abnormal cell when the voltage change rate meets the preset abnormal conditions for multiple consecutive cycles.

[0067] In one example, the preset abnormal condition can be that if the voltage change rate exceeds a preset range for N consecutive cycles, such as being greater than or equal to a preset threshold, cell 110 is determined to be an abnormal cell. Here, N is a positive integer greater than or equal to 1, such as 5, 6, etc.

[0068] In another example, the preset abnormal condition could be that the voltage change rate exceeds a preset range for at least a preset number of cycles out of N consecutive cycles, such as being greater than or equal to a preset threshold, thus determining cell 110 as an abnormal cell. For example, assuming N is 10, if the voltage change rate exceeds the preset range for 9 out of 10 cycles, and only 1 cycle does not exceed the preset range, then cell 110 can also be determined as an abnormal cell.

[0069] The preset range is a pre-set configurable parameter. It can be a fixed range or a dynamic range.

[0070] In one example, a standard voltage change rate can be determined based on the specifications of cell 110, and the sum of the standard voltage change rate and the allowable error value can be used as a preset threshold, with the preset range being a range of values ​​greater than or equal to the preset threshold. In another example, the preset threshold can also be the sum of the statistical values ​​(such as the average value) of the voltage change rates of multiple cells 110 in the energy storage system 100 and the allowable error value, with the preset range being a range of values ​​greater than or equal to the preset threshold.

[0071] The voltage change rate is calculated as follows: for each cell 110, the voltage of cell 110 at the start and end of the current cycle is obtained. The difference between the voltage at the start and end of the cycle is divided by the cycle duration to obtain the voltage change rate. That is, K = (V t0 – V t1 ) / T, where K is the rate of voltage change, Vt0 V is the voltage at the beginning of the current cycle. t1 The voltage is the voltage at the end of the current cycle, and T is the cycle duration.

[0072] In the actual operation of cell 110, especially for cells with gradual voltage changes, inconsistencies in their states, particularly in their state of charge, may not be readily apparent in static state data. In other words, a significant difference in the remaining capacity of two cells 110 may be reflected in a smaller difference in their voltage, less than the allowable error. Relying solely on the difference in state data to determine inconsistency can easily lead to missed detections. However, the rate of voltage change amplifies the inherent differences in the states of cell 110. Compared to static state data, the dynamic rate of change is more effective in revealing whether the states of cell 110 are consistent.

[0073] This application uses the voltage change rate to determine whether the state of the battery cell 110 is consistent. Compared with using static state data, the detection accuracy is higher and the identification of abnormal battery cells is more accurate.

[0074] In one possible implementation, the preset state data change curve is a preset relationship curve between the state of charge and the open-circuit voltage; the state data includes voltage; the parameter generation module 230 is specifically used for: reading the reference state of charge corresponding to the voltage of the abnormal cell from the preset state data change curve; determining the target voltage based on the voltage of other cells, and reading the target state of charge corresponding to the target voltage from the preset state data change curve; and determining the balancing parameters based on the difference between the reference state of charge and the target state of charge.

[0075] The preset curve showing the relationship between the state of charge and the open-circuit voltage is a preset curve showing the change of the open-circuit voltage of each cell 110 with the state of charge.

[0076] In this embodiment, the parameter generation module 230 first determines the state of charge (SOC) corresponding to the voltage of the abnormal cell from a preset SOC vs. open-circuit voltage relationship curve, and records it as the reference SOC. Then, based on the voltages of other cells, it determines the target voltage that the abnormal cell needs to achieve, and determines the SOC corresponding to the target voltage from the preset SOC vs. open-circuit voltage relationship curve, and records it as the target SOC. Finally, based on the difference between the reference SOC and the target SOC, it determines a balancing parameter so that the SOC of the abnormal cell can be changed from the reference SOC to the target SOC.

[0077] One way to determine the target voltage based on the voltage of other cells is to use the statistical values ​​of the voltages of other cells (such as average value, median value, etc.) as the target voltage.

[0078] One method for determining balancing parameters based on the difference is to determine the balancing method according to the polarity of the difference. For example, if the difference is greater than 0, the abnormal cell is discharged; if the difference is less than 0, the abnormal cell is charged. Then, the specific balancing parameters are determined based on the absolute value of the difference.

[0079] For example, the absolute value of the difference can be substituted into a preset formula to calculate the balancing parameters. Alternatively, the balancing parameters can be increased accordingly based on the magnitude of the absolute value of the difference, such as increasing the balancing current or balancing time.

[0080] Since the detection of the state of charge of the battery cell 110 is technically complex and dependent on additional conditions, this application uses the voltage of the battery cell 110 in combination with a preset relationship curve between the state of charge and the open circuit voltage to determine the reference charge state and target charge state of the abnormal battery cell, and then determines the leveling parameters. This not only enables the leveling of the state of charge of the battery cell 110, but also makes the determination method simpler and more convenient.

[0081] Optionally, the leveling parameters include leveling current and leveling time; the leveling parameters are determined based on the difference between the reference state of charge and the target state of charge, including: determining the leveling current according to the leveling current range; calculating the ratio of the product of the difference between the reference state of charge and the target state of charge and the nominal capacity of the abnormal cell to the product of the leveling current and the efficiency coefficient, and determining the ratio as the leveling time.

[0082] The leveling current is the current used to charge or discharge the abnormal battery cell. The leveling time is the time required for leveling.

[0083] The balancing current range is a pre-set allowable range of balancing currents, meaning that the balancing current within this range can ensure equipment safety during the balancing process, i.e., it will not damage the cell balancing device 200 and the energy storage system 100. In some embodiments, the balancing current range can be the minimum value between the maximum balancing current and a preset ratio of the nominal capacity, for example, the balancing current range is ≤min(4A, 0.2C). nom ), where 4A is the maximum leveling current, C nom This refers to the nominal capacity.

[0084] In this embodiment, the method for determining the balancing current based on the balancing current range can be to select a value from the balancing current range as the balancing current. This value can be any value or an initial value.

[0085] In other embodiments, the method for determining the balancing current based on the balancing current range can also be to increase the initial value based on the absolute value of the difference. If the increased initial value is within the balancing current range, it is determined as the balancing current. Specifically, increasing the initial value based on the absolute value of the difference can be achieved by adding the product of the absolute value and a preset coefficient to the initial value, and using this product as the increased initial value.

[0086] In this embodiment, determining the leveling time specifically involves calculating the product of the difference between the reference state of charge and the target state of charge and the nominal capacity of the abnormal cell, and then dividing this product by the product of the leveling current and the efficiency coefficient. The result is the leveling time. This can be expressed by the following formula:

[0087] T = (ΔSOC × C) nom ) / (I × η)

[0088] Where T is the leveling time; ΔSOC is the difference between the reference state of charge and the target state of charge; I is the leveling current; C nom η is the nominal capacity of the abnormal cell; η is the efficiency coefficient, which is 0.95 by default.

[0089] This method allows for the rapid determination of balancing time and balancing current; the determination method is simple and easy to implement.

[0090] In some embodiments, the parameter generation module 230 is further configured to: acquire multiple state data of the abnormal cell during the balancing process collected by the data acquisition module 210; calculate the convergence speed of the state data of the abnormal cell based on the multiple state data during the balancing process; and if the convergence speed is lower than the speed threshold, increase the balancing current to perform balancing based on the increased balancing current.

[0091] In some scenarios, statically determined balancing parameters may not be fully compatible with abnormal battery cells. To improve the adaptability and efficiency of balancing parameters, this application also proposes a mechanism for dynamically determining balancing parameters.

[0092] Specifically, during the balancing process of the balancing module 240 balancing the abnormal battery cell based on determined balancing parameters, the parameter generation module 230 continuously communicates with the data acquisition module 210 to acquire multiple state data of the abnormal battery cell during the balancing process. The rate of change of these multiple state data during the balancing process is calculated to obtain the convergence speed of the abnormal battery cell's state data. If the convergence speed is lower than a preset speed threshold, the balancing current is increased, and the increased balancing current is sent to the balancing module 240. The balancing module 240 then balances the abnormal battery cell based on the increased balancing current.

[0093] In this embodiment, the balancing current can be increased in 10% increments, that is, by increasing the original balancing current by 10% multiplied by the maximum balancing current. It should be noted that the balancing current must not exceed the balancing current range.

[0094] In some embodiments, the parameter generation module 230 may also calculate the convergence speed of the state data of the abnormal cell based on multiple state data during the balancing process at a preset period, such as 60s; if the convergence speed is lower than the speed threshold, the balancing current is increased.

[0095] In some embodiments, after increasing the balancing current, the parameter generation module 230 can also calculate the balancing time. The increased balancing current and balancing time are sent to the balancing module 240 so that the balancing module 240 can balance the abnormal battery cell based on the increased balancing current and balancing time.

[0096] By dynamically adjusting the balancing current, the inefficiency problem that may be caused by a fixed balancing current is avoided, and the state of abnormal cells can be adapted in real time, ultimately achieving efficient and precise balancing.

[0097] In some embodiments, the parameter generation module 230 is further configured to: if there is no preset state data change curve corresponding to the abnormal cell, generate the preset state data change curve corresponding to the abnormal cell by performing a pulse test on a cell of the same model as the abnormal cell.

[0098] In this embodiment, if there is no preset state data change curve corresponding to the abnormal cell in the parameter generation module 230, the preset state data change curve corresponding to the abnormal cell can be generated through pulse testing.

[0099] Pulse testing involves applying pulse signals, such as current signals or voltage signals, to the cell 110 and monitoring the cell 110's response to generate a preset state data change curve.

[0100] Specifically, if the parameter generation module 230 detects that there is no preset state data change curve corresponding to the abnormal cell, it acquires a cell of the same model as the abnormal cell and performs a pulse test. Based on the response of the abnormal cell during the pulse test, it generates the preset state data change curve corresponding to the abnormal cell.

[0101] Cells of the same model as the faulty cell include the faulty cell, the cell used in the energy storage system 100, and the backup cell.

[0102] For example, a 10-second pulse test can be performed on a battery cell of the same model as the abnormal battery cell to generate a curve showing the relationship between the state of charge and the open-circuit voltage, i.e., the curve showing the change of the open-circuit voltage of each battery cell with the state of charge.

[0103] In some embodiments, the pulse test specifically involves determining parameters for the pulse test, such as pulse amplitude, pulse frequency, pulse duration, and pulse duty cycle, based on the specifications of the same type of battery cell. These parameters are then used to perform the pulse test, and sensors are used to collect real-time data on the changes in the battery cell's state during the test. Based on these changes, a state data change curve is generated.

[0104] After generating the preset state data change curve corresponding to the abnormal cell, the parameter generation module 230 can store the preset state data change curve.

[0105] By generating a preset state data change curve through pulse testing, the problem that the cell leveling device 200 cannot level new models or abnormal cells that do not have a preset state data change curve is avoided. This improves the cell leveling device 200 and enhances its applicability.

[0106] In one possible implementation, the preset state data change curve is a preset relationship curve between the state of charge and open-circuit voltage at different temperatures; the state data includes voltage and temperature; the parameter generation module 230 is specifically used to: read the reference state of charge corresponding to the voltage of the abnormal cell at the temperature of the abnormal cell from the preset state data change curve; determine the target voltage based on the voltage of other cells, and read the target voltage and the corresponding target state of charge at the temperature of the abnormal cell from the preset state data change curve; and determine the balancing parameters based on the difference between the reference state of charge and the target state of charge.

[0107] In one possible implementation, the balancing module 240 includes a DC-DC converter connected to a programmable load; the programmable load is used to adjust the output current of the DC-DC converter according to the balancing current, so as to balance the abnormal cell through the output current.

[0108] A DC-DC converter, often simply called a DC-DC converter, is a circuit used to transfer energy from cell 110. By configuring its parameters, the DC-DC converter can control the consumption of power in cell 110 and transfer electrical energy into cell 110.

[0109] A programmable load is a device whose parameters can be set via hardware or software. Programmable loads are connected to DC-DC converters, and by setting their parameters, the output parameters of the DC-DC converter can be changed.

[0110] Specifically, the balancing module 240 includes a DC-DC converter connected to a programmable load. Based on the balancing current indicated in the control command, the parameters of the programmable load are set, causing the programmable load to adjust the output current of the DC-DC converter so that its output current is the balancing current. Then, based on the output current of the DC-DC converter, the abnormal battery cells are balanced.

[0111] Compared to commonly used frequency regulation methods, DC-DC converters can provide higher leveling current. For example, while battery management systems can be used for leveling, they typically only provide leveling current in the mA range, whereas DC-DC converters can provide leveling current in the A range, such as 4A, demonstrating their superior leveling capability. Furthermore, through programmable loads, the output current of DC-DC converters is adjustable, making leveling more flexible and adaptable to a wider range of energy storage systems and application scenarios.

[0112] In some embodiments, the DC-DC converter includes a fuse protector; the fuse protector is configured to: blow when the current of the DC-DC converter exceeds a preset fusing current, thereby cutting off the corresponding branch of the DC-DC converter.

[0113] A fuse is a device that breaks a circuit by melting a fusible element when the current passing through it exceeds the fusing current.

[0114] In this embodiment, the DC-DC converter also includes a fuse protector. The fuse protector can be arbitrarily set in a branch of the DC-DC converter. If the current in the branch exceeds the preset fusing current, the fuse element of the fuse protector will melt, cutting off the corresponding branch of the DC-DC converter. This prevents excessive current from damaging the devices in the branch and protects the safety of the DC-DC converter.

[0115] In some embodiments, a fuse protector can be installed in the output branch of the DC-DC converter, i.e., the branch connected to the energy storage system 100. If the output current of the DC-DC converter is too large and exceeds the fuse current, the fuse protector will blow, cutting off the connection between the DC-DC converter and the energy storage system 100, thereby protecting the safety of the energy storage system 100.

[0116] By setting up a fuse protector, the cell leveling device 200 and the energy storage system 100 can be protected to prevent damage to the cell leveling device 200 and the energy storage system 100 caused by overcurrent or short circuit.

[0117] Figure 3 This is a schematic diagram of another cell leveling device provided in an embodiment of this application. Figure 3 As shown, this embodiment is... Figure 2Based on the embodiment shown, a backup power module 250, a security protection module 260, a gateway module 270, a cloud platform 280, and a display module 290 are added.

[0118] The backup power module 250 is a standby power module that is connected to other modules of the cell leveling device 200. It is used to start the backup power module 250 when the main power supply module fails to work properly, so as to ensure the normal operation of the cell leveling device 200.

[0119] The safety protection module 260 has a built-in insulation monitoring unit and a temperature monitoring unit, which are used to stop the operation of the cell leveling device 200 when an insulation fault is detected or the temperature change exceeds a preset change threshold.

[0120] Specifically, the insulation monitoring unit can monitor whether the cell leveling device 200 is insulated using either the injected signal method or the bridge balancing method. If an insulation fault is detected, i.e., the device is not insulated, a stop operation control command is generated, and in response to the stop operation control command, the cell leveling device 200 stops operating.

[0121] For example, if insulation is detected by the bridge balancing method, and an insulation fault is detected by the bridge imbalance, a stop operation control command is generated to stop the operation of the cell leveling device 200, such as stopping the operation of the leveling module 240.

[0122] The temperature monitoring unit includes a temperature sensor, such as an NTC sensor. The temperature sensor monitors the temperature of the cell leveling device 200, such as the temperature of the cable. If the temperature change exceeds a preset threshold, the operation of the cell leveling device 200 will be stopped.

[0123] In some embodiments, the temperature detection unit is further configured to adjust the current of the cell leveling device 200, such as the leveling current, if the temperature change exceeds a preset change threshold, so as to reduce power consumption and make the temperature change less than or equal to the preset change threshold.

[0124] The gateway module 270 is used to upload the data generated and collected during the operation of the cell leveling device 200 to the cloud platform 280, so that relevant personnel can download the uploaded data at any time through the cloud platform 280 and remotely monitor the operation of the cell leveling device 200.

[0125] The display module 290 is used to display the real-time operating status of the cell leveling device 200, including the leveling current, the voltage of the cell 110, the charging and discharging power of the cell 110, the temperature of the cell 110, the insulation status of the cell leveling device 200, and the temperature of the cell leveling device 200.

[0126] In some embodiments, the display module 290 further includes an input unit, such as a touch screen, through which relevant personnel can control the operation of the battery cell leveling device 200, such as setting leveling parameters.

[0127] In some embodiments, the cell leveling device 200 further includes a mobile carrier on which other modules of the cell leveling device 200 are mounted to facilitate the movement of the cell leveling device 200.

[0128] In this embodiment, the cell leveling device 200 has additional modules to supplement its functions, meet the needs of diverse scenarios, and is more suitable for complex scenarios such as low temperature and high altitude, thus facilitating its use. At the same time, safety protection functions have been added, making the cell leveling device 200 more reliable and reducing the failure rate.

[0129] Figure 4 This is a schematic flowchart illustrating a cell leveling method provided in an embodiment of this application. Figure 4 As shown, the method provided in this application is applied to an energy storage system 100, which includes a plurality of battery cells 110. The method includes:

[0130] S401, Collect status data of multiple battery cells 110.

[0131] In this step, the data acquisition module 210 acquires status data of multiple battery cells 110 at a preset frequency.

[0132] S402. Based on the status data of multiple battery cells 110, identify the abnormal battery cells.

[0133] In this step, the feature analysis module 220 locates inconsistent abnormal cells based on the status data of multiple cells 110, thereby realizing the detection of abnormal cells.

[0134] S403. Determine the leveling parameters based on the status data of the abnormal battery cell and the preset status data change curve corresponding to the abnormal battery cell.

[0135] In this step, the parameter generation module 230 acquires the status data of the abnormal battery cell and reads the preset status data change curve corresponding to the abnormal battery cell, and determines the leveling parameters based on the status data of the abnormal battery cell and the preset status data change curve corresponding to the abnormal battery cell.

[0136] S404. Adjust the abnormal battery cells according to the balancing parameters.

[0137] In this step, the balancing module 240 balances the abnormal battery cell according to the balancing parameters.

[0138] Optionally, the preset state data change curve is a preset relationship curve between the state of charge and the open-circuit voltage; the state data includes voltage; based on the state data of the abnormal cell and the preset state data change curve corresponding to the abnormal cell, the balancing parameters are determined, including: reading the reference state of charge corresponding to the voltage of the abnormal cell from the preset state data change curve; determining the target voltage based on the voltage of other cells, and reading the target state of charge corresponding to the target voltage from the preset state data change curve; and determining the balancing parameters based on the difference between the reference state of charge and the target state of charge.

[0139] Optionally, the leveling parameters include leveling current and leveling time; the leveling parameters are determined based on the difference between the reference state of charge and the target state of charge, including: determining the leveling current according to the leveling current range; calculating the ratio of the product of the difference between the reference state of charge and the target state of charge and the nominal capacity of the abnormal cell to the product of the leveling current and the efficiency coefficient, and determining the ratio as the leveling time.

[0140] Optionally, the cell balancing method provided in this embodiment further includes: acquiring multiple state data of the abnormal cell during the balancing process; calculating the convergence speed of the state data of the abnormal cell based on the multiple state data during the balancing process; if the convergence speed is lower than the speed threshold, increasing the balancing current to perform balancing based on the increased balancing current.

[0141] Optionally, the cell balancing method provided in this embodiment further includes: adjusting the output current of the DC-DC converter according to the balancing current, so as to balance the abnormal cell through the output current.

[0142] Optionally, the cell leveling method provided in this embodiment further includes: when the current of the DC-DC converter exceeds the preset fuse current, the fuse protector blows to cut off the corresponding branch of the DC-DC converter.

[0143] Optionally, based on the status data of multiple cells 110, abnormal cells are identified, including: for each cell 110, the voltage change rate of the cell 110 in the current cycle is calculated based on the collected voltage of the cell 110 in the current cycle; and based on the voltage change rate of multiple consecutive cycles, it is determined whether the cell 110 is an abnormal cell.

[0144] Optionally, the cell leveling method provided in this embodiment further includes: if there is no preset state data change curve corresponding to the abnormal cell, then a preset state data change curve corresponding to the abnormal cell is generated by performing a pulse test on a cell of the same model as the abnormal cell.

[0145] The cell leveling method provided in this embodiment is the same as the operation method of the cell leveling device 200 described above. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0146] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0147] This application also provides a computer-readable storage medium storing computer-executable instructions, which implement the above-described method when the processor executes the computer-executable instructions.

[0148] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0149] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0150] Figure 5 This is a schematic diagram of an energy storage system provided in an embodiment of this application. Figure 5 As shown, the energy storage system 100 provided in this application includes a plurality of battery cells 110 and the battery cell leveling device 200 provided in the above embodiment.

[0151] The division of units is merely a logical functional division; 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 indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0152] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0154] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, 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 of the various embodiments of this invention. 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.

[0155] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0156] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A battery cell leveling device, characterized in that, The device is used in an energy storage system, which includes multiple battery cells, and the battery cell leveling device includes: The data acquisition module is used to collect the status data of the multiple battery cells; The feature analysis module is used to identify abnormal battery cells based on the status data. The parameter generation module is used to determine the balancing parameters based on the state data of the abnormal battery cell and the preset state data change curve corresponding to the abnormal battery cell. A balancing module is connected to multiple cells in the energy storage system and is used to balance the abnormal cells according to the balancing parameters.

2. The device according to claim 1, characterized in that, The preset state data change curve is a preset relationship curve between the state of charge and the open-circuit voltage; the state data includes voltage; the parameter generation module is specifically used for: Read the reference state of charge corresponding to the voltage of the abnormal cell from the preset state data change curve; Based on the voltage of other cells, determine the target voltage and read the target state of charge corresponding to the target voltage from the preset state data change curve; The leveling parameters are determined based on the difference between the reference state of charge and the target state of charge.

3. The device according to claim 2, characterized in that, The leveling parameters include leveling current and leveling time; Based on the difference between the reference state of charge and the target state of charge, the leveling parameters are determined, including: The leveling current is determined based on the leveling current range; The product of the difference between the reference state of charge and the target state of charge and the nominal capacity of the abnormal cell is calculated, and the product of the leveling current and the efficiency coefficient is used to determine the leveling time.

4. The device according to claim 3, characterized in that, The parameter generation module is also used for: The data acquisition module collects multiple status data of the abnormal battery cell during the balancing process. Based on the multiple state data during the balancing process, calculate the convergence rate of the state data of the abnormal battery cell; If the convergence rate is lower than the rate threshold, the leveling current is increased to perform leveling based on the increased leveling current.

5. The device according to claim 3, characterized in that, The leveling module includes a DC-DC converter, which is connected to a programmable load; The programmable load is used to adjust the output current of the DC-DC converter according to the balancing current, so as to balance the abnormal battery cell through the output current.

6. The device according to claim 5, characterized in that, The DC-DC converter includes a fuse protector; the fuse protector is used for: The fuse blows when the current in the DC-DC converter exceeds the preset fuse current, thereby cutting off the corresponding branch of the DC-DC converter.

7. The device according to any one of claims 1-6, characterized in that, The status data includes voltage; the feature analysis module is specifically used for: For each of the aforementioned battery cells, the voltage change rate of the battery cell in the current cycle is calculated based on the collected voltage of the battery cell in the current cycle. Based on the voltage change rate over multiple consecutive cycles, it is determined whether the battery cell is an abnormal battery cell.

8. The device according to any one of claims 1-6, characterized in that, The parameter generation module is also used for: If there is no preset state data change curve corresponding to the abnormal cell, then a preset state data change curve corresponding to the abnormal cell is generated by performing a pulse test on a cell of the same model as the abnormal cell.

9. A method for leveling battery cells, characterized in that, Applied to an energy storage system, the energy storage system comprising multiple battery cells, the method includes: Collect status data of the multiple battery cells; Based on the status data of the multiple battery cells, the abnormal battery cells are identified; The balancing parameters are determined based on the status data of the abnormal battery cell and the preset status data change curve corresponding to the abnormal battery cell. The abnormal battery cell is leveled according to the leveling parameters.

10. An energy storage system, characterized in that, It includes multiple battery cells, and the battery cell leveling device according to any one of claims 1-8.

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