Storage battery pack charging and discharging monitoring management platform

Abstract

The invention discloses a storage battery pack charging and discharging monitoring management platform, and relates to the technical field of battery monitoring management. According to the storage battery pack charging and discharging monitoring management platform, through the static state evaluation module and the charging and discharging state evaluation module, the operation state of the storage battery pack can be comprehensively monitored, and the static deviation coefficient and the dynamic evaluation coefficient are accurately calculated, so that a scientific basis is provided for a management scheme of the storage battery pack. According to the method, the problem that the stability of the storage battery pack in different working states cannot be evaluated and managed in real time in a traditional monitoring mode is effectively solved, the maintenance efficiency of the storage battery pack is improved, the service life of the storage battery pack is prolonged, and the safety and reliability of equipment are ensured.

Description

Technical Field

[0001] This invention relates to the field of battery monitoring and management technology, specifically to a battery pack charging and discharging monitoring and management platform. Background Technology

[0002] Battery packs are independent and reliable operating power sources. They mostly adopt series connection and float charging operation modes and are widely used in various fields such as telecommunications, power, transportation, and construction. As a backup power source, they can ensure the continuous and reliable operation of the system when the mains power is interrupted.

[0003] The performance of a battery pack changes with parameters such as its condition, operating environment, power demand, and cycle count. In actual operation, differences in voltage, internal resistance, and internal temperature of individual cells lead to problems such as reduced battery capacity and accelerated aging, further widening the performance differences between cells in the battery pack. This vicious cycle seriously affects the safety and reliability of the battery pack.

[0004] Existing battery pack charging and discharging monitoring and management platforms have the problem of being unable to comprehensively monitor the operating status of battery packs through static state assessment and charging and discharging state assessment. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a battery pack charging and discharging monitoring and management platform, which solves the problem that existing battery pack charging and discharging monitoring and management platforms are unable to comprehensively monitor the operating status of battery packs through static state assessment and charging and discharging state assessment.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a battery pack charging and discharging monitoring and management platform, comprising a battery pack static state evaluation module, a charging and discharging state evaluation module, and a battery pack state management module, wherein: the battery pack static state evaluation module is used to evaluate the state of the battery pack when it is not charging or discharging, and determine a static deviation coefficient, which represents the stability of the currently monitored battery pack when it is not charging or discharging; the charging and discharging state evaluation module is used to analyze the state of the battery pack during charging and discharging, and obtain a battery pack dynamic evaluation coefficient, which represents the stability of the battery pack during charging and discharging; the battery pack state management module is used to determine a management scheme for the battery pack based on the static deviation coefficient and the battery pack dynamic evaluation coefficient.

[0007] Furthermore, the process of determining the static deviation coefficient is as follows: obtaining static data of the battery pack under static conditions; obtaining parameter static data of the battery pack under static conditions from the database; and comprehensively analyzing the static data of the battery pack under static conditions and the parameter static data of the battery pack under static conditions obtained from the database to obtain the static deviation coefficient.

[0008] Furthermore, the static data includes the amount of power loss within a set time period, and the reference static data includes the reference power loss within a set time period; the static deviation coefficient is the difference between the amount of power loss within a set time period and the reference power loss within a set time period.

[0009] Furthermore, the step of obtaining the parameter static data of the battery pack in a static state from the database includes the following steps: obtaining the ambient temperature of the battery pack; comparing the ambient temperature of the battery pack with the ambient temperature matching values ​​stored in the database to obtain an ambient temperature matching value that is equal to the ambient temperature of the battery pack; and obtaining the parameter static data of the battery pack in a static state corresponding to the ambient temperature matching value from the database based on the ambient temperature matching value.

[0010] Furthermore, the process of obtaining the dynamic evaluation coefficient of the battery pack includes the following steps: obtaining dynamic data of the battery pack during charging and discharging; obtaining dynamic parameter data of the battery pack during charging and discharging stored in the database; obtaining allowable deviation data of the battery pack during charging and discharging; and obtaining the dynamic evaluation coefficient of the battery pack based on the dynamic data, dynamic parameter data, and allowable deviation data.

[0011] Furthermore, the step of obtaining the permissible deviation data during the charging and discharging of the battery pack includes the following steps: obtaining the impact data during the charging and discharging of the battery pack; comparing the impact data during the charging and discharging of the battery pack with each matching impact data stored in the database to obtain the comparison coefficient; and obtaining the permissible deviation data during the charging and discharging of the battery pack corresponding to the matching impact data with the smallest comparison coefficient stored in the database.

[0012] Furthermore, the impact data includes the standard deviation of the power supply voltage and the charge / discharge cycle of the battery pack, and the matching impact data includes the standard deviation of the power supply matching voltage and the battery pack matching charge / discharge cycle;

[0013] The formula for calculating the comparison coefficient is as follows:

[0014]

[0015] In the formula, Gsb is the standard deviation of the power supply voltage, Gcb is the charge / discharge cycle of the battery pack, Gsz is the standard deviation of the matching voltage at the power supply, Gcz is the matching charge / discharge cycle of the battery pack, and σ is the comparison coefficient.

[0016] Furthermore, the dynamic data includes the standard deviation of the charging current, the standard deviation of the discharging current, the average temperature during charging and discharging, and the noise intensity during charging and discharging; the dynamic parameter data includes the standard deviation of the charging current, the standard deviation of the discharging current, the average temperature during charging and discharging, and the noise intensity during charging and discharging; the permissible deviation data includes the permissible deviation of the charging current standard deviation, the permissible deviation of the discharging current standard deviation, the permissible deviation of the average temperature during charging and discharging, and the permissible deviation of the noise intensity during charging and discharging.

[0017] Furthermore, the formula for calculating the dynamic evaluation coefficient of the battery pack is as follows:

[0018]

[0019] In the formula, Csd is the standard deviation of the current during charging, Fsd is the standard deviation of the current during discharging, Wsd is the average temperature during charging and discharging, Zsd is the noise intensity during charging and discharging, Ccd is the reference standard deviation of the current during charging, Fcd is the reference standard deviation of the current during discharging, Wcd is the reference average temperature during charging and discharging, Zcd is the reference noise intensity during charging and discharging, ΔC is the permissible deviation of the standard deviation of the current during charging, ΔF is the permissible deviation of the standard deviation of the current during discharging, ΔW is the permissible deviation of the average temperature during charging and discharging, ΔZ is the permissible deviation of the noise intensity during charging and discharging, and e is a natural constant.

[0020] Further, the management plan for the battery pack is determined, including the following steps: weighting and summing the static deviation coefficient and the dynamic evaluation coefficient of the battery pack to obtain a comprehensive value; comparing the comprehensive value with the comprehensive value intervals stored in the database to determine the comprehensive value interval into which the comprehensive value falls; and retrieving the management plan for the battery pack corresponding to the comprehensive value interval from the database based on the determined comprehensive value interval.

[0021] The present invention has the following beneficial effects:

[0022] This battery pack charging and discharging monitoring and management platform, through two modules—static state assessment and charging and discharging state assessment—can comprehensively monitor the operating status of the battery pack and accurately calculate static deviation coefficients and dynamic assessment coefficients, thus providing a scientific basis for battery pack management solutions. This method effectively solves the problem that traditional monitoring methods cannot assess and manage the stability of battery packs under different operating conditions in real time, improving battery pack maintenance efficiency, extending their service life, and ensuring equipment safety and reliability.

[0023] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0024] Figure 1 This is a flowchart of the battery pack charging and discharging monitoring and management platform of the present invention. Detailed Implementation

[0025] This application embodiment utilizes a battery pack charging and discharging monitoring and management platform. Through two modules—static state assessment and charging and discharging state assessment—it can comprehensively monitor the operating status of the battery pack and accurately calculate the static deviation coefficient and dynamic assessment coefficient, thereby providing a scientific basis for battery pack management schemes. This method effectively solves the problem that traditional monitoring methods cannot assess and manage the stability of battery packs under different operating conditions in real time, improves the maintenance efficiency of battery packs, extends their service life, and ensures the safety and reliability of the equipment.

[0026] Please see Figure 1 The present invention provides a technical solution: a battery pack charging and discharging monitoring and management platform, including a battery pack static state assessment module, a charging and discharging state assessment module and a battery pack state management module.

[0027] By combining static and dynamic condition assessments, monitoring extends beyond the charging and discharging process to include the battery pack's performance in non-operating states. This comprehensive monitoring provides more complete battery operation data. By calculating static deviation coefficients and dynamic assessment coefficients, the stability of the battery under different operating conditions can be quantified, allowing for a more accurate assessment of its health status. Based on real-time monitoring data, the platform provides a scientific basis for management plan development, supporting intelligent management. Through dynamic assessment, the platform can promptly detect problems occurring during battery charging and discharging, reacting quickly and reducing the probability of risks and malfunctions.

[0028] The battery pack static state evaluation module is used to evaluate the state of the battery pack when it is not charging or discharging, and to determine the static deviation coefficient. The static deviation coefficient is used to represent the stability of the currently monitored battery pack when it is not charging or discharging.

[0029] Specifically, the process of determining the static deviation coefficient is as follows: obtaining static data of the battery pack under static conditions; obtaining parameter static data of the battery pack under static conditions from the database; and comprehensively analyzing the static data of the battery pack under static conditions and the parameter static data of the battery pack under static conditions obtained from the database to obtain the static deviation coefficient.

[0030] The static data includes the amount of power loss within a set time period, and the reference static data includes the reference power loss within a set time period; the static deviation coefficient is the difference between the amount of power loss within a set time period and the reference power loss within a set time period.

[0031] The static deviation coefficient provides a clear quantitative indicator that can effectively evaluate the performance of a battery pack and help identify its energy loss under static conditions. By comparing the actual energy loss with the set loss, potential problems of the battery pack, such as aging, failure, or other factors affecting performance, can be identified in a timely manner, so that corresponding maintenance measures can be taken.

[0032] Static deviation coefficient provides managers with a scientific basis to help develop more effective management strategies and maintenance plans, optimize resource allocation and use, and detect battery pack anomalies in a timely manner by monitoring power loss, thereby reducing safety hazards caused by battery performance degradation and ensuring the safety of equipment and personnel. Continuous monitoring and evaluation of static deviation coefficient can enable timely maintenance and management, extend the service life of battery packs, reduce replacement frequency, and save costs.

[0033] The step of obtaining the parameter static data of the battery pack in a static state from the database includes the following steps: obtaining the ambient temperature of the battery pack; comparing the ambient temperature of the battery pack with the ambient temperature matching values ​​stored in the database to obtain an ambient temperature matching value that is equal to the ambient temperature of the battery pack; and obtaining the parameter static data of the battery pack in a static state corresponding to the ambient temperature matching value from the database based on the ambient temperature matching value.

[0034] The acquired ambient temperature is compared with various stored ambient temperature matching values ​​in the database to find the matching value that matches the actual ambient temperature, ensuring the accuracy and relevance of subsequent data. Based on the found ambient temperature matching value, the corresponding static data of the battery pack under static conditions is extracted from the database. This data has been verified and can serve as a benchmark for evaluating battery pack performance. By using ambient temperature as a parameter for data matching, it is ensured that the static state evaluation data of the battery pack is obtained under specific environmental conditions, enhancing the accuracy and reliability of the evaluation.

[0035] The charge / discharge state assessment module is used to analyze the state of the battery pack during charging and discharging, and obtain the dynamic evaluation coefficient of the battery pack. The dynamic evaluation coefficient of the battery pack is used to represent the stability of the battery pack during charging and discharging.

[0036] The process of obtaining the dynamic evaluation coefficient of the battery pack includes the following steps: obtaining dynamic data of the battery pack during charging and discharging; obtaining dynamic parameter data of the battery pack during charging and discharging stored in the database; obtaining allowable deviation data of the battery pack during charging and discharging; and obtaining the dynamic evaluation coefficient of the battery pack based on the dynamic data, dynamic parameter data, and allowable deviation data.

[0037] First, dynamic data generated by the battery pack during charging and discharging is collected, including real-time voltage, current, temperature, and other relevant parameters. This data reflects the operating status of the battery pack under actual working conditions. Dynamic parameter data related to the battery pack during charging and discharging is retrieved from a database. This parameter data is standard performance data, validated, and can serve as a benchmark for evaluating battery pack performance. Data on the permissible deviation range of the battery pack during charging and discharging is obtained; this deviation data provides a reference for performance fluctuations under normal operating conditions.

[0038] The collected dynamic data, parameter dynamic data, and allowable deviation data are comprehensively analyzed to calculate the dynamic evaluation coefficient of the battery pack. This coefficient reflects the performance and stability of the battery pack during charging and discharging, and the health status of the battery pack is assessed by comparing the relationship between actual performance and standard performance.

[0039] The process of obtaining permissible deviation data during battery pack charging and discharging includes the following steps: obtaining impact data during battery pack charging and discharging; comparing the impact data during battery pack charging and discharging with each matching impact data stored in the database to obtain a comparison coefficient; and obtaining the permissible deviation data during battery pack charging and discharging corresponding to the matching impact data with the smallest comparison coefficient stored in the database.

[0040] First, it's necessary to acquire data on various influences that the battery pack might experience during charging and discharging. This acquired data is then compared with matching influence data stored in a database. This comparison process aims to determine the similarity between the current influence data and historical data, thereby understanding the extent of different influencing factors on the battery pack. During the comparison, the system calculates a comparison coefficient for each influence data point compared to the stored data. These coefficients typically represent the closeness between the influence data and historical patterns, helping to identify the permissible deviation range under specific conditions. The matching influence data corresponding to the smallest comparison coefficient is then found, and this data is used to retrieve the relevant permissible deviation data for the battery pack's charging and discharging process from the database. This data will serve as an important reference for judging battery performance during actual charging and discharging.

[0041] The impact data includes the standard deviation of the power supply voltage and the charge / discharge cycle of the battery pack; the matching impact data includes the standard deviation of the matching voltage at the power supply end and the matching charge / discharge cycle of the battery pack.

[0042] The formula for calculating the comparison coefficient is as follows:

[0043]

[0044] In the formula, Gsb is the standard deviation of the power supply voltage, Gcb is the charge / discharge cycle of the battery pack, Gsz is the standard deviation of the matching voltage at the power supply, Gcz is the matching charge / discharge cycle of the battery pack, and σ is the comparison coefficient.

[0045] The influencing data includes the standard deviation of the power supply voltage and the battery pack charge / discharge cycles. These data quantify the factors that may affect battery performance during actual charge / discharge processes. The matching influencing data includes the standard deviation of the power supply matching voltage and the battery pack matching charge / discharge cycles. This data is historical and provides a standard reference for battery performance. A comparison coefficient is calculated using a given formula. This coefficient measures the degree of deviation between the influencing data and the matching influencing data. The similarity between the two is determined by calculating the squared difference between the influencing data and the matching data. The logarithm is used to compress the numerical range, making the calculation results easier to process.

[0046] The dynamic data includes the standard deviation of current during charging, the standard deviation of current during discharging, the average temperature during charging and discharging, and the noise intensity during charging and discharging; the dynamic reference data includes the reference standard deviation of current during charging, the reference standard deviation of current during discharging, the reference average temperature during charging and discharging, and the reference noise intensity during charging and discharging; the permissible deviation data includes the permissible deviation of the standard deviation of current during charging, the permissible deviation of the standard deviation of current during discharging, the permissible deviation of the average temperature during charging and discharging, and the permissible deviation of the noise intensity during charging and discharging.

[0047] Multi-dimensional dynamic data can comprehensively reflect the operating status of battery packs during charging and discharging, helping to identify performance problems or potential faults. Comparing dynamic data with dynamic parameter data can clearly identify the differences between actual and standard states, improving management accuracy. By defining allowable deviation data, it can be clarified which performance changes are within the normal range and which changes require attention, helping to effectively avoid operational risks. The analysis based on dynamic data and allowable deviation data can provide data support for managers, helping them to formulate more scientific and reasonable maintenance plans and operating strategies.

[0048] The formula for calculating the dynamic evaluation coefficient of the battery pack is as follows:

[0049]

[0050] In the formula, Csd is the standard deviation of the current during charging, Fsd is the standard deviation of the current during discharging, Wsd is the average temperature during charging and discharging, Zsd is the noise intensity during charging and discharging, Ccf is the reference standard deviation of the current during charging, Fcd is the reference standard deviation of the current during discharging, Wcd is the reference average temperature during charging and discharging, Zcd is the reference noise intensity during charging and discharging, ΔC is the permissible deviation of the standard deviation of the current during charging, ΔF is the permissible deviation of the standard deviation of the current during discharging, ΔW is the permissible deviation of the average temperature during charging and discharging, ΔZ is the permissible deviation of the noise intensity during charging and discharging, and e is a natural constant.

[0051] The dynamic evaluation coefficient of a battery pack is used to represent the degree of deviation of the battery pack from its standardized parameters (reference data) during dynamic operation. A smaller coefficient indicates that the performance is closer to the standard state, while a larger coefficient may indicate a performance degradation or abnormality. The coefficient is calculated by normalizing the absolute difference between the actual dynamic data and the standardized data (using allowable deviation), summing the normalized differences, and multiplying by a natural constant and a constant coefficient to obtain the final dynamic evaluation coefficient. This process allows the evaluation coefficient to reflect the overall deviation while also controlling the importance of individual factors with different parameters.

[0052] This evaluation coefficient incorporates the influence of multiple dynamic parameters, enabling a comprehensive assessment of the battery pack's operating status from multiple perspectives. It provides a complete performance insight and, by comparing it with allowable deviations, effectively identifies which parameters are within the normal range and which are abnormal, facilitating proactive measures.

[0053] The battery pack status management module is used to determine the management scheme of the battery pack based on the static deviation coefficient and the battery pack dynamic evaluation coefficient.

[0054] The process of determining a management plan for the battery pack includes the following steps: First, a weighted sum of the static deviation coefficient and the dynamic evaluation coefficient of the battery pack is calculated to obtain a comprehensive value (the weighted values ​​are fixed values ​​stored in the database, and the sum of the weighted values ​​is 1). Second, the comprehensive value is compared with the comprehensive value intervals stored in the database to determine the comprehensive value interval into which the comprehensive value falls. Third, based on the determined comprehensive value interval, the management plan for the battery pack corresponding to the comprehensive value interval is retrieved from the database.

[0055] The main function of the battery pack status management module is to formulate a scientific and effective management plan based on static deviation coefficients and dynamic evaluation coefficients to ensure the safety and performance of the battery pack. It calculates a weighted sum of the static deviation coefficient (reflecting long-term characteristics) and the battery pack dynamic evaluation coefficient (reflecting real-time performance) to obtain a comprehensive value. The weighted value is determined by fixed values ​​in the database, ensuring that the relative influence weights of the two are clear and their sum is 1. This step ensures that the calculation of the comprehensive value considers both long-term status and provides an intuitive reflection of current performance. The obtained comprehensive value is compared with preset comprehensive value intervals in the database to determine the interval to which the comprehensive value belongs. Each interval corresponds to a different management plan, reflecting different operational requirements or maintenance strategies. Once a comprehensive value interval is identified, the corresponding management plan can be retrieved from the database. This ensures the ability to dynamically adjust the battery pack management strategy to adapt to different operating states.

[0056] An electronic device includes a processor and a memory, wherein computer program instructions are stored in the memory, and the computer program instructions, when executed by the processor, cause the processor to execute the battery pack charge and discharge monitoring and management platform as described above.

[0057] A computer-readable storage medium for storing a program that, when executed by a processor, implements the battery pack charge / discharge monitoring and management platform as described above.

[0058] In summary, this application has at least the following effects:

[0059] By employing two modules—static state assessment and charge / discharge state assessment—the operating status of the battery pack can be comprehensively monitored, and the static deviation coefficient and dynamic assessment coefficient can be accurately calculated, thus providing a scientific basis for battery pack management solutions. This method effectively solves the problem that traditional monitoring methods cannot assess and manage the stability of battery packs under different operating conditions in real time, improving the maintenance efficiency of the battery pack, extending its service life, and ensuring the safety and reliability of the equipment.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0061] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0064] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0065] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A battery pack charge-discharge monitoring management platform, characterized by, The battery pack static state evaluation module, the charge and discharge state evaluation module and the battery pack state management module are included, wherein: The battery pack static state evaluation module is used for evaluating the state of the battery pack when not charging and discharging, determining a static deviation coefficient, and the static deviation coefficient is used for representing the stability of the currently monitored battery pack when not charging and discharging; The charge and discharge state evaluation module is used for analyzing the state of the battery pack when charging and discharging, obtaining a dynamic evaluation coefficient of the battery pack, and the dynamic evaluation coefficient of the battery pack is used for representing the stability of the battery pack when charging and discharging; The battery pack state management module is used for determining a management scheme of the battery pack based on the static deviation coefficient and the dynamic evaluation coefficient of the battery pack.

2. The battery pack charge and discharge monitoring management platform according to claim 1, wherein, The process of determining the static deviation coefficient is as follows: Obtain static data in the static state of the battery pack; Obtain reference static data in the static state of the battery pack from the database; Comprehensively analyze the static data in the static state of the battery pack and the reference static data in the static state of the battery pack obtained from the database to obtain the static deviation coefficient.

3. The battery pack charge and discharge monitoring management platform according to claim 2, wherein, The static data includes an amount of power loss within a set time, and the reference static data includes a reference amount of power loss within a set time; The static deviation coefficient is the difference between the amount of power loss within a set time and the reference amount of power loss within a set time.

4. The battery pack charge and discharge monitoring management platform according to claim 2, wherein, The process of obtaining the reference static data in the static state of the battery pack from the database includes the following steps: Obtain the ambient temperature of the battery pack; Compare the ambient temperature of the battery pack with each ambient temperature matching value stored in the database to obtain an ambient temperature matching value equal to the ambient temperature of the battery pack; Obtain the reference static data in the static state of the battery pack corresponding to the ambient temperature matching value from the database based on the ambient temperature matching value.

5. The battery pack charge and discharge monitoring management platform according to claim 1, wherein, The process of obtaining the dynamic evaluation coefficient of the battery pack includes the following steps: Obtain dynamic data when the battery pack is charging and discharging; Obtain dynamic reference data of the battery pack when charging and discharging stored in the database; Obtain allowable deviation data of the battery pack when charging and discharging; Obtain the dynamic evaluation coefficient of the battery pack based on the dynamic data, the dynamic reference data and the allowable deviation data.

6. The battery pack charge and discharge monitoring management platform according to claim 5, wherein, The process of obtaining the allowable deviation data of the battery pack when charging and discharging includes the following steps: Obtain influence data when the battery pack is charging and discharging; Compare the influence data when the battery pack is charging and discharging with each matching influence data stored in the database to obtain a comparison coefficient; Obtain the allowable deviation data of the battery pack when charging and discharging corresponding to the matching influence data corresponding to the smallest comparison coefficient stored in the database.

7. The battery pack charge and discharge monitoring management platform according to claim 6, wherein, The influence data includes a standard deviation of supply end voltage and a battery pack charging and discharging cycle, and the matching influence data includes a matching standard deviation of supply end voltage and a matching battery pack charging and discharging cycle; The calculation formula of the comparison coefficient is as follows: In the formula, Gsb is the standard deviation of supply end voltage, Gcb is the battery pack charging and discharging cycle, Gsz is the matching standard deviation of supply end voltage, Gcz is the matching battery pack charging and discharging cycle, and σ is the comparison coefficient.

8. The battery pack charge and discharge monitoring management platform of claim 5, wherein, The dynamic data includes a standard deviation of current when charging, a standard deviation of current when discharging, an average temperature when charging and discharging, and a noise intensity when charging and discharging; The dynamic reference data includes a charging current reference standard deviation, a discharging current reference standard deviation, a charging and discharging reference average temperature, and a charging and discharging reference noise intensity; The allowable deviation data includes a charging current standard deviation allowable deviation, a discharging current standard deviation allowable deviation, a charging and discharging average temperature allowable deviation, and a charging and discharging noise intensity allowable deviation.

9. The battery pack charge and discharge monitoring management platform according to claim 8, wherein, The calculation formula of the battery pack dynamic evaluation coefficient is as follows: In the formula, Csd is the charging current standard deviation, Fsd is the discharging current standard deviation, Wsd is the charging and discharging average temperature, Zsd is the charging and discharging noise intensity, Ccd is the charging current reference standard deviation, Fcd is the discharging current reference standard deviation, Wcd is the charging and discharging reference average temperature, Zcd is the charging and discharging reference noise intensity, ΔC is the charging current standard deviation allowable deviation, ΔF is the discharging current standard deviation allowable deviation, ΔW is the charging and discharging average temperature allowable deviation, ΔZ is the charging and discharging noise intensity allowable deviation, and e is the natural constant.

10. The battery pack charge and discharge monitoring management platform of claim 1, wherein, Determining the management scheme of the battery pack includes the following steps: Weighted sum of the static deviation coefficient and the battery pack dynamic evaluation coefficient to obtain a comprehensive value; Comparing the comprehensive value with each comprehensive value interval stored in the database to determine the comprehensive value interval into which the comprehensive value falls; Based on the determined comprehensive value interval, obtaining the management scheme of the battery pack corresponding to the comprehensive value interval from the database.

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