Pluggable cell self-adaptive configuration method and equipment based on energy storage battery and medium

Abstract

The invention discloses a pluggable cell self-adaptive configuration method and device based on an energy storage battery and a medium, and the method comprises the steps: building cell connection, and obtaining cell state parameters through the cell connection; obtaining a target demand of the energy storage system, and determining a topology configuration scheme set through energy storage battery safety topology constraint analysis based on the target demand of the energy storage system and the cell state parameters; performing multi-objective optimization on the topological configuration scheme set to obtain an optimal configuration scheme of the battery cell; according to the optimal configuration scheme of the battery cell, determining a bus adaptive voltage through battery cell connection dynamic reconstruction; performing operation adaptive analysis on the bus adaptive voltage to obtain battery cell operation feedback data; and based on the battery cell operation feedback data, determining topology decision update logic through configuration strategy weight optimization. According to the method, the technical problem that the configuration method of the pluggable battery cell in the prior art cannot adapt to the type of the energy storage battery is solved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage batteries, and in particular to a method, device, and medium for adaptively configuring pluggable cells based on energy storage batteries. Background Art

[0002] With the rapid development of renewable energy sources such as solar and wind power, the intermittent and unstable nature of their generation requires efficient energy storage systems to smooth power output, improve power quality, and ensure the reliability and stability of power supply. At the same time, the demand for energy storage batteries is also increasing in areas such as distributed generation, microgrids, and electric vehicle charging, prompting the continuous development and innovation of energy storage technology.

[0003] In order to overcome the limitations of traditional energy storage batteries, the concept of modular design has gradually been widely used in the field of energy storage. Modular design decomposes the energy storage system into multiple modules with independent functions. Each module can be independently produced, installed, maintained and replaced, which improves the maintainability and scalability of the system. It is in this context that pluggable batteries came into being. It is a concrete manifestation of modular design in energy storage batteries. By designing the battery cells to be pluggable, it enables rapid assembly, disassembly and replacement of energy storage modules, providing strong support for the efficient operation and management of energy storage systems. The configuration method of pluggable batteries in the existing technology can only be used for specific types of energy storage batteries. For other types or newly added types of energy storage batteries, additional pluggable battery cell design is required, and the cell configuration cannot be adaptive. Summary of the Invention

[0004] The embodiments of the present application provide a method, device, and medium for adaptively configuring pluggable cells based on energy storage batteries, which solves the technical problem in the prior art that the configuration method of pluggable cells cannot adapt to the energy storage battery model.

[0005] In a first aspect, an embodiment of the present application provides a method for adaptively configuring pluggable cells based on an energy storage battery, characterized in that the method includes: establishing a cell connection, and obtaining cell status parameters through the cell connection; obtaining the target requirements of the energy storage system, and based on the target requirements of the energy storage system and the cell status parameters, determining a set of topology configuration schemes through a safety topology constraint analysis of the energy storage battery; performing multi-objective optimization on the set of topology configuration schemes to obtain an optimal cell configuration scheme; determining a busbar adaptation voltage based on the optimal cell configuration scheme through dynamic reconstruction of the cell connection; performing an operation adaptive analysis on the busbar adaptation voltage to obtain cell operation feedback data; and determining a topology decision update logic through configuration strategy weight optimization based on the cell operation feedback data.

[0006] In one implementation of the present application, based on the target requirements of the energy storage system and the cell status parameters, a set of topology configuration schemes is determined through the energy storage battery safety topology constraint analysis, specifically including: based on the target requirements of the energy storage system, the cell connection requirements are determined through virtual bus voltage analysis; wherein the cell connection requirements include: the number of cells in series and the number of cells in parallel; the cell link topology is constructed for the cell status parameters to obtain a candidate topology set; based on the cell connection requirements and the candidate topology set, a set of topology configuration schemes is determined through candidate topology risk assessment.

[0007] In one implementation of the present application, a set of topology configuration schemes is subjected to multi-objective optimization to obtain the optimal configuration scheme for the battery cells, specifically including: determining the optimization objective function through optimization objective analysis based on the set of topology configuration schemes; performing discrete optimization on the objective optimization function to obtain the objective function configuration scheme; and obtaining the optimal configuration scheme for the battery cells through a comprehensive scoring method based on the objective function configuration scheme.

[0008] In one implementation of the present application, the bus adaptation voltage is determined according to the optimal configuration scheme of the battery cells through dynamic reconstruction of the battery cell connections, specifically including: physical connection path control of the optimal configuration scheme of the battery cells to obtain the target associated topology; wherein, the target associated topology includes: target series topology, target parallel topology; based on the target associated topology, the difference compensation parameters are determined by adjusting the equivalent output voltage of the battery cells; wherein, the difference compensation parameters include: line voltage drop compensation parameters, parameter abnormality compensation parameters; according to the difference compensation parameters, the bus adaptation voltage is determined by suppressing the battery cell circulating current.

[0009] In one implementation of the present application, an operation adaptive analysis is performed on the busbar adaptation voltage to obtain battery cell operation feedback data, specifically including: determining a connection health score based on the busbar adaptation voltage by evaluating the energy storage battery connection status; performing a health threshold judgment on the connection health score to obtain abnormal parameters of the energy storage cell; adjusting the energy storage cell connection based on the abnormal parameters of the energy storage cell to obtain abnormal processing data of the energy storage cell; and updating the abnormal processing strategy according to the abnormal processing data of the energy storage cell to obtain battery cell operation feedback data.

[0010] In one implementation of the present application, based on the cell operation feedback data, the topology decision update logic is determined by optimizing the configuration strategy weights, specifically including: performing energy storage cell configuration correlation analysis on the cell operation feedback data to determine the optimization identification direction; based on the optimization identification direction, dynamically adjusting the target to obtain a dynamic adjustment weight; and according to the dynamic adjustment weight, adjusting the weight of the preset energy storage cell configuration strategy to obtain the topology decision update logic.

[0011] In one implementation of the present application, an energy storage cell configuration correlation analysis is performed on the cell operation feedback data to determine the optimization identification direction, specifically including: performing a Pearson correlation coefficient analysis on the cell operation feedback data to obtain the cell configuration parameters that affect the life of the energy storage battery; based on the cell configuration parameters, the optimization identification direction is determined by correlating performance indicators; wherein the optimization identification direction includes: topology adjustment suggestions and virtual impedance optimization intervals.

[0012] In one implementation of the present application, after determining the topology decision update logic by optimizing the configuration strategy weights based on the cell operation feedback data, the method further includes: converting the topology decision update logic into a JSON configuration file to obtain a strategy update configuration file; configuring the strategy update configuration file with a version number, and performing data backing up of the strategy update configuration file after the version number configuration to obtain a strategy update backup library.

[0013] In a second aspect, an embodiment of the present application further provides a pluggable cell adaptive configuration device based on an energy storage battery, characterized in that the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so as to enable the at least one processor to: establish a cell connection, and obtain cell status parameters through the cell connection; obtain the target requirements of the energy storage system, and based on the target requirements of the energy storage system and the cell status parameters, determine a set of topology configuration schemes through energy storage battery safety topology constraint analysis; perform multi-objective optimization on the set of topology configuration schemes to obtain the optimal cell configuration scheme; determine the bus adaptation voltage based on the optimal cell configuration scheme through dynamic reconstruction of the cell connection; perform operation adaptive analysis on the bus adaptation voltage to obtain cell operation feedback data; determine the topology decision update logic through configuration strategy weight optimization based on the cell operation feedback data.

[0014] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium for adaptive configuration of pluggable cells based on an energy storage battery, which stores computer executable instructions, and is characterized in that the computer executable instructions are set to: establish a cell connection, and obtain cell status parameters through the cell connection; obtain the target requirements of the energy storage system, and based on the target requirements of the energy storage system and the cell status parameters, determine a set of topology configuration schemes through energy storage battery safety topology constraint analysis; perform multi-objective optimization on the set of topology configuration schemes to obtain the optimal cell configuration scheme; determine the bus adaptation voltage through dynamic reconstruction of the cell connection according to the optimal cell configuration scheme; perform operation adaptive analysis on the bus adaptation voltage to obtain cell operation feedback data; determine the topology decision update logic through configuration strategy weight optimization based on the cell operation feedback data.

[0015] The embodiments of the present application provide a method, device, and medium for adaptively configuring pluggable cells based on energy storage batteries. By optimizing the topological configuration scheme of energy storage batteries and energy storage cells, the technical problem in the prior art that the configuration method of pluggable cells cannot adapt to the energy storage battery model is solved. The method realizes the adaptive configuration of pluggable cells for different energy storage battery models, improves the degree of cell integration, and reduces the design cost of pluggable cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A flow chart of a method for adaptively configuring pluggable cells based on an energy storage battery provided in an embodiment of the present application; Figure 2 A schematic diagram of the internal structure of a pluggable battery cell adaptive configuration device based on an energy storage battery provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] The embodiments of the present application provide a method, device, and medium for adaptively configuring pluggable cells based on energy storage batteries. By optimizing the topological configuration scheme of energy storage batteries and energy storage cells, the technical problem in the prior art that the configuration method of pluggable cells cannot adapt to the energy storage battery model is solved. The method realizes the adaptive configuration of pluggable cells for different energy storage battery models, improves the degree of cell integration, and reduces the design cost of pluggable cells.

[0019] The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0020] Figure 1 This is a flow chart of a method for adaptively configuring pluggable cells based on energy storage batteries provided in an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a method for adaptively configuring pluggable cells based on an energy storage battery, which specifically includes the following steps: Step 101: Establish cell connection, and obtain cell state parameters through the cell connection.

[0021] For example, energy storage cells convert electrical energy into stored chemical energy through electrochemical reactions, releasing the stored energy through discharge when needed. The battery's positive and negative electrodes are connected by an electrolyte. During charging, lithium ions from the positive electrode migrate to the negative electrode and combine with the negative electrode material, releasing electrical energy. During discharge, lithium ions return from the negative electrode to the positive electrode, restoring the battery's electrical output. For pluggable cells, the operating status of the cell can only be tested after the cell is connected to the energy storage battery.

[0022] With the continuous development of energy storage technology and changes in application requirements, energy storage battery systems may need to be upgraded and modified. Using pluggable cells, when upgrading the system, only some cells with better performance need to be replaced, without replacing the entire battery system. This greatly reduces the cost and difficulty of system upgrades and improves the flexibility and scalability of energy storage battery systems.

[0023] In one embodiment, when a battery cell is inserted into the energy storage system, the mechanical interface's magnetic guide structure uses magnetic force to guide the cell along a predetermined track. A micro-pressure sensor at the end of the track detects that the pressure has reached a threshold, triggering a self-locking mechanism to secure the cell. At this point, the anti-misinsertion detection module activates: the optical positioning mark on the cell casing is scanned by a photoelectric sensor in the slot. If the mark is detected to be offset by an angle greater than 5° or the reflective features do not match, the mechanical lock is triggered and a buzzer alarm sounds.

[0024] After confirming correct insertion, the pre-charge circuit begins operation: a low current of 1A is injected into the cell via a high-precision current source while simultaneously monitoring the difference between the cell terminal voltage and the system bus voltage. When the voltage difference is less than 0.5V, the main power relay closes to establish a full current path. This process prevents contact sparking and shortens balancing time. The communication layer interacts with the cell's embedded microcontroller via the adaptive baud rate CANFD protocol, reading nominal parameters stored in FRAM and real-time dynamic parameters (voltage sampling frequency 1kHz, temperature sampling period 100ms). Upon completion of data acquisition, it sends a "Ready" status packet to the main controller.

[0025] Step 102: Obtain target requirements of the energy storage system, and determine a set of topology configuration solutions based on the target requirements of the energy storage system and cell status parameters through energy storage battery safety topology constraint analysis.

[0026] For example, after receiving the target energy storage system requirements, the energy storage battery master controller calculates basic energy storage battery parameters through energy storage battery safety topology constraint analysis, and performs candidate topology risk assessment, and finally outputs a set of safe topology configuration solutions, thereby realizing the connection requirements of the battery cells in the energy storage battery and improving the safety of the configuration of the energy storage battery cells.

[0027] Specifically, based on the target requirements of the energy storage system and the cell status parameters, a set of topology configuration schemes is determined through the energy storage battery safety topology constraint analysis, including: based on the target requirements of the energy storage system, the cell connection requirements are determined through virtual bus voltage analysis; wherein the cell connection requirements include: the number of cells in series and the number of cells in parallel; the cell link topology is constructed based on the cell status parameters to obtain a set of candidate topologies; based on the cell connection requirements and the candidate topology set, a set of topology configuration schemes is determined through candidate topology risk assessment.

[0028] In one embodiment, first, the target voltage is divided by the maximum allowable voltage of the battery cell and rounded up to obtain the number of battery cells connected in series; similarly, the number of battery cells connected in series can be used as the divisor × the upper limit of the power of a single battery cell, and the target power can be divided by the divisor and rounded up to determine the number of battery cells connected in parallel.

[0029] Then, candidate topologies are generated based on a graph theory model: the cell nodes are mapped into a graph structure according to the physical slot positions, and a depth-first search (DFS) algorithm is used to traverse all possible series-parallel combinations. At the same time, a pruning strategy is applied. That is, when it is detected that the cumulative voltage of a branch has exceeded 110% of the target voltage or the current exceeds the maximum rate of the cell, the path search is immediately terminated.

[0030] Finally, the candidate topologies are scored using a risk assessment model: the SOC differences, internal resistance dispersion, and thermal coupling risks of each branch cell are calculated, and solutions with total scores below the threshold are eliminated, ultimately outputting a set of safe topology configuration solutions.

[0031] Step 103: Perform multi-objective optimization on the topology configuration solution set to obtain the optimal cell configuration solution.

[0032] For example, after obtaining the topology configuration scheme, a three-dimensional target space is established. By performing target optimization analysis on voltage matching, internal resistance balance, and health status balance, the optimal configuration scheme for the battery cells is obtained, realizing multi-objective optimization of the battery cell topology configuration set and improving the adaptability and safety of the energy storage battery cells.

[0033] Specifically, a multi-objective optimization is performed on the set of topology configuration schemes to obtain the optimal battery cell configuration scheme, including: determining the optimization objective function through optimization objective analysis based on the set of topology configuration schemes; performing discrete optimization on the objective optimization function to obtain the objective function configuration scheme; and obtaining the optimal battery cell configuration scheme through a comprehensive scoring method based on the objective function configuration scheme.

[0034] In one embodiment, different energy storage application scenarios have different requirements for battery capacity, voltage, and other parameters. The pluggable cell design allows for flexible configuration of the energy storage battery based on actual needs. By increasing or decreasing the number of cells and adjusting the cell connection method, the battery capacity and voltage can be easily adjusted to meet the needs of different application scenarios, such as home energy storage, distributed photovoltaic energy storage, and grid energy storage.

[0035] Since the cell plug-in interface needs to be adapted to the model of the energy storage battery, the cell configuration requires further optimization of different elements of the obtained topology configuration solution.

[0036] First, a three-dimensional target space is established. The target definitions include: voltage matching, internal resistance balance, and health status balance.

[0037] The voltage matching is characterized by the absolute difference between the target voltage and the actual topology voltage, the internal resistance balance is characterized by the maximum percentage difference of the internal resistance of the parallel branches, and the health status balance is characterized by the standard deviation of the SOH difference between battery cells.

[0038] Then, an improved genetic algorithm was used to analyze chromosome encoding, fitness function, and crossover mutation. The chromosome encoding represents each individual topology, and the gene contains the number of series connections, the number of parallel connections, and the virtual impedance parameter. The fitness function represents the weighted sum of these three metrics (series, parallel, and virtual impedance), with the weights dynamically adjusted based on the energy storage battery type. Crossover mutation uses a single-point crossover on the series connection number and a Gaussian mutation on the virtual impedance parameter. After 100 iterations, the solution with the highest overall score on the Pareto front was selected. For a specific household energy storage scenario, the 16S3P topology (voltage deviation 0.3%, internal resistance difference 8%, and SOH difference 5%) was selected. A backup solution (15S4P) was generated and stored in a buffer pool for failover in the event of an anomaly. Ultimately, the optimal cell configuration for this energy storage scenario was determined.

[0039] Step 104: Determine the busbar adaptation voltage by dynamically reconfiguring the cell connections according to the optimal cell configuration solution.

[0040] Specifically, according to the optimal configuration scheme of the battery cells, the busbar adaptation voltage is determined through dynamic reconstruction of the battery cell connections, including: physical connection path control of the optimal configuration scheme of the battery cells to obtain a target associated topology; wherein the target associated topology includes: a target series topology and a target parallel topology; based on the target associated topology, the difference compensation parameters are determined through adjustment of the battery cell equivalent output voltage; wherein the difference compensation parameters include: line voltage drop compensation parameters and parameter abnormality compensation parameters; according to the difference compensation parameters, the busbar adaptation voltage is determined through battery cell circulating current suppression.

[0041] In one embodiment, a 1 kHz test current (amplitude 10 mA) is injected into the contacts every 5 minutes, and the resistance value is calculated using a four-wire measurement method. If the test value is greater than 0.2 mΩ for three consecutive times, it is determined to be a poor contact.

[0042] Six NTC sensors placed on the cell surface, combined with infrared thermal imaging data, construct a three-dimensional temperature distribution map to identify local hotspots. CAN FD frame bit error rates and response delays are calculated. When an anomaly is detected, the fault-tolerant controller implements a graded response.

[0043] If the resistance of a single contact exceeds the specified value, the system switches to a backup contact and reduces the load factor of the cell to 80%. If a sudden temperature rise (>5°C / s) is detected, the faulty cell is disconnected via a latching relay within 10ms and voltage compensation is initiated for adjacent cells. All events are recorded in the blockchain ledger, generating a traceable operation and maintenance log.

[0044] Step 105: Perform an operation adaptive analysis on the busbar adaptation voltage to obtain battery cell operation feedback data.

[0045] Specifically, an operation adaptive analysis is performed on the busbar adaptation voltage to obtain battery cell operation feedback data, including: determining a connection health score by evaluating the energy storage battery connection status based on the busbar adaptation voltage; determining a health threshold value for the connection health score to obtain abnormal parameters of the energy storage cell; adjusting the energy storage cell connection based on the abnormal parameters of the energy storage cell to obtain abnormal processing data of the energy storage cell; and updating the abnormal processing strategy based on the abnormal processing data of the energy storage cell to obtain battery cell operation feedback data.

[0046] Step 106: Based on the cell operation feedback data, the topology decision update logic is determined by optimizing the configuration strategy weights.

[0047] Specifically, based on the cell operation feedback data, the topology decision update logic is determined by optimizing the configuration strategy weights, including: performing an energy storage cell configuration correlation analysis on the cell operation feedback data to determine the optimization identification direction; based on the optimization identification direction, dynamically adjusting the target to obtain a dynamic adjustment weight; and adjusting the preset energy storage cell configuration strategy according to the dynamic adjustment weight to obtain the topology decision update logic.

[0048] Furthermore, the cell operation feedback data is subjected to an energy storage cell configuration correlation analysis to determine the optimization identification direction, specifically including: performing a Pearson correlation coefficient analysis on the cell operation feedback data to obtain the cell configuration parameters that affect the life of the energy storage battery; based on the cell configuration parameters, the optimization identification direction is determined through performance indicator correlation; wherein, the optimization identification direction includes: topology structure adjustment suggestions and virtual impedance optimization range.

[0049] Furthermore, after determining the topology decision update logic by optimizing the configuration strategy weights based on the cell operation feedback data, the method also includes: converting the topology decision update logic into a JSON configuration file to obtain a strategy update configuration file; configuring the version number of the strategy update configuration file, and backing up the strategy update configuration file after the version number is configured to obtain a strategy update backup library.

[0050] In one embodiment, a grey correlation algorithm is used to calculate the correlation strength between each configuration parameter and performance indicator, screening out key parameters with correlations greater than 0.7. A fault tree analysis (FTA) is performed on high-failure-rate cases, revealing that 80% of failures originate from parallel groups with internal resistance variations greater than 25%. Based on this, an optimization rule is generated: "Parallel branch internal resistance dispersion threshold ≤ 20%." This optimization rule is encoded as if-then logic and pushed to the online strategy library.

[0051] Furthermore, when energy storage demand increases, the battery capacity can be rapidly expanded by directly inserting more pluggable battery cells into the energy storage battery module or system.

[0052] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, the embodiment of this application also provides a pluggable battery cell adaptive configuration device based on energy storage battery, the structure of which is as follows Figure 2 shown.

[0053] Figure 2 This is a schematic diagram of the internal structure of a pluggable cell adaptive configuration device based on an energy storage battery provided in an embodiment of the present application. Figure 2 As shown, the equipment includes: at least one processor 201; and, a memory 202 communicatively coupled to the at least one processor; The memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor 201 to enable the at least one processor 201 to: Establish cell connections and obtain cell status parameters through cell connections; obtain the target requirements of the energy storage system, and based on the target requirements of the energy storage system and the cell status parameters, determine the set of topology configuration schemes through energy storage battery safety topology constraint analysis; perform multi-objective optimization on the set of topology configuration schemes to obtain the optimal cell configuration scheme; based on the optimal cell configuration scheme, determine the busbar adaptation voltage through dynamic reconstruction of cell connections; perform operational adaptive analysis on the busbar adaptation voltage to obtain cell operation feedback data; based on the cell operation feedback data, determine the topology decision update logic through configuration strategy weight optimization.

[0054] Some embodiments of the present application provide corresponding Figure 1A non-volatile computer storage medium with adaptive configuration of pluggable cells based on an energy storage battery stores computer executable instructions, wherein the computer executable instructions are set to: Establish cell connections and obtain cell status parameters through cell connections; obtain the target requirements of the energy storage system, and based on the target requirements of the energy storage system and the cell status parameters, determine the set of topology configuration schemes through energy storage battery safety topology constraint analysis; perform multi-objective optimization on the set of topology configuration schemes to obtain the optimal cell configuration scheme; based on the optimal cell configuration scheme, determine the busbar adaptation voltage through dynamic reconstruction of cell connections; perform operational adaptive analysis on the busbar adaptation voltage to obtain cell operation feedback data; based on the cell operation feedback data, determine the topology decision update logic through configuration strategy weight optimization.

[0055] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from the other embodiments. In particular, the IoT device and media embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0056] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0057] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0061] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0062] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0063] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0064] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0065] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for adaptively configuring pluggable cells based on energy storage batteries, characterized in that: The method comprises: Establishing a cell connection, and obtaining cell state parameters through the cell connection; Obtaining target requirements of the energy storage system, and determining a set of topology configuration solutions based on the target requirements of the energy storage system and the cell state parameters through energy storage battery safety topology constraint analysis; Performing multi-objective optimization on the set of topology configuration solutions to obtain an optimal cell configuration solution; According to the optimal cell configuration scheme, the busbar adaptation voltage is determined by dynamically reconfiguring the cell connections; Performing an adaptive operation analysis on the busbar adaptation voltage to obtain cell operation feedback data; Based on the cell operation feedback data, the topology decision update logic is determined by configuring strategy weight optimization.

2. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: Based on the target requirements of the energy storage system and the cell state parameters, a set of topology configuration solutions is determined through energy storage battery safety topology constraint analysis, specifically including: Based on the target requirements of the energy storage system, determining the cell connection requirements through virtual bus voltage analysis; wherein the cell connection requirements include: the number of cells connected in series and the number of cells connected in parallel; Performing cell link topology construction on the cell state parameters to obtain a candidate topology set; The topology configuration solution set is determined based on the cell connection requirements and the candidate topology set through candidate topology risk assessment.

3. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: Perform multi-objective optimization on the set of topology configuration solutions to obtain the optimal cell configuration solution, specifically including: Based on the set of topology configuration solutions, determining an optimization objective function through optimization objective analysis; Performing discrete optimization on the objective optimization function to obtain an objective function configuration scheme; According to the objective function configuration scheme, the optimal configuration scheme of the battery cell is obtained through a comprehensive scoring method.

4. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: According to the optimal cell configuration solution, the busbar adaptation voltage is determined by dynamically reconfiguring the cell connections, specifically including: Performing physical connection path control on the optimal cell configuration solution to obtain a target association topology; wherein the target association topology includes: a target series topology and a target parallel topology; Based on the target associated topology, the difference compensation parameters are determined by adjusting the equivalent output voltage of the battery cell; wherein the difference compensation parameters include: line voltage drop compensation parameters and parameter abnormality compensation parameters; The busbar adaptation voltage is determined according to the difference compensation parameter by suppressing the cell circulating current.

5. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: Performing an adaptive operation analysis on the busbar adaptation voltage to obtain cell operation feedback data, specifically including: Based on the busbar adaptation voltage, a connection health score is determined by evaluating the connection status of the energy storage battery; Performing a health threshold determination on the connection health score to obtain abnormal parameters of the energy storage cell; Performing energy storage cell connection adjustment on the energy storage cell abnormal parameters to obtain energy storage cell abnormality processing data; According to the energy storage cell abnormality processing data, the abnormality processing strategy is updated to obtain the cell operation feedback data.

6. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: Based on the cell operation feedback data, the topology decision update logic is determined by configuring strategy weight optimization, specifically including: Performing energy storage cell configuration correlation analysis on the cell operation feedback data to determine an optimization identification direction; Based on the optimization identification direction, a dynamic adjustment weight is obtained by dynamically adjusting the target; According to the dynamic adjustment weight, the preset energy storage cell configuration strategy is weight-adjusted to obtain the topology decision update logic.

7. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 6, characterized in that: Performing energy storage cell configuration correlation analysis on the cell operation feedback data to determine the optimization identification direction, specifically including: Performing a Pearson correlation coefficient analysis on the battery cell operation feedback data to obtain battery cell configuration parameters that affect the life of the energy storage battery; Based on the cell configuration parameters, the optimization identification direction is determined by associating performance indicators; wherein the optimization identification direction includes: topology structure adjustment suggestions and virtual impedance optimization intervals.

8. The method for adaptively configuring pluggable cells based on energy storage batteries according to claim 1, characterized in that: After determining the topology decision update logic by configuring strategy weight optimization based on the cell operation feedback data, the method further includes: Convert the topology decision update logic into a JSON configuration file to obtain a policy update configuration file; The policy update configuration file is configured with a version number, and data of the policy update configuration file after the version number configuration is performed to obtain a policy update backup library.

9. A pluggable cell adaptive configuration device based on energy storage battery, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Establishing a cell connection, and obtaining cell state parameters through the cell connection; Obtaining target requirements of the energy storage system, and determining a set of topology configuration solutions based on the target requirements of the energy storage system and the cell state parameters through energy storage battery safety topology constraint analysis; Performing multi-objective optimization on the set of topology configuration solutions to obtain an optimal cell configuration solution; According to the optimal cell configuration scheme, the busbar adaptation voltage is determined by dynamically reconfiguring the cell connections; Performing an adaptive operation analysis on the busbar adaptation voltage to obtain cell operation feedback data; Based on the cell operation feedback data, the topology decision update logic is determined by configuring strategy weight optimization.

10. A non-volatile computer storage medium with adaptive configuration of pluggable cells based on an energy storage battery, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Establishing a cell connection, and obtaining cell state parameters through the cell connection; Obtaining target requirements of the energy storage system, and determining a set of topology configuration solutions based on the target requirements of the energy storage system and the cell state parameters through energy storage battery safety topology constraint analysis; Performing multi-objective optimization on the set of topology configuration solutions to obtain an optimal cell configuration solution; According to the optimal cell configuration scheme, the busbar adaptation voltage is determined by dynamically reconfiguring the cell connections; Performing an adaptive operation analysis on the busbar adaptation voltage to obtain cell operation feedback data; Based on the cell operation feedback data, the topology decision update logic is determined by configuring strategy weight optimization.

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