Electrochemical energy storage power station battery management system

Abstract

The invention provides an electrochemical energy storage power station battery management system, and belongs to the technical field of batteries. State data of a single battery is obtained through a high-precision voltage acquisition module and a multi-point temperature sensor, data processing and verification are carried out through a slave battery management unit, and the state of charge is estimated in combination with current data. And the main battery management unit receives the uploaded comprehensive state data, triggers thermal management according to a temperature abnormity rule, judges an operation risk by combining the voltage and the state of charge, and limits charging and discharging parameters when necessary. Meanwhile, the method can also identify a single body imbalance phenomenon and start equalization operation, and finally feeds back acceptable maximum charging and discharging power to the energy storage converter. According to the system, accurate monitoring of the battery state, timely processing of abnormal conditions and dynamic optimization of operating parameters are realized, and the safety and efficiency of battery management are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery management system for an electrochemical energy storage power station. Background Art

[0002] Battery management systems face a complex technical challenge in practical operation: how to achieve accurate battery status monitoring and balancing control within a multi-level architecture while ensuring real-time performance and reliability. Specifically, the battery monitoring circuitry must frequently collect voltage and temperature data from a large number of battery cells. This data is transmitted to the main battery management unit (BMU) via a multi-level CAN bus, subject to potential data loss or delays during transmission. The BMU must rapidly process this massive amount of data, calculate the overall state of charge, and make decisions regarding thermal management and balancing control, placing high demands on computing power. Furthermore, balancing control requires precise control of the charge and discharge processes of each battery cell, but the number and power of DC / DC converters limit its ability to simultaneously adjust all unbalanced cells. Under high-load conditions, balancing control can conflict with the main charging and discharging processes, impacting overall system performance. Coordinating these various management units to achieve fast and accurate status monitoring and balancing control within limited hardware resources and communication bandwidth remains a key technical challenge facing this system. Summary of the Invention

[0003] The present invention provides a battery management system for an electrochemical energy storage power station, which mainly includes:

[0004] The battery monitoring circuit deploys a high-precision voltage acquisition module and multi-point temperature sensors for each battery cell, acquiring voltage and temperature data with millivolt-level accuracy. This data is then sent to the slave battery management unit at a fixed data transmission frequency using the format specified by the CCAN communication protocol version to obtain a preliminary cell status data set.

[0005] receiving the cell status data set from the battery management unit via the CCAN interface, smoothing the voltage data using a voltage signal filtering method, correcting temperature deviations using a temperature data calibration method, and verifying data reliability using a communication error checking mechanism to determine a processed cell voltage and temperature data set;

[0006] Collecting the total current data of the battery cabinet from the battery management unit through the SCAN interface, combining it with the processed single cell voltage and temperature data sets, and estimating the state of charge of the battery cabinet according to the state of charge calculation logic to obtain a comprehensive state data set including current, voltage, temperature and state of charge;

[0007] The slave battery management unit sorts the comprehensive status data set according to data upload priority through an optimized channel under the bandwidth limitation of the MCAN interface, compresses the voltage data using a voltage data compression algorithm, and ensures transmission stability through a communication interruption recovery mechanism. The data is uploaded to the master battery management unit to obtain a complete upload status data set;

[0008] The main battery management unit receives the uploaded status data set and compares the cell temperature data one by one against the temperature anomaly marking rules. If it is found that the temperature of a cell exceeds the preset threshold or the temperature difference between cells exceeds the predetermined range, it sends a start command to the liquid cooling system through the CAN interface to obtain a thermal management trigger signal;

[0009] Based on the thermal management trigger signal, the main battery management unit combines the cell voltage and state of charge data to determine the battery operation risk level. If the risk level is higher than the preset standard, it sends a command to limit the charge and discharge current to the energy storage converter via the Ethernet interface. At the same time, it notifies the monitoring system through the 485 interface to adjust the voltage upper limit and obtain the restricted operation parameter set;

[0010] receiving the restricted operating parameter set from the battery management unit, determining whether there is a battery cell state of charge imbalance based on the battery cell voltage data and operating status, and if there is an imbalance, selecting a corresponding battery cell channel through internal control logic, starting a balancing DC converter to charge or discharge the target cell, and obtaining a balanced cell state update set;

[0011] The main battery management unit extracts the latest data from the balanced single cell status update set, verifies the data consistency through the data integrity verification mechanism, and determines whether the overall operation of the battery cabinet is stable. If the overall operating status is within the preset safety range, the current acceptable maximum charge and discharge power is fed back to the energy storage inverter through the CAN interface to obtain the final operation optimization instruction set.

[0012] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0013] The present invention discloses a battery management system and method, which obtains battery cell status data through a high-precision voltage acquisition module and a multi-point temperature sensor, processes and verifies the data using a slave battery management unit, and estimates the state of charge in combination with current data. The master battery management unit receives the uploaded comprehensive status data, triggers thermal management based on temperature anomaly rules, and judges operating risks in combination with voltage and state of charge, limiting charge and discharge parameters when necessary. At the same time, the present invention can also identify single cell imbalance and initiate balancing operations, ultimately feeding back the acceptable maximum charge and discharge power to the energy storage converter. The system achieves accurate monitoring of battery status, timely handling of abnormal situations, and dynamic optimization of operating parameters, effectively improving the safety and efficiency of battery management. DETAILED DESCRIPTION

[0014] The technical solutions in the embodiments of the present invention are described clearly and in detail. The described embodiments are only a part of the embodiments of the present invention.

[0015] In this embodiment, a battery management system for an electrochemical energy storage power station may specifically include:

[0016] Multiple battery monitoring circuits for detecting battery cell parameters;

[0017] at least one slave battery management unit, communicating with the battery monitoring circuit and configured to collect battery pack parameters;

[0018] a master battery management unit, communicating with the slave battery management unit for system information management and state of charge calculation;

[0019] and a communication bus for data transmission between the battery monitoring circuit, the slave battery management unit and the master battery management unit;

[0020] The system is used for battery pack thermal management and battery cell balancing management.

[0021] Here, the above system specifically includes:

[0022] The battery monitoring circuit deploys a high-precision voltage acquisition module and multi-point temperature sensor distribution for each battery cell, acquiring voltage and temperature data with millivolt-level accuracy. The data is then sent to the slave battery management unit at a fixed data transmission frequency in the format specified by the CCAN communication protocol version, thereby obtaining a preliminary cell status data set.

[0023] The slave battery management unit receives the single-cell status data set through the CCAN interface, smoothes the voltage data using a voltage signal filtering method, corrects temperature deviations using a temperature data calibration method, and verifies data reliability using a communication error checking mechanism to determine the processed single-cell voltage and temperature data set; the slave battery management unit collects the total current data of the battery cabinet through the SCAN interface, combines the processed single-cell voltage and temperature data set, and estimates the state of charge of the battery cabinet according to the state of charge calculation logic to obtain a comprehensive status data set including current, voltage, temperature and state of charge; the slave battery management unit sorts the comprehensive status data set according to data upload priority through an optimized channel under the bandwidth limitation of the MCAN interface, compresses the voltage data using a voltage data compression algorithm, and ensures transmission stability through a communication interruption recovery mechanism, and uploads it to the master battery management unit to obtain a complete upload status data set;

[0024] The main battery management unit receives the uploaded status data set and compares the cell temperature data one by one against the temperature anomaly marking rule. If it is found that the temperature of a cell exceeds a preset threshold or the temperature difference between cells exceeds a predetermined range, a start instruction is sent to the liquid cooling system via the CAN interface to obtain a thermal management trigger signal. Based on the thermal management trigger signal, the main battery management unit combines the cell voltage and state of charge data to determine the battery operation risk level. If the risk level is higher than the preset standard, an instruction to limit the charge and discharge current is sent to the energy storage converter via the Ethernet interface. At the same time, the monitoring system is notified via the 485 interface to adjust the voltage upper limit to obtain a restricted operation parameter set.

[0025] receiving the restricted operating parameter set from the battery management unit, determining whether there is a battery cell state of charge imbalance based on the battery cell voltage data and operating status, and if there is an imbalance, selecting a corresponding battery cell channel through internal control logic, starting a balancing DC converter to charge or discharge the target cell, and obtaining a balanced cell state update set;

[0026] The main battery management unit extracts the latest data from the balanced single cell status update set, verifies the data consistency through the data integrity verification mechanism, and determines whether the overall operation of the battery cabinet is stable. If the overall operating status is within the preset safety range, the current acceptable maximum charge and discharge power is fed back to the energy storage inverter through the CAN interface to obtain the final operation optimization instruction set.

[0027] To understand the technical solution of this application, the following describes the technical details of the technical solution of this application in detail. The electrochemical energy storage power station battery management system of this application is used to perform the following steps:

[0028] S101. The battery monitoring circuit deploys a high-precision voltage acquisition module and a multi-point temperature sensor distribution for each battery cell to obtain voltage data and temperature data with a cell voltage acquisition accuracy of millivolt level. The data is sent to the slave battery management unit at a fixed data transmission frequency in the format specified by the CCAN communication protocol version to obtain a preliminary cell status data set.

[0029] By collecting voltage and monitoring battery cells with temperature sensors, high-precision millivolt data and multi-point temperature data generated by a module are acquired to form an initial dataset. Based on this initial dataset, the voltage data is initially screened using a preset threshold range. If a cell's voltage exceeds the threshold, it is marked as an abnormal data point, generating an abnormally marked dataset. Within this abnormally marked dataset, correlation and comparison are performed on the multi-point temperature data. If the temperature data at the location corresponding to the abnormal data point is excessively high or low, the cell is identified as potentially faulty, generating a list of fault candidates. Cell status information is obtained from the candidate list and, combined with fixed-frequency data transmitted via the CCAN protocol, time series analysis is performed on the potentially faulty cells to determine their voltage and temperature trends, generating trend analysis results. Based on the trend analysis results, a support vector machine algorithm is used to classify the trends, distinguishing between persistent abnormalities and temporary fluctuations, and identifying a list of cells with persistent abnormalities. Using the persistently abnormal cell list and historical data from the management unit, the locations of the abnormal cells are spatially mapped to generate an abnormality distribution map. According to the abnormal distribution map, a targeted monitoring frequency adjustment strategy is generated for the location information and status of the abnormal monomer, and the adjusted data transmission plan is output.

[0030] S102. Receive the cell status data set from the battery management unit via the CCAN interface, smooth the voltage data using a voltage signal filtering method, correct the temperature deviation using a temperature data calibration method, and verify the data reliability using a communication error checking mechanism to determine the processed cell voltage and temperature data set.

[0031] The initial cell status dataset is obtained from the battery management unit via the CCAN interface. The voltage and temperature data contained therein are initially stored to verify the integrity of the original dataset. Based on the stored original dataset, the voltage data is smoothed using a filtering method to eliminate noise interference, resulting in a smoothed voltage dataset. The temperature data is calibrated to correct for deviations in the smoothed voltage dataset and the original temperature data, resulting in a corrected temperature dataset. The smoothed voltage and corrected temperature datasets are verified for reliability using a communication verification mechanism. If the verification results indicate data anomalies, the original dataset is re-acquired; if the verification results are normal, the processed dataset is confirmed. Based on the processed dataset, the cell status stability is analyzed and compared using a preset threshold. If the cell status exceeds the threshold range, it is marked as abnormal, resulting in an abnormality-marked dataset. The abnormality-marked dataset is classified using a support vector machine algorithm to distinguish different abnormalities and determine a classified abnormality feature set. This classified abnormality feature set, combined with the battery management system's operational log data, is used to trace the context of the abnormality and obtain the final abnormality analysis dataset.

[0032] S103. Collect the total current data of the battery cabinet from the battery management unit through the SCAN interface, combine it with the processed single cell voltage and temperature data set, estimate the charge state of the battery cabinet according to the charge state calculation logic, and obtain a comprehensive status data set including current, voltage, temperature and charge state.

[0033] Total current data is obtained from the battery management unit through a data interface and continuously monitored at a preset acquisition frequency to generate an initial current dataset. Based on this initial current dataset, the battery cell voltage and temperature data are integrated, and data cleaning methods are used to remove outliers to determine a processed basic status dataset. Based on this processed basic status dataset, computational logic is applied to estimate the state of charge (SOC), and a Kalman filter algorithm is used for state prediction to obtain a preliminary SOC value. If the preliminary SOC value exceeds the preset threshold, the basic status dataset is recalibrated, integrating historical data for bias correction, and determining the calibrated SOC value. Based on this calibrated SOC value, the processed current, voltage, and temperature data are combined to construct a comprehensive status dataset, providing complete battery cabinet status information. The comprehensive status dataset is used to analyze correlations between parameters. If any parameter experiences abnormal fluctuations, a data backtracking mechanism is triggered to identify the source of the anomaly and update the dataset. Time series analysis is used on this updated comprehensive status dataset to predict the battery cabinet status trend and obtain a future state forecast.

[0034] S104. The slave battery management unit uses an optimized channel under the bandwidth limitation of the MCAN interface to sort the comprehensive status data set according to the data upload priority, compress the voltage data using a voltage data compression algorithm, and ensure transmission stability through a communication interruption recovery mechanism. The data is uploaded to the master battery management unit to obtain a complete upload status data set.

[0035] The battery management unit's interface optimization mechanism acquires an initial comprehensive status data set and performs preliminary classification to produce a classified status data set. Based on the classified status data set, the data is sorted using a priority sorting rule to determine the transmission order of high- and low-priority data. For high-priority data, a voltage data compression algorithm is used to process the voltage-related data to produce a compressed voltage data set. If the compressed voltage data set is interrupted during transmission, the communication recovery mechanism detects and repairs the transmission link to determine whether the transmission stability meets the preset threshold. If the transmission stability meets the preset threshold, the compressed voltage data set is uploaded to the main management unit via the optimized MCAN interface channel to obtain the uploaded status data record. Based on the uploaded status data record, the subsequent transmission of low-priority data is scheduled to determine the complete uploaded status data set. The complete uploaded status data set is verified to determine whether the data integrity meets the preset standard, resulting in the final transmission result.

[0036] S105. The main battery management unit receives the uploaded status data set and compares the cell temperature data one by one according to the temperature anomaly marking rule. If it is found that the temperature of a certain cell exceeds the preset threshold or the temperature difference between cells exceeds the predetermined range, a start command is sent to the liquid cooling system through the CAN interface to obtain a thermal management trigger signal.

[0037] The battery management unit extracts cell temperature data from the uploaded status data and performs a preliminary analysis of each data set to determine the cell temperature distribution characteristics. Based on the distribution characteristics, the system compares each cell temperature data against the temperature anomaly rules, using a preset temperature threshold and a predetermined temperature difference range as a benchmark, to determine whether any conditions exceed the threshold or the temperature difference exceeds the predetermined range. If a cell temperature exceeds the preset temperature threshold or the temperature difference between cells exceeds the predetermined range, a startup command is sent to the liquid cooling system via the CAN interface to obtain the corresponding response status. Based on the response status, the system analyzes whether the liquid cooling system startup is successful. If the response status indicates failure, the startup command is sent again via the CAN interface to determine the execution result of the startup command. After obtaining the startup command execution result, the thermal management trigger signal is recorded and verified to determine whether the signal meets the preset trigger conditions. If the thermal management trigger signal meets the trigger conditions, the system continuously monitors the changing trend of the cell temperature data to obtain real-time temperature control feedback. Based on the temperature control feedback, the system dynamically adjusts the operating parameters of the liquid cooling system to determine whether further optimization of the thermal management trigger mechanism is needed to achieve the final system stable state.

[0038] S106. Based on the thermal management trigger signal, the main battery management unit combines the cell voltage and state of charge data to determine the battery operation risk level. If the risk level is higher than the preset standard, it sends an instruction to limit the charge and discharge current to the energy storage converter through the Ethernet interface. At the same time, it notifies the monitoring system through the 485 interface to adjust the voltage upper limit and obtain the restricted operation parameter set.

[0039] By collecting thermal management signals and processing them in conjunction with the main battery management module, the system obtains cell voltage data and state-of-charge values ​​to determine the battery's operational risk level. If the operational risk level exceeds a preset threshold, a charge / discharge current limit instruction is transmitted to the energy storage converter via the Ethernet interface, generating a preliminary control signal. Based on this charge / discharge current limit instruction and combined with data processing on the monitoring system, the voltage upper limit is adjusted to determine the initial range of the restricted operational parameter set. Within this initial range of the restricted operational parameter set, a support vector machine algorithm is used to classify and analyze the cell voltage data and state-of-charge values ​​to obtain optimized parameter boundaries. Based on these optimized parameter boundaries and combined with real-time feedback data from the energy storage converter, the need for dynamic charge / discharge current adjustment is determined. If the feedback data exceeds the parameter boundaries, a correction instruction is generated. Based on this correction instruction and combined with the control logic of the main battery management, the final value of the restricted parameter set is adjusted to determine a battery management strategy appropriate for the current operational status. The final restricted parameter set, combined with the monitoring system's logging function, stores the operational risk level and adjusted voltage upper limit, providing a basis for continuous monitoring of the system's operational status.

[0040] S107: Receive the restricted operating parameter set from the battery management unit, and determine whether there is a battery cell state of charge imbalance based on the battery cell voltage data and operating status. If there is an imbalance, select the corresponding battery cell channel through the internal control logic, start the balancing DC converter to charge or discharge the target cell, and obtain a balanced cell state update set.

[0041] The battery management unit collects operating parameters and cell voltage data, monitoring the operating status of each cell in real time to generate a preliminary SOC distribution set. Based on the SOC distribution set, the system analyzes whether imbalance exists. If the SOC difference between cells exceeds a preset threshold, imbalance is determined and an imbalance indicator set is generated. Based on the imbalance indicator set, the internal control logic locates the target cell and selects the corresponding channel using a pre-established mapping table to generate a target cell channel set. Based on the target cell channel set, the DC converter is activated to charge or discharge the target cell, generating an updated cell state set. Based on the updated cell state set, the SOC distribution of each cell is recalculated. If imbalance still exists, the DC converter operating parameters are iteratively adjusted to generate an optimized state adjustment set. This optimized state adjustment set, combined with historical operating parameter data, uses a support vector machine algorithm to predict long-term SOC trends, determine potential imbalance risks, and generate a risk assessment set. Through the risk assessment set, based on the predicted potential imbalance risks, the priority strategy of the internal control logic is adjusted, the key target entities for subsequent monitoring and balancing operations are determined, and an updated monitoring strategy set is obtained.

[0042] S108. The main battery management unit extracts the latest data from the balanced single cell status update set, verifies the data consistency through the data integrity verification mechanism, and determines whether the overall operation of the battery cabinet is stable. If the overall operating status is within the preset safety range, the current acceptable maximum charge and discharge power is fed back to the energy storage inverter through the CAN interface to obtain the final operation optimization instruction set.

[0043] By extracting the latest data from the balanced cell status set and applying a data integrity verification mechanism to verify the collected information, the system determines whether the data meets consistency requirements and obtains preliminary data reliability results. Based on this preliminary data reliability result, the status information after data consistency verification is compared against a preset threshold range. If the consistency verification result meets the preset standard, the overall operation of the battery cabinet is determined to be stable. By confirming the overall stable operation of the battery cabinet, the degree of compatibility between the operating status and the safety range is determined. If the operating status is within the preset safety range, the system is determined to enter the power feedback phase. Based on the results of the power feedback phase, the currently acceptable charge and discharge power data is transmitted to the energy storage inverter via the CAN interface, and the energy storage inverter returns power allocation information. Based on the power allocation information returned by the energy storage inverter, the support vector machine algorithm is used to evaluate the rationality of the power allocation and obtain an optimized power allocation plan. Based on the optimized power allocation plan, the final operation optimization instruction set is generated. The instruction set is then determined to be compatible with the current battery management state. If so, the instruction set is determined to be executable. Based on the executable judgment of the instruction set, the optimized instruction set is transmitted to the battery management system through the feedback mechanism to complete the dynamic adjustment of the operating status.

[0044] The present invention discloses a battery management system and method, which obtains battery cell status data through a high-precision voltage acquisition module and a multi-point temperature sensor, processes and verifies the data using a slave battery management unit, and estimates the state of charge in combination with current data. The master battery management unit receives the uploaded comprehensive status data, triggers thermal management based on temperature anomaly rules, and judges operating risks in combination with voltage and state of charge, limiting charge and discharge parameters when necessary. At the same time, the present invention can also identify single cell imbalance and initiate balancing operations, ultimately feeding back the acceptable maximum charge and discharge power to the energy storage converter. The system achieves accurate monitoring of battery status, timely handling of abnormal situations, and dynamic optimization of operating parameters, effectively improving the safety and efficiency of battery management.

[0045] The above embodiments are intended to illustrate the technical solutions of the present invention and are not intended to limit the present invention. The present invention is described in detail with reference to the preferred embodiments. It should be understood by those skilled in the art that the technical solutions of the present invention may be modified or replaced with equivalents without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications and replacements should be included within the scope of the claims of the present invention.

Claims

1. A battery management system for an electrochemical energy storage power station, characterized in that: The system comprises: Multiple battery monitoring circuits for detecting battery cell parameters; at least one slave battery management unit, communicating with the battery monitoring circuit and configured to collect battery pack parameters; a master battery management unit, communicating with the slave battery management unit for system information management and state of charge calculation; and a communication bus for data transmission between the battery monitoring circuit, the slave battery management unit and the master battery management unit; The system is used for battery pack thermal management and battery cell balancing management.

2. The electrochemical energy storage power station battery management system according to claim 1, characterized in that: The battery monitoring circuit deploys a high-precision voltage acquisition module and multi-point temperature sensor distribution for each battery cell, acquiring voltage and temperature data with millivolt-level accuracy. The data is then sent to the slave battery management unit at a fixed data transmission frequency in the format specified by the CCAN communication protocol version, thereby obtaining a preliminary cell status data set. The slave battery management unit receives the single-cell status data set through the CCAN interface, smoothes the voltage data using a voltage signal filtering method, corrects temperature deviations using a temperature data calibration method, and verifies data reliability using a communication error checking mechanism to determine the processed single-cell voltage and temperature data set; the slave battery management unit collects the total current data of the battery cabinet through the SCAN interface, combines the processed single-cell voltage and temperature data set, and estimates the state of charge of the battery cabinet according to the state of charge calculation logic to obtain a comprehensive status data set including current, voltage, temperature and state of charge; the slave battery management unit sorts the comprehensive status data set according to data upload priority through an optimized channel under the bandwidth limitation of the MCAN interface, compresses the voltage data using a voltage data compression algorithm, and ensures transmission stability through a communication interruption recovery mechanism, and uploads it to the master battery management unit to obtain a complete upload status data set; The main battery management unit receives the uploaded status data set and compares the cell temperature data one by one against the temperature anomaly marking rule. If it is found that the temperature of a cell exceeds a preset threshold or the temperature difference between cells exceeds a predetermined range, a start instruction is sent to the liquid cooling system via the CAN interface to obtain a thermal management trigger signal. Based on the thermal management trigger signal, the main battery management unit combines the cell voltage and state of charge data to determine the battery operation risk level. If the risk level is higher than the preset standard, an instruction to limit the charge and discharge current is sent to the energy storage converter via the Ethernet interface. At the same time, the monitoring system is notified via the 485 interface to adjust the voltage upper limit to obtain a restricted operation parameter set. receiving the restricted operating parameter set from the battery management unit, determining whether there is a battery cell state of charge imbalance based on the battery cell voltage data and operating status, and if there is an imbalance, selecting a corresponding battery cell channel through internal control logic, starting a balancing DC converter to charge or discharge the target cell, and obtaining a balanced cell state update set; The main battery management unit extracts the latest data from the balanced single cell status update set, verifies the data consistency through the data integrity verification mechanism, and determines whether the overall operation of the battery cabinet is stable. If the overall operating status is within the preset safety range, the current acceptable maximum charge and discharge power is fed back to the energy storage inverter through the CAN interface to obtain the final operation optimization instruction set.

3. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The battery monitoring circuit deploys a high-precision voltage acquisition module and multi-point temperature sensor distribution for each battery cell, acquiring voltage and temperature data with millivolt-level accuracy. This data is then sent to the slave battery management unit at a fixed data transmission frequency in the format specified by the CCAN communication protocol version, obtaining a preliminary cell status data set, including: By collecting voltage and monitoring temperature sensors on battery cells, we obtain millivolt-level data generated by high-precision modules and multi-point distributed temperature data to form an initial data set. Based on the initial data set, the voltage data is preliminarily screened using a preset threshold range. If a single cell voltage data exceeds the threshold range, it is marked as an abnormal data point, and an abnormal marked data set is obtained; For the abnormal marked data set, by correlating and comparing the temperature data distributed at multiple points, if the temperature data at the location corresponding to the abnormal data point is too high or too low, it is determined to be a potential fault unit and a list of fault candidates is obtained; Obtain cell status information from the fault candidate list, combine it with the fixed-frequency data transmitted by the CCAN protocol, perform time series analysis on the potential fault cells, determine their voltage and temperature change trends, and obtain trend analysis results; Based on the trend analysis results, the support vector machine algorithm is used to classify the change trend, distinguish between the two states of continuous abnormality and temporary fluctuation, and determine the list of monomers with continuous abnormality; By continuously listing abnormal monomers and combining them with historical data records of management units, we can spatially map the distribution locations of abnormal monomers and obtain an abnormal distribution map. According to the abnormal distribution map, a targeted monitoring frequency adjustment strategy is generated for the location information and status of the abnormal monomer, and the adjusted data transmission plan is output.

4. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The slave battery management unit receives the cell status data set through the CCAN interface, smoothes the voltage data using a voltage signal filtering method, corrects the temperature deviation using a temperature data calibration method, and verifies the data reliability using a communication error checking mechanism to determine the processed cell voltage and temperature data set, including: Obtain the initial cell status data set from the battery management unit through the CCAN interface, perform preliminary storage on the voltage and temperature data contained therein, and determine the integrity of the original data set; According to the stored original data set, the voltage data is smoothed by using a filtering method to eliminate noise interference and obtain a smoothed voltage data set; For the smoothed voltage data set and the original temperature data, a calibration method is used to correct the deviation of the temperature data to obtain a corrected temperature data set; The smoothed voltage dataset and the corrected temperature dataset are verified for reliability through a communication verification mechanism. If the verification result shows data anomalies, the original dataset is retrieved again. If the verification result is normal, the processed data set is confirmed; Based on the processed data set, the stability of the monomer state is analyzed and compared using a preset threshold. If the monomer state exceeds the threshold range, it is marked as an abnormal state to obtain an abnormal marked data set; For the abnormal labeling data set, the support vector machine algorithm is used to perform classification processing, distinguish different types of abnormal states, and determine the abnormal feature set after classification; By combining the classified anomaly feature set with the battery management operation log data, the context information of the anomaly is traced back to obtain the final anomaly analysis data set.

5. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The slave battery management unit collects the total current data of the battery cabinet through the SCAN interface, combines the processed single cell voltage and temperature data sets, and estimates the state of charge of the battery cabinet according to the state of charge calculation logic to obtain a comprehensive state data set including current, voltage, temperature and state of charge, including: Obtain total current data from the battery management unit through the data interface, continuously monitor using a preset acquisition frequency, and obtain an initial current data set; Based on the initial current data set, the cell voltage and temperature data are fused, and the data cleaning method is used to remove outliers to determine the processed basic state data set; For the processed basic state data set, the calculation logic is applied to estimate the state of charge, and the Kalman filter algorithm is used for state prediction to obtain the preliminary state of charge value; If the initial state of charge value exceeds the preset threshold range, the basic state data set is recalibrated, the historical data is integrated to correct the deviation, and the calibrated state of charge value is determined; Based on the calibrated state of charge value and combined with the processed current, voltage and temperature data, a comprehensive status data set is constructed to obtain complete battery cabinet status information; By integrating the status data set, the correlation between various parameters is analyzed. If a parameter fluctuates abnormally, the data backtracking mechanism is triggered to determine the source of the anomaly and update the data set. For the updated comprehensive status data set, the time series analysis method is used to predict the status change trend of the battery cabinet and obtain the status estimation results for a period of time in the future.

6. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The slave battery management unit uses the optimized channel under the bandwidth limitation of the MCAN interface to sort the comprehensive status data set according to the data upload priority, compresses the voltage data using a voltage data compression algorithm, and ensures transmission stability through a communication interruption recovery mechanism. The data is uploaded to the master battery management unit to obtain a complete upload status data set, including: Through the interface optimization mechanism of the battery management unit, the initial comprehensive status data set is obtained, and the data is preliminarily classified and processed to obtain the classified status data group; According to the classified status data groups, the data is arranged using priority sorting rules to determine the transmission order of high-priority data and low-priority data; For high-priority data, a voltage data compression algorithm is used to process voltage-related data to obtain a compressed voltage data group; If the compressed voltage data group is interrupted during transmission, the transmission link is detected and repaired through the communication recovery mechanism to determine whether the transmission stability reaches the preset threshold; If the transmission stability reaches the preset threshold, the compressed voltage data group is uploaded to the main management unit through the optimized MCAN interface channel to obtain the uploaded status data record; According to the status data record after uploading, arrange the subsequent transmission of low-priority data and determine the complete upload status data set; By verifying the complete uploaded status data set, we can determine whether the data integrity meets the preset standards and obtain the final transmission result.

7. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The main battery management unit receives the uploaded status data set and compares the cell temperature data one by one according to the temperature anomaly marking rule. If it is found that the temperature of a cell exceeds a preset threshold or the temperature difference between cells exceeds a predetermined range, a start instruction is sent to the liquid cooling system via the CAN interface to obtain a thermal management trigger signal, including: The battery management unit extracts cell temperature data from the uploaded status data, performs preliminary analysis on each set of data, and obtains the distribution characteristics of cell temperature; Based on the distribution characteristics, the preset temperature threshold and predetermined temperature difference range are used as the benchmark to compare the temperature data of each cell with the temperature anomaly rules one by one to determine whether there is a condition that exceeds the threshold or the temperature difference is abnormal; If it is detected that the cell temperature data exceeds the preset temperature threshold or the temperature difference between cells exceeds the predetermined range, a start command is sent to the liquid cooling system via CAN interface communication to obtain the corresponding response status; Based on the response status, analyze whether the liquid cooling system is started successfully. If the response status shows that the startup is not successful, send the startup command again through the CAN interface communication to determine the execution result of the startup command; After obtaining the execution result of the startup command, the thermal management trigger signal is recorded and verified to determine whether the signal meets the preset trigger conditions; If the thermal management trigger signal meets the trigger conditions, the temperature data of the cell will be continuously monitored to obtain real-time temperature control feedback. Based on the temperature control feedback, the operating parameters of the liquid cooling system are dynamically adjusted to determine whether the thermal management trigger mechanism needs to be further optimized to obtain the final system stable state.

8. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: According to the thermal management trigger signal, the main battery management unit combines the cell voltage and charge state data to determine the battery operation risk level. If the risk level is higher than the preset standard, it sends a command to limit the charge and discharge current to the energy storage converter through the Ethernet interface, and at the same time notifies the monitoring system through the 485 interface to adjust the voltage upper limit and obtain the restricted operation parameter set, including: By collecting thermal management signals and combining them with the processing of the main battery management module, the battery voltage data and state of charge values ​​are obtained from the system to determine the battery operation risk level. If the operating risk level is higher than the preset threshold line, the instruction to limit the charge and discharge current is transmitted to the energy storage converter through the Ethernet interface to obtain a preliminary limited control signal; According to the instruction to limit the charge and discharge current, combined with the data processing on the monitoring system side, the voltage upper limit value is adjusted to determine the initial range of the restricted operating parameter set; Based on the initial range of the restricted operating parameter set, the support vector machine algorithm is used to classify and analyze the cell voltage data and state of charge values ​​to obtain the optimized parameter boundaries; The optimized parameter boundaries are combined with the real-time feedback data from the energy storage converter to determine the dynamic adjustment requirements for the charge and discharge currents. If the feedback data exceeds the parameter boundaries, a correction instruction is generated. According to the correction instructions, combined with the control logic of the main battery management, the final value of the restricted parameter set is adjusted to obtain a battery management strategy suitable for the current operating state; Through the final restricted parameter set, combined with the logging function of the monitoring system, the operation risk level and the adjusted voltage upper limit value are stored to determine the basis for continuous monitoring of the system operation status.

9. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The slave battery management unit receives the restricted operating parameter set, determines whether there is a battery cell state of charge imbalance based on the battery cell voltage data and operating status, and if there is an imbalance, selects the corresponding battery cell channel through internal control logic, starts a balancing DC converter to charge or discharge the target cell, and obtains a balanced cell state update set, including: The battery management unit collects operating parameters and cell voltage data, monitors the operating status of each cell in real time, and obtains a preliminary state of charge distribution set; Analyze whether there is an imbalance based on the state of charge distribution set. If the difference in state of charge between cells exceeds a preset threshold, it is determined that there is an imbalance and an imbalance identification set is generated. For the imbalance identification set, the target monomer is located through the internal control logic, and the corresponding channel is selected using the pre-established mapping table to obtain the target monomer channel set; Starting from the target monomer channel set, starting the DC converter to perform a charging operation or a discharging operation on the target monomer, and obtaining a monomer state update set after the operation; Based on the updated state set of cells, the state of charge distribution of each cell is recalculated. If imbalance still exists, the operating parameters of the DC converter are iteratively adjusted to obtain the optimized state adjustment set. Obtain the optimized state adjustment set, combine it with historical operating parameter data, use the support vector machine algorithm to predict the long-term trend of the state of charge, determine whether there is potential imbalance risk, and generate a risk assessment set; Through the risk assessment set, based on the predicted potential imbalance risks, the priority strategy of the internal control logic is adjusted, the key target entities for subsequent monitoring and balancing operations are determined, and an updated monitoring strategy set is obtained.

10. The electrochemical energy storage power station battery management system according to claim 2, characterized in that: The main battery management unit extracts the latest data from the balanced single cell status update set, verifies the data consistency through the data integrity verification mechanism, and determines whether the overall operation of the battery cabinet is stable. If the overall operating status is within the preset safety range, the current acceptable maximum charge and discharge power is fed back to the energy storage converter through the CAN interface to obtain the final operation optimization instruction set, including: By extracting the latest data from the balanced monomer state, the data integrity verification mechanism is used to verify the collected information to determine whether the data meets the consistency requirements and obtain preliminary data reliability results. Based on the preliminary data reliability results, the status information after the data consistency check is compared using the preset threshold range. If the consistency check results meet the preset standards, it is determined that the overall operation of the battery cabinet is in a stable state; By confirming the overall operating stability of the battery cabinet, the matching degree between the operating status and the safety range is obtained. If the operating status is within the preset safety range, it is determined that the current system can enter the power feedback stage; According to the judgment results of the power feedback stage, the currently acceptable charging and discharging power data is transmitted to the energy storage converter through the CAN interface to obtain the power distribution information returned by the energy storage converter; Based on the power distribution information returned by the energy storage converter, the support vector machine algorithm is used to evaluate the rationality of the power distribution and obtain the optimized power distribution plan; The optimized power allocation scheme is used to generate the final optimized operation instruction set. The system then determines whether the instruction set matches the current battery management state. If so, the instruction set is determined to be executable. Based on the executable judgment of the instruction set, the optimized instruction set is transmitted to the battery management system through the feedback mechanism to complete the dynamic adjustment of the operating status.