Early warning method and device for thermal runaway of electrochemical energy storage power station battery

Abstract

This invention provides a method and apparatus for early warning of thermal runaway in batteries of an electrochemical energy storage power station, applied in the field of battery prediction technology. The method includes: obtaining multiple fault triggering results for multiple battery cells based on the discharge current and battery voltage changes of multiple battery cells within a battery cluster; if the results indicate that at least one potential battery cell has triggered a fault, obtaining a target fault characteristic value for at least one potential battery cell based on the discharge energy change during a target sampling period; based on an energy fault threshold, and according to the target fault characteristic value of at least one potential battery cell, performing fault judgment on at least one potential battery cell, and identifying at least one intermediate battery cell with abnormal operation from the at least one potential battery cell; and classifying at least one intermediate battery cell into fault and aging categories according to aging rules corresponding to the multiple battery cells, and identifying a target faulty battery cell from the at least one intermediate battery cell.

Description

Technical Field

[0001] This invention relates to the field of battery prediction technology, and more specifically to a method and device for early warning of thermal runaway of batteries in electrochemical energy storage power stations. Background Technology

[0002] Energy storage power stations can be equipped with multiple battery clusters, each containing multiple battery cells connected in series. These cells switch between charging and discharging states to provide a large and stable power supply. However, there is a risk of short circuits and other faults during battery cell operation; therefore, real-time monitoring of the battery cells within the energy storage power station is necessary.

[0003] In the process of realizing the above-mentioned inventive concept, it was found through research that: on the eve of a battery cell failure, the relevant technologies are unable to provide accurate fault warnings for battery cells that are about to fail based on simple relevant performance parameters of the battery cells. At the same time, in the process of providing fault warnings for battery cells, it is usually necessary to rely on complex prediction algorithms or models, which leads to the technical problem of low warning efficiency for faulty battery cells. Summary of the Invention

[0004] In view of the above problems, the present invention provides a method and device for early warning of thermal runaway of batteries in electrochemical energy storage power stations.

[0005] According to a first aspect of the present invention, a method for early warning of thermal runaway of batteries in an electrochemical energy storage power station is provided, comprising: determining the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells in any battery cluster, and performing fault trigger judgment on multiple battery cells respectively based on the discharge current and battery voltage change of multiple battery cells to obtain multiple fault trigger results of multiple battery cells, wherein the battery voltage change represents the voltage change of a battery cell within a sampling period; when the multiple fault trigger results indicate that at least one potential battery cell among the multiple battery cells has triggered a fault, obtaining a target fault feature value of at least one potential battery cell based on the discharge energy change of at least one potential battery cell within a target sampling period, wherein the target sampling period includes at least one sampling period; based on an energy fault threshold, performing fault judgment on at least one potential battery cell based on the target fault feature value of at least one potential battery cell, and determining at least one intermediate battery cell with abnormal operation from at least one potential battery cell; classifying at least one intermediate battery cell into faults and aging according to aging rules corresponding to multiple battery cells, and determining a target faulty battery cell from at least one intermediate battery cell.

[0006] A second aspect of the present invention provides an early warning device for thermal runaway of batteries in an electrochemical energy storage power station, comprising: a judgment module, configured to determine the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells in any battery cluster, and to perform fault trigger judgment on multiple battery cells respectively based on the discharge current and battery voltage change of multiple battery cells, thereby obtaining multiple fault trigger results of multiple battery cells, wherein the battery voltage change represents the voltage change of a battery cell within a sampling period; a obtaining module, configured to, when multiple fault trigger results indicate that at least one potential battery cell among the multiple battery cells has triggered a fault, obtain a target fault feature value of at least one potential battery cell based on the discharge energy change of at least one potential battery cell within a target sampling period, wherein the target sampling period includes at least one sampling period; a first determining module, configured to, based on an energy fault threshold and the target fault feature value of at least one potential battery cell, determine at least one intermediate battery cell with abnormal operation from at least one potential battery cell; and a second determining module, configured to, based on an aging rule corresponding to multiple battery cells, classify at least one intermediate battery cell into fault and aging categories, thereby determining a target faulty battery cell from at least one intermediate battery cell.

[0007] A third aspect of the present invention provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the method described above.

[0008] A fourth aspect of the present invention also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0009] A fifth aspect of the invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0010] According to the method and apparatus for early warning of thermal runaway of batteries in electrochemical energy storage power stations of the present invention, by real-time monitoring of the discharge current and battery voltage changes of multiple battery cells in each battery cluster in the energy storage power station, the discharge current and battery voltage changes can be used as the underlying triggering early warning conditions for judging whether a battery cell has failed, so as to obtain preliminary fault triggering results and perform preliminary early warning screening of potential risks of battery cells.

[0011] When a battery cell is deemed likely to trigger a fault, it is identified as a potential fault cell. Based on the changes in discharge current and discharge energy of the potential fault cells during the target sampling period, a target fault characteristic value is calculated to characterize the severity of the potential fault. This target fault characteristic value is then used as a criterion for determining the fault severity. A second warning screening is performed from the potential fault cells based on a baseline judgment line for determining whether a fault has occurred (the energy fault threshold), identifying intermediate battery cells. This approach incorporates the potential for pseudo-normal parameters in battery thermal runaway as a prerequisite for fault judgment, combining battery voltage and discharge current changes with energy changes as a core judgment criterion. By dynamically and flexibly selecting the target sampling period based on a comprehensive consideration of battery state categories, accurate target fault characteristic values ​​are determined, providing a basis for accurate fault judgment based on the energy characteristics of the battery cell. Furthermore, the precisely determined energy fault threshold serves as the gold standard for fault warning in this invention, significantly improving the accuracy and efficiency of battery cell warning judgment.

[0012] Furthermore, based on the aging rules determined by the charging period of each battery cell, abnormal energy changes that may be caused by battery aging are further classified and identified. This improves the accuracy and reliability of early warning of thermal runaway of battery cells without the need for complex algorithm models to calculate and evaluate faults, making it more widely applicable in actual industrial production and expanding the applicable scenarios and scope of the early warning method proposed in this invention. Attached Figure Description

[0013] The above-mentioned contents, as well as other objects, features and advantages of the present invention, will become clearer from the following description of embodiments of the present invention with reference to the accompanying drawings.

[0014] Figure 1 An application scenario diagram of an early warning method for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0015] Figure 2 A flowchart of an early warning method for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0016] Figure 3 A flowchart illustrating the multiple fault triggering results of multiple battery cells according to an embodiment of the present invention is shown.

[0017] Figure 4 A flowchart for determining an energy failure threshold according to an embodiment of the present invention is shown.

[0018] Figure 5 A flowchart illustrating the determination of at least one intermediate battery cell according to another embodiment of the present invention is shown.

[0019] Figure 6 A flowchart for determining a target faulty battery cell according to an embodiment of the present invention is shown.

[0020] Figure 7A A schematic diagram of a battery cluster comprising a plurality of normal battery cells is shown according to an embodiment of the present invention.

[0021] Figure 7B A schematic diagram of a battery cluster comprising multiple normal battery cells and faulty battery cells according to an embodiment of the present invention is shown.

[0022] Figure 8 A schematic diagram comparing the voltages of a faulty battery cell and a normal battery cell according to an embodiment of the present invention is shown.

[0023] Figure 9 A schematic diagram illustrating the entire process of an early warning method for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0024] Figure 10 A structural block diagram of an early warning device for thermal runaway of any battery in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0025] Figure 11 A block diagram of an electronic device for an early warning method of battery thermal runaway in an electrochemical energy storage power station according to an embodiment of the present invention is shown. Detailed Implementation

[0026] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0028] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0029] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0030] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0031] Energy storage power stations can be equipped with multiple battery clusters for generating renewable energy. Each cluster can contain multiple lithium-ion battery cells connected in series. Lithium-ion battery cells offer advantages such as fast charging, high energy density, and long lifespan. By switching between charging and discharging states, multiple lithium-ion battery cells can provide a large and stable amount of power. However, due to inadequate protection facilities in energy storage power stations, safety accidents occur frequently, necessitating real-time monitoring of the battery cells within the power station.

[0032] Current energy storage power stations can achieve thermal runaway early warning through Battery Management Systems (BMS) by judging whether battery parameters such as voltage and current exceed set safety thresholds to protect against thermal runaway. However, for batteries about to experience thermal runaway, their basic parameters can be kept within reasonable safety thresholds. Therefore, relying solely on threshold judgments such as voltage, current, and temperature is insufficient for accurate and effective thermal runaway early warning. In addition, methods such as model-based methods, neural network methods, and data mining are commonly used for thermal runaway early warning of battery cells; however, these methods are inefficient and difficult to implement. During the research and development process, researchers found that, in the lead-up to battery cell failure, related technologies struggle to accurately predict impending failure based on simple performance parameters. Furthermore, the process of predicting battery cell failures typically relies on complex prediction algorithms or models, leading to low efficiency in predicting failing battery cells.

[0033] In view of this, embodiments of the present invention provide an early warning method for thermal runaway of batteries in an electrochemical energy storage power station, comprising: determining the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells in any battery cluster; and performing fault trigger judgment on multiple battery cells respectively based on the discharge current and battery voltage change of multiple battery cells to obtain multiple fault trigger results of multiple battery cells, wherein the battery voltage change represents the voltage change of a battery cell within a sampling period; when multiple fault trigger results indicate that at least one potential battery cell among the multiple battery cells has triggered a fault, obtaining a target fault feature value of at least one potential battery cell based on the discharge energy change of at least one potential battery cell within a target sampling period, wherein the target sampling period includes at least one sampling period; based on an energy fault threshold, performing fault judgment on at least one potential battery cell based on the target fault feature value of at least one potential battery cell, and identifying at least one intermediate battery cell with abnormal operation from at least one potential battery cell; and classifying at least one intermediate battery cell into faults and aging according to aging rules corresponding to multiple battery cells, and identifying a target faulty battery cell from at least one intermediate battery cell.

[0034] Figure 1 An application scenario diagram of an early warning method for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0035] like Figure 1 As shown, the application scenario according to this embodiment may include an energy storage power station 101, battery clusters 102, battery cells 103, and a terminal processor 104. The energy storage power station 101 may include multiple battery clusters 102, and each battery cluster 102 may include multiple battery cells 103. Each battery cell 103 can generate a large amount of electricity to supply power.

[0036] The terminal processor 104 can be a terminal processor used to monitor the operating status and health status of each battery cell. For example, the terminal processor 104 can manage and switch the charging and discharging states of the battery cells (for example only). The terminal processor 104 can also provide fault warnings and fault analysis for abnormal battery cells, so as to issue alerts to the staff and feed back the fault analysis results (such as fault data, fault cause, fault location, etc.) to the terminal device.

[0037] It should be noted that the early warning method for thermal runaway of the electrochemical energy storage power station battery provided in this embodiment of the invention can generally be executed by the terminal processor 104. Correspondingly, the early warning device for thermal runaway of the electrochemical energy storage power station battery provided in this embodiment of the invention can generally be installed in the terminal processor 104. The early warning method for thermal runaway of the electrochemical energy storage power station battery provided in this embodiment of the invention can also be executed by a terminal processor or a cluster of terminal processors that is different from the terminal processor 104 and can communicate with the energy storage power station 101, battery cluster 102, battery unit 103, and / or terminal processor 104. Correspondingly, the early warning device for thermal runaway of the electrochemical energy storage power station battery provided in this embodiment of the invention can also be installed in a terminal processor or a cluster of terminal processors that is different from the terminal processor 104 and can communicate with the energy storage power station 101, battery cluster 102, battery unit 103, and / or terminal processor 104.

[0038] It should be understood that Figure 1 The number of energy storage power stations, battery clusters, battery cells, and terminal processors shown is merely illustrative. Any number of energy storage power stations, battery clusters, battery cells, and terminal processors can be included depending on implementation needs.

[0039] The following will be based on Figure 1 The described scene, through Figures 2-8 The method for early warning of thermal runaway of batteries in electrochemical energy storage power stations according to embodiments of the present invention is described in detail.

[0040] Figure 2 A flowchart of an early warning method for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0041] like Figure 2 As shown, the early warning method for thermal runaway of the battery in the electrochemical energy storage power station of this embodiment includes operations S210 to S240.

[0042] In operation S210, the battery voltage change of multiple battery cells is determined based on the discharge voltage of multiple battery cells in any battery cluster, and fault trigger judgment is performed on multiple battery cells respectively based on the discharge current and battery voltage change of multiple battery cells to obtain multiple fault trigger results of multiple battery cells.

[0043] Among them, the change in battery voltage can characterize the change in voltage of a battery cell within a sampling period.

[0044] A battery cluster can be a collection of batteries formed by connecting multiple battery cells in series or in parallel. Each electrochemical energy storage power station can contain multiple battery clusters, and each battery cluster can include multiple battery cells. In this invention, the battery cluster is an example of multiple battery cells connected in series, and a battery cell can be characterized as a single battery cell.

[0045] By analyzing the discharge voltage of each battery cell obtained through real-time monitoring and acquisition, the voltage change of each battery cell is determined. Then, the discharge current of each battery cell obtained through real-time monitoring and acquisition, along with the determined voltage change, are used as initial constraints to determine whether a potential fault trigger exists. This allows for dynamic assessment of each battery cell, resulting in the fault triggering outcome for each cell.

[0046] In operation S220, when multiple fault triggering results characterize at least one potential battery cell among multiple battery cells as having triggered a fault, the target fault characteristic value of at least one potential battery cell is obtained based on the amount of discharge energy change of at least one potential battery cell during the target sampling period.

[0047] The target sampling period may include at least one sampling period.

[0048] Potential battery cells can be those that have triggered a fault. When the fault triggering results indicate that at least one battery cell among multiple battery cells has triggered a fault, the battery cells identified as potentially triggering a fault can be designated as potential battery cells. Then, based on the collected discharge current and battery voltage changes, the discharge energy change of the potential battery cell within the current at least one sampling period can be calculated.

[0049] Then, based on information such as the historical state of the potential battery cell, the target sampling period corresponding to the potential battery cell can be determined. Based on the number of sampling cycles included within the target sampling period, the change in discharge energy corresponding to each sampling cycle is integrated to obtain the target fault characteristic value of the potential battery cell.

[0050] The target fault characteristic value can be characterized as a parameter index used to judge the degree of fault of the battery cell.

[0051] In operation S230, based on the energy fault threshold, at least one potential battery cell is judged for fault according to the target fault characteristic value of at least one potential battery cell, and at least one intermediate battery cell with abnormal operation is identified from at least one potential battery cell.

[0052] Once the target fault characteristic value of each potential battery cell is obtained, it can be compared with the target fault characteristic value of each potential battery cell according to the predetermined energy fault threshold, so as to determine whether a fault may occur.

[0053] An intermediate battery cell can be characterized as a battery cell that may be faulty, that is, a battery cell in an abnormal operating state. When it is determined that a potential battery cell is operating abnormally, the potentially faulty battery cell is identified as an intermediate battery cell.

[0054] In operation S240, at least one intermediate battery cell is classified as faulty and aged according to the aging rules corresponding to multiple battery cells, and at least one target faulty battery cell is identified from the at least one intermediate battery cell.

[0055] Once the intermediate battery cells are identified, they are classified as faulty or aged according to an aging rule determined based on the charging time of multiple battery cells. The battery cells that are identified as faulty or aged are designated as target faulty battery cells.

[0056] Based on the relevant information of the identified target faulty battery unit, alarm information can be generated and reported to staff and host computer systems, thereby providing timely early warning of the faulty battery unit.

[0057] According to an embodiment of the present invention, by real-time monitoring of the discharge current and battery voltage changes of multiple battery cells in each battery cluster within an energy storage power station, the discharge current and battery voltage changes can be used as the underlying triggering and early warning conditions for determining whether a battery cell has failed, thus obtaining preliminary fault triggering results and conducting preliminary early warning screening of potential risks to the battery cells.

[0058] When a battery cell is deemed likely to trigger a fault, it is identified as a potential fault cell. Based on the changes in discharge current and discharge energy of the potential fault cells during the target sampling period, a target fault characteristic value is calculated to characterize the severity of the potential fault. This target fault characteristic value is then used as a criterion for determining the fault severity. A second warning screening is performed from the potential fault cells based on a baseline judgment line for determining whether a fault has occurred (the energy fault threshold), identifying intermediate battery cells. This approach incorporates the potential for pseudo-normal parameters in battery thermal runaway as a prerequisite for fault judgment, combining battery voltage and discharge current changes with energy changes as a core judgment criterion. By dynamically and flexibly selecting the target sampling period based on a comprehensive consideration of battery state categories, accurate target fault characteristic values ​​are determined, providing a basis for accurate fault judgment based on the energy characteristics of the battery cell. Furthermore, the precisely determined energy fault threshold serves as the gold standard for fault warning in this invention, significantly improving the accuracy and efficiency of battery cell warning judgment.

[0059] Furthermore, based on the aging rules determined by the charging period of each battery cell, abnormal energy changes that may be caused by battery aging are further classified and identified. This improves the accuracy and reliability of early warning of thermal runaway of battery cells without the need for complex algorithm models to calculate and evaluate faults, making it more widely applicable in actual industrial production and expanding the applicable scenarios and scope of the early warning method proposed in this invention.

[0060] According to an embodiment of the present invention, a method for determining the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells in any battery cluster, and for performing fault trigger judgment on multiple battery cells respectively based on the discharge current and battery voltage change of multiple battery cells, to obtain multiple fault trigger results of multiple battery cells may include the following operations.

[0061] Figure 3 A flowchart illustrating the multiple fault triggering results of multiple battery cells according to an embodiment of the present invention is shown.

[0062] like Figure 3 As shown, the method for obtaining multiple fault triggering results of multiple battery cells in this embodiment includes operations S310 to S340.

[0063] In operation S310, if any battery cluster includes N battery cells, for the nth battery cell, the discharge current and discharge voltage of the nth battery cell at time t and the discharge voltage of the (n-1)th battery cell at time t are collected.

[0064] Where N is an integer greater than or equal to 2, n is an integer greater than or equal to 2 and less than or equal to N, and time t-1 and time t are the start and end times of a sampling period, respectively.

[0065] The discharge current and discharge voltage of the nth battery cell are collected in real time. Then, based on the discharge voltage of the nth battery cell at time t and the discharge voltage of the adjacent battery cells at time t, the change in battery voltage of the nth battery cell can be calculated, thereby determining whether the nth battery cell has triggered a fault at time t.

[0066] The interval between the start and end times of the sampling period can also be set according to specific circumstances.

[0067] In operation S320, the initial voltage change of the nth battery cell is determined based on the difference between the discharge voltage of the nth battery cell at time t and the discharge voltage of the nth battery cell at time t-1; the initial voltage change of the (n-1)th battery cell is determined based on the difference between the discharge voltage of the (n-1)th battery cell at time t and the discharge voltage of the (n-1)th battery cell at time t-1.

[0068] The initial voltage change of the nth battery cell in one sampling period can be shown in formula (1), and the initial voltage change of the (n-1)th battery cell in one sampling period can be shown in formula (2).

[0069] △U n (t) = U n (t)-U n (t-1)(1);

[0070] Among them, △U n (t) can be characterized as the initial voltage change of the nth battery cell within one sampling period, U n (t) can be characterized as the discharge voltage of the nth battery cell at time t, U n (t-1) can be represented as the discharge voltage of the nth battery cell at time t-1, and the sampling period can be the time period from time t-1 to time t.

[0071] △U n-1 (t) = U n-1 (t)-U n-1 (t-1)(2);

[0072] Among them, △U n-1 (t) can be characterized as the initial voltage change of the (n-1)th battery cell within one sampling period, U n-1 (t) can be characterized as the discharge voltage of the (n-1)th battery cell at time t, U n-1 (t-1) can be characterized as the discharge voltage of the (n-1)th battery cell at time t-1.

[0073] In operation S330, the battery voltage change of the nth battery cell is determined based on the initial voltage change of the nth battery cell and the initial voltage change of the (n-1)th battery cell.

[0074] The change in battery voltage of the first battery cell can be obtained from the difference between the discharge voltage of the first battery cell at time t and the discharge voltage of the first battery cell at time t-1.

[0075] The change in battery voltage of the nth battery cell within a sampling period can be represented by formula (3).

[0076] △U n '(t)=△U n (t)-△U n-1 (t)(3);

[0077] Among them, △U n '(t) can be characterized as the change in battery voltage of the nth battery cell within one sampling period.

[0078] For the change in battery voltage of the first battery cell, the above formula (1) can be used as a reference. The initial voltage change obtained by directly subtracting the discharge voltage at time t-1 and the discharge voltage at time t can be used as the change in battery voltage of the first battery cell for fault triggering judgment.

[0079] After determining the battery voltage change of the 2nd to Nth battery cells, the average of the summation can be obtained to get the average battery voltage change of the multiple battery cells in the battery cluster. Then, referring to the above formulas (1) and (3), the battery voltage change of the 1st battery cell used for fault triggering judgment can be obtained based on the initial voltage change and the average battery voltage change of the 1st battery cell.

[0080] In operation S340, based on the discharge current and battery voltage change of the nth battery cell at time t, a fault trigger judgment is made for the nth battery cell, and the fault trigger result of the nth battery cell is obtained. The above-mentioned operations of collecting data and determining the battery voltage change based on the obtained initial voltage change are repeated until the fault trigger result of the Nth battery cell is obtained.

[0081] The fault triggering result of the first battery cell is obtained by judging the fault triggering of the first battery cell based on the discharge current and battery voltage change of the first battery cell at time t.

[0082] Given the discharge current of the nth battery cell at time t and the change in battery voltage within a sampling period, the operating status of the nth battery cell can be monitored and judged to determine whether the nth battery cell may trigger a fault, and the fault trigger result of the nth battery cell can be obtained.

[0083] Having determined the fault triggering result of the nth battery cell, based on the sequence identifier of the nth battery cell and the sequence identifiers of the N battery cells within the battery cluster, it is determined whether there are any remaining battery cells that have not undergone fault triggering. If it is confirmed that there are still battery cells that have not undergone fault triggering, the aforementioned collection of discharge current and battery voltage changes and fault triggering are performed sequentially on the remaining battery cells until the fault triggering result of the Nth battery cell is obtained. This confirms that the battery cluster within the energy storage power station has completed its preliminary inspection, and early warning judgments can be made for other battery clusters.

[0084] According to an embodiment of the present invention, when a battery cluster includes multiple battery cells, the discharge current and discharge voltage of the battery cell at the current time t, as well as the discharge voltage of the adjacent battery cells, are collected. Based on the voltage difference between the adjacent battery cells at the current time and the previous time, and the voltage difference between the battery cell at the current time and the previous time, the voltage change of the battery cell within this sampling period is determined. The discharge current and voltage change of the battery cell are then used as the underlying triggering warning conditions for determining whether a battery cell has failed, thereby obtaining preliminary fault triggering results. This preliminary fault triggering warning judgment is then performed sequentially on each battery cell within the battery cluster to accurately screen for potential risks in each battery cell.

[0085] According to an embodiment of the present invention, a method for determining the fault triggering result of the nth battery cell based on the discharge current and battery voltage change of the nth battery cell at time t may include the following operations.

[0086] According to an embodiment of the present invention, when the discharge current of the nth battery cell at time t is less than a first predetermined threshold and the change in battery voltage of the nth battery cell is greater than a second predetermined threshold, the fault triggering result of the nth battery cell is determined to characterize the triggering fault.

[0087] The fault triggering judgment conditions related to the discharge current and battery voltage change of the nth battery cell at time t can be shown in formulas (4) and (5).

[0088] I n (t) < 0 (4);

[0089] Among them, I n (t) can be represented as the discharge current of the nth battery cell at time t. The first predetermined threshold can be set to 0. The first predetermined threshold can be specifically set and adjusted according to the actual situation. When the discharge current of the nth battery cell at time t is less than 0, it can be confirmed that the battery cell is in a discharge state at this time.

[0090] △U n '(t)=△U n (t)-△U n-1 (t) > 0 (5);

[0091] The second predetermined threshold can also be set to 0, and the second predetermined threshold can be adjusted according to the actual situation.

[0092] According to an embodiment of the present invention, if the discharge current of the nth battery cell at time t is less than or equal to a first predetermined threshold or the change in battery voltage of the nth battery cell is less than or equal to a second predetermined threshold, the fault triggering result of the nth battery cell is determined to indicate that a fault has not been triggered.

[0093] If either the discharge current or the change in battery voltage fails to reach a predetermined threshold, it can be concluded that the current battery cell has not met the conditions for triggering a discharge fault at the power station.

[0094] According to an embodiment of the present invention, by using a first predetermined threshold and a second predetermined threshold as limiting constraints for evaluating fault triggering based on discharge current and battery voltage changes, and by performing the above-mentioned judgment on each battery cell, an accurate fault triggering determination result is obtained. This achieves full utilization of the fault characteristic of a continuous drop in battery voltage across the battery cell before thermal runaway occurs, and by determining the corresponding first and second predetermined thresholds based on this fault characteristic for accurate fault judgment.

[0095] According to an embodiment of the present invention, when multiple fault triggering results characterize at least one potential battery cell among multiple battery cells as having triggered a fault, a method for obtaining a target fault characteristic value of at least one potential battery cell based on the amount of discharge energy change of at least one potential battery cell during a target sampling period may include the following operations.

[0096] According to an embodiment of the present invention, the change in discharge energy of at least one potential battery cell during the target sampling period is integrally calculated to obtain the target fault characteristic value of at least one potential battery cell.

[0097] The larger the target fault characteristic value, the longer the battery abnormality lasts and the more severe the fault.

[0098] Based on the changes in discharge current and battery voltage of the potential battery cell within a sampling period, the change in discharge energy of the potential battery cell within a sampling period can be obtained, as shown in formula (6).

[0099] △Q(t)=△U'(t)*I'(t)*△t(6);

[0100] Wherein, ΔQ(t) can be characterized as the change in discharge energy of a potential battery cell within a sampling period, ΔU'(t) can be characterized as the change in battery voltage of a potential battery cell within a sampling period, I'(t) can be characterized as the discharge current of a potential battery cell within a sampling period, and Δt can be characterized as the sampling period.

[0101] The method for calculating the target fault characteristic value is as shown in formula (7).

[0102] (7);

[0103] Where F can be represented as the target fault characteristic value, t end t0 can be represented as the end time of the target sampling period, and t0 can be represented as the start time of the target sampling period.

[0104] Furthermore, the target sampling period can be obtained in the following way.

[0105] According to an embodiment of the present invention, a time period weight corresponding to at least one potential battery cell is determined based on the historical category status and battery aging degree of at least one potential battery cell.

[0106] Since the change in discharge energy of a potential battery cell within a sampling period may lead to misdiagnosis due to fluctuations in signal or current, it is necessary to accumulate the change in discharge energy over a certain period of time in order to determine the degree of failure of the battery cell based on the target fault characteristic value after reasonable accumulation.

[0107] Historical category status can be characterized as the operating state to which the battery cell was previously identified. This operating state can include normal state (non-aging state) and aging state, but is not limited to these.

[0108] The degree of battery aging can be determined by comparing the charging time of an aged battery cell with that of a normal battery cell or other battery cells. For example, it can be pre-set that if a battery cell's charging time is less than that of a normal battery cell, and the charging time is within 90% of the normal charging time, the battery cell is considered to have a mild degree of battery aging; if the charging time is less than that of a normal battery cell, and the charging time is between 80% and 90% of the normal charging time, the battery cell is considered to have a moderate degree of battery aging; and if the charging time is less than that of a normal battery cell, and the charging time is less than 80% of the normal charging time, the battery cell is considered to have a severe degree of battery aging.

[0109] Based on the historical category status and battery aging degree of potential battery cells, when the most recent category status of a potential battery cell is normal, the time period weight corresponding to that potential battery cell can be determined to be 1; when the most recent category status of a potential battery cell is aging, the time period weight corresponding to that potential battery cell is determined according to its battery aging degree.

[0110] For example, if the most recent classification of a potential battery cell is aging and the degree of battery aging is relatively mild, the time period weight corresponding to that potential battery cell can be determined to be 0.9; if the most recent classification of a potential battery cell is aging and the degree of battery aging is moderate, the time period weight corresponding to that potential battery cell can be determined to be 0.8; and if the most recent classification of a potential battery cell is aging and the degree of battery aging is severe, the time period weight corresponding to that potential battery cell can be determined to be 0.7.

[0111] In addition to pre-setting the mapping based on battery aging degree and time period weight, the time period weight corresponding to a potential battery cell can also be determined directly based on the ratio of the charging time of the battery cell to the charging time of the battery cell in normal condition.

[0112] For example, if the most recent classification of a potential battery cell is an aging state and the ratio of the charging time of the potential battery cell to the charging time of a battery cell in a normal state is 0.86, the time period weight corresponding to the potential battery cell can be determined to be 0.86.

[0113] According to an embodiment of the present invention, a predetermined time period of at least one potential battery cell is weighted using the time period weight corresponding to at least one potential battery cell to obtain the target sampling time period of at least one potential battery cell.

[0114] The predetermined time period represents the period from when at least one battery cell that has not aged triggers a discharge fault to when no discharge fault is triggered.

[0115] The predetermined time period can include multiple sampling periods. After determining the time period weight corresponding to the potential battery cell, the predetermined time period can be weighted using the time period weight to obtain the target sampling time period corresponding to each potential battery cell.

[0116] For example, if the predetermined time period is 30s, the weight of the time period corresponding to the first potential battery cell can be 0.9, then the target sampling time period for the first potential battery cell is 27s; the weight of the time period corresponding to the second potential battery cell can be 0.7, then the target sampling time period for the second potential battery cell is 21s; and the weight of the time period corresponding to the third potential battery cell can be 0.63, then the target sampling time period for the third potential battery cell is 18.9s.

[0117] In addition to the above-mentioned methods for determining the target sampling period, the time period weight can also be disregarded, and the target sampling period for all potential battery cells can be directly assumed to be the period from the triggering of a discharge fault to the non-triggering of a discharge fault.

[0118] According to an embodiment of the present invention, a time period weight corresponding to a potential battery cell is determined based on the historical category status and battery aging degree of the potential battery cell. Then, the predetermined time period is weighted using the time period weight to obtain the target sampling time period for each potential battery cell. Subsequently, based on the target sampling time period, a target fault characteristic value for judging the fault degree is obtained by integrating the battery voltage change and discharge current. This incorporates the influencing factors of the potential battery cell's own state into the determination process of the target sampling time period for calculating the target fault characteristic value. This reduces the fault confirmation time period for potential battery cells that have been historically identified as aging batteries, preventing potentially faulty aging batteries from further exacerbating the risk of thermal runaway as normal batteries are processed within the predetermined time period, thus improving the flexibility and agility of fault degree confirmation. Then, based on the target fault characteristic value calculated within the target sampling time period, the fault degree of the current potential battery cell is accurately and efficiently determined.

[0119] According to an embodiment of the present invention, the energy failure threshold can be obtained in the following manner.

[0120] Figure 4 A flowchart for determining an energy failure threshold according to an embodiment of the present invention is shown.

[0121] like Figure 4 As shown, the method for determining the energy fault threshold in this embodiment includes operations S410 to S420.

[0122] In operation S410, the historical fault characteristic attenuation value is determined based on the first historical fault parameters of the first battery cell in the predetermined historical period and the second historical fault parameters of the second battery cell in the predetermined historical period.

[0123] The first battery cell represents the battery cell with the highest voltage when at rest, and the second battery cell represents the battery cell with the lowest voltage when at rest.

[0124] After obtaining the target fault characteristic values ​​of potential battery cells, it is necessary to determine whether the potential battery cells have failed based on the energy fault threshold.

[0125] In energy storage power stations, all battery cells within a battery cluster can be connected in series. Therefore, the current flowing through each cell is the same, the charging and discharging processes are synchronized, and the state of charge (SOC) is essentially the same. Theoretically, the voltage of each cell should be identical. However, in actual operation, due to factors such as manufacturing processes, the SOC of each cell is not completely consistent. A cell with a low SOC may experience a faster rate of decline than a cell with a high SOC over a certain period, leading to potential misdiagnosis. Therefore, it is necessary to set specific energy fault thresholds. The energy fault thresholds required for the current application can be pre-determined from multiple battery cells.

[0126] The historical predetermined time period can be characterized as the period of the most recent discharge process of a battery cell. Historical fault parameters can include the historical discharge current and historical battery voltage changes of the battery cell within a sampling period of the most recent discharge process. The historical predetermined time period can be the same as the predetermined time period length, that is, the period from when the first / second battery cell that has not yet aged triggers a discharge fault to when it does not trigger a discharge fault.

[0127] Multiple battery cells within a battery cluster can be considered as a single cell partition. The corresponding first and second battery cells are then located from among these cells. Based on the first historical discharge current of the first battery cell during its most recent discharge process and the second historical discharge current of the second battery cell during its most recent discharge process (the magnitudes of the first and second historical discharge currents are equal), as well as the difference between the first and second historical battery voltage changes, the historical fault characteristic attenuation value is determined. The historical fault characteristic attenuation value can be represented by formula (8).

[0128] (8);

[0129] Among them, F h This can be characterized as the historical fault characteristic decay value, t end 't0' can be represented as the end time of a predetermined historical time period, and 't0' can be represented as the start time of a predetermined historical time period. △U max This can be characterized as the difference between the first historical battery voltage change and the second historical battery voltage change, I. h It can be characterized as the historical discharge current flowing through the first and second battery cells.

[0130] In operation of S420, the energy failure threshold is obtained based on the historical failure characteristic attenuation value and reliability coefficient.

[0131] The energy failure threshold can be expressed as shown in formula (9).

[0132] F g =K r *F h (9);

[0133] Among them, F g This can be characterized as the energy failure threshold, K r It can be characterized as a reliability coefficient.

[0134] According to an embodiment of the present invention, a first battery cell and a second battery cell are determined from multiple battery cells based on the voltage state of the battery cells in a static state. A historical fault characteristic attenuation value is determined based on the difference in historical discharge current and the difference in historical battery voltage change during the previous discharge process of the first and second battery cells. Then, based on the historical fault characteristic attenuation value and a reliability coefficient, a constraint baseline (energy fault threshold) for judging the fault degree of a potential battery cell is obtained, so as to determine the fault degree of a potential battery cell based on the energy fault threshold. This method incorporates the differences in the state of charge of multiple battery cells as a potential factor that may cause misjudgment into the calculation process of obtaining the energy fault threshold. By combining the maximum and minimum battery voltage change and the maximum and minimum discharge current of all battery cells in the entire battery cluster, the energy fault threshold is accurately obtained. This greatly improves the accuracy, reliability, and efficiency of battery cell early warning judgment, while avoiding misdiagnosis caused by signal fluctuations.

[0135] According to embodiments of the present invention, the method for determining the energy fault threshold described above may further include the following operations.

[0136] Figure 5 A flowchart illustrating the determination of at least one intermediate battery cell according to another embodiment of the present invention is shown.

[0137] like Figure 5 As shown, the method for determining at least one intermediate battery cell in this embodiment includes operations S510 to S550.

[0138] In operation S510, based on the predetermined weight allocation principle, the historical category status, battery aging degree, historical fault characteristic quantity and location information of multiple battery cells are initially weighted to obtain an initial weight set.

[0139] The initial weight set may include initial state weights, initial aging weights, initial feature weights, and initial position weights.

[0140] In addition to treating multiple battery cells within a battery cluster as a single unit partition, energy fault thresholds can be specifically determined for multiple battery cell partitions based on factors such as the different historical states of the battery cells, so as to make more refined and accurate fault judgments for different battery cells.

[0141] The predetermined weight allocation principle can be characterized as the principle of initially assigning weights to the historical category status, battery aging degree, historical fault characteristics and location information corresponding to the battery cell based on the comprehensive state of multiple battery cells.

[0142] For example, the predetermined weight allocation principle may include allocating a larger initial weight corresponding to the historical category state and degree of battery aging when more than 30% of the battery cells in a multi-cell configuration are in an aged state; the predetermined weight allocation principle may also include allocating a larger initial weight corresponding to the historical fault characteristic values ​​of a number of battery cells when many of the battery cells have historical fault characteristic values ​​that remain close to but not exceeding the energy fault threshold; the predetermined weight allocation principle may also include allocating a larger initial weight corresponding to the location information of different battery cells because the heat dissipation environment of battery cells located in the middle is poor. These predetermined weight allocation principles can be set specifically according to the specific circumstances and are not limited to the above embodiments.

[0143] In operation S520, the initial weight set is adjusted based on the historical fault accuracy and the historical weight set corresponding to the historical fault accuracy to obtain the target weight set.

[0144] The target weight set includes the target state weight, target aging weight, target feature weight, and target position weight obtained after adjusting the initial state weight, initial aging weight, initial feature weight, and initial position weight.

[0145] After obtaining the initial weight set, the historical characteristics of multiple battery cells in the battery cluster can be further analyzed and determined based on the accuracy of the historical faulty batteries in the battery cluster and the historical weight set (historical state weight, historical aging weight, historical feature weight, and historical position weight) corresponding to the historical fault accuracy. The initial weight set is then adaptively adjusted to obtain the target weight set.

[0146] For example, from the historical fault accuracy and the corresponding historical weight set, it can be seen that in judging the historical discharge fault (thermal runaway warning) of the battery cells in this battery cluster, when the weight quotas of the historical state weight and the historical aging weight are each greater than 0.3, the corresponding cell partition and fault accuracy are relatively high. Therefore, with the current initial state weight of 0.25, initial aging weight of 0.3, initial feature weight of 0.25 and initial position weight of 0.2, we can consider adaptively adjusting the initial weight set so that the target weight set includes the adjusted target state weight of 0.3, target aging weight of 0.3, target feature weight of 0.225 and target position weight of 0.185.

[0147] Furthermore, the weights used for cell partitioning are not limited to initial state weights, initial aging weights, initial feature weights, and initial position weights. Additionally, depending on the specific circumstances, one or more of these weights can be selectively used as the judgment weights for the current cell partitioning. For example, based on a predetermined weight allocation principle, initial weights can be allocated only to the historical category state, battery aging degree, and historical fault feature quantities of multiple battery cells to obtain an initial weight set.

[0148] Furthermore, multiple battery cells can be partitioned using only a single historical category status, battery aging level, historical fault characteristics, or location information as the partitioning criteria.

[0149] In operation S530, the target weight set is used to perform weighted summation on the category parameters, aging parameters, feature parameters and location parameters of each battery cell to obtain the partition evaluation of each battery cell.

[0150] The category parameter of a battery cell can be obtained by comparing the total number of aged cells in the battery cluster to the total number of all cells. The aging parameter of a battery cell can be obtained by comparing the charging time of that cell to the charging time of a cell in normal condition. The characteristic parameter of a battery cell can be obtained by comparing the number of times the difference between the historical fault characteristic quantity and the energy fault threshold of that cell is less than a predetermined proportion. The location parameter of a battery cell can be obtained by comparing the location information of that cell within the battery cluster.

[0151] By using each target weight in the target weight set, a weighted summation is performed on each parameter to obtain the partition rating of each battery cell.

[0152] For example, the battery cluster may include 5 battery cells. The first battery cell has a category parameter of 0.6, an aging parameter of 0.8, a feature parameter of 0.7, and a position parameter of 0.125; the second battery cell has a category parameter of 0.6, an aging parameter of 0.9, a feature parameter of 1, and a position parameter of 0.2; the third battery cell has a category parameter of 1, an aging parameter of 1, a feature parameter of 1, and a position parameter of 0.35; the fourth battery cell has a category parameter of 0.6, an aging parameter of 0.6, a feature parameter of 0.3, and a position parameter of 0.2; and the fifth battery cell has a category parameter of 1, an aging parameter of 1, a feature parameter of 0.3, and a position parameter of 0.125. The target state weight is 0.3, the target aging weight is 0.4, the target feature weight is 0.2, and the target position weight is 0.1. These weights are used to perform a weighted summation, resulting in a partition rating of 0.6525 for the first battery unit, 0.76 for the second battery unit, 0.935 for the third battery unit, 0.5 for the fourth battery unit, and 0.4925 for the fifth battery unit.

[0153] In operation S540, based on the partition evaluation of each of the multiple battery cells, the multiple battery cells are divided to obtain at least one cell partition and at least one energy fault threshold for the cell partition.

[0154] The cell partition may include at least two battery cells.

[0155] Having obtained the partition rating for each battery cell, multiple battery cells can be partitioned based on predetermined partitioning rules to obtain at least one cell partition. Then, based on at least one cell partition, its energy failure threshold is determined. If, after partitioning, there exists a cell partition consisting of only one battery cell, that battery cell can be assigned to the cell partition with the closest partition rating.

[0156] For example, the predetermined partitioning rule could be to divide partitions with a partition score less than or equal to 0.5 into one unit partition, partitions with a partition score greater than 0.5 and less than or equal to 0.8 into one unit partition, and partitions with a partition score greater than 0.8 into one unit partition. Referring to the above-described partitioning score implementation, the first and second battery units can be divided into the first unit partition, the third battery unit into the second unit partition, and the fourth and fifth battery units into the third unit partition. Since the second unit partition contains only one battery unit, the third battery unit is assigned to the first unit partition, and the third unit partition, consisting of the fourth and fifth battery units, is updated to the second unit partition.

[0157] After obtaining the energy fault threshold and cell partitioning as described above, the method of determining at least one potential battery cell for fault judgment based on the energy fault threshold and the target fault characteristic value of at least one potential battery cell, and identifying at least one abnormal intermediate battery cell from at least one potential battery cell, may further include the following operations.

[0158] In operation S550, at least one potential battery cell is fault-determined based on the energy fault threshold of the cell partition where at least one potential battery cell is located and the target fault characteristic value of at least one potential battery cell, and at least one intermediate battery cell is determined.

[0159] Having determined the cell partitions and the energy failure threshold for each cell partition, the cell partition in which a potential battery cell is located, and its corresponding energy failure threshold, can be determined based on the sequence identifier of the potential battery cell. Therefore, based on the determined energy failure threshold, each potential battery cell can be assessed for fault status, and the faulty potential battery cell can be designated as an intermediate battery cell.

[0160] According to embodiments of the present invention, multiple battery cells within a battery cluster can be partitioned based on a predetermined weighting principle, incorporating parameters such as historical battery category, aging degree, and historical fault characteristics. This results in at least one unit partition and a specific energy fault threshold corresponding to each unit partition. Combining the sequence identifier of potential battery cells, the corresponding energy fault threshold is selected from the multiple unit partitions to accurately determine the fault of each potential battery cell. This approach enables more accurate fault determination of potential battery cells within a battery cluster by introducing a weighted partitioning concept, considering the parameter information of the battery cells, to obtain multiple unit partitions and determine the energy fault threshold corresponding to each unit partition. When determining the fault threshold, the energy fault threshold corresponding to the potential battery cell is used as a baseline for the determination constraint. This significantly improves the accuracy, reliability, and efficiency of the early warning judgment of battery cells while avoiding misdiagnosis due to signal fluctuations.

[0161] According to an embodiment of the present invention, a method for dividing multiple battery cells based on their respective partition ratings to obtain at least one cell partition and an energy fault threshold for at least one cell partition may include the following operations.

[0162] According to an embodiment of the present invention, based on the partition evaluation of each of the multiple battery cells, the multiple battery cells are partitioned to obtain at least one cell partition.

[0163] According to an embodiment of the present invention, the historical fault characteristic attenuation value of at least one cell partition is determined based on the first historical fault parameter of the first battery cell in at least one cell partition within a predetermined historical time period and the second historical fault parameter of the second battery cell within a predetermined historical time period.

[0164] After dividing the unit into multiple partitions, for each unit partition, the first battery unit and the second battery unit can be determined. The historical fault characteristic attenuation value of each unit partition can be obtained by referring to the above process of determining the historical fault characteristic attenuation value based on the first battery unit and the second battery unit (formula (8)).

[0165] According to an embodiment of the present invention, the energy failure threshold of at least one unit partition is obtained based on the historical fault characteristic attenuation value and reliability coefficient of at least one unit partition.

[0166] After obtaining the historical fault characteristic attenuation value of each unit partition, the energy fault threshold of each unit partition can be obtained by referring to the above formula (9).

[0167] According to an embodiment of the present invention, after dividing multiple battery cells into zones, the first and second battery cells of each zone are determined based on the voltage state of the battery cells in the resting state. Historical fault characteristic attenuation values ​​are determined based on the difference in historical discharge current and the difference in historical battery voltage change during the previous discharge process of the first and second battery cells. Then, based on the historical fault characteristic attenuation values ​​and the reliability coefficient, a constraint baseline (energy fault threshold) corresponding to each cell zone can be obtained. This facilitates the determination of the fault degree of potential battery cells based on the energy fault threshold of each cell zone. This incorporates the differences in the state of charge of different battery cells as a potential factor causing misjudgment into the calculation process for obtaining the energy fault threshold. By combining the maximum and minimum battery voltage change and the maximum and minimum discharge current of all battery cells in the entire battery cluster, the energy fault threshold is accurately obtained. This significantly improves the accuracy, reliability, and efficiency of battery cell early warning judgment while avoiding misdiagnosis caused by signal fluctuations.

[0168] According to an embodiment of the present invention, a method for determining at least one intermediate battery cell by fault judgment of at least one potential battery cell based on the energy fault threshold of the cell partition where at least one potential battery cell is located and the target fault characteristic value of at least one potential battery cell may include the following operations.

[0169] According to an embodiment of the present invention, a target cell partition corresponding to each potential battery cell is determined from at least one cell partition based on the sequence identifier of each potential battery cell.

[0170] According to an embodiment of the present invention, the target fault feature value of each potential battery cell is inverted using the time period weight corresponding to each potential battery cell to obtain the inverted fault feature value of each potential battery cell.

[0171] Since the energy fault threshold is determined based on a predetermined historical time period, which, like the predetermined time period, is the period from when a non-aged battery cell triggers a discharge fault to when it does not, regardless of whether multiple battery cells are partitioned, when faced with the target fault characteristic value obtained from the target sampling time period after weighted processing based on time period weights, a weight inversion calculation is required to ensure that the comparison between the fault characteristic value of the potential battery cell and the energy fault threshold can be made on the same baseline.

[0172] For example, if the time period weight of the first potential battery cell is 0.8 and the target fault feature value is 50, then through inversion processing, the inversion fault feature value of the first potential battery cell can be 62.5.

[0173] According to an embodiment of the present invention, if the inversion fault characteristic value of any potential battery cell is greater than the energy fault threshold corresponding to any potential battery cell, any potential battery cell is determined as an intermediate battery cell.

[0174] Based on the energy fault threshold of the target cell partition corresponding to each potential battery cell, if the inverted fault characteristic value of the potential battery cell is greater than the energy fault threshold, the potential battery cell can be determined to be faulty and identified as an intermediate battery cell; if the inverted fault characteristic value of the potential battery cell is less than or equal to the energy fault threshold, the potential battery cell can be determined to be currently not faulty. The fault judgment process can be shown in formula (10).

[0175] F / β> F g =K r *F h (10);

[0176] Here, β can be represented as the time period weight.

[0177] According to an embodiment of the present invention, by determining the expected target cell partition based on the sequence identifier of the potential battery cell, and then performing inversion processing on the time period weight of the potential battery cell, each potential battery cell can be fault-determined under the same standard, thereby improving the reliability of fault detection while enabling high response speed.

[0178] According to an embodiment of the present invention, a method for classifying at least one intermediate battery cell as faulty and aged according to aging rules corresponding to multiple battery cells, and for determining a target faulty battery cell from at least one intermediate battery cell, may include the following operations.

[0179] Figure 6 A flowchart illustrating the determination of at least one target faulty battery cell according to an embodiment of the present invention is shown.

[0180] like Figure 6 As shown, the method for determining the target faulty battery cell in this embodiment includes operations S610 to S630.

[0181] In operation S610, at least one intermediate battery cell is classified as faulty and aged according to the aging rules corresponding to multiple battery cells, resulting in at least one faulty battery cell and at least one aged battery cell.

[0182] Among them, the aging rule corresponding to multiple battery cells indicates that if the charging period of the intermediate battery cell is less than the minimum charging period among the multiple battery cells, the intermediate battery cell is identified as an aged battery cell; if the charging period of the intermediate battery cell is greater than or equal to the minimum charging period among the multiple battery cells, the intermediate battery cell is identified as a faulty battery cell.

[0183] Since battery aging can cause its voltage to drop faster than other battery cells, additional anti-malfunction conditions can be introduced to distinguish aged batteries from faulty batteries.

[0184] Because aged batteries have increased internal resistance, they can reach the charging cutoff voltage earlier during the charging process. In contrast, faulty batteries have additional energy decay, resulting in a slow voltage rise that lags behind other batteries in reaching the cutoff voltage. Therefore, the charging period of a battery cell can be introduced as one of the factors for judging aging or faults.

[0185] When at least one intermediate battery cell is identified using the energy failure threshold, the abnormal intermediate battery cells can be classified as faulty or aged according to the aging rules to preliminarily determine the faulty battery cells and the aged battery cells that may have faults. The aging rules can be as shown in formula (11).

[0186] t last,n <min{t last,1 , t last,2 ,……, t last,n-1 , t last,n+1 ,……, t last,N}(11)

[0187] Among them, tlast,n This can be represented as the charging period of the nth battery cell, t last,1 This can be characterized as the charging period of the first battery cell, t last,2 This can be characterized as the charging period of the second battery cell, t last,n-1 This can be represented as the charging period of the (n-1)th battery cell, t last,n+1 This can be represented as the charging period of the (n+1)th battery cell, t last,N This can be represented as the charging period of the Nth battery cell.

[0188] In operation S620, an aged faulty battery cell is identified from at least one aged battery cell based on the increase in the amount of discharge energy change of at least one aged battery cell over multiple sampling cycles during the target sampling period.

[0189] Once the aged battery cell is identified, its failure status can be determined by analyzing the trend (increase) of the discharge energy change during the target sampling period (multiple sampling cycles). Specifically, for battery cells that have only aged without failure, the increase in discharge energy change should be uniform; for battery cells that have failed, the increase in discharge energy change may exhibit uneven changes such as sharp spikes.

[0190] In operation S630, a target faulty battery cell is obtained based on at least one faulty battery cell and an aged faulty battery cell.

[0191] According to embodiments of the present invention, by further classifying and judging the aging and faults of intermediate battery cells based on charging period and aging rules, the accuracy and reliability of thermal runaway early warning of battery cells can be further improved without using complex algorithm models for fault calculation and evaluation. This facilitates its widespread application in actual industrial production and expands the application scenarios and scope of the early warning method proposed in this invention.

[0192] Figure 7A A schematic diagram of a battery cluster comprising a plurality of normal battery cells is shown according to an embodiment of the present invention. Figure 7B A schematic diagram of a battery cluster comprising multiple normal battery cells and faulty battery cells according to an embodiment of the present invention is shown.

[0193] like Figures 7A-7B As shown, Figures 7A-7B A battery cluster containing multiple normal battery cells and a battery cluster containing multiple normal battery cells and faulty battery cells are shown. Figure 7AIt can include N normal battery cells, which can be powered by a power source. The power supply flows through resistor R0 and provides voltage U to the load. For a faulty battery cell, a short circuit fault has occurred inside. Figure 7B The circuit diagram shown can be powered by a power source, but the power supplied flows through resistor R0 and then through short-circuit resistor R. ISC Instead of supplying voltage U to the load, it fails to do so.

[0194] Figure 8 A schematic diagram comparing the voltages of a faulty battery cell and a normal battery cell according to an embodiment of the present invention is shown.

[0195] like Figure 8 As shown, Figure 8 The horizontal axis can represent time, and the vertical axis can represent voltage. As can be seen from the figure, the voltage of a normal battery cell decreases slowly and at a stable amplitude, while the voltage of a faulty battery cell can drop abruptly.

[0196] Figure 9 A schematic diagram illustrating the entire process of an early warning method for thermal runaway of any battery in an electrochemical energy storage power station according to an embodiment of the present invention.

[0197] like Figure 9 As shown, Figure 9 The entire process of the early warning method for thermal runaway of batteries in an electrochemical energy storage power station is shown. Specifically, it begins with S901, collecting the discharge current and discharge voltage of the nth battery cell at time t, and the discharge voltage of the (n-1)th battery cell at time t; S902, determining the initial voltage change of the nth battery cell based on the difference between the discharge voltages of the nth battery cell at time t and at time t-1; S903, determining the initial voltage change of the (n-1)th battery cell based on the difference between the discharge voltages of the (n-1)th battery cell at time t and at time t-1; S904, determining the battery voltage change of the nth battery cell based on the initial voltage change of the nth battery cell and the initial voltage change of the (n-1)th battery cell; and S905, performing a fault trigger judgment on the nth battery cell based on the discharge current and battery voltage change of the nth battery cell at time t.

[0198] If the discharge current of the nth battery cell at time t is less than or equal to a first predetermined threshold and the battery voltage change is less than or equal to a second predetermined threshold, the sampling time of the nth battery cell is increased (S906), and the thermal runaway early warning judgment is restarted. If the discharge current of the nth battery cell at time t is greater than the first predetermined threshold and the battery voltage change is greater than the second predetermined threshold, the nth battery cell is determined as a potential battery cell. Based on the discharge current and battery voltage change of the potential battery cell (nth battery cell) at time t, the discharge energy change (S907) is calculated. Based on the discharge energy change of the potential battery cell (nth battery cell) during the target sampling period, the target fault characteristic value (S908) is obtained. Based on the energy fault threshold, the potential battery cell (nth battery cell) is judged for fault (S909).

[0199] If the target fault characteristic value of a potential battery cell (the nth battery cell) is less than or equal to the energy fault threshold, the sampling time of the nth battery cell is increased by S906, and the thermal runaway early warning judgment is restarted. If the target fault characteristic value of a potential battery cell (the nth battery cell) is greater than the energy fault threshold, the nth battery cell is determined as an intermediate battery cell. According to the aging rules, the intermediate battery cell (the nth battery cell) is judged for fault and aging by S910.

[0200] If the charging period of the intermediate battery cell (the nth battery cell) is greater than or equal to the minimum charging period among the charging periods of multiple battery cells, the intermediate battery cell (the nth battery cell) is identified as a faulty battery cell (S911), and a thermal runaway warning is issued (S912). If the charging period of the intermediate battery cell (the nth battery cell) is less than the minimum charging period among the charging periods of multiple battery cells and the increase in the amount of discharge energy change is not abnormal, the sampling time of the nth battery cell is increased (S906), and the thermal runaway warning judgment is restarted.

[0201] Figure 10 A structural block diagram of an early warning device for thermal runaway of batteries in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0202] like Figure 10 As shown, the early warning device for thermal runaway of the battery in the electrochemical energy storage power station of this embodiment includes: a judgment module 1010, an acquisition module 1020, a first determination module 1030, and a second determination module 1040.

[0203] The judgment module 1010 is used to determine the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells within any battery cluster, and to perform fault trigger judgment on each of the multiple battery cells based on the discharge current and battery voltage change, thereby obtaining multiple fault trigger results for the multiple battery cells. The battery voltage change represents the voltage change of a battery cell within one sampling period. The judgment module 1010 can be used to execute the operation S210 described above, which will not be repeated here.

[0204] The obtaining module 1020 is used to obtain a target fault feature value of at least one potential battery cell based on the change in discharge energy of at least one potential battery cell during a target sampling period, when multiple fault triggering results characterize at least one potential battery cell among multiple battery cells as having triggered a fault. The target sampling period includes at least one sampling cycle. The obtaining module 1020 can be used to perform the operation S220 described above, which will not be repeated here.

[0205] The first determining module 1030 is used to determine the fault of at least one potential battery cell based on an energy fault threshold and according to the target fault characteristic value of at least one potential battery cell, and to determine at least one intermediate battery cell with abnormal operation from the at least one potential battery cell. The first determining module 1030 can be used to perform the operation S230 described above, which will not be repeated here.

[0206] The second determining module 1040 is used to classify at least one intermediate battery cell into fault and aging categories according to aging rules corresponding to multiple battery cells, and to determine the target faulty battery cell from the at least one intermediate battery cell. The second determining module 1040 can be used to perform the operation S240 described above, which will not be repeated here.

[0207] According to embodiments of the present invention, any plurality of modules among the judgment module 1010, the obtaining module 1020, the first determining module 1030, and the second determining module 1040 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of the present invention, at least one of the judgment module 1010, the obtaining module 1020, the first determining module 1030, and the second determining module 1040 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in hardware or firmware, or in any one of software, hardware, and firmware implementations, or in a suitable combination of any of these. Alternatively, at least one of the judgment module 1010, the obtaining module 1020, the first determining module 1030, and the second determining module 1040 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0208] Figure 11 A block diagram of an electronic device for an early warning method of battery thermal runaway in an electrochemical energy storage power station according to an embodiment of the present invention is shown.

[0209] like Figure 11 As shown, an electronic device according to an embodiment of the present invention includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in ROM 1102 or a program loaded from storage portion 1108 into RAM 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0210] RAM 1103 stores various programs and data required for the operation of the electronic device. Processor 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. Processor 1101 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 1102 and / or RAM 1103. It should be noted that the programs may also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in said one or more memories.

[0211] According to embodiments of the present invention, the electronic device may further include an input / output (I / O) interface 1105, which is also connected to a bus 1104. The electronic device may also include one or more of the following components connected to the input / output (I / O) interface 1105: an input section 1106 including a keyboard, mouse, etc.; an output section 1107 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a LAN card, modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the input / output (I / O) interface 1105 as needed. A removable medium 1111, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1110 as needed so that computer programs read from it can be installed into the storage section 1108 as needed.

[0212] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0213] According to embodiments of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of the present invention, a computer-readable storage medium may include ROM 1102 and / or RAM 1103 and / or one or more memories other than ROM 1102 and RAM 1103 described above.

[0214] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the early warning method for battery thermal runaway in electrochemical energy storage power stations provided in the embodiments of the present invention.

[0215] When the computer program is executed by the processor 1101, it performs the functions defined in the system / apparatus of this embodiment of the invention. According to embodiments of the invention, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0216] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 1109, and / or installed from the removable medium 1111. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0217] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 1109, and / or installed from removable medium 1111. When the computer program is executed by processor 1101, it performs the functions defined in the system of this embodiment of the invention. According to embodiments of the invention, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0218] Those skilled in the art will understand that the features described in the various embodiments of the present invention can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention can be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or combinations fall within the scope of the present invention.

Claims

1. A method for early warning of thermal runaway in an electrochemical energy storage power station battery, characterized in that, The method includes: Based on the discharge voltage of multiple battery cells in any battery cluster, the battery voltage change of multiple battery cells is determined, and based on the discharge current and battery voltage change of multiple battery cells, fault trigger judgment is performed on the multiple battery cells respectively to obtain multiple fault trigger results of multiple battery cells. The battery voltage change represents the voltage change of a battery cell within a sampling period. When the multiple fault triggering results characterize at least one potential battery cell among multiple battery cells as having triggered a fault, the target fault feature value of at least one potential battery cell is obtained based on the change in discharge energy of at least one potential battery cell during the target sampling period, wherein the target sampling period includes at least one sampling cycle. Based on the energy fault threshold, and according to the target fault characteristic value of the at least one potential battery cell, a fault judgment is made on the at least one potential battery cell, and at least one intermediate battery cell with abnormal operation is identified from the at least one potential battery cell. Based on the aging rules corresponding to multiple battery cells, at least one intermediate battery cell is classified as faulty and aged, and the target faulty battery cell is identified from at least one intermediate battery cell.

2. The method according to claim 1, characterized in that, The method involves determining the voltage variation of multiple battery cells within any battery cluster based on their discharge voltages, and then performing fault triggering judgments on each of the multiple battery cells based on their discharge currents and voltage variations, resulting in multiple fault triggering results for the multiple battery cells. This includes: In any given battery cluster containing N battery cells, for the nth battery cell, Collect the discharge current and discharge voltage of the nth battery cell at time t and the discharge voltage of the (n-1)th battery cell at time t, where N is an integer greater than or equal to 2, n is an integer greater than or equal to 2 and less than or equal to N, and time t-1 and time t are the start and end times of a sampling period, respectively. The initial voltage change of the nth battery cell is determined based on the difference between the discharge voltage of the nth battery cell at time t and the discharge voltage of the nth battery cell at time t-1; the initial voltage change of the (n-1)th battery cell is determined based on the difference between the discharge voltage of the (n-1)th battery cell at time t and the discharge voltage of the (n-1)th battery cell at time t-1. The battery voltage change of the nth battery cell is determined based on the initial voltage change of the nth battery cell and the initial voltage change of the (n-1)th battery cell. The battery voltage change of the first battery cell is obtained based on the difference between the discharge voltage of the first battery cell at time t and the discharge voltage of the first battery cell at time t-1. Based on the discharge current and battery voltage change of the nth battery cell at time t, a fault trigger judgment is made for the nth battery cell to obtain the fault trigger result of the nth battery cell. The above-mentioned operations of collecting data and determining the battery voltage change based on the obtained initial voltage change are repeated until the fault trigger result of the Nth battery cell is obtained. The fault trigger result of the 1st battery cell is obtained by making a fault trigger judgment for the 1st battery cell based on the discharge current and battery voltage change of the 1st battery cell at time t.

3. The method according to claim 2, characterized in that, The step of determining the fault trigger of the nth battery cell based on the discharge current and battery voltage change of the nth battery cell at time t, and obtaining the fault trigger result of the nth battery cell, includes: If the discharge current of the nth battery cell at time t is less than a first predetermined threshold and the change in battery voltage of the nth battery cell is greater than a second predetermined threshold, the fault triggering result of the nth battery cell is determined to characterize the fault triggering of the nth battery cell. If the discharge current of the nth battery cell at time t is greater than or equal to the first predetermined threshold or the change in battery voltage of the nth battery cell is less than or equal to the second predetermined threshold, the nth fault triggering result of the nth battery cell indicates that the nth battery cell has not triggered a fault.

4. The method according to claim 1, characterized in that, When the multiple fault triggering results characterize at least one potential battery cell among multiple battery cells as having triggered a fault, the target fault characteristic value of at least one potential battery cell is obtained based on the change in discharge energy of at least one potential battery cell during the target sampling period, including: The target fault characteristic value of the at least one potential battery cell is obtained by integrating the change in discharge energy of the at least one potential battery cell during the target sampling period. The target sampling time period is obtained in the following way: Based on the historical category status and battery aging degree of at least one potential battery cell, determine the time period weight corresponding to at least one potential battery cell; Using the time period weight corresponding to at least one potential battery cell, a predetermined time period of at least one potential battery cell is weighted to obtain the target sampling time period of at least one potential battery cell, wherein the predetermined time period represents the period from when at least one unaged battery cell triggers a discharge fault to when it does not trigger a discharge fault.

5. The method according to claim 1, characterized in that, The energy fault threshold is obtained as follows: Based on the first historical fault parameters of the first battery cell and the second historical fault parameters of the second battery cell within the predetermined historical period, a historical fault characteristic attenuation value is determined, wherein the first battery cell represents the battery cell with the highest voltage in the static state, and the second battery cell represents the battery cell with the lowest voltage in the static state. The energy failure threshold is obtained based on the historical failure characteristic attenuation value and reliability coefficient.

6. The method according to claim 1, characterized in that, The method further includes: Based on a predetermined weight allocation principle, initial weights are allocated to the historical category states, battery aging degree, historical fault characteristics and location information of multiple battery cells to obtain an initial weight set, wherein the initial weight set includes initial state weight, initial aging weight, initial feature weight and initial location weight. Based on the historical fault accuracy and the historical weight set corresponding to the historical fault accuracy, the initial weight set is adjusted to obtain the target weight set, wherein the target weight set includes the target state weight, target aging weight, target feature weight and target position weight obtained after adjusting the initial state weight, initial aging weight, initial feature weight and initial position weight. Using the target weight set, the category parameters, aging parameters, feature parameters and location parameters of each battery cell are weighted and summed to obtain the partition rating of each battery cell; Based on the partition evaluation of each of the multiple battery cells, the multiple battery cells are divided to obtain at least one cell partition and at least one energy fault threshold of the cell partition, wherein the cell partition includes at least two battery cells. The step of determining at least one potential battery cell based on an energy failure threshold and according to the target failure characteristic value of the at least one potential battery cell, and identifying at least one intermediate battery cell with abnormal operation from the at least one potential battery cell, includes: Based on the energy fault threshold of the cell partition where at least one potential battery cell is located and the target fault characteristic value of at least one potential battery cell, a fault judgment is made on at least one potential battery cell to determine at least one intermediate battery cell.

7. The method according to claim 6, characterized in that, The process of dividing multiple battery cells based on their respective partition evaluations to obtain at least one cell partition and at least one energy fault threshold for that cell partition includes: Based on the partition evaluation of each of the multiple battery cells, the multiple battery cells are partitioned to obtain at least one cell partition; Based on the first historical fault parameters of the first battery cell in at least one unit partition and the second historical fault parameters of the second battery cell in the same historical predetermined period, determine the historical fault characteristic attenuation value of at least one unit partition. Based on the historical fault characteristic attenuation value and reliability coefficient of at least one unit partition, the energy fault threshold of at least one unit partition is obtained.

8. The method according to claim 6, characterized in that, The step of determining at least one intermediate battery cell by performing fault assessment on at least one potential battery cell based on the energy fault threshold of the cell partition where the at least one potential battery cell is located and the target fault characteristic value of the at least one potential battery cell includes: Based on the sequence identifier of each potential battery cell, a target cell partition corresponding to each potential battery cell is determined from the at least one cell partition; Using the time period weights corresponding to each potential battery cell, the target fault feature values ​​of each potential battery cell are inverted to obtain the inverted fault feature values ​​of each potential battery cell. If the inversion fault characteristic value of any potential battery cell is greater than the energy fault threshold of the target cell partition corresponding to any potential battery cell, then any potential battery cell is identified as an intermediate battery cell.

9. The method according to claim 1, characterized in that, The step of classifying at least one intermediate battery cell into fault and aging categories according to aging rules corresponding to multiple battery cells, and identifying a target faulty battery cell from at least one intermediate battery cell, includes: According to the aging rules corresponding to multiple battery cells, at least one intermediate battery cell is classified as faulty and aged to obtain at least one faulty battery cell and at least one aged battery cell. The aging rules corresponding to multiple battery cells are as follows: if the charging period of the intermediate battery cell is less than the minimum charging period among the charging periods of multiple battery cells, the intermediate battery cell is identified as an aged battery cell; if the charging period of the intermediate battery cell is greater than or equal to the minimum charging period among the charging periods of multiple battery cells, the intermediate battery cell is identified as the faulty battery cell. Based on the increase in the discharge energy change of at least one aged battery cell in multiple sampling cycles during the target sampling period, an aged faulty battery cell is identified from at least one aged battery cell. The target faulty battery cell is obtained based on at least one faulty battery cell and the aged faulty battery cell.

10. An early warning device for thermal runaway of batteries in an electrochemical energy storage power station, characterized in that, The device includes: The judgment module is used to determine the battery voltage change of multiple battery cells based on the discharge voltage of multiple battery cells in any battery cluster, and to perform fault trigger judgment on the multiple battery cells respectively based on the discharge current and battery voltage change of the multiple battery cells, so as to obtain multiple fault trigger results of the multiple battery cells. The battery voltage change represents the voltage change of the battery cell within one sampling period. The module is configured to, when the plurality of fault triggering results characterize at least one potential battery cell among a plurality of battery cells as having triggered a fault, obtain a target fault feature value of at least one potential battery cell based on the amount of discharge energy change of at least one potential battery cell during a target sampling period, wherein the target sampling period includes at least one sampling cycle. The first determining module is used to determine the fault of at least one potential battery cell based on an energy fault threshold and according to the target fault characteristic value of the at least one potential battery cell, and to determine at least one intermediate battery cell with abnormal operation from the at least one potential battery cell. The second determining module is used to classify at least one intermediate battery cell into faults and aging based on aging rules corresponding to multiple battery cells, and to determine the target faulty battery cell from at least one intermediate battery cell.

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