Method and equipment for querying abnormal state of battery cell in energy storage cabinet and storage medium

Abstract

The invention discloses a method and equipment for querying an abnormal state of a battery cell in an energy storage cabinet and a storage medium, and relates to the technical field of battery cell management. The method comprises the following steps: generating a local abnormal event message containing an abnormal source identifier based on a preset local abnormal triggering condition when monitoring that any battery cell monomer in the energy storage cabinet is abnormal; broadcasting the abnormal event message to other battery cell monomer nodes in the energy storage cabinet; based on a preset aggregation triggering strategy, aggregating the state information of each cell monomer node in the abnormal and associated monitoring state at a local network level; according to the received abnormal event message, the battery cell monomers in the associated monitoring state are judged by other battery cell monomer nodes according to the association relation topology between the battery cell monomers and the abnormal source; and uploading the aggregated state abstract to a query terminal through single transaction communication. The method aims to provide technical support for safe and efficient operation and maintenance of a large-scale energy storage system.

Description

Technical Field

[0001] This application belongs to the field of battery cell management technology, and in particular relates to a method, device and storage medium for querying abnormal status of battery cells in an energy storage cabinet. Background Technology

[0002] With the rapid expansion of electrochemical energy storage power stations, energy storage cabinets, consisting of hundreds to thousands of individual battery cells, have become the core energy storage unit. To ensure system safety and operational efficiency, real-time and efficient monitoring of the health status of each individual battery cell within the cabinet is crucial. However, current mainstream battery cell status monitoring architectures face severe challenges in dealing with sudden and concurrent anomalies, becoming a bottleneck restricting operational efficiency and system safety response. Summary of the Invention

[0003] In view of this, the embodiments of this application provide a method, device and storage medium for querying abnormal status of battery cells in energy storage cabinets, aiming to improve the timeliness of abnormal event perception in monitoring abnormal status of battery cells in energy storage cabinet scenarios, and to provide technical support for the safe and efficient operation and maintenance of large-scale energy storage systems.

[0004] This application provides a method for querying the abnormal status of battery cells in an energy storage cabinet, including: Based on preset local anomaly triggering conditions, when an anomaly is detected in any single cell in the energy storage cabinet, a local anomaly event message containing an anomaly source identifier is generated. The abnormal event message is broadcast to other individual battery cell nodes in the energy storage cabinet; Based on a preset aggregation triggering strategy, the status information of each battery cell node in the abnormal and associated monitoring states is aggregated at the local network level; the battery cell in the associated monitoring state is determined by other battery cell nodes according to the topology of their association with the abnormal source based on the received abnormal event message. The aggregated state summary is uploaded to the query terminal via a single transaction.

[0005] In one embodiment, the preset local exception triggering condition includes: Obtain the health score of a single battery cell calculated locally in real time, and trigger a mechanism when the health score is lower than a first threshold. Alternatively, based on the horizontal comparison results of parameters between adjacent individual cells, a trigger is triggered when the deviation of a cell's parameters from the average value of adjacent cells exceeds a second threshold, and its own health score is lower than a third threshold; wherein, the second threshold is dynamically adjusted according to the topological density of the cell cluster.

[0006] In one embodiment, determining whether to enter the associated monitoring state includes: The physical location identifier in the abnormal event message is analyzed, and several battery cells that are electrically or physically adjacent to the abnormal battery cell are identified as primary associated objects based on the preset topology map inside the energy storage cabinet. If the abnormality type of the abnormal cell belongs to the heat diffusion risk category, then the cell located in the same air duct or heat dissipation area as it will be listed as a secondary related object.

[0007] In one embodiment, the preset aggregation triggering strategy includes at least one of the following triggering conditions: the cumulative number of detected abnormal battery cells reaches a preset first quantity threshold; the elapsed time since the generation of the first abnormal event message reaches a preset aggregation time window threshold; or at least one triggering condition is received from an active broadcast query instruction initiated by a query terminal.

[0008] In one embodiment, when the aggregation triggering strategy is to receive an active broadcast query instruction initiated by a query terminal, the aggregation at the local network layer includes: The main control unit or each individual cell node in the energy storage cabinet synchronously receives the active broadcast query command. Filter out abnormal battery cell nodes and associated monitoring nodes whose current status meets the filtering conditions in the active broadcast query instruction as response nodes; Coordinate each responding cell node to report its status summary within the preset response time window, in accordance with the predetermined multiple access rules; At the local network level of the energy storage cabinet, multiple reported status summaries are integrated to form a unified aggregated status summary.

[0009] In one embodiment, the method further includes: Based on the properties of the abnormal battery cell, its position in the topology map of the cabinet, and the overall operating conditions of the current energy storage cabinet, the potential propagation path and impact range of the abnormal state are predicted. An adjustment strategy is generated based on the propagation path and the scope of influence, and then written into the aggregated state summary for reporting.

[0010] In one embodiment, broadcasting the abnormal event message to other individual cell nodes in the energy storage cabinet includes: The abnormal event message is sent to other individual cell nodes in the energy storage cabinet via local multicast or broadcast.

[0011] A second aspect of this application provides a device for querying the abnormal status of battery cells in an energy storage cabinet, comprising: The generation module is used to generate a local abnormal event message containing an abnormality source identifier when any abnormality is detected in any single cell in the energy storage cabinet, based on preset local abnormality triggering conditions. The broadcast module is used to broadcast the abnormal event message to other individual cell nodes in the energy storage cabinet; The aggregation module is used to aggregate the status information of each battery cell node in the abnormal and associated monitoring states at the local network level based on a preset aggregation trigger strategy; the battery cell in the associated monitoring state is determined by other battery cell nodes according to the topology of their association with the abnormal source based on the received abnormal event message. The upload module is used to upload the aggregated state summary to the query terminal through a single transaction communication.

[0012] In one embodiment, the preset local exception triggering condition includes: Obtain the health score of a single battery cell calculated locally in real time, and trigger a mechanism when the health score is lower than a first threshold. Alternatively, based on the horizontal comparison results of parameters between adjacent individual cells, a trigger is triggered when the deviation of a cell's parameters from the average value of adjacent cells exceeds a second threshold, and its own health score is lower than a third threshold; wherein, the second threshold is dynamically adjusted according to the topological density of the cell cluster.

[0013] In one embodiment, determining whether to enter the associated monitoring state includes: The physical location identifier in the abnormal event message is analyzed, and several battery cells that are electrically or physically adjacent to the abnormal battery cell are identified as primary associated objects based on the preset topology map inside the energy storage cabinet. If the abnormality type of the abnormal cell belongs to the heat diffusion risk category, then the cell located in the same air duct or heat dissipation area as it will be listed as a secondary related object.

[0014] In one embodiment, the preset aggregation triggering strategy includes at least one of the following triggering conditions: the cumulative number of detected abnormal battery cells reaches a preset first quantity threshold; the elapsed time since the generation of the first abnormal event message reaches a preset aggregation time window threshold; or at least one triggering condition is received from an active broadcast query instruction initiated by a query terminal.

[0015] In one embodiment, when the aggregation triggering strategy is to receive an active broadcast query instruction initiated by a query terminal, the aggregation module is specifically used for: The system controls each individual cell node to synchronously receive the active broadcast query command; it filters out abnormal individual cell nodes and associated monitoring nodes whose current status meets the filtering conditions in the active broadcast query command as response nodes; it coordinates each response individual cell node to report its own status summary within a preset response time window according to a predetermined multiple access rule; and it integrates the multiple reported status summaries at the local network level of the energy storage cabinet to form a unified aggregated status summary.

[0016] In one embodiment, the device further includes: The prediction module is used to predict the potential propagation path and impact range of the abnormal state based on the attributes of the abnormal cell, its position in the topology map of the cabinet, and the overall operating conditions of the current energy storage cabinet. The writing module is used to generate an adjustment strategy based on the propagation path and the scope of influence, and write it into the aggregated state summary for reporting.

[0017] In one embodiment, the broadcast module is specifically used for: The abnormal event message is sent to other individual cell nodes in the energy storage cabinet via local multicast or broadcast.

[0018] A third aspect of this application provides a device for querying abnormal cell status in an energy storage cabinet, characterized in that it includes: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, it implements the steps of the method described in the first aspect above.

[0019] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0020] The method for querying abnormal cell status in an energy storage cabinet provided in this application includes: generating a local abnormal event message containing an abnormal source identifier when any cell in the energy storage cabinet is detected to be abnormal, based on preset local abnormal triggering conditions; broadcasting the abnormal event message to other cell nodes in the energy storage cabinet; aggregating the status information of each cell node in abnormal and associated monitoring states at the local network layer based on a preset aggregation triggering strategy; determining the cell in the associated monitoring state by other cell nodes according to their own association topology with the abnormal source based on the received abnormal event message; and uploading the aggregated status summary to the query terminal through a single transaction communication. This method aims to improve the timeliness of abnormal event perception in the monitoring of abnormal cell status in energy storage cabinet scenarios, and to provide technical support for the safe and efficient operation and maintenance of large-scale energy storage systems. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a method for querying abnormal cell status in an energy storage cabinet according to an embodiment of this application; Figure 2 A flowchart illustrating a method for querying abnormal cell status in an energy storage cabinet according to an embodiment of this application; Figure 3 A schematic diagram of the structure of a battery cell abnormality query device provided in an embodiment of this application; Figure 4 A schematic diagram of a battery cell abnormality query device provided in an embodiment of this application. Detailed Implementation

[0023] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0025] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0027] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0028] In the description of the embodiments of this application, the term "multiple frames" refers to two or more (including two).

[0029] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0030] Please see Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for querying abnormal cell status within an energy storage cabinet, provided in one embodiment of this application. The method operates on the local monitoring network of the energy storage cabinet, which consists of individual cell monitoring units and communication links at the cabinet's main control unit level. Its purpose is to establish an efficient, low-latency, and self-organizing mechanism for detecting and reporting abnormal statuses.

[0031] Depend on Figure 1 As can be seen, the method for querying the abnormal status of battery cells in the energy storage cabinet in this application includes steps S110 to S140. Details are as follows: S110: Based on preset local anomaly triggering conditions, when an anomaly is detected in any single cell in the energy storage cabinet, a local anomaly event message containing the anomaly source identifier is generated.

[0032] This step is executed independently by each individual cell monitoring unit. The preset local anomaly triggering conditions are a set of pre-configured judgment rules within the monitoring unit, designed to quickly and accurately identify genuine anomalies from massive amounts of monitoring data. Specifically, this includes two complementary judgment logics: acquiring a real-time health score calculated locally for each individual cell, and triggering a trigger when the health score falls below a first threshold. Specifically, the monitoring unit calculates the health score in real-time based on parameters such as voltage, current, and temperature collected in real time, using a preset algorithm (e.g., state estimation based on an equivalent circuit model or a data-driven scoring model). This health score is a comprehensive quantification of the cell's internal state. A first threshold is set (e.g., a score below 80). When the health score falls below this first threshold, the cell is determined to be abnormal and immediately triggered. This triggering method is direct and fast, suitable for identifying significant degradation in the cell's performance. This can also be called independent health score triggering.

[0033] Alternatively, based on the horizontal comparison of parameters between adjacent individual cells, a trigger is established when the deviation of a cell's parameters from the average of its adjacent cells exceeds a second threshold, and its own health score is lower than a third threshold. The second threshold is dynamically adjusted according to the topological density of the cell cluster. Under this logic, the monitoring unit not only focuses on itself but also performs group consistency comparisons by exchanging key parameters (such as individual cell voltage and surface temperature) with adjacent cells (determined based on preset topological relationships). Specifically, a second threshold is set as the upper limit of the allowable deviation by calculating the deviation of its own parameters from the average of the parameters of adjacent cells. An anomaly is only identified and triggered when the deviation of its own parameters exceeds the second threshold, and its own health score is simultaneously lower than the third threshold (the third threshold can be equal to or slightly higher than the first threshold). This triggering method, also known as horizontal parameter comparison triggering, effectively identifies cells that exhibit abnormal behavior within the group but whose absolute parameters may not yet exceed limits, improving the detection rate of early anomalies such as consistency degradation. By incorporating absolute scoring, misjudgments caused by the failure of individual adjacent cells are avoided. For example, if a cell failure causes abnormal parameters, normal cells should not be falsely triggered due to large deviations from the average value. The second threshold is not a fixed value but is dynamically adjusted according to the topological density of the cell cluster. For example, for clusters with tight electrical series connection and high parameter consistency requirements, the second threshold is set smaller to improve sensitivity; for parallel or physically dispersed clusters, the threshold can be appropriately relaxed to reduce noise interference.

[0034] When any triggering condition is met, a structured local abnormal event message is generated. This message contains at least: a unique physical location identifier of the cell that generated the message (such as rack-box-module-serial number), a basic abnormality type (such as voltage abnormality, temperature abnormality, consistency abnormality), and a timestamp.

[0035] S120: Broadcast the abnormal event message to other individual cell nodes in the energy storage cabinet.

[0036] The cell monitoring unit that generates the message sends the abnormal event message to the communication network within the energy storage cabinet via its communication interface, using a link-layer method of local multicast or broadcast. This communication network can be based on a CAN bus, RS-485 bus, or low-power wireless mesh network, etc. Broadcast or multicast ensures that the message is received almost simultaneously by all other nodes within the cabinet within a very short time (typically within milliseconds), providing a unified information foundation for subsequent distributed collaborative processing.

[0037] S130: Based on a preset aggregation triggering strategy, the status information of each cell node in the abnormal and associated monitoring states is aggregated at the local network level; the cell in the associated monitoring state is determined by other cell nodes according to the topology of their association with the abnormal source based on the received abnormal event message.

[0038] Each non-abnormal source node (i.e., other individual cell nodes receiving status information) does not passively record the broadcast abnormal event message, but instead initiates a correlation self-check process. This process is based on a preset topology map of the energy storage cabinet stored locally on the node. This map defines the electrical connection relationships (such as series and parallel paths) and physical spatial relationships (such as installation location coordinates and module / cabinet affiliation) between cells.

[0039] Other individual cell nodes parse the anomaly source location identifier in the message and query the topology map to determine whether to enter the associated monitoring state. This includes: parsing the physical location identifier in the anomaly event message; based on the preset energy storage cabinet topology map, identifying several cell nodes that are electrically or physically adjacent to the abnormal cell node as primary associated objects and entering the associated monitoring state; if the anomaly type of the abnormal cell node belongs to the heat diffusion risk category, such as excessively high temperature or excessively rapid temperature rise, further querying the thermal management zoning information defined in the topology map, such as airflow direction and heat sink coverage, etc. If this cell node and the anomaly source cell node are in the same airflow or heat dissipation area, they are listed as secondary associated objects and also enter the associated monitoring state. Cell nodes that enter the associated monitoring state will increase their data collection frequency or accuracy and prepare to report their status during aggregation.

[0040] The preset aggregation triggering strategy determines when to initiate the process of collecting and integrating status information scattered across multiple nodes (abnormal source-related objects). Specifically, the preset aggregation triggering strategy includes: triggering when the cumulative number of detected abnormal battery cells reaches a preset first quantity threshold, for example, 3; automatically triggering if the time elapsed since the generation of the first abnormal event message reaches a preset aggregation time window threshold, for example, 5 seconds, and other triggering conditions are still not met; or triggering when an active broadcast query command initiated from a query terminal is received.

[0041] For example, determining whether to enter the associated monitoring state includes: when the aggregation triggering strategy is to receive an active broadcast query instruction initiated by the query terminal, the aggregation at the local network level includes: controlling each individual cell node to synchronously receive the active broadcast query instruction; filtering out abnormal individual cell nodes and associated monitoring nodes whose current status meets the filtering conditions in the active broadcast query instruction as response nodes; coordinating each response individual cell node to report its own status summary according to predetermined multiple access rules within a preset response time window; and integrating the reported multiple status summaries at the local network level of the energy storage cabinet to form a unified aggregated status summary.

[0042] This aggregated state summary clearly lists all anomaly sources and their key parameters, as well as the status of each associated object, forming a panoramic view of the anomaly events.

[0043] S140: Upload the aggregated state summary to the query terminal via a single transaction communication.

[0044] The main control unit inside the cabinet encapsulates the generated unified aggregated state summary into a complete data packet and sends it to the query terminal, such as the handheld device of the maintenance personnel or the central monitoring room, through a single communication transaction (e.g., a TCP packet or a LoRaWAN uplink frame). Compared with the traditional method that requires multiple interactions and batch uploads of large amounts of data, this greatly reduces the number of communications, lowers network latency and power consumption, and enables maintenance personnel to obtain a complete snapshot of anomalies within the energy storage cabinet in near real-time (second-level). Specifically, broadcasting the anomaly event message to other individual cell nodes in the energy storage cabinet includes: sending the anomaly event message to other individual cell nodes in the energy storage cabinet via local multicast or broadcast.

[0045] As can be seen from the above analysis, the method for querying abnormal cell status in an energy storage cabinet provided in this application includes: generating a local abnormal event message containing an abnormal source identifier when any cell in the energy storage cabinet is detected to be abnormal based on preset local abnormal triggering conditions; broadcasting the abnormal event message to other cell nodes in the energy storage cabinet; aggregating the status information of each cell node in abnormal and associated monitoring states at the local network layer based on a preset aggregation triggering strategy; determining the cell in the associated monitoring state by other cell nodes according to their own association topology with the abnormal source based on the received abnormal event message; and uploading the aggregated status summary to the query terminal through a single transaction communication. This method aims to improve the timeliness of abnormal event perception in the monitoring of abnormal cell status in energy storage cabinet scenarios, and to provide technical support for the safe and efficient operation and maintenance of large-scale energy storage systems.

[0046] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for querying abnormal cell status within an energy storage cabinet, provided as another embodiment of this application. Figure 2 It can be seen that this embodiment is similar to... Figure 1 Compared to the illustrated embodiment, S210 to S240 are implemented in the same way as S110 to S140, except that S250 to S260 are included after S240. S250 and S240 are executed in parallel. Details are as follows: S210: Based on preset local anomaly triggering conditions, when an anomaly is detected in any single cell in the energy storage cabinet, a local anomaly event message containing an anomaly source identifier is generated.

[0047] S220: Broadcast the abnormal event message to other individual cell nodes in the energy storage cabinet.

[0048] S230: Based on a preset aggregation triggering strategy, the status information of each cell node in the abnormal and associated monitoring states is aggregated at the local network level; the cell in the associated monitoring state is determined by other cell nodes according to the received abnormal event message and their own association topology with the abnormal source.

[0049] S240: Upload the aggregated state summary to the query terminal via a single transaction communication.

[0050] S250: Based on the properties of the abnormal battery cell, its position in the topology map of the cabinet, and the overall operating conditions of the current energy storage cabinet, predict the potential propagation path and impact range of the abnormal state.

[0051] Specifically, the attributes of the abnormal individual battery cell are obtained from the generated abnormal event messages and subsequent high-precision data acquisition, including the type of abnormality (such as sudden increase in internal resistance, sudden drop in voltage, and abnormal temperature), the degree of abnormality (such as the specific value exceeding the threshold), and the battery cell chemical system (obtained from the first type of state information). The cabinet topology map is the aforementioned topology map, which clearly provides the electrical connection matrix (reflecting the series and parallel relationships and connection impedances between each battery cell) and the physical spatial relationships (three-dimensional coordinates, airflow layout, and heat sink coverage).

[0052] The current overall operating conditions include, but are not limited to: the current total output / input power of the energy storage cabinet, ambient temperature, cooling system operating status (such as fan speed and water pump flow), and current of each branch.

[0053] By employing a multiphysics-coupled prediction model, the potential propagation path and impact range of the abnormal state are predicted. Predicting these paths and ranges allows for the identification of potential fault chains in the early stages of an anomaly, providing a crucial early warning window and decision-making basis for preventing cascading failures, such as fires triggered by thermal runaway of a single battery cell affecting the module or even the entire cabinet.

[0054] S260: Generate an adjustment strategy based on the propagation path and the scope of influence, and write it into the aggregated state summary for reporting.

[0055] Based on the predicted propagation path (electrical path / thermal diffusion path) and the scope of impact (a list of affected battery cells and their predicted risk levels), the system automatically generates corresponding proactive intervention and adjustment strategies. Strategy generation follows a pre-defined expert rule base. For example, regarding electrical propagation risk, if an imbalance in branch current is predicted, the strategy suggests: "Limit the current in the affected branches and adjust the maximum output current."

[0056] If a voltage over-limit risk is predicted, the strategy recommendation is: "Adjust the charge / discharge cutoff voltage of the battery management system and actively balance the relevant modules." Regarding heat propagation risks, if a rapid localized temperature rise is predicted, the strategy recommendation is: "Initiate targeted enhanced cooling and increase the power of the XX air duct fan to 100%" or "Implement reduced power operation for cells in the risk area." If a large impact area and high risk are predicted, the strategy recommendation is: "Manual inspection and examination of the mechanical connections and thermal interface materials of cells surrounding the anomaly source are recommended." For complex risks: the strategy may include integrated instructions for "electrical isolation and thermal management linkage."

[0057] The generated adjustment strategy, a set of structured suggestion instructions or parameters, and the prediction results, including propagation path, impact range map, risk timeline, etc., are encapsulated together to form an advanced early warning information package.

[0058] This advanced warning information packet is appended as a separate data segment to the aggregated status summary generated in the S230-S240 process. Alternatively, in one implementation, due to its high priority, it can be reported first through a separate alarm channel (such as SMS or a dedicated high-priority communication link) to ensure that critical warnings are not delayed.

[0059] The final report sent to the query terminal includes not only basic aggregated summaries such as which battery cells are currently problematic, but also advanced early warning information such as which battery cells may be affected in the future, and recommended measures to prevent or mitigate the impact. This transforms operational decision-making from emergency response to preventative intervention.

[0060] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0061] Please see Figure 3 , Figure 3 This is a schematic diagram of a battery cell abnormality query device provided in an embodiment of this application. The battery cell abnormality query device in the energy storage cabinet includes modules or units for performing... Figure 1 or Figure 2 The steps in the corresponding embodiments. Please refer to the details. Figure 1 or Figure 2 The relevant descriptions in the corresponding embodiments are shown below. For ease of explanation, only the parts relevant to this embodiment are shown. See also... Figure 3 The energy storage cabinet cell abnormality status query device 300 includes: The generation module 310 is used to generate a local abnormal event message containing an abnormality source identifier when any abnormality is detected in any single cell in the energy storage cabinet, based on preset local abnormality triggering conditions. Broadcast module 320 is used to broadcast the abnormal event message to other individual cell nodes in the energy storage cabinet; The aggregation module 330 is used to aggregate the status information of each cell node in the abnormal and associated monitoring states at the local network level based on a preset aggregation trigger strategy; the cell in the associated monitoring state is determined by other cell nodes according to the topology of their own association with the abnormal source based on the received abnormal event message. Upload module 340 is used to upload the aggregated state summary to the query terminal through a single transaction communication.

[0062] In one embodiment, the preset local exception triggering condition includes: Obtain the health score of a single battery cell calculated locally in real time, and trigger a mechanism when the health score is lower than a first threshold. Alternatively, based on the horizontal comparison results of parameters between adjacent individual cells, a trigger is triggered when the deviation of a cell's parameters from the average value of adjacent cells exceeds a second threshold, and its own health score is lower than a third threshold; wherein, the second threshold is dynamically adjusted according to the topological density of the cell cluster.

[0063] In one embodiment, determining whether to enter the associated monitoring state includes: The physical location identifier in the abnormal event message is analyzed, and several battery cells that are electrically or physically adjacent to the abnormal battery cell are identified as primary associated objects based on the preset topology map inside the energy storage cabinet. If the abnormality type of the abnormal cell belongs to the heat diffusion risk category, then the cell located in the same air duct or heat dissipation area as it will be listed as a secondary related object.

[0064] In one embodiment, the preset aggregation triggering strategy includes at least one of the following triggering conditions: the cumulative number of detected abnormal battery cells reaches a preset first quantity threshold; the elapsed time since the generation of the first abnormal event message reaches a preset aggregation time window threshold; or at least one triggering condition is received from an active broadcast query instruction initiated by a query terminal.

[0065] In one embodiment, when the aggregation triggering strategy is to receive an active broadcast query instruction initiated by the query terminal, the aggregation module 330 is specifically used for: The system controls each individual cell node to synchronously receive the active broadcast query command; it filters out abnormal individual cell nodes and associated monitoring nodes whose current status meets the filtering conditions in the active broadcast query command as response nodes; it coordinates each response individual cell node to report its own status summary within a preset response time window according to a predetermined multiple access rule; and it integrates the multiple reported status summaries at the local network level of the energy storage cabinet to form a unified aggregated status summary.

[0066] In one embodiment, the device 300 further includes: The prediction module is used to predict the potential propagation path and impact range of the abnormal state based on the attributes of the abnormal cell, its position in the topology map of the cabinet, and the overall operating conditions of the current energy storage cabinet. The writing module is used to generate an adjustment strategy based on the propagation path and the scope of influence, and write it into the aggregated state summary for reporting.

[0067] In one embodiment, the broadcast module 320 is specifically used for: The abnormal event message is sent to other individual cell nodes in the energy storage cabinet via local multicast or broadcast.

[0068] Please see Figure 4 , Figure 4 This is a schematic diagram of a battery cell abnormality query device provided in an embodiment of this application. Figure 4 It is understood that the energy storage cabinet cell abnormality status query device 400 includes: a processor 410, a memory 420, and a computer program 430 stored in the memory 420 and executable on the processor 410; when the processor 410 executes the computer program 430, it implements the steps in the above-mentioned embodiments of the energy storage cabinet cell abnormality status query method, for example... Figure 1 The steps S110 to S140 are shown. Alternatively, when the processor 410 executes the computer program 430, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of modules 310 to 340 are shown.

[0069] For example, the computer program 430 may be divided into one or more modules / units, one or more of which are stored in the memory 420 and executed by the processor 410 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 430 in the cell abnormality query device in the energy storage cabinet.

[0070] The energy storage cabinet cell abnormality status query device 400 provided in this embodiment may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that... Figure 4 This is merely an example of the cell abnormality query device 400 in the energy storage cabinet, and does not constitute a limitation on the cell abnormality query device 400 in the energy storage cabinet. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the cell abnormality query device 400 in the energy storage cabinet may also include input / output devices, network access devices, buses, etc.

[0071] The processor 410 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0072] The memory 420 can be an internal storage unit of the energy storage cabinet cell anomaly status query device 400, such as a hard drive or memory of the energy storage cabinet cell anomaly status query device 400. The memory 420 can also be an external storage device of the energy storage cabinet cell anomaly status query device 400, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the energy storage cabinet cell anomaly status query device 400. Furthermore, the energy storage cabinet cell anomaly status query device 400 can include both internal storage units and external storage devices. The memory 420 is used to store computer programs and other programs and data required by the energy storage cabinet cell anomaly status query device 400. The memory 420 can also be used to temporarily store data that has been output or will be output.

[0073] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0074] This application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above method embodiments.

[0075] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0076] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0077] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0079] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0080] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for querying abnormal cell status in an energy storage cabinet, characterized in that, The method includes: Based on preset local anomaly triggering conditions, when an anomaly is detected in any single cell in the energy storage cabinet, a local anomaly event message containing an anomaly source identifier is generated. The abnormal event message is broadcast to other individual battery cell nodes in the energy storage cabinet; Based on a preset aggregation triggering strategy, the status information of each battery cell node in the abnormal and associated monitoring states is aggregated at the local network level; the battery cell in the associated monitoring state is determined by other battery cell nodes according to the topology of their association with the abnormal source based on the received abnormal event message. The aggregated state summary is uploaded to the query terminal via a single transaction.

2. The method according to claim 1, characterized in that, The preset local exception triggering conditions include: Obtain the health score of a single battery cell calculated locally in real time, and trigger a mechanism when the health score is lower than a first threshold. Alternatively, based on the horizontal comparison results of parameters between adjacent individual cells, a trigger is triggered when the deviation of a cell's parameters from the average value of adjacent cells exceeds a second threshold, and its own health score is lower than a third threshold; wherein, the second threshold is dynamically adjusted according to the topological density of the cell cluster.

3. The method according to claim 1, characterized in that, The determination of whether to enter the associated monitoring state includes: The physical location identifier in the abnormal event message is analyzed, and several battery cells that are electrically or physically adjacent to the abnormal battery cell are identified as primary associated objects based on the preset topology map inside the energy storage cabinet. If the abnormality type of the abnormal battery cell belongs to the heat diffusion risk category, then the battery cell located in the same air duct or heat dissipation area as it will be listed as a secondary related object.

4. The method according to claim 1, characterized in that, The preset aggregation triggering strategy includes at least one of the following triggering conditions: the cumulative number of abnormal battery cells detected reaches a preset first quantity threshold; the time elapsed since the generation of the first abnormal event message reaches a preset aggregation time window threshold; or at least one triggering condition is received from an active broadcast query instruction initiated by a query terminal.

5. The method according to claim 4, characterized in that, When the aggregation triggering strategy is to receive an active broadcast query instruction initiated by the query terminal, the aggregation at the local network layer includes: Control each individual cell node to synchronously receive the active broadcast query command; Filter out abnormal battery cell nodes and associated monitoring nodes whose current status meets the filtering conditions in the active broadcast query instruction as response nodes; Coordinate each responding cell node to report its status summary within the preset response time window, in accordance with the predetermined multiple access rules; At the local network level of the energy storage cabinet, multiple reported status summaries are integrated to form a unified aggregated status summary.

6. The method according to claim 3, characterized in that, The method further includes: Based on the properties of the abnormal battery cell, its position in the topology map of the cabinet, and the overall operating conditions of the current energy storage cabinet, the potential propagation path and impact range of the abnormal state are predicted. An adjustment strategy is generated based on the propagation path and the scope of influence, and then written into the aggregated state summary for reporting.

7. The method according to claim 1, characterized in that, The step of broadcasting the abnormal event message to other individual cell nodes in the energy storage cabinet includes: The abnormal event message is sent to other individual cell nodes in the energy storage cabinet via local multicast or broadcast.

8. A device for querying abnormal cell status in an energy storage cabinet, characterized in that, include: The generation module is used to generate a local abnormal event message containing an abnormality source identifier when any abnormality is detected in any single cell in the energy storage cabinet, based on preset local abnormality triggering conditions. The broadcast module is used to broadcast the abnormal event message to other individual cell nodes in the energy storage cabinet; The aggregation module is used to aggregate the status information of each individual cell node that is in an abnormal or associated monitoring state at the local network level based on a preset aggregation trigger strategy. The associated monitoring status is determined by other individual cell nodes based on the received abnormal event messages and their respective association topology with the abnormal source. The upload module is used to upload the aggregated state summary to the query terminal through a single transaction communication.

9. A device for querying abnormal cell status in an energy storage cabinet, characterized in that, include: Processor, memory, and computer programs stored in said memory and executable on said processor; When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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