Intelligent management system for electrochemical energy storage application

Abstract

The invention relates to the technical field of electrochemical energy storage, in particular to an intelligent management system for electrochemical energy storage application, which comprises a state real-time monitoring module, a dynamic regulation control module, a fault diagnosis and analysis module, an emergency response module, a health monitoring and analysis module and a charging and discharging strategy module. According to the invention, by monitoring key performance parameters such as voltage, current and temperature of the electrochemical energy storage equipment in real time and combining data of the environment monitoring sensor, external and internal changes can be responded in real time, the response speed and preventive maintenance capability of the equipment are improved, and upcoming load requirements are met by adjusting discharge parameters in time; according to the invention, the device can be used for preventing overdischarge and potential equipment damage, effectively prolonging the service life of the battery, optimizing the energy consumption, adjusting the maintenance period according to real-time data, reducing the risk of sudden failure, improving the stability and safety of the electrochemical energy storage equipment in a complex environment, and supporting the stable operation of the equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of electrochemical energy storage, and in particular to an intelligent management system for electrochemical energy storage applications. Background Art

[0002] The field of electrochemical energy storage technology involves technologies and methods for storing energy using electrochemical devices. The core technologies in this field include various types of batteries, such as lithium-ion batteries, lead-acid batteries, nickel-metal hydride batteries, etc. Electrochemical energy storage devices can release stored electrical energy when needed, supporting a wide range of applications from portable electronic devices to electric vehicles to large-scale grid energy storage. Electrochemical energy storage technology plays a key role in mobile devices, electric vehicles, renewable energy systems, and large-scale grid regulation and energy storage, effectively supporting the sustainable development of energy and the stable operation of the grid.

[0003] Among them, the intelligent management system for electrochemical energy storage applications is a system used to optimize and control the operation of electrochemical energy storage devices. The system uses data analysis to optimize the charging and discharging process of energy storage, improve energy efficiency, and extend the service life of equipment by monitoring the working status, energy input and output, and environmental parameters of energy storage equipment in real time. The scope of application includes grid regulation, energy balance of renewable energy systems, and improving battery performance and reliability of electric vehicles and mobile devices. The key to the system is that it can ensure that energy storage equipment operates efficiently, stably, and safely in complex application environments.

[0004] Traditional management systems lack the ability to monitor equipment status in depth and adjust performance in real time, which results in batteries and other energy storage devices being unable to effectively adjust their operating status when faced with environmental changes or load fluctuations, reducing the equipment's operating efficiency and lifespan. Traditional systems' response measures after a fault occurs are mostly limited to post-processing rather than prevention, which delays the timeliness of fault handling, increases maintenance costs, limits the widespread application and long-term reliability of the technology, and cannot meet application requirements for stability and security. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent management system for electrochemical energy storage applications.

[0006] In order to achieve the above-mentioned object, the present invention adopts the following technical solution: an intelligent management system for electrochemical energy storage application, the system comprising: The real-time status monitoring module is based on electrochemical energy storage devices. It obtains corresponding detection data and operation data from EMS and BMS, extracts voltage, current and temperature data of electrochemical energy storage devices, collects temperature and humidity data of the working environment of electrochemical energy storage devices, unifies the format of data and synchronizes the time to obtain a status monitoring data set. The dynamic regulation control module evaluates the load change trend and load fluctuation based on the state monitoring data set, adjusts the discharge parameters of the electrochemical energy storage device, and obtains a discharge regulation instruction; The fault diagnosis and analysis module evaluates the deviation of the electrochemical energy storage device from the standard operation data based on the discharge adjustment instruction and the state monitoring data set, identifies the abnormal mode of the electrochemical energy storage device, locates the fault type and location, and obtains fault diagnosis information; The emergency response module isolates the electrochemical energy storage device with faults based on the fault diagnosis information, formulates corresponding maintenance measures, and obtains fault response measures; The health monitoring and analysis module evaluates the battery health status of the electrochemical energy storage device based on the fault response measures, predicts the battery performance degradation trend and remaining life, adjusts the maintenance and replacement cycle of the electrochemical energy storage device, and obtains battery health monitoring information; The charge and discharge strategy module adjusts the battery charge and discharge cycle of the electrochemical energy storage device based on the battery health monitoring information and the load data of the electrochemical energy storage device to generate an optimized charge and discharge strategy.

[0007] As a further solution of the present invention, the state monitoring data set includes voltage level, current intensity, temperature reading, ambient humidity and ambient pressure, the discharge adjustment instruction includes adjusted discharge rate, discharge depth and energy distribution information, the fault diagnosis information includes fault type information, fault location information and fault cause information, the fault response measures include equipment isolation measures and safety inspection measures, the battery health monitoring information includes battery life information, performance degradation trend and maintenance plan, and the optimized charging and discharging strategy includes optimized charging time point, discharge strategy and energy efficiency optimization measures.

[0008] As a further solution of the present invention, the real-time status monitoring module includes: The device parameter recording submodule is based on electrochemical energy storage devices. It uses sensors to monitor and record the basic electrical parameters of the device in real time, including voltage, current intensity, and temperature changes of the core parts of the device, to obtain the device operating parameters. The environmental monitoring submodule is based on the electrochemical energy storage device. It collects the temperature and humidity data of the working environment of the electrochemical energy storage device through the environmental monitoring sensor to obtain the environmental status data; The time synchronization processing submodule timestamps the data based on the equipment operating parameters and environmental status data, optimizes the time consistency and accuracy of the data, unifies the data format, and obtains a status monitoring data set.

[0009] As a further solution of the present invention, the dynamic adjustment control module includes: The load analysis submodule analyzes the real-time and historical load data of the electrochemical energy storage device based on the state monitoring data set, identifies the change trend and periodic fluctuation of the device load, and obtains the load trend analysis result; The parameter adjustment submodule adjusts the discharge parameters of the electrochemical energy storage device, including discharge voltage and current, based on the load trend analysis result, to match the current load change and obtain real-time parameter adjustment information; The demand matching submodule analyzes the energy demand in the future period based on the real-time parameter adjustment information, predicts the future load conditions, adjusts the operating parameters of the electrochemical energy storage device, matches the load demand in the future period, and obtains the discharge adjustment instruction.

[0010] As a further solution of the present invention, the fault diagnosis and analysis module includes: The operation data analysis submodule analyzes the operation data of the electrochemical energy storage device based on the discharge adjustment instruction and the state monitoring data set, compares the current operation data with the historical standard operation data, identifies the data deviation, analyzes and identifies the degree of data deviation, and obtains the data deviation identification result; The abnormal pattern recognition submodule performs pattern analysis on the deviation data based on the data deviation recognition result, compares it with the fault pattern pre-stored in the database, evaluates the matching degree of the fault pattern, identifies the matching abnormal pattern, and obtains the abnormal pattern matching information; The fault location analysis submodule analyzes the cause and impact of the fault based on the abnormal pattern matching information and according to the type and location of the fault to obtain fault diagnosis information.

[0011] As a further solution of the present invention, the calculation formula for evaluating the matching degree of the fault mode is:

[0012] in, Represents an abnormal data point The measured value of Represents the data points in the failure mode stored in the database The average value of Represents the data deviation dimension The weight of Representative data points The standard deviation of Represents the total number of data dimensions, is the matching degree of the failure mode.

[0013] As a further solution of the present invention, the emergency response module includes: The fault isolation submodule isolates the electrochemical energy storage device with the fault based on the fault diagnosis information, blocks the connection of the electrochemical energy storage device with the fault, and obtains isolation operation execution information; The safety monitoring submodule monitors the operation stability and safety of the electrochemical energy storage device based on the isolation operation execution information, checks whether there are potential safety issues, and obtains safety monitoring records; The maintenance measures formulation submodule formulates corresponding maintenance measures based on the safety monitoring records, including the repair time, required materials and technician arrangements of the faulty equipment, and obtains fault response measures.

[0014] As a further solution of the present invention, the health monitoring and analysis module includes: The battery status evaluation submodule analyzes the internal resistance, voltage fluctuation and charge and discharge frequency of the battery based on the fault response measures and the real-time monitoring data of the electrochemical energy storage device, calculates the health index of the battery by comparing the historical performance data with the standard indicators, evaluates the current health status of the battery, and obtains the battery health status indicator; The performance degradation prediction submodule analyzes the degradation trend of battery performance over time based on the battery health status indicator, and predicts the remaining life and future performance of the battery in combination with the battery historical usage data and charge and discharge cycles to obtain a performance degradation prediction result; The maintenance cycle adjustment submodule adjusts the maintenance and replacement cycle of the electrochemical energy storage device based on the performance degradation prediction result, formulates a maintenance plan that matches the predicted performance degradation, optimizes operating efficiency, and extends the service life of the equipment to obtain battery health monitoring information.

[0015] As a further solution of the present invention, the formula for calculating the health index of the battery is:

[0016] in, Represents the measured value of the internal resistance of the battery, Represents the battery voltage fluctuation range, Represents the average voltage of the battery during the test, Represents the charge and discharge frequency, , and is the weight coefficient, It is the health index of the battery.

[0017] As a further solution of the present invention, the charging and discharging strategy module includes: The load data analysis submodule analyzes the energy demand of the electrochemical energy storage device in the differentiated operation time periods based on the battery health monitoring information and the real-time load data of the electrochemical energy storage device, identifies the peak and valley of energy use, and obtains the load demand analysis results; The charging adjustment submodule adjusts the charging rate and discharge depth of the battery based on the load demand analysis result, balances the load demand and the battery life, and obtains a charging parameter adjustment result; The battery optimization strategy submodule optimizes the energy efficiency of the battery based on the charging parameter adjustment result, analyzes the response efficiency and energy consumption data of the battery, adjusts the battery operating parameters, optimizes the battery performance and energy efficiency, and generates an optimized charging and discharging strategy.

[0018] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by real-time monitoring of key performance parameters of the electrochemical energy storage device such as voltage, current and temperature, and combining the data of the environmental monitoring sensor, it is possible to respond to external and internal changes in real time, thereby improving the response speed and preventive maintenance capability of the device. When the operating parameters of the device are abnormal, the discharge parameters are adjusted in time to adapt to the upcoming load demand, thereby avoiding excessive discharge and potential equipment damage, effectively extending the service life of the battery and optimizing energy consumption. By analyzing the health status of the battery, the decline trend of the battery performance can be predicted, and the maintenance cycle can be adjusted according to the real-time data, thereby reducing the risk of sudden failures and reducing maintenance costs, thereby improving the stability and safety of the electrochemical energy storage device in a complex environment and supporting the stable operation of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a system flow chart of the present invention; Figure 2 It is a schematic diagram of the system framework of the present invention; Figure 3 This is a flow chart of the real-time status monitoring module of the present invention; Figure 4 This is a flow chart of the dynamic adjustment control module of the present invention; Figure 5 It is a flow chart of the fault diagnosis and analysis module of the present invention; Figure 6 is a flow chart of the emergency response module of the present invention; Figure 7 This is a flow chart of the health monitoring and analysis module of the present invention; Figure 8 It is a flow chart of the charge and discharge strategy module of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0022] See also Figure 1 , an intelligent management system for electrochemical energy storage applications, the system includes: The real-time status monitoring module performs real-time data acquisition based on electrochemical energy storage devices, obtains corresponding detection data and operation data from EMS and BMS, extracts voltage, current and temperature data of electrochemical energy storage devices, and collects temperature and humidity data of the working environment of electrochemical energy storage devices through environmental monitoring sensors. The data is formatted and time synchronized to obtain a status monitoring data set. The dynamic adjustment control module is based on the state monitoring data set. By analyzing the load data over a period of time, the load change trend and load fluctuation are evaluated, and the discharge parameters of the electrochemical energy storage device are adjusted to match the future time period demand to obtain the discharge adjustment instruction; The fault diagnosis and analysis module is based on the discharge adjustment instructions and the state monitoring data set. By analyzing the operation data of the electrochemical energy storage device, the deviation of the electrochemical energy storage device from the standard operation data is evaluated. According to the deviation of the operation data, the abnormal mode of the electrochemical energy storage device is identified, and compared with the known fault mode, the fault type and location are located, the cause and impact of the fault are analyzed, and the fault diagnosis information is obtained; The emergency response module isolates the electrochemical energy storage device with faults based on the fault diagnosis information, monitors the operating stability and safety of the electrochemical energy storage device, formulates corresponding maintenance measures, and obtains fault response measures; The health monitoring and analysis module evaluates the battery health status of the electrochemical energy storage device based on the fault response measures and the real-time monitoring data of the electrochemical energy storage device, including internal resistance, voltage fluctuation, and charge and discharge frequency, predicts the battery performance degradation trend and remaining life, adjusts the maintenance and replacement cycle of the electrochemical energy storage device, and obtains battery health monitoring information; The charge and discharge strategy module adjusts the battery charge and discharge cycle of the electrochemical energy storage device based on the battery health monitoring information and the load data of the electrochemical energy storage device, adjusts the charging rate and discharge depth, prolongs the battery life, optimizes the energy efficiency, and generates an optimized charge and discharge strategy; The condition monitoring data set includes voltage level, current intensity, temperature reading, ambient humidity and ambient pressure. The discharge adjustment instructions include the adjusted discharge rate, discharge depth and energy distribution information. The fault diagnosis information includes fault type information, fault location information and fault cause information. The fault response measures include equipment isolation measures and safety inspection measures. The battery health monitoring information includes battery life information, performance degradation trend and maintenance plan. The optimized charging and discharging strategy includes the optimized charging time point, discharge strategy and energy efficiency optimization measures.

[0023] See also Figure 2 and Figure 3 ,The real-time status monitoring module includes the equipment parameter recording submodule, the environment monitoring submodule, and the time synchronization processing submodule; The device parameter recording submodule is based on electrochemical energy storage devices. It uses sensors to monitor and record the basic electrical parameters of the device in real time, including voltage, current intensity, and temperature changes of the core parts of the device, to obtain the device operating parameters. Based on the electrochemical energy storage device, the operating status of the electrochemical energy storage device is initially monitored through the connected sensors, including real-time data acquisition of voltage, current and temperature. The data is sampled at high frequency through the data acquisition interface. The sampling frequency can be adjusted according to the operating speed and accuracy requirements of the equipment. The accuracy and reliability of the data are ensured by preliminary filtering and calibration of the collected data. Each reading of the voltage and current intensity is accurately measured. At the same time, the temperature changes of the core parts of the equipment are monitored, and abnormal temperatures are captured and recorded in real time to enable fault prediction and maintenance decisions to be made during the operation of the equipment. The collected electrical parameter data is processed and stored in the local data cache for further data analysis and historical trend evaluation to obtain the equipment operation parameters.

[0024] The environmental monitoring submodule is based on the electrochemical energy storage device. It collects the temperature and humidity data of the working environment of the electrochemical energy storage device through the environmental monitoring sensor to obtain the environmental status data; Based on electrochemical energy storage devices, environmental monitoring sensors are used to collect surrounding temperature and humidity data in real time. Sensors are distributed in key locations around the equipment, and the layout of monitoring points can be dynamically adjusted to maximize data coverage and improve data collection accuracy. The data collected by the sensors are first cleaned and formatted in real time, and then integrated with data fusion technology to improve the representativeness of environmental data and reduce the impact of environmental noise. Accurately processed environmental data will be converted into environmental status indicators, such as standardized temperature index and humidity index. The indicators are summarized into environmental status data to provide support for long-term operation and maintenance decisions of the equipment.

[0025] The time synchronization processing submodule timestamps the data based on the equipment operating parameters and environmental status data, optimizes the time consistency and accuracy of the data, unifies the data format, and obtains the status monitoring data set.

[0026] Based on the equipment operating parameters and environmental status data, a timestamp will be assigned when the data arrives. The process involves time calibration to ensure that the timestamps of all data are synchronized. The data will be formatted after time stamping, including unified data encoding and storage format to facilitate data integration and subsequent processing. In the process of optimizing the time consistency and accuracy of the data, by integrating and formatting data from various sources, the processed data set is not only time synchronized, but also in a unified format, which improves the efficiency and accuracy of data processing and obtains a status monitoring data set.

[0027] See also Figure 2 and Figure 4 ,The dynamic regulation control module includes a load analysis submodule, a parameter adjustment submodule, and a demand matching submodule; The load analysis submodule analyzes the real-time and historical load data of the electrochemical energy storage device based on the condition monitoring data set, identifies the change trend and periodic fluctuation of the device load, and obtains the load trend analysis results; Based on the condition monitoring data set, the received condition monitoring data set is sorted and archived, and key performance indicators are extracted from real-time and historical data, including the load size, frequency and duration analysis of the electrochemical energy storage equipment. These indicators are statistically analyzed to determine the load change trend, especially the identification of periodic fluctuations. Peak detection and trend line analysis technology are used in the identification process. Through the analysis of historical load data, future load patterns can be predicted. The analysis results are summarized to obtain load trend analysis results.

[0028] The parameter adjustment submodule adjusts the discharge parameters of the electrochemical energy storage device, including discharge voltage and current, based on the load trend analysis results to match the current load changes and obtain real-time parameter adjustment information; Based on the load trend analysis results, the discharge parameters of the current equipment are evaluated, including the set values ​​of voltage and current. According to the specific needs of the load trend, the discharge parameters are adjusted, including the simulation of the current equipment status and the optimization of the discharge parameters to ensure the rationality and practicality of the adjustment. The discharge parameters are then sent to the equipment for execution to complete the real-time adjustment of the parameters. Through dynamic adjustment, the optimal operation of the equipment under different load conditions is ensured, and real-time parameter adjustment information is obtained.

[0029] The demand matching submodule analyzes the energy demand in the future period based on the real-time parameter adjustment information, predicts the future load conditions, adjusts the operating parameters of the electrochemical energy storage equipment, matches the load demand in the future period, and obtains the discharge adjustment instructions.

[0030] Based on the real-time parameter adjustment information, the received real-time parameter adjustment information is analyzed to predict the load changes in the next time period. The prediction is based on multiple algorithms, including time series analysis and regression analysis, to ensure the accuracy and reliability of the prediction. The operating parameters of the electrochemical energy storage device are adjusted according to the prediction results. The parameters include voltage adjustment, current adjustment and charging strategy optimization. The adjustment is automatically performed through the control protocol to match the load demand in the future period. During the adjustment process, the device response and system stability are monitored in real time to ensure the correct execution of the adjustment and obtain the discharge adjustment instruction.

[0031] See also Figure 2 and Figure 5 ,The fault diagnosis and analysis module includes an operation data analysis submodule, an abnormal pattern recognition submodule, and a fault location analysis submodule; The operation data analysis submodule analyzes the operation data of the electrochemical energy storage device based on the discharge adjustment instruction and the state monitoring data set, compares the current operation data with the historical standard operation data, identifies the data deviation, analyzes and identifies the degree of data deviation, and obtains the data deviation identification result; Based on the discharge regulation instructions and status monitoring data sets, the current real-time operating data is compared with the historical standard operating data. The process involves data cleaning, normalization and outlier detection. These processing steps ensure the accuracy of data comparison. Statistical analysis methods, such as standard deviation calculation and variance analysis, are used to quantify the deviations between data. Calculations help identify abnormal areas of operating data, classify the degree of deviation, and evaluate its possible impact on equipment performance. Data deviation identification results are output based on the severity of the deviation, providing a basis for fault prediction and maintenance.

[0032] The abnormal pattern recognition submodule performs pattern analysis on the deviation data based on the data deviation recognition result, compares it with the fault patterns pre-stored in the database, evaluates the matching degree of the fault patterns, identifies the matching abnormal patterns, and obtains the abnormal pattern matching information; The calculation formula for evaluating the matching degree of the failure mode is:

[0033] in, Represents an abnormal data point The measured value of Represents the data points in the failure mode stored in the database The average value of Represents the data deviation dimension The weight of Representative data points The standard deviation of Represents the total number of data dimensions, is the matching degree of the failure mode.

[0034] formula:

[0035] The meaning and acquisition methods of the parameters are as follows: Representative The measured values ​​of abnormal data points are obtained from the real-time monitoring system and involve the operating parameters of the electrochemical energy storage device, such as current and voltage, which are usually collected in real time by sensors.

[0036] Represents the first These values ​​are calculated based on historical failure data, usually by analyzing the average performance of the corresponding parameters in the equipment's past failure records.

[0037] Representative The weight of each data point is assigned according to the importance of each data point in the fault mode identification in the historical data. The weight assignment is usually based on expert experience or statistical analysis of historical fault data, reflecting the influence of each parameter.

[0038] Representative The standard deviation of each data point is used to characterize the volatility of the data. The standard deviation is calculated based on historical data and describes the degree of variation of the parameter in normal operation.

[0039] Calculation example: Set the following parameter values: An array of measured values, An array of average values, The weight array, Array of standard deviations.

[0040] The calculation process is as follows: For the first data point :

[0041] For the second data point :

[0042] For the third data point :

[0043] sum:

[0044] Calculate the matching degree :

[0045] Calculation results Indicates a relatively low match, meaning the measured value is slightly different from the pre-set failure mode, but does not match it exactly. A small match value indicates that the data point matches the failure mode to some extent, although there are some differences. This match calculation is critical for early identification and prevention of potential equipment problems.

[0046] The fault location analysis submodule analyzes the cause and impact of the fault based on the abnormal pattern matching information and the type and location of the fault to obtain fault diagnosis information; Based on the abnormal pattern matching information, the abnormal pattern matching information is analyzed, and the type and location of the fault are determined according to the matching results. The root cause of the fault is analyzed using fault tree analysis and cause analysis technology. The analysis process takes into account the design, manufacturing and operating environment factors of the equipment to ensure the comprehensiveness and accuracy of the diagnostic results. The specific cause and possible impact of the fault are obtained through analysis, and structured fault diagnosis information is formed to provide guidance for subsequent maintenance and repair.

[0047] See also Figure 2 and Figure 6 ,The emergency response module includes a fault isolation submodule, a safety monitoring submodule, and a maintenance measure formulation submodule; The fault isolation submodule isolates the electrochemical energy storage device with faults based on the fault diagnosis information, blocks the connection of the faulty electrochemical energy storage device, and obtains isolation operation execution information; Based on the fault diagnosis information, by receiving the fault diagnosis results, analyzing the fault information, determining the equipment and components that need to be isolated, issuing an isolation command, and cutting off the power and data connections of the faulty electrochemical energy storage equipment through the automated control interface, ensuring that the fault does not spread to other equipment while keeping other parts operating normally. The isolation process is monitored and recorded in real time to ensure the accurate execution of the operation and form isolation operation execution information.

[0048] The safety monitoring submodule monitors the operating stability and safety of the electrochemical energy storage device based on the isolation operation execution information, checks whether there are potential safety issues, and obtains safety monitoring records; Based on the isolation operation execution information, by continuously tracking the operating status of the electrochemical energy storage equipment after isolation, using real-time data analysis technology, evaluate the stability and safety of the equipment operation, and check whether there are unidentified potential safety issues, such as overheating, voltage abnormalities or current leakage. The monitoring process includes continuous monitoring of relevant parameters and early warning of abnormal trends. Through comprehensive safety monitoring, the safety status can be updated in real time and detailed safety monitoring records can be generated.

[0049] The maintenance measures formulation submodule formulates corresponding maintenance measures based on the safety monitoring records, including the repair time of the faulty equipment, the required materials and the arrangement of technicians, and obtains the fault response measures.

[0050] Based on the safety monitoring records, and using the collected safety monitoring data and fault isolation results, a specific maintenance plan is developed. The plan lists in detail the equipment parts that need to be repaired, the estimated maintenance time and the list of materials required. At the same time, necessary technicians and work shifts are arranged to ensure the effective implementation of the maintenance work. In addition, the impact on production during the maintenance period is evaluated, and corresponding production adjustment measures are formulated to reduce the impact of maintenance work on overall operations and obtain detailed fault response measures.

[0051] See also Figure 2 and Figure 7 ,The health monitoring and analysis module includes a battery status assessment submodule, a performance degradation prediction submodule, and a maintenance cycle adjustment submodule; The battery status assessment submodule analyzes the internal resistance, voltage fluctuation and charge and discharge frequency of the battery based on fault response measures and real-time monitoring data of electrochemical energy storage devices. By comparing historical performance data with standard indicators, the battery health index is calculated, the current health status of the battery is evaluated, and the battery health status indicator is obtained; The formula for calculating the battery health index is:

[0052] in, Represents the measured value of the internal resistance of the battery, Represents the battery voltage fluctuation range, Represents the average voltage of the battery during the test, Represents the charge and discharge frequency, , and is the weight coefficient, It is the health index of the battery.

[0053] formula:

[0054] Parameter details and how to obtain them: : The internal resistance of the battery, usually obtained by a dedicated internal resistance measuring device during charging and discharging. The internal resistance can reflect the health of the battery. A higher internal resistance usually indicates that the battery may be aged or damaged.

[0055] : The voltage fluctuation of the battery, which is the difference between the highest and lowest voltage values ​​recorded by the real-time monitoring system during the battery charging and discharging process. Large voltage fluctuations usually indicate an unstable battery state.

[0056] : The average voltage of the battery during the test, which is also obtained through real-time monitoring and reflects the voltage level of the battery under normal working conditions.

[0057] : Charge and discharge frequency, that is, the number of times the battery is charged and discharged per unit time. This data can be obtained from the battery management system. Frequent charge and discharge will accelerate battery aging.

[0058] , and : Weight coefficient, used to adjust the influence of internal resistance, voltage fluctuation and charge and discharge frequency in calculating the battery health index. These coefficients are usually set based on historical data statistical analysis or expert experience.

[0059] Calculation example: Set the following parameter values: Set the internal resistance Ohm, voltage fluctuation Volts, average voltage Volt, charge and discharge frequency times / hour, weight coefficient , , ,The coefficient reflects that voltage fluctuation has a higher importance in battery health assessment, while the importance of charge and discharge frequency is relatively low.

[0060] Calculation process:

[0061]

[0062]

[0063]

[0064] Calculation results , a health index of 0.1 indicates that the battery may have certain health problems and requires further inspection or maintenance. This calculation method provides a way to quantify the health of the battery, which can help operation and maintenance personnel make more targeted maintenance decisions.

[0065] The performance degradation prediction submodule analyzes the degradation trend of battery performance over time based on the battery health status indicators, and combines the battery's historical usage data and charge and discharge cycles to predict the remaining life and future performance of the battery, and obtain the performance degradation prediction results; Based on the battery health status indicators, statistical and predictive models such as regression analysis and machine learning algorithms are used to analyze the decline trend of battery performance over time. The historical battery usage data and charge and discharge cycle information are integrated to predict the future performance and remaining life of the battery, providing accurate performance decline prediction results. The results will help formulate future maintenance and replacement strategies.

[0066] The maintenance cycle adjustment submodule adjusts the maintenance and replacement cycle of the electrochemical energy storage equipment based on the performance degradation prediction results, formulates a maintenance plan that matches the predicted performance degradation, optimizes operating efficiency, and extends the service life of the equipment to obtain battery health monitoring information.

[0067] Based on the performance degradation prediction results, the possible future maintenance needs of the electrochemical energy storage equipment are evaluated. According to the predicted degree of performance degradation, the maintenance and replacement cycles are adjusted. When formulating the maintenance plan, the operating efficiency and economic benefits of the equipment are taken into consideration, and the maintenance operations are optimized to reduce operating costs and extend the life of the equipment. Through the whole, a maintenance strategy that matches the performance degradation of the equipment is formulated, and finally the battery health monitoring information is obtained.

[0068] See also Figure 2 and Figure 8 ,The charge and discharge strategy module includes a load data analysis submodule, a charge adjustment submodule, and a battery optimization strategy submodule; The load data analysis submodule analyzes the energy demand of electrochemical energy storage devices in differentiated operating periods based on battery health monitoring information and real-time load data of electrochemical energy storage devices, identifies energy usage peaks and valleys, and obtains load demand analysis results. Based on battery health monitoring information and combined with real-time load data of electrochemical energy storage devices, the battery health monitoring information and real-time load data are imported into the data analysis platform. Through peak and valley analysis, the energy demand differences of the equipment in different operating periods are identified, especially during peak and valley periods of energy use. The analysis involves statistical calculations and pattern recognition to determine the changing trends and periodic fluctuations of energy demand, so as to accurately obtain the load demand analysis results.

[0069] The charging adjustment submodule adjusts the charging rate and discharge depth of the battery based on the load demand analysis results, balances the load demand and battery life, and obtains the charging parameter adjustment results; Based on the results of load demand analysis, the charging rate and discharge depth of the battery are adjusted. By implementing the adjustment of charging and discharging parameters, the charging rate is dynamically adjusted based on real-time and predicted load data to maximize the efficiency and life of the battery. At the same time, the battery health status is considered, and the load demand is balanced with the long-term sustainability of the battery to obtain the charging parameter adjustment results.

[0070] The battery optimization strategy submodule optimizes the battery's energy efficiency based on the charging parameter adjustment results, analyzes the battery's response efficiency and energy consumption data, adjusts the battery's operating parameters, optimizes the battery's performance and energy efficiency, and generates an optimized charging and discharging strategy.

[0071] Based on the charging parameter adjustment results, the battery energy efficiency is optimized and evaluated. Combined with the battery response efficiency and energy consumption data, data analysis technology is used to comprehensively consider multiple parameters of battery operation, such as temperature, voltage, current, etc., and adjust parameters to improve battery performance and energy efficiency. The optimization process aims to reduce energy consumption while increasing response speed. The adjusted operating parameters help improve the efficiency of the overall battery system and form an optimized charging and discharging strategy.

[0072] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent management system for electrochemical energy storage applications, characterized in that: The system comprises: The real-time status monitoring module is based on electrochemical energy storage devices. It obtains corresponding detection data and operation data from EMS and BMS, extracts voltage, current and temperature data of electrochemical energy storage devices, collects temperature and humidity data of the working environment of electrochemical energy storage devices, unifies the format of data and synchronizes the time to obtain a status monitoring data set. The dynamic regulation control module evaluates the load change trend and load fluctuation based on the state monitoring data set, adjusts the discharge parameters of the electrochemical energy storage device, and obtains a discharge regulation instruction; The fault diagnosis and analysis module evaluates the deviation of the electrochemical energy storage device from the standard operation data based on the discharge adjustment instruction and the state monitoring data set, identifies the abnormal mode of the electrochemical energy storage device, locates the fault type and location, and obtains fault diagnosis information; The emergency response module isolates the electrochemical energy storage device with faults based on the fault diagnosis information, formulates corresponding maintenance measures, and obtains fault response measures; The health monitoring and analysis module evaluates the battery health status of the electrochemical energy storage device based on the fault response measures, predicts the battery performance degradation trend and remaining life, adjusts the maintenance and replacement cycle of the electrochemical energy storage device, and obtains battery health monitoring information; The charge and discharge strategy module adjusts the battery charge and discharge cycle of the electrochemical energy storage device based on the battery health monitoring information and the load data of the electrochemical energy storage device to generate an optimized charge and discharge strategy.

2. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The condition monitoring data set includes voltage level, current intensity, temperature reading, ambient humidity and ambient pressure; the discharge adjustment instruction includes adjusted discharge rate, discharge depth and energy distribution information; the fault diagnosis information includes fault type information, fault location information and fault cause information; the fault response measures include equipment isolation measures and safety inspection measures; the battery health monitoring information includes battery life information, performance degradation trend and maintenance plan; the optimized charging and discharging strategy includes optimized charging time point, discharge strategy and energy efficiency optimization measures.

3. The intelligent management system for electrochemical energy storage application according to claim 1 is characterized in that: The real-time status monitoring module includes: The device parameter recording submodule is based on electrochemical energy storage devices. It uses sensors to monitor and record the basic electrical parameters of the device in real time, including voltage, current intensity, and temperature changes of the core parts of the device, to obtain the device operating parameters. The environmental monitoring submodule is based on the electrochemical energy storage device. It collects the temperature and humidity data of the working environment of the electrochemical energy storage device through the environmental monitoring sensor to obtain the environmental status data; The time synchronization processing submodule timestamps the data based on the equipment operating parameters and environmental status data, optimizes the time consistency and accuracy of the data, unifies the data format, and obtains a status monitoring data set.

4. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The dynamic adjustment control module includes: The load analysis submodule analyzes the real-time and historical load data of the electrochemical energy storage device based on the state monitoring data set, identifies the change trend and periodic fluctuation of the device load, and obtains the load trend analysis result; The parameter adjustment submodule adjusts the discharge parameters of the electrochemical energy storage device, including discharge voltage and current, based on the load trend analysis result, to match the current load change and obtain real-time parameter adjustment information; The demand matching submodule analyzes the energy demand in the future period based on the real-time parameter adjustment information, predicts the future load conditions, adjusts the operating parameters of the electrochemical energy storage device, matches the load demand in the future period, and obtains the discharge adjustment instruction.

5. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The fault diagnosis and analysis module comprises: The operation data analysis submodule analyzes the operation data of the electrochemical energy storage device based on the discharge adjustment instruction and the state monitoring data set, compares the current operation data with the historical standard operation data, identifies the data deviation, analyzes and identifies the degree of data deviation, and obtains the data deviation identification result; The abnormal pattern recognition submodule performs pattern analysis on the deviation data based on the data deviation recognition result, compares it with the fault pattern pre-stored in the database, evaluates the matching degree of the fault pattern, identifies the matching abnormal pattern, and obtains the abnormal pattern matching information; The fault location analysis submodule analyzes the cause and impact of the fault based on the abnormal pattern matching information and according to the type and location of the fault to obtain fault diagnosis information.

6. The intelligent management system for electrochemical energy storage application according to claim 5, characterized in that: The calculation formula for evaluating the matching degree of the fault mode is: in, Represents abnormal data points The measured value of Represents the data points in the failure mode stored in the database The average value of Represents the data deviation dimension The weight of Representative data points The standard deviation of Represents the total number of data dimensions, is the matching degree of the failure mode.

7. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The emergency response module includes: The fault isolation submodule isolates the electrochemical energy storage device with the fault based on the fault diagnosis information, blocks the connection of the electrochemical energy storage device with the fault, and obtains isolation operation execution information; The safety monitoring submodule monitors the operation stability and safety of the electrochemical energy storage device based on the isolation operation execution information, checks whether there are potential safety issues, and obtains safety monitoring records; The maintenance measures formulation submodule formulates corresponding maintenance measures based on the safety monitoring records, including the repair time, required materials and technician arrangements of the faulty equipment, and obtains fault response measures.

8. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The health monitoring and analysis module includes: The battery status evaluation submodule analyzes the internal resistance, voltage fluctuation and charge and discharge frequency of the battery based on the fault response measures and the real-time monitoring data of the electrochemical energy storage device, calculates the health index of the battery by comparing the historical performance data with the standard indicators, evaluates the current health status of the battery, and obtains the battery health status indicator; The performance degradation prediction submodule analyzes the degradation trend of battery performance over time based on the battery health status indicator, and predicts the remaining life and future performance of the battery in combination with the battery historical usage data and charge and discharge cycles to obtain a performance degradation prediction result; The maintenance cycle adjustment submodule adjusts the maintenance and replacement cycle of the electrochemical energy storage device based on the performance degradation prediction result, formulates a maintenance plan that matches the predicted performance degradation, optimizes operating efficiency, and extends the service life of the equipment to obtain battery health monitoring information.

9. The intelligent management system for electrochemical energy storage application according to claim 8, characterized in that: The formula for calculating the battery health index is: in, Represents the measured value of the internal resistance of the battery, Represents the battery voltage fluctuation range, Represents the average voltage of the battery during the test, Represents the charge and discharge frequency, , and is the weight coefficient, It is the health index of the battery.

10. The intelligent management system for electrochemical energy storage application according to claim 1, characterized in that: The charging and discharging strategy module includes: The load data analysis submodule analyzes the energy demand of the electrochemical energy storage device in the differentiated operation time periods based on the battery health monitoring information and the real-time load data of the electrochemical energy storage device, identifies the peak and valley of energy use, and obtains the load demand analysis results; The charging adjustment submodule adjusts the charging rate and discharge depth of the battery based on the load demand analysis result, balances the load demand and the battery life, and obtains a charging parameter adjustment result; The battery optimization strategy submodule optimizes the energy efficiency of the battery based on the charging parameter adjustment result, analyzes the response efficiency and energy consumption data of the battery, adjusts the battery operating parameters, optimizes the battery performance and energy efficiency, and generates an optimized charging and discharging strategy.

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