Battery equalization method and device, battery management system and vehicle

Abstract

The application provides a battery equalization method and device, a battery management system and a vehicle. The battery equalization method comprises the following steps: obtaining an equalization instruction issued by a cloud; the equalization instruction is issued after the cloud identifies that there is voltage inconsistency among each cell of the battery; calculating a first voltage difference between each cell of the battery and a reference cell to obtain a first voltage difference corresponding to each cell; the reference cell is a cell corresponding to the minimum cell voltage among the cells; verifying the equalization instruction according to the first voltage differences; and performing equalization on the battery according to the equalization instruction in response to the verification. Based on the above, the high efficiency of the cloud is utilized, and the matching between the equalization instruction and the actual state of the battery is ensured through local real-time pressure difference verification, so that the equalization misstart or equalization amount misalignment caused by the battery equalization in the prior art is effectively avoided, and the accuracy of the identification and equalization control of the cells to be equalized is improved.

Description

Technical Field

[0001] This application relates to the field of battery management technology, specifically to a battery balancing method, device, battery management system, and vehicle. Background Technology

[0002] In the field of battery management, equalization identification and control of individual cells and improvement of consistency between cells are important technical requirements for maintaining the long-term stable operation of battery packs.

[0003] To meet this requirement, existing technologies typically employ the open-circuit voltage method, measuring the open-circuit voltage (OCV) of each cell and then using the OCV-SOC mapping relationship to estimate the SOC (State of Charge) value of each cell, thereby identifying cells with high SOC (i.e., inconsistent voltage) that need to be balanced. However, for the widely used lithium iron phosphate batteries, their OCV-SOC characteristic curve contains a plateau region with extremely gradual voltage changes within a relatively wide SOC range. Within this plateau region, even if there are significant differences in SOC between cells, the corresponding differences in open-circuit voltage are extremely small. Therefore, under common operating conditions such as when the battery is in this voltage plateau region or has not been sufficiently rested, it is difficult to accurately and reliably identify cells that need balancing based solely on local voltage measurements. Summary of the Invention

[0004] In view of this, this application aims to provide a battery balancing method, apparatus, battery management system, and vehicle to solve problems such as the difficulty in reliably identifying cells that need balancing in related technologies.

[0005] In a first aspect, this application provides a battery balancing method, comprising: obtaining a balancing instruction sent from the cloud; wherein the balancing instruction is sent after the cloud identifies voltage inconsistencies among the battery cells; calculating a first voltage difference between each battery cell and a reference cell to obtain a first voltage difference corresponding to each cell; wherein the reference cell is the cell with the lowest cell voltage among the cells; verifying the balancing instruction based on each first voltage difference; and balancing the battery according to the balancing instruction in response to a successful verification.

[0006] Optionally, the balancing instruction includes a list of cells to be balanced; the balancing instruction is verified based on each first voltage difference, including: determining the cells to be balanced based on each first voltage difference; when the matching degree between the cells to be balanced and the list of cells to be balanced exceeds a first preset value, the verification is deemed successful.

[0007] Optionally, determining the battery cell to be balanced based on each first voltage difference includes: comparing each first voltage difference with a second preset value; when the first voltage difference is greater than the second preset value, determining the corresponding cell as the cell to be balanced.

[0008] Optionally, the balancing instruction includes a balancing amount corresponding to the cells in the cell list to be balanced; balancing the battery according to the balancing instruction includes: in response to a successful verification, balancing the cells in the cell list to be balanced according to the balancing amount; and in response to a successful verification, balancing the cells not in the cell list to be balanced according to a preset ratio of the balancing amount.

[0009] Optionally, the method further includes: after balancing the battery according to the balancing command, obtaining the voltage difference change trend of each cell before and after balancing; if the voltage difference change trend indicates that the voltage difference between each cell does not show a decreasing trend, then in response to the stop balancing command, executing the step of obtaining the balancing command sent from the cloud.

[0010] Optionally, the voltage difference change trend of each cell before and after equalization is obtained, including: obtaining the second voltage difference between each cell before equalization; obtaining the third voltage difference between each cell after battery equalization; and obtaining the voltage difference change trend based on the second voltage difference and the third voltage difference.

[0011] Optionally, obtaining the voltage difference change trend based on the second voltage difference and the third voltage difference includes: comparing the second voltage difference and the third voltage difference corresponding to each cell to obtain the voltage difference change trend; wherein, when the number of cells whose third voltage difference is greater than or equal to the second voltage difference exceeds a third preset value, it is determined that the voltage difference change trend does not show a downward trend.

[0012] Secondly, this application provides a battery balancing device, comprising: an acquisition module for acquiring a balancing instruction sent from the cloud; wherein the balancing instruction is sent after the cloud identifies voltage inconsistencies among the battery cells; a calculation module for calculating a first voltage difference between each battery cell and a reference cell to obtain a first voltage difference corresponding to each battery cell; wherein the reference cell is the battery cell with the lowest cell voltage among the battery cells; a verification module for verifying the balancing instruction based on each of the first voltage differences; and a balancing control module for balancing the battery according to the balancing instruction in response to successful verification.

[0013] Thirdly, this application provides a battery management system, including: a power battery; and a controller connected to the power battery and configured to perform the battery balancing method described in the first aspect above.

[0014] Fourthly, this application provides a vehicle including a battery management system as described in the third aspect above.

[0015] Based on the above, the battery balancing method provided in this application utilizes cloud-based generation of balancing commands and verifies these commands by calculating the first voltage difference between each cell and a reference cell, forming a dual confirmation mechanism of cloud-based identification and local verification. This leverages the high computing power of the cloud while ensuring the matching of the balancing commands with the actual battery state through local real-time voltage difference verification. This effectively avoids erroneous balancing activation or inaccurate balancing quantities caused by using existing battery balancing technologies, thereby improving the accuracy of cell identification and balancing control. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure 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 only embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the battery balancing system provided in an embodiment of this disclosure.

[0018] Figure 2 This is a schematic flowchart of the battery balancing method provided in the embodiments of this disclosure.

[0019] Figure 3 This is provided by the embodiments of this disclosure. Figure 2 A flowchart illustrating step S23.

[0020] Figure 4 This is provided by the embodiments of this disclosure. Figure 2 A flowchart illustrating step S24.

[0021] Figure 5 This is another schematic diagram of the battery balancing method provided in this embodiment.

[0022] Figure 6 This is provided by the embodiments of this disclosure. Figure 5 A flowchart of step S51.

[0023] Figure 7 This is a schematic diagram of the battery balancing device provided in an embodiment of this disclosure.

[0024] Figure 8 This is a schematic diagram of the structure of the battery management system provided in an embodiment of this disclosure.

[0025] Figure 9 This is a schematic diagram of the vehicle structure provided in the embodiments of this disclosure. Detailed Implementation

[0026] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0027] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.

[0028] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0029] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Words such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0030] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined herein.

[0031] Currently, in the field of battery management, balancing and controlling individual cells in a series-connected battery pack, and improving cell consistency, are crucial technical requirements for maintaining long-term stable operation and delaying capacity degradation. To meet this need, existing technologies typically employ the Open Circuit Voltage (OCV) method. Its basic principle is as follows: First, the open circuit voltage of each individual cell is measured using a voltage acquisition circuit under static or low-current conditions. Second, using a pre-calibrated mapping relationship between the open circuit voltage (OCV) and the state of charge (SOC) (i.e., the OCV-SOC characteristic curve), the measured open circuit voltage value is used to estimate the SOC value of each individual cell. Finally, by comparing the differences in SOC values ​​among the individual cells, cells with excessively high or low SOC values ​​are identified and require balancing.

[0032] However, the OCV-SOC characteristic curve of batteries such as lithium iron phosphate batteries has a very special physical characteristic that is unfavorable for measurement: within the wide range of 40% to 80% SOC, the open-circuit voltage changes extremely smoothly, forming an approximately horizontal voltage plateau region. Within this plateau region, even if there are significant differences in the actual state of charge between individual cells (for example, some cells have an SOC of 60%, while others have dropped to 50%), the corresponding open-circuit voltage difference is only on the order of millivolts, even less than the measurement noise and error tolerance of the voltage sampling circuit itself. In other words, within the voltage plateau region, tiny capacity differences correspond to extremely weak voltage signal changes.

[0033] Therefore, when the battery is under typical operating conditions (such as not being fully rested, in the early to mid-stages of charging, or when the SOC is within the plateau region), the voltage measurement capability of the local Battery Management System (BMS) alone is insufficient to effectively extract and distinguish the true degree of inconsistency of each individual cell from the voltage signal with extremely low signal-to-noise ratio. The system may misjudge minute voltage fluctuations caused by measurement noise or instantaneous equalization as individual cell inconsistencies, incorrectly activating equalization operations and resulting in unnecessary energy loss; or it may miss truly inconsistent cells that require equalization processing due to the voltage signal changes being too weak, causing the inconsistency to accumulate and worsen with increasing cycle count.

[0034] This application proposes a different technical approach. It combines the cloud's ability to analyze and identify historical operating data with the local real-time voltage difference detection capability under specific operating conditions, forming a dual confirmation mechanism of cloud identification and local verification. Specifically, the cloud generates balancing commands, the local controller detects the voltage of each individual cell, and uses the detected individual cell voltage differences to verify the accuracy of the balancing commands issued from the cloud. Balancing is only executed according to the command if the verification passes. Based on this, it utilizes the efficient computing power of the cloud while ensuring the matching of the balancing commands with the actual state of the battery through local real-time voltage difference verification. This effectively avoids erroneous balancing activation or inaccurate balancing quantities caused by using existing battery balancing technologies, thereby improving the accuracy of cell identification and balancing control.

[0035] It should be noted that the battery balancing method of this application can be widely applied to any electrical system or equipment containing series-connected cell packs that faces the problem of inconsistent cell voltages due to differences in cell characteristics or changes in the operating environment. Its application areas include, but are not limited to: electric vehicles (such as pure electric vehicles, hybrid electric vehicles, fuel cell vehicles), electric bicycles, electric ships, electric aircraft, energy storage power stations (such as grid frequency regulation, peak-valley regulation, home energy storage systems), uninterruptible power supplies, portable electronic devices, and industrial-grade battery packs (such as forklifts, AGVs, robots), etc. In the above applications, the battery pack's composition, chemical system (such as lithium iron phosphate, ternary lithium, lithium titanate, lead-acid, etc.), capacity level, series-parallel connection method, and the type of balancing circuit used (passive balancing, active balancing) do not constitute a limitation on the scope of protection of the technical solution of this application. The remote identification-local verification dual confirmation mechanism proposed in this application aims to solve the problem of insufficient balancing accuracy caused by the plateau region of the OCV-SOC characteristic curve or by relying on differences between historical data and real-time operating conditions.

[0036] See Figure 1 , Figure 1 This is a schematic diagram of the battery balancing system 100 provided in this embodiment. The battery balancing system 100 includes two main parts: a cloud-side 110 and a vehicle-side 120. The cloud-side 110 is equipped with a cloud computing device 101, which has data receiving, storage, and processing capabilities. The vehicle-side 120 is equipped with a battery 102, a local controller 103, a balancing circuit 104, and a communication module 105 for data interaction with the cloud-side 110.

[0037] Among them, battery 102 consists of multiple individual cells ( Figure 1 (Not shown) The cells are connected in series and parallel. The working voltage and current of each cell can be collected by the local controller 103. The equalization circuit 104 is connected to each cell and is used to balance the power of the selected cells under the control of the local controller 103.

[0038] The communication module 105 is connected to the cloud computing device 101 via a wireless communication network, establishing a bidirectional data channel between the vehicle-side 120 and the computing resources of the cloud computing device 101. The local controller 103 continuously collects data such as voltage, current, and temperature of each individual battery cell during vehicle operation or charging, and uploads the collected operating data to the cloud computing device 101 via the communication module 105. The cloud computing device 101 then uses this historical operating data for analysis and calculation, generates balancing commands for specific individual battery cells, and sends these balancing commands to the vehicle-side 120 via the communication network.

[0039] The local controller 103 on the vehicle side 120 interacts with the communication module 105 via the vehicle bus, etc. After receiving the balancing command sent from the cloud, the local controller 103 performs subsequent processing based on the current operating condition of the battery 102, and finally drives the balancing circuit 104 to perform balancing operation on the corresponding individual cells.

[0040] See Figure 2 , Figure 2 This is a flowchart illustrating the battery balancing method provided in this embodiment of the disclosure. The method can be... Figure 1 The local controller 103 executes the following steps: Step S21: Obtain the load balancing instructions sent from the cloud.

[0041] Among them, the equalization command is issued after the cloud identifies that there is a voltage inconsistency among the cells of battery 102.

[0042] Specifically, during vehicle operation or charging, the local controller 103 continuously collects operating data such as voltage, current, and temperature of each individual cell in the battery 102, and uploads this data to the cloud computing device 101 via the communication module 105. The cloud computing device 101 uses historical operating data from multiple vehicles to execute an inconsistency identification algorithm. When it detects a voltage inconsistency among the cells of the battery 102, it generates an equalization command and sends it to the vehicle. The local controller 103 receives this equalization command via the communication module 105.

[0043] In this application, the balancing instruction refers to any information carrier generated and issued by the cloud computing device 101 based on historical operating data analysis, used to instruct the vehicle-side 120 to perform individual cell balancing operations. Its specific content may include, but is not limited to: the serial number or identifier of the cell to be balanced, the suggested balancing capacity corresponding to each cell, the timing indication for balancing activation, and combinations of this information. For example, in one specific implementation, the balancing instruction includes a list of cells to be balanced and a balancing amount (such as balancing ampere-hours or balancing duration) corresponding to each cell in the list. In another implementation, the balancing instruction includes a weight value, which is calculated by the local controller 103 based on local measurement results to determine the final balancing amount to be executed.

[0044] In one embodiment, the specific means of obtaining the equalization instruction issued by the cloud may include: at the hardware level, using the vehicle wireless communication module 105 (e.g., a 4G / 5G module) to receive data packets sent by the cloud computing device 101 through the cellular network; at the software or logic level, extracting the equalization instruction field from the communication protocol data unit through a message parsing program and storing it in the buffer memory of the local controller 103 for subsequent steps to call.

[0045] It should be noted that the cloud-based identification of inconsistent states utilizes the massive amount of operational data accumulated by battery 102 over a long period under various operating conditions. This can compensate for the blind spots caused by the wide plateau region of the OCV-SOC curve when relying solely on local single-cell voltage measurements. However, cloud-based analysis is based on historical statistical states and lacks cross-validation with real-time operating conditions. Therefore, issuing equalization commands directly without verification may lead to the risk of misjudging normal cells as cells requiring equalization or performing improper equalization under changed operating conditions. To eliminate this risk, this application includes a subsequent local verification step.

[0046] Step S22: Calculate the first voltage difference between each cell in the battery and the reference cell to obtain the first voltage difference corresponding to each cell.

[0047] Specifically, upon receiving the balancing command, the local controller 103 does not immediately perform the balancing operation. Instead, it first waits for the battery 102 to enter a predetermined specific operating condition. This specific operating condition refers to a condition where the voltage difference between individual cells reliably reflects the degree of capacity inconsistency, thus allowing local voltage measurements to be used to verify the accuracy of the cloud command. As a specific implementation, this predetermined operating condition can be the final stage of the charging process, where the current is low and the individual cell voltage has significantly deviated from the OCV plateau region, making even small capacity differences correspond to clearly discernible voltage differences. For example, the local controller 103 determines that the battery 102 has entered the final charging condition when both the individual cell voltage and the charging current are simultaneously greater than or equal to 3.6V and less than 0.3C. Under this condition, the local controller 103 collects the real-time voltage values ​​of all individual cells.

[0048] The reference cell is the cell with the lowest cell voltage among all cells.

[0049] Specifically, the reference cell is defined as the cell with the lowest cell voltage among all cells. The local controller 103 identifies the cell with the lowest voltage value from all the collected individual cell voltage values ​​and uses this cell as the reference cell. Based on this, the voltage difference between each cell and the cell with the lowest voltage is calculated one by one, and the resulting difference is the first voltage difference for each cell. These first voltage differences reflect the degree of inconsistency of each cell relative to the lowest voltage cell under the current operating conditions. Of course, in other embodiments, the reference cell can also be selected as a cell with a fixed number, but using the lowest voltage cell as the reference can most intuitively characterize the difference between each cell and the weakest cell in its own battery pack 102, which is beneficial for identifying high-voltage cells that need to be balanced.

[0050] Step S23: Verify the equalization command based on the first voltage difference.

[0051] Specifically, the local controller 103 uses the calculated first voltage differences to verify the accuracy of the previously acquired balancing commands. Verification can be implemented in various ways. For example, it may include: determining whether the set of locally identified cells to be balanced is included in or substantially overlaps with the list of cells to be balanced in the cloud command; or, calculating a confidence score for each locally identified cell and comparing it with the confidence score carried in the cloud command; or, performing correlation analysis between the binary sequence obtained by comparing the first voltage differences with a threshold and the suggested balancing sequence contained in the cloud command.

[0052] Step S24: In response to the successful verification, the battery is balanced according to the balancing command.

[0053] Specifically, if the verification passes, it indicates that the cloud-based identification result is confirmed by the local real-time differential pressure measurement, and the balancing command has sufficient accuracy. At this time, the local controller 103 controls the balancing circuit 104 to perform balancing operations on the target cell according to the information in the balancing command.

[0054] The equalization circuit 104 is connected to each individual battery cell and is typically composed of a switch array and energy-consuming resistors or energy transfer elements. Under the control signal of the local controller 103, it can discharge or transfer energy to designated battery cells, thereby reducing their excess power and improving consistency. For example, if the equalization command includes the equalization capacity of each battery cell to be equalized, the local controller 103 controls the equalization circuit 104 to perform discharge equalization one by one according to the capacity.

[0055] It should be noted that the synergistic effect of the above steps S21 to S24 combines the macroscopic identification capability of the cloud based on historical data with the microscopic verification capability of the local system under real-time voltage comparable operating conditions, forming a dual confirmation mechanism of cloud identification plus local verification. This improves the accuracy of equalization control while reducing unnecessary energy loss.

[0056] To further optimize the accuracy of the verification process in the above embodiments and avoid misclassifying normal cells as cells requiring balancing, this application also provides the following preferred solutions. In a preferred embodiment, see [reference needed]. Figure 3 , Figure 3 This is provided by the embodiments of this disclosure. Figure 2 A flowchart illustrating step S23.

[0057] The balancing instruction includes a list of cells to be balanced.

[0058] In this application, the list of cells to be balanced refers to a data set included in the balancing instructions issued from the cloud, used to identify specific cells that require power balancing operations. This list is generated by the cloud computing device 101 based on the historical operating data of the battery 102, through inconsistency identification algorithms (such as a weighted combination of dynamic time warping, cosine similarity, and Pearson correlation coefficient). Specifically, the list of cells to be balanced is typically presented as a list of cell serial numbers, such as #3, #7, #12, indicating that the local controller 103 on the vehicle side 120 needs to perform balancing operations on cells with serial numbers 3, 7, and 12. In other embodiments, the list may also include physical location identifiers, barcodes, or other unique identifiers of the cells to be balanced to adapt to different battery pack topologies.

[0059] Step S23, which verifies the equalization command based on each first voltage difference, specifically includes the following steps: Step S231: Determine the cells to be balanced in the battery based on the first voltage difference.

[0060] Specifically, in step S231, the local controller 103, based on the first voltage difference between each cell and the reference cell calculated in step S22, selects and determines the individuals that need to be listed as cells to be balanced from all cells through preset logic rules (e.g., comparing the voltage difference with an internal benchmark, or sorting the voltage differences and selecting the first few). This generates a local set of cells to be balanced.

[0061] Step S232: When the matching degree between the cell to be balanced and the list of cells to be balanced exceeds the first preset value, the verification is deemed successful.

[0062] Specifically, the local controller 103 calculates the matching degree between the local set of cells to be balanced and the list of cells to be balanced sent from the cloud. The matching degree can be defined as the ratio of the number of local cells to be balanced included in the cloud list to the total number of local cells to be balanced, or a similarity metric such as the Jaccard coefficient can be used. When the matching degree exceeds a first preset value (e.g., 0.5 or 0.8), the verification is considered successful.

[0063] In addition, alternative solutions to achieve the same goal include: instead of judging the matching degree, directly judging whether the local set of cells to be balanced is a subset of the set of cells to be balanced in the cloud, or requiring that the number of intersection elements between the two reach a certain value. For example, if the list of cells to be balanced issued by the cloud contains 5 cells, and the local system identifies 3 cells, as long as all or part of these 3 cells appear in the cloud list, the system can be deemed to have passed the test.

[0064] Based on the above method, misjudgments caused by local measurement noise or transient fluctuations can be effectively filtered out without missing any truly inconsistent individual cells, thus significantly reducing the probability of falsely activating equalization.

[0065] Optionally, step S231, which determines the cells to be balanced based on the first voltage difference, may specifically include the following steps: Step S2311: Compare each first voltage difference with the second preset value.

[0066] The second preset value represents the equalization activation voltage difference threshold, which can be pre-calibrated based on the battery 102 chemical system, historical data, or engineering experience. For example, it can be set between 10mV and 50mV. The second preset value is not limited to a fixed value and can be dynamically adjusted according to factors such as the aging degree of the battery 102 and seasonal temperature.

[0067] Alternatively, instead of comparing the first voltage difference with the second preset value, the N cells with the largest differences after sorting the first voltage differences can be selected as the local cells to be balanced, and then matched with the list of cells to be balanced in the cloud.

[0068] Step S2312: When the first voltage difference is greater than the second preset value, the corresponding cell is determined to be the cell to be balanced.

[0069] Specifically, when the first voltage difference of a certain cell is greater than the second preset value, the cell is determined to be a locally identified cell to be balanced, and its serial number is recorded, thereby generating a local set of cells to be balanced.

[0070] This application also provides preferred solutions for further optimizing the execution method. In a preferred embodiment, the balancing instruction includes a balancing amount corresponding to the cells in the list of cells to be balanced.

[0071] In this application, the balancing quantity refers to a specific quantitative parameter included in the balancing instruction issued from the cloud, corresponding one-to-one with each cell in the list of cells to be balanced, used to instruct the local controller 103 to perform a balancing operation on that cell. This balancing quantity is estimated online by the cloud computing device 101 based on the historical operating data of the battery 102 through an inconsistency identification algorithm, and is a precise quantitative suggestion from the cloud for the amount of power to be released or replenished for each cell to be balanced.

[0072] Specifically, the balancing quantity can be presented in various physical quantities. For example, it can be the balancing ampere-hour (e.g., 0.5 Ah), indicating that the local controller 103 needs to discharge 0.5 Ah of electricity from the cell; it can also be the balancing duration (e.g., 30 minutes), indicating continuous discharge at a fixed balancing current for 30 minutes; or it can be the balancing charge or balancing energy value. In different implementations, the balancing quantity can be an absolute value or a percentage value relative to the rated capacity of the battery 102.

[0073] See Figure 4 , Figure 4 This is provided by the embodiments of this disclosure. Figure 2 The flowchart of step S24 shows that balancing the battery according to the balancing command in step S24 may include the following steps: Step S241: In response to the successful verification, balance the cells to be balanced in the list of cells to be balanced according to the balancing amount.

[0074] Specifically, after the local controller 103 passes the verification logic in step S22 (e.g., all or part of the local cells to be balanced are included in the cloud list, and the matching degree exceeds the first preset value), it performs a full-scale, standard balancing operation on the cells according to the balancing amount (e.g., balancing ampere-hours or balancing duration) that corresponds one-to-one with each cell in the cell list in the balancing instruction. For example, if the cloud instruction specifies that the balancing amount of cell #3 is 0.5Ah, and the cell is identified locally and included in the cloud list, then the local controller 103 controls the balancing circuit 104 to perform discharge balancing on it with 0.5Ah of power.

[0075] Step S242: In response to the successful verification, balance the cells not included in the cell list to be balanced according to the preset ratio of the balancing amount.

[0076] Specifically, after the local controller 103 determines that the verification is successful (for example, although most cells match, a few locally identified cells are not in the list of cells to be balanced), for these locally unbalanced cells, the balancing operation is performed according to a preset ratio (e.g., 60%) of the balancing amount corresponding to the balancing amount in the balancing instruction. For example, if the balancing amount of cell #7 in the cloud instruction is 0.5Ah, but this cell is not included in the list of cells to be balanced, and the local controller identifies it as a cell to be balanced based on the real-time voltage difference, then the local controller 103 performs balancing on it at 60% of 0.5Ah (i.e., 0.3Ah).

[0077] Due to differences in information dimensions between the cloud and local systems, some battery cells may exhibit inconsistencies only in a single dimension. Completely ignoring local screening might lead to missing minor inconsistencies in some cells, while relying solely on local screening would excessively undermine the advantages of the cloud. By employing differentiated execution ratios, we can both incorporate the fine-grained calculations from the cloud and accommodate supplementary real-time local measurements, thereby improving the robustness of the balancing strategy.

[0078] To further prevent consistency degradation caused by dynamic changes in the state of battery 102 during the equalization process, this application provides a closed-loop monitoring scheme based on the core solution. In a preferred embodiment, see [reference needed]. Figure 5 , Figure 5 This is another schematic flowchart of the battery balancing method provided in this embodiment. After balancing the battery according to the balancing command in step S24, the method further includes the following steps: Step S51: Obtain the voltage difference change trend of each cell before and after equalization.

[0079] Specifically, the local controller 103 monitors and records cell voltage data at two time points—before the equalization operation begins and during or after the equalization operation—and calculates and compiles a trend indicator characterizing the direction or magnitude of the voltage difference between cells before and after equalization. This trend can be obtained by collecting two voltage measurements and comparing the difference, or by continuously monitoring and fitting a change curve.

[0080] Step S52: If the pressure difference change trend indicates that the pressure difference between each cell does not show a decreasing trend, then in response to the stop balancing command, return to the step of obtaining the balancing command sent from the cloud.

[0081] Specifically, after equalization is activated, the local controller 103 continuously monitors the voltage difference between each cell during two consecutive driving cycles (or two charging cycles).

[0082] When the acquired voltage difference trend indicates that the voltage difference between the cells has not decreased as expected (i.e., it does not show a downward trend), the local controller 103 will respond with a stop balancing command (which can be sent from the cloud or generated locally) to immediately terminate the currently executing balancing operation. Subsequently, the control flow returns to the beginning of the entire method—that is, re-execute the step of acquiring the balancing command sent from the cloud to start a new round of cloud identification and local verification process.

[0083] See Figure 6 , Figure 6 This is provided by the embodiments of this disclosure. Figure 5 The flowchart of step S51 shows that obtaining the voltage difference change trend of each cell before and after equalization specifically includes the following steps: Step S511: Obtain the second voltage difference between each cell before equalization.

[0084] The local controller 103 records and calculates the voltage difference between all cells (or relative to a common reference) at the moment of equalization activation or at a point immediately before activation, and defines these difference data as the second voltage difference.

[0085] Step S512: After battery equalization, obtain the third voltage difference between each cell.

[0086] The local controller 103 records and calculates the voltage difference between all cells again after the equalization process ends or reaches a certain preset time, and defines these difference data as the third voltage difference.

[0087] Step S513: Obtain the voltage difference change trend based on the second voltage difference and the third voltage difference.

[0088] Specifically, the local controller 103 compares and analyzes the second voltage difference of each cell or the third voltage difference of the entire battery pack (e.g., calculating the difference, ratio, or rate of change) to deduce whether the voltage difference tends to decrease, increase, or remain unchanged before and after equilibrium. This deduction result is the voltage difference change trend.

[0089] Optionally, step S513, which involves obtaining the voltage difference change trend based on the second voltage difference and the third voltage difference, may specifically include the following steps: Step S5131: Compare the second voltage difference and the third voltage difference corresponding to each cell to obtain the voltage difference change trend.

[0090] Specifically, when the number of cells with a third voltage difference greater than or equal to the second voltage difference exceeds a third preset value, it is determined that the voltage difference change trend does not show a downward trend.

[0091] Specifically, the second voltage difference and the third voltage difference corresponding to each cell of battery 102 are compared. When the third voltage difference of a certain cell is greater than or equal to its corresponding second voltage difference, it indicates that the voltage difference of that cell relative to other cells has increased rather than decreased or has not been substantially improved. The number of such cells is counted. When the number exceeds a third preset value (for example, more than half of the total number of cells, or more than a fixed number such as 3), it is determined that the voltage difference change trend does not show a downward trend.

[0092] At this point, the cloud computing device 101 generates a stop balancing command and sends it to the vehicle (or the local controller 103 generates a stop signal based on its own trend judgment). The local controller 103 responds to the stop balancing command, terminates the current balancing operation, and returns to step S21 to retrieve the balancing command sent from the cloud for a new round of identification. This design creates a closed loop in the balancing process, enabling timely detection and termination of invalid or harmful balancing operations, thus ensuring the safety of the battery 102.

[0093] In other embodiments, the cloud computing device 101 can execute an inconsistency identification algorithm based on vehicle-uploaded data, statistically analyze the slope or mean change of pressure difference in each cell within two driving cycles, and compare it with the trend before equalization began. If the slope changes from negative to positive or the mean difference widens, it is determined that the consistency has deteriorated, and a stop equalization command is issued. This combination of continuous cloud monitoring and local execution further enhances the ability to control equalization risks.

[0094] See Figure 7 , Figure 7 This is a schematic diagram of the battery balancing device provided in an embodiment of the present disclosure. The battery balancing device 700 includes: an acquisition module 710, a calculation module 720, a verification module 730, and a balancing control module 740.

[0095] The acquisition module 710 is used to acquire balancing instructions sent from the cloud, wherein the balancing instructions are sent after the cloud detects voltage inconsistencies among the battery cells; the calculation module 720 calculates the first voltage difference between each battery cell and a reference cell, obtaining the first voltage difference corresponding to each battery cell; wherein the reference cell is the cell with the lowest cell voltage among all the battery cells; the verification module 730 verifies the balancing instructions based on each of the first voltage differences; the balancing control module 740 is used to balance the battery according to the balancing instructions in response to the successful verification. These four modules can be fully or partially integrated into the local controller 103, implemented through software and / or hardware, which will not be described in detail here.

[0096] See Figure 8 , Figure 8 This is a schematic diagram of the structure of a battery management system provided in an embodiment of this disclosure. The battery management system 800 includes a power battery 810 and a controller 820.

[0097] The controller 820 is connected to the power battery 810 and is configured to execute the battery balancing method described in any of the above embodiments. The power battery 810 is the battery 102 as described above, and the controller 820 is the local controller 103 as described above. Specifically, it can be a separate microcontroller unit or integrated into an existing BMS main control chip, which will not be described in detail here.

[0098] See Figure 9 , Figure 9 This is a schematic diagram of the vehicle structure provided in the embodiments of this disclosure.

[0099] The vehicle 900 includes a battery management system 910, which is the same as the battery management system 800 described above, and will not be repeated here.

[0100] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0101] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0102] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0103] 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.

[0104] 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.

[0105] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion 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 invention. The aforementioned storage medium includes various media capable of storing program verification codes, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] Furthermore, it should be noted that the combination of the various technical features in this case is not limited to the combination methods described in the claims of this case or the combination methods described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way, unless they contradict each other.

[0107] It should be noted that the above examples are merely specific embodiments of the present invention, and the present invention is obviously not limited to the above embodiments, with many similar variations. All modifications that can be directly derived or conceived by those skilled in the art from the content disclosed in this invention should fall within the protection scope of this invention.

[0108] It should be understood that the terms "first," "second," etc., mentioned in the embodiments of the present invention are used only to more clearly describe the technical solutions of the embodiments of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A battery balancing method, characterized in that, include: Obtain balancing instructions sent from the cloud; wherein, the balancing instructions are sent from the cloud after the cloud identifies that there is a voltage inconsistency among the cells of the battery; Calculate the first voltage difference between each cell in the battery and the reference cell to obtain the first voltage difference corresponding to each cell; wherein, the reference cell is the cell with the lowest cell voltage among all the cells. The equalization command is verified based on each of the first voltage differences; In response to the successful verification, the battery is balanced according to the balancing instruction.

2. The method according to claim 1, characterized in that, The balancing instruction includes a list of cells to be balanced; The step of verifying the equalization command based on each of the first voltage differences includes: The cells to be balanced in the battery are determined based on the first voltage difference. When the matching degree between the cell to be balanced and the list of cells to be balanced exceeds a first preset value, the verification is deemed successful.

3. The method according to claim 2, characterized in that, The step of determining the cells to be balanced in the battery based on the first voltage difference includes: Each of the first voltage differences is compared with a second preset value; When the first voltage difference is greater than the second preset value, the corresponding cell is determined to be the cell to be balanced.

4. The method according to claim 2, characterized in that, The balancing instruction includes a balancing amount, which corresponds to the cell in the list of cells to be balanced; The step of balancing the battery according to the balancing command includes: In response to the successful verification, the cells to be balanced in the list of cells to be balanced are balanced according to the balancing amount. In response to the successful verification, the cells not included in the list of cells to be balanced are balanced according to the preset ratio of the balancing amount.

5. The method according to claim 1, characterized in that, After balancing the battery according to the balancing command, the process further includes: Obtain the voltage difference change trend of each cell before and after equalization; If the pressure difference change trend indicates that the pressure difference between each cell does not show a decreasing trend, then in response to the stop balancing command, the step of obtaining the balancing command sent from the cloud is executed.

6. The method according to claim 5, characterized in that, The process of obtaining the voltage difference change trend of each of the battery cells before and after equalization includes: Obtain the second voltage difference between each of the cells before equalization; After the battery is balanced, the third voltage difference between each cell is obtained; The voltage difference change trend is obtained based on the second voltage difference and the third voltage difference.

7. The method according to claim 6, characterized in that, The step of obtaining the voltage difference change trend based on the second voltage difference and the third voltage difference includes: The second voltage difference corresponding to each of the battery cells is compared with the third voltage difference to obtain the voltage difference change trend; Specifically, when the number of cells whose third voltage difference is greater than or equal to the second voltage difference exceeds a third preset value, it is determined that the voltage difference change trend does not show a downward trend.

8. A battery balancing device, characterized in that, include: The acquisition module is used to acquire balancing instructions sent from the cloud; wherein, the balancing instructions are sent from the cloud after the cloud detects that there is a voltage inconsistency among the cells of the battery. The calculation module calculates the first voltage difference between each cell in the battery and the reference cell to obtain the first voltage difference corresponding to each cell; wherein, the reference cell is the cell with the lowest cell voltage among all the cells. The verification module verifies the equalization command based on each of the first voltage differences; The equalization control module is used to equalize the battery according to the equalization command in response to a successful verification.

9. A battery management system, characterized in that, include: Power battery; The controller, connected to the power battery, is configured to perform the battery balancing method as described in any one of claims 1-7.

10. A vehicle, characterized in that, include: The battery management system as described in claim 9.

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