A battery life cycle management method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application disclose a battery life cycle management method and device, electronic equipment and storage medium. Embodiments of the present application include: obtaining original battery data corresponding to a battery to be managed; standardizing the original battery data to obtain standardized battery data corresponding to the battery to be managed; performing twice capacity grading on the battery to be managed according to the standardized battery data to obtain a battery cluster formed after twice capacity grading of the battery to be managed; performing clustering processing on the battery cluster to obtain a battery stack after clustering processing; configuring an energy storage system through the battery stack after clustering processing to obtain battery operation parameters; and identifying a faulty battery according to the battery operation parameters based on a fault diagnosis model. The present application not only reduces the bias current between the battery clusters, but also reduces the cost, shortens the project debugging period, improves the battery utilization rate and the safety of battery operation, and reduces the battery scrap rate.

Description

Technical Field

[0001] This application relates to the field of battery management technology, specifically to a battery lifecycle management method, device, electronic device, and storage medium. Background Technology

[0002] As one of the core components of various energy storage systems, batteries have always been the main source of system cost and the most valuable component. For example, in recent years, with technological advancements and large-scale development, the safety of electric vehicle power batteries, as an important part of vehicle safety, has been a major concern. In addition, the energy storage characteristics of batteries themselves may open up new business models, making the full life cycle management of power batteries of great significance.

[0003] However, the current full lifecycle management of batteries still relies on manual analysis by personnel on-site. This analysis is used to match battery cells to adapt to different energy storage systems. As the proportion of energy storage systems increases, the time and complexity of the analysis gradually increase, making it difficult to trace the origin of battery cell assembly. Furthermore, due to the lack of professional guidance on battery operation and maintenance after commissioning, it is impossible to accurately understand the battery degradation trend. At the same time, battery replacement and repair are not tracked, making it impossible to reflect the value at the end of the battery's lifecycle in a timely manner. Data lag means that data cannot be updated in real time and the operational status cannot be analyzed, making it impossible to accurately determine whether the battery product has a quality problem or a usage problem, hindering rapid decision-making and increasing time and economic costs. Summary of the Invention

[0004] In view of the above problems, this specification is proposed to provide a battery life cycle management method, apparatus, electronic device and storage medium that overcomes or at least partially solves the above problems.

[0005] Other features and advantages disclosed herein will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0006] In a first aspect, embodiments of this application provide a battery lifecycle management method, comprising: acquiring original cell data corresponding to a cell to be managed; standardizing the original cell data to obtain standardized cell data corresponding to the cell to be managed; performing two capacity grading processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity grading processes; clustering the battery cluster to obtain a clustered battery stack; configuring an energy storage system using the clustered battery stack to obtain battery operating parameters; and identifying faulty batteries based on a fault diagnosis model according to the battery operating parameters to complete battery lifecycle management.

[0007] In some embodiments, the raw cell data is standardized to obtain standardized cell data corresponding to the cells to be managed, including: obtaining the activation terminal voltage and process flow number of the cells to be managed from the raw cell data; performing preliminary classification of the cells to be managed based on the activation terminal voltage and process flow number to obtain several original battery pack groups, each original battery pack group including several cells; calculating the standard deviation and mean of the activation terminal voltage of any one of the original battery pack groups; obtaining the activation terminal voltage of any cell in any one of the original battery pack groups; subtracting the mean of the activation terminal voltage from the activation terminal voltage of any cell to obtain a first parameter; and using the ratio between the first parameter and the standard deviation of the activation terminal voltage as the standardized cell data corresponding to any cell.

[0008] In some embodiments, the battery cells to be managed are subjected to two capacity grading processes based on standardized cell data to obtain a battery cluster composed of the battery cells to be managed after the two capacity grading processes. This includes: performing charge and discharge tests on each cell in the original battery pack under the same environment to output the calibrated capacity and initial capacity; performing a first capacity grading process on each cell in the original battery pack based on the calibrated capacity and initial capacity to obtain a battery pack after the first capacity grading process; and performing a second capacity grading process on the battery pack after the first capacity grading process to obtain a battery cluster after the second capacity grading process.

[0009] In some embodiments, a second capacity grading is performed on the battery pack after the first capacity grading to obtain a battery cluster after the second capacity grading, including: performing charge and discharge tests on the battery pack after the first capacity grading under the same environment to output the dynamic voltage range and the static terminal voltage; and performing a second capacity grading on the battery pack after the first capacity grading based on the dynamic voltage range and the static terminal voltage to obtain a plurality of battery clusters after the second capacity grading.

[0010] In some embodiments, clustering battery clusters to obtain a clustered battery stack includes: acquiring capacity data corresponding to each of the several battery clusters; calculating the correlation coefficient between the several battery clusters based on the capacity data corresponding to each of the several battery clusters; and clustering the several battery clusters according to the correlation coefficient to obtain a clustered battery stack.

[0011] In some embodiments, the battery lifecycle management method further includes: creating a raw material warehouse and a traceability warehouse; synchronizing the original cell data corresponding to the cells to be managed to the raw material warehouse; numbering the battery pack after one capacity grading, and synchronizing the battery pack number and the initial capacity of the individual cells to the raw material warehouse; numbering the battery clusters, and synchronizing the battery cluster number and the capacity grading data of the battery clusters to the traceability warehouse; and numbering the battery stacks, and synchronizing the battery stack number to the traceability warehouse.

[0012] In some embodiments, based on a fault diagnosis model, faulty batteries are identified according to battery operating parameters to complete battery lifecycle management. This also includes: when a faulty battery needs to be replaced, matching the faulty battery with a replaceable battery from the raw material warehouse and traceability warehouse, and replacing the faulty battery with the replaceable battery; when a faulty battery needs to be repaired, repairing the faulty battery and storing the repaired faulty battery in a battery cascade utilization warehouse; when a faulty battery needs to be scrapped, disassembling the faulty battery and recovering carbon, determining the battery degradation factors corresponding to the faulty battery, and obtaining a disassembly report to optimize the production process.

[0013] Secondly, embodiments of this application provide a battery lifecycle management device, comprising: a data acquisition module for acquiring original cell data corresponding to a cell to be managed; a standardization processing module for standardizing the original cell data to obtain standardized cell data corresponding to the cell to be managed; a capacity grading processing module for performing two capacity grading processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity grading processes; a clustering module for performing clustering processing on the battery cluster to obtain a clustered battery stack; a battery configuration module for configuring an energy storage system through the clustered battery stack to obtain battery operating parameters; and a fault identification module for identifying faulty batteries based on a fault diagnosis model and the battery operating parameters to complete battery lifecycle management.

[0014] Thirdly, embodiments of this application provide an electronic device, including a memory storing multiple instructions; a processor loads instructions from the memory to execute steps in any of the battery lifecycle management methods provided in embodiments of this application.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing multiple instructions adapted for loading by a processor to execute steps in any of the battery lifecycle management methods provided in embodiments of this application.

[0016] This application embodiment first obtains the original cell data corresponding to the cell to be managed; then, it standardizes the original cell data to obtain standardized cell data corresponding to the cell to be managed; then, it performs two capacity sizing processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity sizing processes; next, it performs clustering processing on the battery cluster to obtain a clustered battery stack; then, it configures the energy storage system through the clustered battery stack to obtain battery operating parameters; finally, based on the fault diagnosis model, it identifies faulty batteries according to the battery operating parameters to complete battery life cycle management.

[0017] This invention not only improves the aggregation degree of battery capacity classification to enhance the consistency of individual cells within a battery cluster, but also enables full lifecycle traceability of the battery, providing data support for production processes and integrated design, and accurately determining the residual value of the battery pack after its retirement from energy storage. Furthermore, this invention not only alleviates current imbalances between battery clusters but also reduces personnel and time costs, shortens project commissioning cycles, accurately understands battery degradation, and thus distinguishes between quality and usage issues. It further provides professional maintenance methods for battery operation and maintenance after commissioning, ensuring an orderly process throughout the entire battery lifecycle, from production and operation to maintenance and recycling. This invention not only improves battery utilization but also enhances operational safety while reducing the scrap rate. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0019] Figure 1 This is a schematic diagram of a scenario for the battery lifecycle management method provided in an embodiment of this application; Figure 2a This is a flowchart illustrating the battery lifecycle management method provided in an embodiment of this application; Figure 2b This is a flowchart illustrating different measures for managing and processing batteries, provided in an embodiment of this application. Figure 3 This is a schematic diagram of the battery lifecycle management device provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] This application provides a battery lifecycle management method, apparatus, electronic device, and storage medium.

[0022] Specifically, the battery lifecycle management device can be integrated into an electronic device, such as a terminal or server. The terminal can be a mobile phone, tablet, smart Bluetooth device, laptop, or personal computer (PC); the server can be a single server or a server cluster consisting of multiple servers.

[0023] In some embodiments, the battery lifecycle management device can also be integrated into multiple electronic devices. For example, the battery lifecycle management device can be integrated into multiple servers, and the battery lifecycle management method of this application can be implemented by multiple servers.

[0024] In some embodiments, the server may also be implemented as a terminal.

[0025] For example, refer to Figure 1 This is a schematic diagram of a scenario for the battery lifecycle management method provided in the embodiments of this application. It may include a server 100, a storage terminal 110, an energy storage system 120, a raw material warehouse 130, a traceability warehouse 140, a battery cascade utilization warehouse 150, etc. The server 100, the storage terminal 110, and the energy storage system 120 can communicate and connect with each other, which will not be described in detail here.

[0026] Server 100 can first obtain the original cell data corresponding to the cell to be managed; then, it can standardize the original cell data to obtain standardized cell data corresponding to the cell to be managed; next, it can perform two capacity-sharing processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity-sharing processes; then, it can perform clustering processing on the battery cluster to obtain a clustered battery stack; then, it can configure the energy storage system through the clustered battery stack to obtain battery operating parameters; finally, based on the fault diagnosis model, it can identify faulty batteries according to the battery operating parameters to complete battery life cycle management, etc. Storage terminal 110 can store the original cell data corresponding to the cell to be managed, etc.

[0027] The energy storage system 120 can be a power battery for electric vehicles, or an energy storage battery for various types of power stations. The raw material warehouse 130 can be used to synchronize the original cell data corresponding to the cells under management, the battery pack number after one capacity allocation, and the initial capacity of a single cell; it can also store different types of cells. The traceability warehouse 140 can be used to synchronize battery cluster numbers, battery cluster capacity allocation data, battery stack numbers, etc.; it can also store different types of battery clusters and battery stacks. The battery cascade utilization warehouse 150 can be used to store repaired faulty batteries.

[0028] The following sections provide detailed descriptions of each example. It should be noted that the sequence numbers of the following embodiments are not intended to limit the preferred order of the embodiments.

[0029] In this embodiment, a battery lifecycle management method is provided, such as... Figure 2a As shown, when applied to a server, the specific process of this battery lifecycle management method can be as follows: 200. Obtain the original cell data corresponding to the cell to be managed.

[0030] In this embodiment, the battery cell to be managed can be a battery cell that has just been produced from the production line. The original battery cell data of the battery cell to be managed may include production data and process data. Production data includes, but is not limited to, production line number and production date; process data includes, but is not limited to, process number, battery cell number, and initial terminal voltage.

[0031] This application embodiment can print (e.g., QR code) on the casing of the battery cell and automatically record production information and process information: production line number, process number, battery cell code, production date, initial (activation) terminal voltage, etc.

[0032] 210. Standardize the original cell data to obtain standardized cell data corresponding to the cells to be managed.

[0033] In some embodiments, the raw cell data is standardized to obtain standardized cell data corresponding to the cells to be managed, including: obtaining the activation terminal voltage and process flow number of the cells to be managed from the raw cell data; performing preliminary classification of the cells to be managed based on the activation terminal voltage and process flow number to obtain several original battery pack groups, each original battery pack group including several cells; calculating the standard deviation and mean of the activation terminal voltage of any one of the original battery pack groups; obtaining the activation terminal voltage of any cell in any one of the original battery pack groups; subtracting the mean of the activation terminal voltage from the activation terminal voltage of any cell to obtain a first parameter; and using the ratio between the first parameter and the standard deviation of the activation terminal voltage as the standardized cell data corresponding to any cell.

[0034] In this embodiment, the activation voltage is the initial voltage of the battery cell, which refers to the voltage of the battery cell when it leaves the factory. Different types of battery cells have different initial voltages.

[0035] This application embodiment can store the sprayed battery cells and their data in a raw material warehouse, and perform preliminary classification based on activation terminal voltage and process flow number to form initial battery pack groups. The standard deviation and mean of the activation terminal voltage for any given initial battery pack group are calculated. Using these values, each cell in any initial battery pack group is standardized to obtain standardized cell data for any given cell. This standardization process improves the consistency of the individual cells within the battery pack.

[0036] 220. Based on the standardized cell data, the cells to be managed are subjected to two capacity grading processes to obtain the battery cluster formed by the cells to be managed after the two capacity grading processes.

[0037] In some embodiments, the battery cells to be managed are subjected to two capacity grading processes based on standardized cell data to obtain a battery cluster composed of the battery cells to be managed after the two capacity grading processes. This includes: performing charge and discharge tests on each cell in the original battery pack under the same environment to output the calibrated capacity and initial capacity; performing a first capacity grading process on each cell in the original battery pack based on the calibrated capacity and initial capacity to obtain a battery pack after the first capacity grading process; and performing a second capacity grading process on the battery pack after the first capacity grading process to obtain a battery cluster after the second capacity grading process.

[0038] In this embodiment, after a batch of battery cells are manufactured, although they are the same size, their capacities may differ. The capacity grading process in this embodiment involves testing each cell under the same charging and discharging conditions to detect its capacity, outputting a calibrated capacity and the initial capacity of each cell, and then selecting qualified cells based on the calibrated capacity and the initial capacity of each cell to assemble a battery pack.

[0039] In some embodiments, a second capacity grading is performed on the battery pack after the first capacity grading to obtain a battery cluster after the second capacity grading, including: performing charge and discharge tests on the battery pack after the first capacity grading under the same environment to output the dynamic voltage range and the static terminal voltage; and performing a second capacity grading on the battery pack after the first capacity grading based on the dynamic voltage range and the static terminal voltage to obtain a plurality of battery clusters after the second capacity grading.

[0040] In this embodiment, after the first capacity grading, several battery packs are obtained, and the terminal voltages of different battery packs are also different. The second capacity grading process in this embodiment involves performing charge and discharge tests on the battery packs after the first capacity grading under the same environment, outputting the dynamic voltage range and static terminal voltage, and then selecting qualified battery packs based on the dynamic voltage range and static terminal voltage to form battery clusters.

[0041] The capacity matching process in this application involves two capacity matching steps. The first step involves conducting charge-discharge tests on each cell in the original battery pack under the same environment to output the calibrated capacity and initial capacity. Then, based on the calibrated capacity and initial capacity, the cells in the original battery pack are subjected to a second capacity matching process to obtain a battery pack with the first capacity matching. The second step involves conducting charge-discharge tests on the battery pack with the first capacity matching process under the same environment to output the dynamic voltage range and static terminal voltage. Then, based on the dynamic voltage range and static terminal voltage, the battery pack with the first capacity matching process is subjected to a second capacity matching process to obtain several battery clusters with the second capacity matching.

[0042] This application embodiment can perform charge-discharge tests on the standardized original battery pack under the same environment, outputting the calibrated capacity and initial capacity. The batch is then subjected to a first capacity grading to form a PACK (battery pack), which is then numbered, and the battery pack number and initial capacity of each cell are stored in the raw material warehouse. Next, the battery packs formed in the first capacity grading are charged and discharged under the same environment, outputting the dynamic voltage range and static terminal voltage. A second capacity grading is then performed to form battery clusters, which are then numbered, and the battery cluster numbers are synchronized to the traceability warehouse.

[0043] In this embodiment, the dynamic voltage range of the battery pack is the difference between the maximum and minimum voltage values ​​at a certain moment during use. The static terminal voltage of the battery pack is the terminal voltage measured after the battery pack is fully charged, the terminals are disconnected, and the pack is left for a preset period of time.

[0044] 230. Perform clustering on the battery clusters to obtain the clustered battery stacks.

[0045] In some embodiments, clustering battery clusters to obtain a clustered battery stack includes: acquiring capacity data corresponding to each of the several battery clusters; calculating the correlation coefficient between the several battery clusters based on the capacity data corresponding to each of the several battery clusters; and clustering the several battery clusters according to the correlation coefficient to obtain a clustered battery stack.

[0046] In this embodiment, the capacity rating data corresponding to the battery cluster may include dynamic voltage range and static terminal voltage. The dynamic voltage range corresponding to the battery cluster is the difference between the maximum and minimum voltage values ​​at a certain moment during the use of the battery cluster. The static terminal voltage corresponding to the battery cluster is the terminal voltage measured after the battery cluster is fully charged, the terminals are disconnected, and the cluster is left for a preset period of time.

[0047] In this embodiment, battery cells are paired to form three levels: battery pack, battery cluster, and battery stack. These three levels are then randomly combined to adapt to energy storage systems in different scenarios. When forming the battery stack level, a clustering algorithm can be used to cluster the battery clusters, resulting in a clustered battery stack.

[0048] In this embodiment, the capacity data obtained from two capacity divisions are clustered to obtain the correlation coefficients corresponding to different data groups. The greater the distance, the less similar the two data groups are. The cluster numbers are divided by the correlation coefficients to form battery stacks and the battery stack numbers are associated with the traceability warehouse.

[0049] 240. Configure the energy storage system by clustering the battery stacks to obtain battery operating parameters.

[0050] In this embodiment, the energy storage system can be configured using clustered battery stacks. Specifically, it can be adapted to different scenarios through random combinations of three levels: battery packs, battery clusters, and battery stacks. This application configures different battery levels according to the type of energy storage system and then acquires battery operating parameters in real time during the operation of the energy storage system.

[0051] In this embodiment, the energy storage system can consist of several battery packs, several battery clusters, and several battery stacks. Each battery cluster includes several battery packs, and a battery management system can be installed within each battery pack. The battery management system manages the charging and discharging protection of the battery pack. When fully charged, it ensures that the voltage difference between individual cells is less than a set value, achieving equal charging of all individual cells in the battery pack and effectively improving the charging effect under series charging. Simultaneously, it detects the overvoltage, undervoltage, overcurrent, short circuit, and overtemperature conditions of each individual cell in the battery pack, protecting and extending battery life. This embodiment can adopt a three-level architecture, with one control unit each for the battery pack, battery cluster, and battery stack.

[0052] 250. Based on the fault diagnosis model, identify faulty batteries according to battery operating parameters to complete battery life cycle management.

[0053] In this embodiment, the battery operating parameters are first input into the fault diagnosis model. The fault diagnosis model can be set with different threshold parameters. The fault diagnosis model compares and analyzes the battery operating parameters with different threshold parameters, outputs the fault type corresponding to the faulty battery, and then performs corresponding management measures on the faulty battery according to the fault type.

[0054] In this application embodiment, the fault types may include, but are not limited to: low single-cell SOC (State of Charge) consistency, high single-cell SOC consistency, large self-discharge, insufficient capacity, poor electrical connection, etc. Then, in some embodiments, the battery lifecycle management method further includes: creating a raw material warehouse and a traceability warehouse; synchronizing the original cell data corresponding to the cells to be managed to the raw material warehouse; numbering the battery pack after one capacity grading, and synchronizing the battery pack number and the initial capacity of each cell to the raw material warehouse; numbering the battery clusters, and synchronizing the battery cluster number and the capacity grading data of the battery clusters to the traceability warehouse; numbering the battery stacks, and synchronizing the battery stack number to the traceability warehouse.

[0055] In some embodiments, based on a fault diagnosis model, faulty batteries are identified according to battery operating parameters to complete battery lifecycle management. This also includes: when a faulty battery needs to be replaced, matching the faulty battery with a replaceable battery from the raw material warehouse and traceability warehouse, and replacing the faulty battery with the replaceable battery; when a faulty battery needs to be repaired, repairing the faulty battery and storing the repaired faulty battery in a battery cascade utilization warehouse; when a faulty battery needs to be scrapped, disassembling the faulty battery and recovering carbon, determining the battery degradation factors corresponding to the faulty battery, and obtaining a disassembly report to optimize the production process.

[0056] This application embodiment identifies battery faults in real time using a fault diagnosis model and provides conclusions. Based on these conclusions, it automatically provides appropriate handling measures for the battery: no replacement (a fault expert database provides maintenance or other professional maintenance methods); once operational requirements are met, the model returns to its judgment. Repair: Repaired cells and battery packs are stored in a battery reuse warehouse for secondary use or as spare parts. Scrap: Batteries that meet scrapping standards are disassembled to determine the cause of battery degradation, carbon is recovered, and a disassembly report is generated to optimize production processes.

[0057] Specifically, such as Figure 2bAs shown, in this embodiment, the cell casing is marked with a QR code and production and process information is automatically entered: production line number, process number, cell code, production date, and initial (activation) terminal voltage. A raw material warehouse is created, and the marked cell data is stored in the raw material warehouse. Preliminary classification is performed based on the activation terminal voltage and process flow number to form initial battery pack groups. The standard deviation of the initial battery pack groups is calculated, and the initial battery pack groups are standardized. Then, based on the standardized initial battery pack groups, charge-discharge tests are performed on the groups under the same environment, and the calibrated capacity and initial capacity are output. The batch is then subjected to a first capacity grading to form battery packs, which are numbered, and the battery pack number and the initial capacity of each cell are stored in the raw material warehouse. A traceability warehouse is created, and the battery packs formed in the first capacity grading are then charged and discharged under the same environment, outputting the dynamic voltage range and static terminal voltage. A second capacity grading is performed to form battery clusters, which are then numbered, and the battery cluster numbers are synchronized to the traceability warehouse. Next, cluster analysis was performed on the data obtained from the two capacity divisions to derive the correlation coefficients corresponding to different data groups. The greater the distance between the two groups, the less similar they are. The battery cluster numbers were then divided based on the correlation coefficients to form battery stacks, and the battery stack numbers were linked to the traceability warehouse. The energy storage system was configured according to the type of energy storage system (such as the type of power station site), and battery operating parameters were obtained in real time. The battery operating parameters were then input into the fault diagnosis model to identify battery fault problems in real time and provide conclusions. Finally, based on the conclusions, automatic measures were provided for handling faulty batteries: no replacement (the fault expert database provides maintenance or other professional maintenance methods for the batteries), and the model was returned for judgment after the operating requirements were met. Replacement: matching raw materials corresponding to the faulty cells or battery packs from the raw material warehouse (i.e., battery replacement). Scrap: batteries that have reached the scrapping standard were disassembled to determine the cause of battery degradation. Repair: repaired cells and battery packs were stored in the battery cascade utilization warehouse for secondary use or as spare parts. Scrapped products, as well as repaired cells and battery packs, can undergo carbon recovery and be disassembled to generate a disassembly report to determine battery problems and continue to optimize the production process.

[0058] Currently, traditional battery management methods still rely on manual analysis by personnel on-site for the entire battery process, from production and capacity matching to activation and maintenance / replacement. This manual analysis pairs cells into three levels: battery packs, battery clusters, and battery stacks, ultimately forming energy storage systems suitable for different scenarios. As the proportion of energy storage systems increases, the time and complexity required also increase, making traceability of cells and battery packs difficult. Furthermore, there is a lack of professional guidance for post-commissioning battery operation and maintenance, making it impossible to accurately understand battery degradation trends. Existing technologies generate massive amounts of data for capacity matching of battery packs, battery clusters, and battery stacks, requiring significant manpower and time for analysis. The analysis results have low error tolerance, often leading to unsatisfactory allocation results, directly impacting the operational level of the power station. Currently, manual collection of battery operating information is lagging and cannot provide real-time monitoring of battery status. There is no continuous recording and tracking method for post-commissioning battery replacement and repair, making subsequent traceability difficult. On-site maintenance decisions cannot be made quickly, and the professionalism and accuracy of maintenance methods cannot be guaranteed.

[0059] Compared to traditional battery management methods, this application not only improves the aggregation of battery capacity to enhance the consistency of individual cells within a battery cluster, but also enables full lifecycle traceability of the battery, providing data support for production processes and integrated design, and accurately determining the residual value of the battery pack after its retirement from energy storage. Furthermore, this invention not only mitigates current imbalances between battery clusters but also reduces personnel and time costs, shortens project commissioning cycles, accurately assesses battery degradation, and determines whether a battery issue stems from quality or usage. It further provides professional maintenance methods for the operation and maintenance of batteries after commissioning, ensuring an orderly process throughout the entire battery lifecycle, from production and operation to maintenance and recycling. This invention not only improves battery utilization but also enhances operational safety while reducing the scrap rate.

[0060] To better implement the above methods, this application also provides a battery lifecycle management device, which can be integrated into an electronic device, such as a terminal or server. The terminal can be a mobile phone, tablet computer, smart Bluetooth device, laptop computer, or personal computer; the server can be a single server or a server cluster composed of multiple servers.

[0061] For example, in this embodiment, the method of this application embodiment will be described in detail by taking the battery life management device specifically integrated into an electronic device as an example.

[0062] For example, such as Figure 3As shown, the battery lifecycle management device may include: a data acquisition module 300, a standardization processing module 310, a capacity grading processing module 320, a clustering module 330, a battery configuration module 340, and a fault identification module 350. The data acquisition module 300 is configured to acquire the original cell data corresponding to the cell to be managed; the standardization processing module 310 is configured to standardize the original cell data to obtain standardized cell data corresponding to the cell to be managed; the capacity grading processing module 320 is configured to perform two capacity grading processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity grading processes; the clustering module 330 is configured to cluster the battery clusters to obtain a clustered battery stack; the battery configuration module 340 is configured to configure the energy storage system using the clustered battery stack to obtain battery operating parameters; and the fault identification module 350 is configured to identify faulty batteries based on a fault diagnosis model and the battery operating parameters to complete battery lifecycle management.

[0063] In some embodiments, the standardization processing module 310 includes a standardization processing submodule, which is configured to: obtain the activation terminal voltage and process flow number corresponding to the cell to be managed through the original cell data; perform preliminary classification of the cells to be managed according to the activation terminal voltage and process flow number corresponding to the cell to be managed, to obtain several original battery pack groups, each original battery pack group including several cells; calculate the standard deviation and mean value of the activation terminal voltage corresponding to any one of the original battery pack groups; obtain the activation terminal voltage corresponding to any cell in any one of the original battery pack groups; subtract the activation terminal voltage corresponding to any cell from the mean value of the activation terminal voltage to obtain a first parameter; and use the ratio between the first parameter and the standard deviation of the activation terminal voltage as the standardized cell data corresponding to any cell.

[0064] In some embodiments, the capacity grading processing module 320 includes a capacity grading processing submodule, which is configured to: perform charge and discharge tests on each cell in the original battery pack under the same environment, and output the calibrated capacity and initial capacity; perform a first capacity grading on each cell in the original battery pack based on the calibrated capacity and initial capacity to obtain a battery pack after the first capacity grading; and perform a second capacity grading on the battery pack after the first capacity grading to obtain a battery cluster after the second capacity grading.

[0065] In some embodiments, the capacity grading submodule includes a secondary capacity grading module, which is configured to: perform charge and discharge tests on the battery pack after the first capacity grading under the same environment, and output the dynamic voltage range and static terminal voltage; and perform secondary capacity grading on the battery pack after the first capacity grading based on the dynamic voltage range and static terminal voltage to obtain several battery clusters after secondary capacity grading.

[0066] In some embodiments, the clustering module 330 includes a clustering submodule, which is configured to: acquire capacity data corresponding to each of several battery clusters; calculate the correlation coefficient between the several battery clusters based on the capacity data corresponding to each of the several battery clusters; and perform clustering processing on the several battery clusters according to the correlation coefficient to obtain the clustered battery stack.

[0067] In some embodiments, the battery lifecycle management device further includes a warehouse establishment module, which is configured to: create a raw material warehouse and a traceability warehouse; synchronize the original cell data corresponding to the cells to be managed to the raw material warehouse; number the battery pack after one capacity grading and synchronize the battery pack number and the initial capacity of the individual cells to the raw material warehouse; number the battery clusters and synchronize the battery cluster number and the capacity grading data of the battery clusters to the traceability warehouse; and number the battery stacks and synchronize the battery stack number to the traceability warehouse.

[0068] In some embodiments, the fault identification module 350 further includes a fault identification submodule, which is configured to: when a faulty battery needs to be replaced, match a replaceable battery corresponding to the faulty battery according to the raw material warehouse and the traceability warehouse, and replace the faulty battery with the replaceable battery; when a faulty battery needs to be repaired, repair the faulty battery and store the repaired faulty battery in the battery cascade utilization warehouse; when a faulty battery needs to be scrapped, disassemble the faulty battery and recover carbon, determine the battery degradation factors corresponding to the faulty battery, and obtain a disassembly report to optimize the production process.

[0069] In practice, each of the above units can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units, please refer to the previous method embodiments, which will not be repeated here.

[0070] As can be seen from the above, the battery lifecycle management device in this embodiment can first obtain the original cell data corresponding to the cell to be managed; then, it can standardize the original cell data to obtain standardized cell data corresponding to the cell to be managed; then, it can perform two capacity division processes on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity division processes; then, it can perform clustering processing on the battery cluster to obtain a clustered battery stack; then, it can configure the energy storage system through the clustered battery stack to obtain battery operating parameters; finally, based on the fault diagnosis model, it can identify faulty batteries according to the battery operating parameters to complete the battery lifecycle management.

[0071] This invention not only improves the aggregation degree of battery capacity classification to enhance the consistency of individual cells within a battery cluster, but also enables full lifecycle traceability of the battery, providing data support for production processes and integrated design, and accurately determining the residual value of the battery pack after its retirement from energy storage. Furthermore, this invention not only alleviates current imbalances between battery clusters but also reduces personnel and time costs, shortens project commissioning cycles, accurately understands battery degradation, and thus distinguishes between quality and usage issues. It further provides professional maintenance methods for battery operation and maintenance after commissioning, ensuring an orderly process throughout the entire battery lifecycle, from production and operation to maintenance and recycling. This invention not only improves battery utilization but also enhances operational safety while reducing the scrap rate.

[0072] This application also provides an electronic device, which can be a terminal, a server, or other similar device. The terminal can be a mobile phone, tablet computer, smart Bluetooth device, laptop computer, personal computer, etc.; the server can be a single server or a server cluster composed of multiple servers, etc.

[0073] In some embodiments, the battery lifecycle management device can also be integrated into multiple electronic devices. For example, the battery lifecycle management device can be integrated into multiple servers, and the battery lifecycle management method of this application can be implemented by multiple servers.

[0074] In this embodiment, a server will be used as an example for detailed description. For example, ... Figure 4 As shown, it illustrates a schematic diagram of the server structure involved in an embodiment of this application. Specifically: The server may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, an input module 404, and a communication module 405. Those skilled in the art will understand that... Figure 4 The server architecture shown does not constitute a limitation on the server and may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. Wherein: Processor 401 is the control center of the server, connecting various parts of the server through various interfaces and lines. It performs various server functions and processes data by running or executing software programs and / or modules stored in memory 402, and by calling data stored in memory 402, thereby providing overall monitoring of the server. In some embodiments, processor 401 may include one or more processing cores; in some embodiments, processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 401.

[0075] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the server, etc. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0076] The server also includes a power supply 403 that supplies power to the various components. In some embodiments, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0077] The server may also include an input module 404, which can be used to receive input numeric or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0078] The server may also include a communication module 405. In some embodiments, the communication module 405 may include a wireless module, through which the server can perform short-range wireless transmission, thereby providing users with wireless broadband internet access. For example, the communication module 405 can be used to help users send and receive emails, browse web pages, and access streaming media.

[0079] Although not shown, the server may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the server loads the executable files corresponding to the processes of one or more applications into the memory 402 according to the following instructions, and the processor 401 runs the applications stored in the memory 402, thereby realizing various functions in the battery life management device.

[0080] In some embodiments, a computer program product is also provided, including a computer program or instructions that, when executed by a processor, implement the steps in any of the above-described battery lifecycle management methods.

[0081] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0082] As can be seen from the above, the embodiments of this application not only improve the aggregation degree of battery capacity to enhance the consistency of individual cells within the battery cluster, but also enable full lifecycle traceability of the battery, providing data support for production processes and integrated design, and accurately determining the residual value of the battery pack after its retirement from energy storage. Furthermore, this invention not only alleviates current imbalances between battery clusters but also reduces personnel and time costs, shortens project commissioning cycles, accurately understands battery degradation, and thus determines whether a battery issue is quality-related or usage-related, further providing professional maintenance methods for battery operation and maintenance after commissioning; ensuring an orderly state throughout the entire battery lifecycle, from production and operation to maintenance and recycling. This invention not only improves battery utilization but also enhances battery operational safety while reducing the scrap rate.

[0083] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0084] To this end, embodiments of this application provide a computer-readable storage medium storing multiple instructions that can be loaded by a processor to execute steps in any of the battery lifecycle management methods provided in this application. For example, the instructions can execute the following steps: obtaining raw cell data corresponding to the cell to be managed; standardizing the raw cell data to obtain standardized cell data corresponding to the cell to be managed; performing two capacity-division processing on the cell to be managed based on the standardized cell data to obtain a battery cluster formed by the two capacity-division processing; clustering the battery cluster to obtain a clustered battery stack; configuring the energy storage system using the clustered battery stack to obtain battery operating parameters; and identifying faulty batteries based on a fault diagnosis model and the battery operating parameters to complete battery lifecycle management, etc.

[0085] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0086] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in various alternative implementations of battery lifecycle management in the above embodiments.

[0087] Since the instructions stored in the storage medium can execute the steps of any of the battery life cycle management methods provided in the embodiments of this application, the beneficial effects that any of the battery life cycle management methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0088] The foregoing has provided a detailed description of a battery lifecycle management method, apparatus, server, and computer-readable storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A battery lifecycle management method, characterized in that, include: Obtain the original cell data corresponding to the cell to be managed; The original cell data is standardized to obtain the standardized cell data corresponding to the cell to be managed; The cells to be managed are subjected to two capacity grading processes based on the standardized cell data to obtain a battery cluster formed by the two capacity grading processes of the cells to be managed. The battery clusters are clustered to obtain clustered battery stacks. The energy storage system is configured using the clustered battery stack to obtain battery operating parameters; Based on the fault diagnosis model, faulty batteries are identified according to the battery operating parameters to complete battery life cycle management; The standardization process of the original cell data to obtain standardized cell data corresponding to the cell to be managed includes: The activation terminal voltage and process flow number of the cell to be managed are obtained by using the original cell data. Based on the activation terminal voltage and process flow number of the cell to be managed, the cells to be managed are initially classified to obtain several original battery pack groups, each of which includes several cells. Calculate the standard deviation and mean value of the activation terminal voltage for any one of the original battery pack groups; Obtain the activation terminal voltage of any cell in any original group of the battery pack; The first parameter is obtained by subtracting the average value of the activation terminal voltage from the activation terminal voltage corresponding to any one of the battery cells. The ratio between the first parameter and the standard deviation of the activation terminal voltage is used as the standardized cell data corresponding to any one of the cells. The step of performing two capacity-differentiating processes on the cells to be managed based on the standardized cell data to obtain a battery cluster composed of the cells to be managed after the two capacity-differentiating processes includes: Perform charge and discharge tests on each cell in the original battery pack under the same environment, and output the calibrated capacity and initial capacity. Based on the calibrated capacity and the initial capacity, each cell in the original group of the battery pack is divided into individual cells to obtain the battery pack after the first capacity division. The battery pack after the first capacity division is then subjected to a second capacity division to obtain a battery cluster after the second capacity division.

2. The battery lifecycle management method as described in claim 1, characterized in that, The step of performing a second capacity division on the battery pack after the first capacity division to obtain a battery cluster after the second capacity division includes: The battery pack after the first capacity test was subjected to charge and discharge tests under the same environment, and the dynamic voltage range and static terminal voltage were output. Based on the dynamic voltage range and static terminal voltage, the battery pack after the first capacity grading is subjected to a second capacity grading to obtain several battery clusters after the second capacity grading.

3. The battery lifecycle management method as described in claim 2, characterized in that, The process of clustering the battery clusters to obtain clustered battery stacks includes: Obtain the capacity breakdown data corresponding to each of the plurality of battery clusters; Based on the capacity breakdown data corresponding to each of the battery clusters, the correlation coefficient between the battery clusters is calculated. The battery clusters are clustered according to the correlation coefficient to obtain the clustered battery stack.

4. The battery lifecycle management method as described in claim 3, characterized in that, The method further includes: Create raw material warehouses and traceability warehouses; Synchronize the original cell data corresponding to the cell to be managed to the raw material warehouse; The battery packs after the first capacity division are numbered, and the battery pack numbers and the initial capacity of each cell are synchronized to the raw material warehouse; The battery clusters are numbered, and the battery cluster numbers and the capacity data of the battery clusters are synchronized to the traceability warehouse; The battery stacks are numbered, and the battery stack numbers are synchronized to the traceability warehouse.

5. The battery lifecycle management method as described in claim 4, characterized in that, The method of identifying faulty batteries based on the fault diagnosis model and the battery operating parameters to complete battery lifecycle management also includes: When the faulty battery needs to be replaced, a replacement battery corresponding to the faulty battery is matched according to the raw material warehouse and the traceability warehouse, and the faulty battery is replaced using the replacement battery. When the faulty battery needs to be repaired, it shall be repaired and the repaired battery shall be stored in the battery cascade utilization warehouse. When the faulty battery needs to be scrapped, the faulty battery is disassembled and carbon is recovered. The battery degradation factors corresponding to the faulty battery are determined, and a disassembly report is obtained to optimize the production process.

6. A battery lifecycle management device, applicable to the battery lifecycle management method as described in any one of claims 1 to 5, characterized in that, include: The data acquisition module is used to acquire the original cell data corresponding to the cell to be managed; The standardization processing module is used to standardize the original cell data to obtain the standardized cell data corresponding to the cell to be managed. The capacity grading module is used to perform two capacity grading processes on the cells to be managed based on the standardized cell data, so as to obtain a battery cluster formed by the two capacity grading processes of the cells to be managed. A clustering module is used to perform clustering processing on the battery clusters to obtain clustered battery stacks; The battery configuration module is used to configure the energy storage system through the clustered battery stack to obtain battery operating parameters; The fault identification module is used to identify faulty batteries based on the fault diagnosis model and the battery operating parameters, so as to complete the battery life cycle management.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory storing multiple instructions; the processor loads instructions from the memory to execute the steps in the battery life management method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to perform the steps of the battery life management method according to any one of claims 1 to 5.

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