Fusion current balanced dual-core power supply cascade energy storage collaborative management system and method

Abstract

The application belongs to the technical field of collaborative management, and discloses a dual-core power supply cascade energy storage collaborative management system and method fusing current balance, which comprises the following steps: collecting operation parameters of each energy storage node in a dual-core power supply cascade energy storage terminal and performing data cleaning to output a basic data set; defining the roles of each energy storage node, assigning the roles of the parent core and the child core, and outputting a dual-core control response table; extracting power parameters and electrothermal parameters to construct a current scheduling matrix for energy distribution calculation and output a multi-node current scheduling instruction set; tracking the temperature trend of the nodes, identifying a high-temperature path for amplitude limiting instruction processing; detecting an energy storage path switching request signal in a communication field to perform waveform state analysis, confirming an optimal switching time, and performing power supply path switching; constructing a management feedback evaluation index, updating the path priority of the dual-core control response table, and synchronizing to a preset energy storage management platform; and ensuring the power supply continuity and operation reliability under different working conditions.

Description

Technical Field

[0001] This invention relates to the field of collaborative management technology, and more specifically, to a collaborative management system and method for dual-core power supply cascaded energy storage with integrated current balancing. Background Technology

[0002] Collaborative management of cascaded dual-core energy storage terminals is a core link and key step in the manufacturing and operation of energy storage systems. Multi-node collaborative scheduling of this process enables precise control of efficient load response, ensuring the power supply continuity and operational safety of the energy storage system. However, traditional management methods still face many technical bottlenecks when dealing with more complex dual-core collaborative scheduling scenarios and dynamic load conditions.

[0003] In real-world scenarios, the master and slave cores of dual-core cascaded energy storage terminals often experience state synchronization delays due to the independence of task execution. The slave core cannot obtain the target scheduling data issued by the master core in real time when executing tasks; for example, output voltage response lags under load surges. However, traditional management methods neglect the lack of a lightweight communication coroutine scheduling coordination mechanism between the master and slave cores, and cannot establish a task mapping synchronization table and a cache structure to match scheduling targets. This easily leads to the risk of deadlock in the program task queue or power supply scheduling out of sync. Furthermore, the difference in the state of charge (SOC) of each energy storage node can cause a severe mismatch between power allocation strategies and actual power supply capacity. Low-charge nodes and high-charge nodes are still allocated power supply tasks according to a fixed ratio, but traditional management methods do not address the relationship between SOC and power supply capacity. The dynamic adjustment of physical correspondences can cause the current at low-charge nodes to rise rapidly to the rated upper limit, resulting in undervoltage power failure and interruption of the overall system power supply. At the same time, in parallel power supply scenarios, uneven internal temperature distribution can lead to heat accumulation on specific paths. Traditional management methods lack the ability to perceive heat dissipation status information when allocating current, which can easily lead to a situation where the temperature of one module is much higher than that of other modules, but the control logic continues to schedule, resulting in thermal load imbalance. On the other hand, there is a risk of sudden changes in power output during power supply path switching. Traditional management methods cannot lock the optimal time to perform the switching operation, which can trigger current surges. This makes it difficult to guarantee the continuity of power supply under complex operating conditions, affecting the overall scheduling efficiency and system reliability of dual-core power supply cascaded energy storage terminals.

[0004] In view of this, the present invention proposes a dual-core power supply cascaded energy storage collaborative management system and method with integrated current balancing to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a dual-core power supply cascaded energy storage collaborative management method integrating current balancing, comprising: S1. Collect the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal and perform data cleaning to output a basic dataset; the basic dataset includes power parameters, electrothermal parameters and communication fields; S2. Define roles for each energy storage node based on the basic dataset, assign roles to the parent core and child core respectively, perform task management matching based on the role assignment results, and output a dual-core control response table; S3. Extract electrical energy parameters and electrothermal parameters to construct a current dispatch matrix, perform energy allocation calculations on the current dispatch matrix, and output a multi-node current dispatch instruction set; S4. Track the node temperature trend of the energy storage node based on the electrothermal parameters, identify the high-temperature path based on the tracking results, process the high-temperature path with the limiting command, and update the scheduling weight of the dual-core control response table based on the adjustment results; S5. Detect the energy storage path switching request signal in the communication field, extract voltage status information in combination with power parameters, perform waveform status analysis on the voltage status information, confirm the optimal switching time based on the analysis results, and perform power supply path switching based on the optimal switching time, and output the power supply path switching strategy. S6. Obtain relevant terminal information in real time, construct management feedback evaluation indicators by combining dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, update the path priority of dual-core control response table, and synchronize the updated dual-core control response table to the preset energy storage management platform.

[0006] On the other hand, the dual-core power supply cascaded energy storage collaborative management system with integrated current balancing, and its method for achieving integrated current balancing of dual-core power supply cascaded energy storage collaborative management, includes: The data acquisition module collects the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal and performs data cleaning to output a basic dataset; the basic dataset includes electrical parameters, electrothermal parameters and communication fields. The role allocation module defines roles for each energy storage node based on the basic dataset, assigns roles to the parent core and child core respectively, performs task management matching based on the role allocation results, and outputs a dual-core control response table. The energy consumption scheduling module extracts electrical energy parameters and electrothermal parameters to construct a current scheduling matrix, performs energy allocation calculations on the current scheduling matrix, and outputs a multi-node current scheduling instruction set. The electrothermal regulation module tracks the node temperature trend of the energy storage node based on electrothermal parameters, identifies high-temperature paths based on the tracking results, processes limiting commands for high-temperature paths, and updates the scheduling weights of the dual-core control response table based on the regulation results. The strategy generation module detects the energy storage path switching request signal in the communication field, extracts voltage status information by combining power parameters, performs waveform status analysis on the voltage status information, confirms the optimal switching time based on the analysis results, performs power supply path switching based on the optimal switching time, and outputs the power supply path switching strategy. The feedback update module acquires terminal response information in real time, constructs management feedback evaluation indicators by combining the dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, updates the path priority of the dual-core control response table, and synchronizes the updated dual-core control response table to the preset energy storage management platform; the modules are connected to each other by wired and / or wireless means.

[0007] The technical effects and advantages of this invention, which integrates a dual-core power supply cascaded energy storage collaborative management system and method with current balancing, are as follows: By collecting and cleaning the operating parameters of each energy storage node in a dual-core power cascaded energy storage terminal in real time, and performing dual-core role allocation, energy allocation calculation, temperature trend tracking, and power supply path analysis based on the basic dataset, a collaborative management system and method for dual-core power cascaded energy storage with integrated current balancing was realized. Compared with existing technologies, by establishing a master-slave core task response chain, the risk of task deadlock and power supply scheduling out-of-sync caused by state synchronization delay between dual cores was eliminated. By constructing a power supply capacity scoring mechanism and introducing dynamic activation logic for backup nodes, the overload power failure of low-power nodes caused by the fixed power equalization strategy under charge difference was optimized. By constructing a triple temperature judgment index, the local heat accumulation and degradation caused by the current allocation strategy being out of touch with heat dissipation status information was avoided. By optimizing the selection of power supply path switching time, the current surge phenomenon caused by switching at the voltage rise edge or peak was eliminated. The multi-node collaborative scheduling capability and dynamic load response accuracy of the dual-core power cascaded energy storage terminal were improved, ensuring the continuity of power supply under high power change conditions and the operational reliability under complex temperature rise conditions. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the dual-core power supply cascaded energy storage collaborative management method with integrated current balancing according to the present invention. Figure 2 This is a schematic diagram of the dual-core power supply cascaded energy storage collaborative management system with integrated current balancing according to the present invention. Detailed Implementation

[0009] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1:

[0010] Please see Figure 1 As shown in this embodiment, the dual-core power supply cascaded energy storage collaborative management method with integrated current balancing includes: S1. Collect the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal and perform data cleaning to output a basic dataset; the basic dataset includes power parameters, electrothermal parameters and communication fields; S2. Define roles for each energy storage node based on the basic dataset, assign roles to the parent core and child core respectively, perform task management matching based on the role assignment results, and output a dual-core control response table; S3. Extract electrical energy parameters and electrothermal parameters to construct a current dispatch matrix, perform energy allocation calculations on the current dispatch matrix, and output a multi-node current dispatch instruction set; S4. Track the node temperature trend of the energy storage node based on the electrothermal parameters, identify the high-temperature path based on the tracking results, process the high-temperature path with the limiting command, and update the scheduling weight of the dual-core control response table based on the adjustment results; S5. Detect the energy storage path switching request signal in the communication field, extract voltage status information in combination with power parameters, perform waveform status analysis on the voltage status information, confirm the optimal switching time based on the analysis results, and perform power supply path switching based on the optimal switching time, and output the power supply path switching strategy. S6. Obtain relevant terminal information in real time, construct management feedback evaluation indicators by combining dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, update the path priority of dual-core control response table, and synchronize the updated dual-core control response table to the preset energy storage management platform.

[0011] In this embodiment, the operating parameters refer to the relevant parameters reflecting the operating status of the dual-core power cascaded energy storage terminal, collected from data acquisition devices such as sensors. Data cleaning is achieved through filtering, noise reduction, and missing value imputation, resulting in a more accurate basic dataset. The electrical parameters include parameters such as SOC (State of Charge), current output, voltage output, and power supply capacity, reflecting the battery's operating status and manufacturing specifications. The electrothermal parameters include parameters such as real-time node temperature and historical temperature, indicating the conversion of electrical energy into heat energy during power supply operation. The communication fields include fields such as node address, communication response delay, and node reachability status, reflecting the communication status between nodes.

[0012] The methods for assigning roles include: The communication field is extracted from the basic dataset. Based on this communication field, the device identifier corresponding to each energy storage node is identified, and the nodes are divided into parent core energy storage nodes and child core energy storage nodes.

[0013] The process involves decoding and querying the node address of each energy storage node in the communication field to determine the corresponding hardware structure identifier in the dual-core power cascaded energy storage terminal. At the same time, based on the design requirements of the dual-core power cascaded energy storage terminal, energy storage nodes with strong communication capabilities are identified as parent core energy storage nodes, and the remaining nodes are identified as child core energy storage nodes, thus realizing the initialization of an energy storage network with a basic information structure for role division.

[0014] Write the master control core role field to each parent core energy storage node, and write the execution core role field to each child core energy storage node. Then, index and map the role fields to all energy storage nodes to construct a role configuration dictionary.

[0015] The master control core role field includes fields with control permissions, such as task scheduling permission field and control response interface field, indicating that the corresponding node plays the role of master control core; the execution core role field refers to fields such as task receiving flag bit, instruction confirmation cache configuration and status report permission bit, indicating that the corresponding node has the ability to issue control tasks in the dual-core power cascaded energy storage terminal; by mapping each role field to the node number of the corresponding energy storage node, a role configuration dictionary is formed.

[0016] Extract the task execution status record, instruction receiving address, and instruction latency from the communication parameters and bind them to the corresponding role fields in the role configuration dictionary to form a task-node mapping relationship.

[0017] The task execution status record refers to the task status report fed back by each energy storage node during the previous round of task execution, such as whether the task was successfully executed; the instruction receiving address refers to the address responded by the node after executing the task; the instruction latency refers to the time interval between the issuance of the task instruction and the receipt of the response; these information are mapped to the corresponding role fields in the role configuration dictionary and the relevant energy storage nodes to realize the mapping between the task source and the execution path.

[0018] Based on the task-node mapping relationship, a task control list is generated for the parent core energy storage node corresponding to the role field of the master control core, and a task registration list is generated for the child core energy storage node corresponding to the role field of the execution core. The task control list and the task registration list are mapped and connected to establish a master-slave core task response chain.

[0019] The task-node mapping relationship is parsed into a linked list structure. The parent core energy storage node generates a task control list containing task content, instruction information, and expected feedback time. The child core energy storage node registers its supported task types, response addresses, and execution paths to form a task registration list. The task chain is mapped by comparing the task number with the response strategy. This establishes a master-slave core task response chain with a closed loop structure, from master control to child core response, then to status receipt, and finally scheduling and judgment. This enables stable collaboration and response pairing of tasks between the two cores.

[0020] The methods for task management matching include: Write the corresponding task number and target parameter value to any task entry in the master-slave core task response chain. The task number of each task is written as a unique identifier into the corresponding task entry in the master-slave core task response chain. At the same time, the target parameter value that the task entry needs to achieve is written, such as the target current or voltage.

[0021] Identify the feedback signal corresponding to the task entry, construct a task status label set based on the feedback signal, and bind the task number with the task status label to establish a task status mapping relationship.

[0022] Each task entry corresponds to task feedback information, namely feedback signals, including task execution status, parameter execution deviation range, and execution exception interruption flags, etc. The task status label of the corresponding task entry is constructed based on the feedback signal, such as not issued, executing, or executing successfully. At the same time, the task number of the corresponding task entry is bound to the task status label to establish the connection relationship between task status and task entry.

[0023] Set the feedback update response time window and polling interval, and periodically refresh the task status mapping relationship based on the polling interval.

[0024] To ensure real-time acquisition of feedback status from sub-core energy storage nodes, the window size of the feedback update response time window is set based on the design requirements and parameter configuration of the dual-core power cascaded energy storage terminal. At the same time, a polling interval for detecting task status is defined. Within the polling interval, the task execution status is continuously refreshed and compared with the task status mapping relationship, which reduces the probability of scheduling failures caused by inconsistent task status.

[0025] When the task entry corresponding to the task status mapping relationship after each refresh does not receive valid feedback within the feedback update response time window, and the difference between the feedback parameter and the target parameter value of the task entry is greater than the preset tolerance threshold, the task status label at this time is updated, and the task is redistributed based on the priority of the corresponding energy storage node.

[0026] When the task status has not been updated for a long time or the feedback signal delay exceeds the timeout, and the error between the feedback value and the target parameter value is higher than the preset tolerance threshold set based on historical experience, the task status label of the task will be updated and marked as a failed task. Furthermore, the task will be redistributed based on the task execution priority of the corresponding energy storage node in the design requirements of the dual-core power cascaded energy storage terminal, so as to realize the fault-tolerant scheduling and load balancing adjustment of the task.

[0027] The task number, task status label, task content information of the corresponding task entry, task scheduling attributes, and feedback parameters are integrated to construct a dual-core control response table with the task number as the index. The task scheduling attributes refer to information such as the scheduling importance weight, expected execution time, and scheduling cycle label of the corresponding scheduling process when scheduling tasks. By integrating the above information, a dual-core control response table containing the complete link content of task source, task status, and task feedback is formed.

[0028] Methods for performing energy allocation calculations include: The node number of the energy storage node is used as an index to match the electrical and electrothermal parameters, and a current dispatch matrix is ​​formed in a matrix arrangement. The node number of each energy storage node is used as a row index, and all electrical and electrothermal parameters are used as column fields to form a matrix data structure. Each row represents all parameter configurations of the corresponding energy storage node, which is the current dispatch matrix. This matrix structure integrates the scattered multi-source parameters into a unified input format, which facilitates subsequent operations.

[0029] The state of charge (SOC) value and temperature rise rate of each energy storage node in the current dispatch matrix are extracted to form an operational risk index group. The SOC value and temperature rise rate of each energy storage node are combined to obtain the operational risk index group. The SOC value reflects the remaining charge of the node and reflects the power supply capacity of the corresponding battery capacity, while the temperature rise rate is used to reflect the heat load change trend of the corresponding energy storage node.

[0030] If the temperature rise rate in the operational risk index group is higher than the corresponding preset threshold and the state of charge value is lower than the safe power threshold, the corresponding energy storage node will be set as a standby node.

[0031] Based on the relevant theoretical knowledge of power generation specifications, safe power threshold and temperature rise rate threshold are set respectively. Each component in the operation risk index group is compared with the corresponding threshold. If the temperature rise rate is high and the state of charge value is low, it means that the corresponding node is in a high-risk operation state and is not suitable to participate in the power supply task. It is marked as a standby node and removed from the main scheduling process, but retained in the system resources for subsequent load surges.

[0032] In the set of relevant energy storage nodes excluding the backup nodes, the voltage response delay of each energy storage node is detected, and energy storage nodes with voltage response delays higher than a preset stabilization time threshold are selected as high-latency nodes.

[0033] Voltage response delay refers to the time required for an energy storage node to output a stable voltage after receiving a dispatch command. If this value is too large, it will cause the power supply response to lag and affect the voltage stability on the load side. Based on the relevant theoretical knowledge of power generation specifications, a preset stabilization time threshold is set, and nodes that exceed the preset stabilization time threshold are marked as high-delay nodes.

[0034] Extract and filter the historical task coverage of the remaining energy storage nodes, and calculate the power supply capacity score based on the state of charge value and historical task coverage of the energy storage node.

[0035] The historical task coverage rate refers to the proportion of the corresponding energy storage node that has successfully completed tasks in the past several scheduling cycles. The formula for calculating the power supply capacity score is as follows: ;in, This represents the power supply capacity score of a remaining energy storage node. This represents the state of charge value of the energy storage node corresponding to the power supply capacity score; This indicates the historical task coverage rate of the energy storage node corresponding to the power supply capacity score; it should be noted that... and All parameters have been normalized and belong to the same order of magnitude; and They represent and The weight, which is based on and The importance of information is assigned, with each element having a greater weight in scheduling decisions under specific operating conditions. The specific values ​​are determined based on historical power supply capacity scoring experience, while ensuring... and The sum of is 1.

[0036] The power supply capacity score is normalized to output the power supply capacity weight. The power supply capacity scores of all remaining energy storage nodes are normalized to eliminate the differences in the scoring dimensions between different nodes and uniformly map them to the same interval to obtain the corresponding power supply capacity weight, which reflects the proportion of power supply undertaken by the corresponding energy storage node in the corresponding scheduling cycle.

[0037] Obtain the load demand threshold, and calculate the product of the load demand threshold and the power supply capacity weight to obtain the target current expected value.

[0038] The load demand threshold is the theoretical maximum power of the load side for a certain scheduling cycle, set according to the design specifications and configuration requirements of the dual-core power cascaded energy storage terminal. This threshold is multiplied by the power supply capacity weight of each energy storage node that can work normally to obtain the expected target current value of the energy storage node.

[0039] Calculate the difference between the expected value of the target current and the current value of the previous adjacent scheduling cycle. If the difference is higher than the preset current change threshold, construct a correction function to perform correction calculation and obtain the corrected current value.

[0040] This process involves calculating the difference between the expected target current value and the actual current output value in the previous scheduling cycle. This difference is then compared with a preset current change threshold set based on relevant theoretical knowledge of power generation specifications. In this embodiment, an exponential decay function is used as a correction function for calculation to keep the current change rate within the theoretically safe range, thereby obtaining a corrected current value and suppressing sudden current changes.

[0041] Set a waiting window for the standby node. When the total expected value of the target current is lower than the load demand threshold within the scheduling cycle, select the standby node with the best value corresponding to the operating risk index group to enter the scheduling process.

[0042] The waiting window is a standby time interval set for the backup node. The specific size of the window is set based on historical control experience. During this period, the backup node remains in a ready state but does not participate in scheduling. When the sum of the expected target current values ​​of the main energy storage nodes cannot meet the total load demand, the node with the best corresponding operating risk index group, that is, the node with the healthiest state in the range of values ​​of each component that is closest to the theoretical state, is activated and added to the scheduling process to realize the dynamic access of the backup power supply.

[0043] Set up a buffer queue for high-latency nodes, set their target current expectation value to the basic redundant power supply, and perform low-latency load matching.

[0044] The buffer queue is a storage structure that serves as a task waiting area for high-latency nodes. The size of this storage structure is set based on the capacity occupied by the high-latency nodes, ensuring that it can accommodate all high-latency nodes and related parameter data. By calculating the expected target current value of the corresponding high-latency node and setting it as the basic redundant power supply, it is indicated that the node only undertakes redundant and protective power supply tasks rather than real-time response tasks. In this embodiment, low-time-efficiency load matching refers to prioritizing the allocation of loads with low response requirements to high-latency nodes for power supply, thereby making full use of all available power supply resources without affecting the overall response speed.

[0045] The corrected current value is combined with the corresponding energy storage node number, as well as the standby node number and the high-latency node number, to form a current dispatch instruction entry, which is written into the multi-node current dispatch instruction set. The output multi-node current dispatch instruction set serves as the execution input of the dual-core control response table, thereby realizing the implementation of multi-node cascaded energy storage.

[0046] Methods for tracking node temperature trends include: Extract the continuous scheduling cycle node temperature records of each energy storage node from the electrothermal parameters, construct a temperature sampling sequence, and plot the temperature change trend curve based on the temperature sampling sequence.

[0047] The continuous scheduling cycle refers to several adjacent consecutive scheduling cycles that have already existed in the historical records. By extracting the node temperature corresponding to each energy storage node from the electrothermal parameters, the node temperature at each timestamp in each corresponding scheduling cycle is obtained by sorting the data according to the time order. The temperature sampling sequence is then plotted as a temperature change trend curve to visually reflect the node temperature change trend.

[0048] Calculate the slope of the temperature trend curve and the rate of change of the slope over a continuous scheduling cycle. Calculate the temperature drift acceleration based on this rate of change of slope.

[0049] The temperature trend slope for the corresponding scheduling period is obtained by taking the first derivative of the temperature change trend curve. The rate of change of the slope for the continuous scheduling period is calculated by taking the first derivative to obtain the slope change rate, which reflects whether the temperature rise is accelerating or slowing down. The temperature drift acceleration is a further quantification of the slope change rate. It is calculated by taking the first derivative to determine whether the node temperature is in a state of accelerated heating.

[0050] The formula for calculating temperature drift acceleration is: ;in It represents the rate of change of the slope of the timestamp corresponding to a node in a continuous scheduling cycle; That is, the timestamps corresponding to the above nodes; This represents the temperature drift acceleration corresponding to the timestamp of the above nodes.

[0051] Screen the parent core energy storage nodes and identify the corresponding pathways. Use the temperature drift acceleration of the parent core energy storage node, the average temperature of the latest cycle node, and the average temperature of nodes in the same pathway as the temperature determination indicators.

[0052] The process involves identifying the core energy storage node within the energy storage nodes and simultaneously identifying the power supply path corresponding to that core energy storage node. The temperature determination index is formed by combining the temperature drift acceleration of the core energy storage node with the average temperature of that node in the latest collected scheduling cycle, and the average temperature of other energy storage nodes in the same power supply path.

[0053] If the temperature drift acceleration of an adjacent scheduling cycle is higher than the preset temperature rise trend threshold, the average temperature of the latest cycle node is higher than the dangerous temperature threshold, and the temperature difference between the average temperature of nodes in the same path and the average temperature of nodes in the same path is higher than the preset temperature difference upper limit, the path corresponding to the mother core energy storage node is marked as a high temperature path.

[0054] The safety operation specifications for dual-core power cascaded energy storage terminals include preset temperature rise trend thresholds, dangerous temperature thresholds, and preset temperature difference upper limits. If the temperature drift acceleration of the mother core energy storage node in an adjacent scheduling cycle is higher than the corresponding preset temperature rise trend threshold, it indicates that the node is in a rapid temperature rise state. If the average node temperature in the latest cycle is higher than the dangerous temperature threshold, it indicates that the node has entered a high-risk temperature range. If the temperature difference is higher than the preset temperature difference upper limit, it indicates that there is a significant overheating phenomenon in the power supply path of the corresponding node. At this time, the power supply path of the corresponding mother core energy storage node is identified as a high-temperature path, ensuring the accuracy and reliability of the high-temperature path judgment.

[0055] The methods for handling amplitude limiting instructions include: Set target output current limits for all energy storage nodes in the high-temperature path, and update the scheduling weights of each energy storage node in the dual-core control response table according to a fixed reduction ratio.

[0056] The system sets a target output current limit for all energy storage nodes marked as high-temperature paths. This limit is calculated proportionally based on the difference between the node's latest temperature and a temperature threshold set according to safety specifications. The closer the temperature is to the threshold, the lower the limit. At the same time, the scheduling weight of each energy storage node in the dual-core control response table on this path is reduced by a fixed proportion. This means that the corresponding node will be assigned less power supply tasks in subsequent current allocation calculations, thereby reducing its thermal load.

[0057] Setting a freeze cycle flag controls the output current weight of this channel to not exceed the set upper limit in subsequent scheduling cycles.

[0058] The freeze cycle flag is a control parameter used to limit the output current weight of the high-temperature path to not recover to the upper limit set based on safety specifications within a certain number of consecutive scheduling cycles after being marked. The number of consecutive scheduling cycles is set based on safety specifications to ensure that the high-temperature path maintains a low-load operation state until the temperature drops significantly and tends to be fully stable, thus avoiding thermal oscillation caused by immediately resuming scheduling after a brief drop in temperature.

[0059] Methods for performing waveform state analysis include: If the energy storage path switching request signal is valid, the energy storage path switching request signal corresponding to the sub-core energy storage node will be used as a trigger condition and sent to the parent core energy storage node for identification.

[0060] The energy storage path switching request signal is a path switching application signal initiated by the sub-core energy storage node when it detects insufficient power supply, abnormal temperature, or receives a system scheduling instruction. The validity of the signal means that the sub-core energy storage node has indeed detected parameter changes that meet the triggering requirements of the energy storage path switching request signal. The signal is transmitted to the parent core energy storage node through the communication channel for identification and confirmation, realizing orderly management under dual-core collaboration.

[0061] Extract the voltage status information of the relevant path corresponding to the trigger condition in the latest scheduling cycle, and construct a voltage waveform sampling sequence. The voltage status information refers to the real-time voltage output data of the power supply path related to the trigger condition. The voltage waveform sampling sequence is constructed by sampling the output voltage value and sorting it according to time.

[0062] Identify the periodic zero intersection point of the voltage waveform sampling sequence, and simultaneously extract the voltage rising edge slope or voltage falling edge slope to calculate the voltage fluctuation amplitude in the voltage waveform sampling sequence.

[0063] The zero-crossing point of the cycle refers to the moment when the voltage waveform crosses the zero potential from positive to negative or from negative to positive within a complete cycle; the voltage rise slope refers to the rate of change of the voltage as it rises from the zero-crossing point to the positive peak value; the voltage fall slope refers to the rate of change of the voltage as it falls from the positive peak value to the zero-crossing point; and the voltage fluctuation amplitude refers to the difference between the maximum and minimum values ​​of the voltage in a certain range, reflecting the stability of the voltage.

[0064] If there is a continuous segment before and after the zero intersection of the cycle where the slope of the falling edge is in a preset gentle range and the voltage fluctuation amplitude is lower than the stability tolerance threshold, then the time period corresponding to this segment is taken as the optimal switching time.

[0065] Based on relevant theoretical knowledge of power generation specifications, a preset smooth range corresponding to the voltage change slope and a stability tolerance threshold corresponding to the voltage fluctuation amplitude are set. By analyzing the voltage slope before and after the zero intersection, if there is a continuous period where the falling edge slope is in the preset smooth range and the voltage fluctuation amplitude is lower than the stability tolerance threshold, it indicates that the voltage change is smooth and the state is stable within the corresponding continuous period. Then, the time segment corresponding to this continuous period is taken as the optimal switching time, avoiding current surges caused by switching at the voltage rising edge or peak.

[0066] The methods for performing power path switching include: Once the scheduling cycle enters the optimal switching time, the voltage parameters of the target switching path are identified, and the voltage parameters are matched with the carrying capacity of the core energy storage node of the target switching path.

[0067] The process involves identifying the target power supply path to be switched, i.e., the voltage parameters of the target switching path, including voltage value, frequency, and phase; and matching the carrying capacity parameters of the parent core energy storage node of the target switching path by querying the design specifications and parameter configuration of the dual-core power cascaded energy storage terminal. The carrying capacity refers to parameters representing upper limit thresholds, such as maximum output current, rated power, and maximum load rate. The process verifies whether the target switching path has sufficient power supply capacity to meet the current load demand. The path switching operation is only allowed when the voltage parameters match and the carrying capacity is sufficient.

[0068] If the path switching conditions are met, a path switching execution command is output. This path switching execution command, along with the attribute information of the relevant paths before the switching and the attribute information of the target switching path, is integrated into a power supply path switching strategy.

[0069] Once all path switching conditions are met, a path switching execution command can be issued to control the original power supply path to disconnect and simultaneously connect to the target switching path. In order to ensure the visualization of the switching process, the relevant information of this switching is structured and integrated to form a power supply path switching strategy for recording.

[0070] Methods for constructing management feedback evaluation indicators include: The node response success rate is calculated based on the task instruction status in the dual-core control response table. The node response success rate is used to measure the task execution capability of each energy storage node. The node's response success rate is calculated by comparing the number of tasks that were successfully executed and returned valid feedback in the dual-core control response table with the total number of task instructions received by each energy storage node.

[0071] The system receives feedback information on the power supply path switching strategy and calculates the path switching stability score based on this feedback information. In this embodiment, each time feedback information on the power supply path switching strategy is received, it includes a rating for this path switching. The path switching stability score for the power supply path is obtained by averaging the ratings of each path switching belonging to the same power supply path.

[0072] Obtain instruction execution feedback data from the multi-node current scheduling instruction set, calculate the feedback current difference, and calculate the instability ratio of the number of instructions with feedback current differences exceeding a preset target tolerance threshold to the total number of instructions.

[0073] The feedback current difference is obtained by extracting the actual output current value from the instruction execution feedback data and comparing it with the corrected current value of the corresponding current dispatch instruction. At the same time, based on the relevant theoretical knowledge of power generation specifications, a preset target tolerance threshold is set, and the ratio of the number of instructions with feedback current differences higher than the corresponding threshold to the total number of instructions is used as the instability ratio to reflect the actual dispatch effect.

[0074] The system integrates node response success rate, path switching stability score, and instability ratio to output management feedback evaluation indicators.

[0075] The node response success rate, path switching stability score, and instability ratio are combined and output as a management feedback evaluation index. This index serves as the basis for updating the path priority in the dual-core control response table. The better the performance of the management feedback evaluation index matches the theoretical state, the higher the allocation weight of the corresponding power supply path can be in the subsequent scheduling process. At the same time, the index can also be used to issue early warnings and protect the dual-core power supply cascaded energy storage terminal, realizing closed-loop operation and maintenance of the dual-core power supply cascaded energy storage terminal.

[0076] This embodiment collects and cleans the operating parameters of each energy storage node in a dual-core power cascaded energy storage terminal in real time. Based on the basic dataset, it performs dual-core role allocation, energy allocation calculation, temperature trend tracking, and power supply path analysis, realizing a dual-core power cascaded energy storage collaborative management system and method with integrated current balancing. Compared with existing technologies, by establishing a master-slave core task response chain, it eliminates the risk of task deadlock and power supply scheduling out-of-sync caused by state synchronization delay between dual cores. By constructing a power supply capacity scoring mechanism and introducing dynamic activation logic for backup nodes, it optimizes the overload power failure of low-power nodes caused by the fixed power equalization strategy under charge difference. By constructing a triple temperature judgment index, it avoids local heat accumulation and degradation caused by the current allocation strategy being out of touch with heat dissipation status information. By optimizing the selection of power supply path switching time, it eliminates the current surge phenomenon caused by switching at the voltage rise edge or peak. It improves the multi-node collaborative scheduling capability and dynamic load response accuracy of the dual-core power cascaded energy storage terminal, ensuring power supply continuity under high power change conditions and operational reliability under complex temperature rise conditions. Example 2:

[0077] Please see Figure 2 As shown, parts not described in detail in this embodiment are described in Embodiment 1. A dual-core power supply cascaded energy storage collaborative management system with integrated current balancing is provided, including: The data acquisition module collects the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal and performs data cleaning to output a basic dataset; the basic dataset includes electrical parameters, electrothermal parameters and communication fields. The role allocation module defines roles for each energy storage node based on the basic dataset, assigns roles to the parent core and child core respectively, performs task management matching for the parent core and child core based on the role allocation results, and outputs a dual-core control response table. The energy consumption scheduling module extracts electrical energy parameters and electrothermal parameters to construct a current scheduling matrix, performs energy allocation calculations on the current scheduling matrix, and outputs a multi-node current scheduling instruction set. The electrothermal regulation module tracks the node temperature trend of the energy storage node based on electrothermal parameters, identifies high-temperature paths based on the tracking results, processes limiting commands for high-temperature paths, and updates the scheduling weights of the dual-core control response table based on the regulation results. The strategy generation module detects the energy storage path switching request signal in the communication field, extracts voltage status information by combining power parameters, performs waveform status analysis on the voltage status information, confirms the optimal switching time based on the analysis results, performs power supply path switching based on the optimal switching time, and outputs the power supply path switching strategy. The feedback update module acquires terminal response information in real time, constructs management feedback evaluation indicators by combining the dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, updates the path priority of the dual-core control response table, and synchronizes the updated dual-core control response table to the preset energy storage management platform; the modules are connected to each other by wired and / or wireless means.

[0078] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0079] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0080] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for coordinated management of cascaded dual-core power supplies and energy storage with integrated current balancing, characterized in that, include: S1. Collect the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal and perform data cleaning to output the basic dataset; The basic dataset includes electrical energy parameters, electrothermal parameters, and communication fields; S2. Define roles for each energy storage node based on the basic dataset, assign roles to the parent core and child core respectively, perform task management matching based on the role assignment results, and output a dual-core control response table; S3. Extract electrical energy parameters and electrothermal parameters to construct a current dispatch matrix, perform energy allocation calculations on the current dispatch matrix, and output a multi-node current dispatch instruction set; S4. Track the node temperature trend of the energy storage node based on electrothermal parameters, and identify high-temperature pathways based on the tracking results; The high-temperature path is subjected to a limiting instruction, and the scheduling weight of the dual-core control response table is updated based on the adjustment result; S5. Detect the energy storage path switching request signal in the communication field, extract voltage status information in combination with power parameters, perform waveform status analysis on the voltage status information, confirm the optimal switching time based on the analysis results, and perform power supply path switching based on the optimal switching time, and output the power supply path switching strategy. S6. Obtain relevant terminal information in real time, construct management feedback evaluation indicators by combining dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, update the path priority of dual-core control response table, and synchronize the updated dual-core control response table to the preset energy storage management platform.

2. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 1, characterized in that, The methods for assigning roles include: The communication field is extracted from the basic dataset. Based on the communication field, the device identifier corresponding to each energy storage node is identified and divided into parent core energy storage nodes and child core energy storage nodes. Write the master control core role field to each parent core energy storage node, and write the execution core role field to each child core energy storage node. Then, index and map the role fields to all energy storage nodes to construct a role configuration dictionary. Extract the task execution status record, instruction receiving address and instruction latency from the communication parameters and bind them with the corresponding role field in the role configuration dictionary to form a task-node mapping relationship; Based on the task-node mapping relationship, a task control list is generated for the parent core energy storage node corresponding to the role field of the master control core, and a task registration list is generated for the child core energy storage node corresponding to the role field of the execution core. The task control list and the task registration list are mapped and connected to establish a master-slave core task response chain.

3. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 2, characterized in that, The methods for performing task management matching include: Write the corresponding task number and target parameter value to any task entry in the master-slave core task response chain; Identify the feedback signal corresponding to the task item, construct a task status label set based on the feedback signal, and bind the task number with the task status label to establish a task status mapping relationship; Set the feedback update response time window and polling interval, and periodically refresh the task status mapping relationship based on the polling interval; When the task entry corresponding to the task status mapping relationship after each refresh does not receive valid feedback within the feedback update response time window, and the difference between the feedback parameter and the target parameter value of the task entry is greater than the preset tolerance threshold, the task status label at this time is updated, and the task is redistributed based on the priority of the corresponding energy storage node. The task number, task status label, task content information of the corresponding task entry, task scheduling attributes, and feedback parameters are integrated to construct a dual-core control response table with the task number as the index.

4. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 3, characterized in that, The methods for performing energy allocation calculations include: The node number of the energy storage node is used as an index to match the electrical energy parameters and electrothermal parameters, and a current dispatch matrix is ​​formed in a matrix arrangement. Extract the state of charge value and temperature rise rate of each energy storage node in the current dispatch matrix to form an operation risk index group; if the temperature rise rate in the operation risk index group is higher than the corresponding preset threshold and the state of charge value is lower than the safe power threshold, the corresponding energy storage node is set as a standby node. In the set of relevant energy storage nodes excluding the backup nodes, the voltage response delay of each energy storage node is detected, and energy storage nodes with voltage response delays higher than the preset stabilization time threshold are selected as high-latency nodes. Extract and filter the historical task coverage of the remaining energy storage nodes, calculate the power supply capacity score based on the state of charge value and historical task coverage of the energy storage node, and normalize the power supply capacity score to output the power supply capacity weight. Obtain the load demand threshold, calculate the product of the load demand threshold and the power supply capacity weight to obtain the target current expected value; calculate the difference between the target current expected value and the current value of the previous adjacent scheduling cycle; if the difference is higher than the preset current change threshold, construct a correction function to perform correction calculation to obtain the corrected current value. Set a waiting window for the standby node. When the total expected value of the target current within the scheduling cycle is lower than the load demand threshold, select the standby node with the lowest value in the operating risk index group to enter the scheduling process. Set up a buffer queue for high-latency nodes, set their target current expectation value to the basic redundant power supply, and perform low-latency load matching; The corrected current value is combined with the corresponding energy storage node number, as well as the standby node number and the high-latency node number, into a current dispatch instruction entry, which is then written into the multi-node current dispatch instruction set.

5. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 4, characterized in that, The methods for tracking node temperature trends include: Extract the continuous scheduling cycle node temperature records of each energy storage node from the electrothermal parameters, construct a temperature sampling sequence, and plot the temperature change trend curve based on the temperature sampling sequence; Calculate the slope of the temperature trend curve and the rate of change of the slope over a continuous scheduling cycle. Calculate the temperature drift acceleration based on this rate of change of slope. Screen the parent core energy storage nodes and identify the corresponding pathways. Use the temperature drift acceleration of the parent core energy storage node, the average temperature of the latest cycle node, and the average temperature of the nodes in the same pathway as the temperature judgment indicators. If the temperature drift acceleration of an adjacent scheduling cycle is higher than the preset temperature rise trend threshold, the average temperature of the latest cycle node is higher than the dangerous temperature threshold, and the temperature difference between the average temperature of nodes in the same path and the average temperature of nodes in the same path is higher than the preset temperature difference upper limit, the path corresponding to the mother core energy storage node is marked as a high temperature path.

6. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 5, characterized in that, The methods for processing the amplitude limiting command include: Set target output current limit values ​​for all energy storage nodes in the high-temperature path, and update the scheduling weights of each energy storage node in the dual-core control response table according to a fixed reduction ratio. Setting a freeze cycle flag controls the output current weight of this channel to not exceed the set upper limit in subsequent scheduling cycles.

7. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 6, characterized in that, The methods for performing waveform state analysis include: If the energy storage path switching request signal is valid, the energy storage path switching request signal corresponding to the sub-core energy storage node will be used as the trigger condition and sent to the parent core energy storage node for identification. Extract the voltage state information of the relevant paths corresponding to the triggering conditions in the latest scheduling cycle, and construct a voltage waveform sampling sequence; Identify the periodic zero intersection of the voltage waveform sampling sequence, and simultaneously extract the voltage rising edge slope or voltage falling edge slope to calculate the voltage fluctuation amplitude in the voltage waveform sampling sequence; if there is a continuous segment before and after the periodic zero intersection where the falling edge slope is in a preset flat range and the voltage fluctuation amplitude is lower than the stability tolerance threshold, then the time period corresponding to this segment is taken as the optimal switching time.

8. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 7, characterized in that, The methods for switching the power supply path include: Once the scheduling cycle enters the optimal switching time, the voltage parameters of the target switching path are identified, and the voltage parameters are matched with the carrying capacity of the core energy storage node of the target switching path. If the path switching conditions are met, a path switching execution command is output. This path switching execution command, along with the attribute information of the relevant paths before the switching and the attribute information of the target switching path, is integrated into a power supply path switching strategy.

9. The dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in claim 8, characterized in that, The methods for constructing management feedback evaluation indicators include: Calculate the node response success rate based on the task instruction status in the dual-core control response table; Receive feedback information on the power supply path switching strategy and calculate the path switching stability score based on the feedback information; Obtain instruction execution feedback data from the multi-node current scheduling instruction set, calculate the feedback current difference, and calculate the instability ratio of the number of instructions with feedback current differences exceeding the preset target tolerance threshold to the total number. The system integrates node response success rate, path switching stability score, and instability ratio to output management feedback evaluation indicators.

10. A dual-core power supply cascaded energy storage collaborative management system with integrated current balancing, used to implement the dual-core power supply cascaded energy storage collaborative management method with integrated current balancing as described in any one of claims 1-9, characterized in that, include: The data acquisition module collects the operating parameters of each energy storage node in the dual-core power cascaded energy storage terminal, performs data cleaning, and outputs a basic dataset. The basic dataset includes electrical energy parameters, electrothermal parameters, and communication fields; The role allocation module defines roles for each energy storage node based on the basic dataset, assigns roles to the parent core and child core respectively, performs task management matching based on the role allocation results, and outputs a dual-core control response table. The energy consumption scheduling module extracts electrical energy parameters and electrothermal parameters to construct a current scheduling matrix, performs energy allocation calculations on the current scheduling matrix, and outputs a multi-node current scheduling instruction set. The electrothermal regulation module tracks the node temperature trend of the energy storage node based on electrothermal parameters and identifies high-temperature pathways based on the tracking results. The high-temperature path is subjected to a limiting instruction, and the scheduling weight of the dual-core control response table is updated based on the adjustment result; The strategy generation module detects the energy storage path switching request signal in the communication field, extracts voltage status information by combining power parameters, performs waveform status analysis on the voltage status information, confirms the optimal switching time based on the analysis results, performs power supply path switching based on the optimal switching time, and outputs the power supply path switching strategy. The feedback update module acquires terminal response information in real time, constructs management feedback evaluation indicators by combining the dual-core control response table, multi-node current scheduling instruction set and power supply path switching strategy, updates the path priority of the dual-core control response table, and synchronizes the updated dual-core control response table to the preset energy storage management platform; the modules are connected to each other by wired and / or wireless means.

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