Battery safety control system and method based on remote monitoring

Abstract

The present invention discloses a battery safety control system and method based on remote monitoring, which belongs to the field of batteries. The present invention imports the operation abnormality analysis results and the obtained operation temperature data of the battery into a battery abnormality analysis model to analyze the battery abnormality degree, imports the analyzed battery abnormality degree and the battery usage time into a battery remaining life prediction model to predict the battery remaining life, and performs battery operation early warning according to the battery remaining life prediction result. The present invention comprehensively evaluates the battery operation electrical signal data and the operation temperature data, and then accurately analyzes the battery operation abnormality degree, and predicts the battery remaining life by accurately obtaining the battery operation abnormality degree change rate, thereby improving the accuracy of battery remaining life prediction and thus improving the ability to grasp the danger of the battery.

Description

Technical Field

[0001] The present invention belongs to the field of storage batteries, and specifically relates to a storage battery safety control system and method based on remote monitoring. Background Art

[0002] During the continuous use of a storage battery, the performance of the storage battery decreases with the use frequency. During the continuous decrease of the storage battery performance, due to external forces or the reasons of the storage battery itself, it is easy to cause a storage battery fire. A storage battery fire is an abnormal reaction that occurs during the charging and discharging process of the storage battery, resulting in an increase in temperature, electrolyte leakage, or short circuit, etc., and then causing a fire accident. Therefore, many storage battery safety control systems have been designed in the prior art to prevent storage battery fires;

[0003] However, when the prior art prevents storage battery fires, it is unable to comprehensively evaluate the operating electrical signal data and operating temperature data of the storage battery, resulting in an inability to accurately analyze the abnormal degree of the storage battery operation. Furthermore, it is unable to predict the remaining life of the storage battery through the change rate of the accurately obtained abnormal degree of the storage battery operation, reducing the accuracy of predicting the remaining life of the storage battery, and thus reducing the ability to master the danger of the storage battery. Most of the prior art has the above problems;

[0004] For example, in a Chinese patent with the application publication number CN118209208A, a non-destructive temperature measurement device for the inspection and maintenance of power supply equipment belongs to the field of non-destructive temperature measurement for the inspection and maintenance of power supply equipment. The non-destructive temperature measurement device for the inspection and maintenance of power supply equipment includes a power transmission component, a temperature measurement component, a moving component, and a guiding component. The power transmission component includes a moving plate, and two storage batteries, a controller, and a solar panel are respectively installed inside the moving plate. The two storage batteries, the controller, and the solar panel are electrically connected. Through the cooperation of the power transmission component, the temperature measurement component, the moving component, and the guiding component set in the present invention, not only can the temperature measurement device be powered by solar energy, thereby saving electric energy and reducing power consumption, but also through the mutual cooperation of the above structures, the whole process and comprehensive temperature inspection of multiple transmission lines with different spacings can be carried out, and a guiding effect can be achieved to prevent the temperature measurement device from falling. Therefore, the versatility of the temperature measurement device can be enhanced, and the temperature measurement quality and use safety can be improved;

[0005] The above patents all have the problems proposed in this background art. To solve the problems proposed in this background art, the present application designs a storage battery safety control system and method based on remote monitoring. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention proposes a storage battery safety control system and method based on remote monitoring.

[0007] To achieve the above object, the present invention provides the following technical solutions: A battery safety control method based on remote monitoring, which includes the following specific steps:

[0008] The data acquisition module collects the operation data of the battery during the operation of the battery, and at the same time obtains the operation temperature data of the battery;

[0009] Import the operation data of the battery collected during the operation of the battery into the operation anomaly analysis model for operation anomaly analysis;

[0010] Import the operation anomaly analysis result and the obtained operation temperature data of the battery into the battery anomaly analysis model for battery anomaly degree analysis;

[0011] Import the analyzed battery anomaly degree and the battery usage time into the battery remaining life prediction model for battery remaining life prediction;

[0012] Perform battery operation early warning according to the battery remaining life prediction result.

[0013] It should be noted here that, as a preferred technical solution of the battery safety control method based on remote monitoring, the specific steps for the data acquisition module to collect the operation data of the battery during the operation of the battery and at the same time obtain the operation temperature data of the battery are as follows:

[0014] S11. Collect the voltage change data curve and current change data curve during the operation of the battery through the power information acquisition terminal, and store them in the first storage component;

[0015] S12. Set a number of temperature acquisition points on the surface of the battery, collect the temperature data of the temperature acquisition points on the surface of the battery through the temperature acquisition terminal, and store them in the second storage component.

[0016] It should be noted here that, as a preferred technical solution of the battery safety control method based on remote monitoring, the importing the operation data of the battery collected during the operation of the battery into the operation anomaly analysis model for operation anomaly analysis includes the following specific steps:

[0017] S21. Obtain the voltage change data curve and current change data curve during the operation of the battery within the monitoring period, divide the monitoring period evenly into several monitoring time periods, where the duration of the monitoring time period is 1s to 3s, and obtain the average voltage change data curve of each monitoring time period and import it into the voltage anomaly value calculation formula to calculate the voltage anomaly value, where the voltage anomaly value calculation formula is:

[0018] Wherein, a is the coefficient of the voltage difference amplitude ratio, N is the number of monitoring time periods in the monitoring cycle, Vi is the average voltage value of the i-th monitoring time period, and Vm is the standard voltage value of the i-th monitoring time period;

[0019] S22. Obtain the current change data curve within the monitoring cycle, and import the current change data within the monitoring cycle into the current outlier calculation formula to calculate the current outlier. The current outlier calculation formula is as follows: Wherein, T is the duration of the monitoring cycle, dt is the time integral, It is the current output value at time t, and its is the standard current output value at time t;

[0020] S23. Obtain the voltage outlier and current outlier within the monitoring cycle, and import them into the operation anomaly analysis value calculation formula to calculate the operation anomaly analysis value of the monitoring cycle. The operation anomaly analysis value calculation formula is: XY = λXV + (1 - λ)XI, where λ is the voltage anomaly ratio coefficient.

[0021] It should be noted here that as a preferred technical solution of the battery safety control method based on remote monitoring, the step of importing the operation anomaly analysis result and the obtained operation temperature data of the battery into the battery anomaly analysis model to analyze the battery anomaly degree includes the following specific steps:

[0022] S31. Obtain the temperature data of each monitoring point on the battery surface at the end moment of the monitoring cycle, and import the temperature data of each monitoring point on the battery surface at the end moment of the monitoring cycle into the temperature anomaly analysis value calculation formula to calculate the temperature anomaly analysis value. The temperature anomaly analysis value calculation formula is: Wherein, m is the number of monitoring points, Tj is the temperature value of the j-th monitoring point, Tjm is the median of the temperature safety range of the j-th monitoring point, Tjmax is the maximum value of the temperature safety range of the j-th monitoring point, and Tjmin is the minimum value of the temperature safety range of the j-th monitoring point;

[0023] S32. Substitute the calculated operation anomaly analysis value and temperature anomaly analysis value within the monitoring cycle into the battery anomaly degree analysis value calculation formula to calculate the battery anomaly degree analysis value. The battery anomaly degree analysis value calculation formula is: XZ = (λXV + (1 - λ)XI + 1) × exp(XT), where exp() is the exponential power of the natural constant e.

[0024] It should be noted here that as a preferred technical solution of the battery safety control method based on remote monitoring, the specific content of importing the analyzed battery anomaly degree and the battery usage time into the battery remaining life prediction model to predict the battery remaining life includes the following:

[0025] Obtain the analyzed value of the abnormal degree of the battery in the current monitoring period and the analyzed value of the abnormal degree of the battery in the previous monitoring period. Compare the analyzed value of the abnormal degree of the battery in the current monitoring period with that in the previous monitoring period. If the analyzed value of the abnormal degree of the battery in the current monitoring period is less than or equal to that in the previous monitoring period, no life prediction is performed. If the analyzed value of the abnormal degree of the battery in the current monitoring period is greater than that in the previous monitoring period, life prediction is performed, and substitute it into the battery remaining life prediction formula to calculate the remaining life of the battery. Among them, the battery remaining life prediction formula is: Among them, XZM is the set threshold for analyzing the abnormal degree, XZ(Tt-1) is the analyzed value of the abnormal degree of the battery in the previous monitoring period, and t s is the duration of the monitoring period.

[0026] It should be noted here that as a preferred technical solution of the battery safety control method based on remote monitoring, the battery operation warning based on the battery remaining life prediction result includes the following specific content: Compare the calculated battery remaining life prediction value with the set battery remaining life threshold. If the battery remaining life prediction value is greater than the set battery remaining life threshold, no battery maintenance warning is issued to the maintenance personnel. If the battery remaining life prediction value is less than or equal to the set battery remaining life threshold, a battery maintenance warning is issued to the maintenance personnel to remind the maintenance personnel to maintain the battery. It should be noted here that the set battery remaining life threshold is set according to the habits of the maintenance personnel and is at least one day.

[0027] The battery safety control system based on remote monitoring is implemented based on the above battery safety control method based on remote monitoring, and specifically includes:

[0028] The data acquisition module is used to collect the operation data of the battery during the operation of the battery, and at the same time obtain the operation temperature data of the battery;

[0029] The operation abnormality analysis module is used to import the operation data of the battery collected during the operation of the battery into the operation abnormality analysis model for operation abnormality analysis;

[0030] The battery abnormal degree analysis module is used to import the operation abnormality analysis result and the obtained operation temperature data of the battery into the battery abnormal degree analysis model for battery abnormal degree analysis;

[0031] The battery remaining life prediction module is used to import the analyzed battery abnormal degree and the battery usage time into the battery remaining life prediction model for battery remaining life prediction;

[0032] An early warning module, which is used to give an early warning of the operation of the storage battery according to the prediction result of the remaining life of the storage battery;

[0033] A control module, which is used to control the operation of the data acquisition module, the operation anomaly analysis module, the storage battery anomaly degree analysis module, the storage battery remaining life prediction module and the early warning module.

[0034] An electronic device includes: a processor and a memory, wherein a computer program that can be called by the processor is stored in the memory;

[0035] The processor executes the above-mentioned storage battery safety control method based on remote monitoring by calling the computer program stored in the memory.

[0036] A computer-readable storage medium stores instructions, and when the instructions run on a computer, the computer is made to execute the storage battery safety control method based on remote monitoring as described above.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] In the present invention, the operation data of the storage battery during the operation of the storage battery is collected by the data acquisition module, and at the same time, the operation temperature data of the storage battery is obtained. The collected operation data of the storage battery during the operation of the storage battery is imported into the operation anomaly analysis model for operation anomaly analysis. The operation anomaly analysis result and the obtained operation temperature data of the storage battery are imported into the storage battery anomaly degree analysis model for storage battery anomaly degree analysis. The analyzed storage battery anomaly degree and the storage battery usage time are imported into the storage battery remaining life prediction model for storage battery remaining life prediction. An early warning of the operation of the storage battery is given according to the prediction result of the remaining life of the storage battery. The present invention comprehensively evaluates the operation electrical signal data and operation temperature data of the storage battery, and then accurately analyzes the operation anomaly degree of the storage battery. The remaining life of the storage battery is predicted based on the accurately obtained change rate of the operation anomaly degree of the storage battery, improving the accuracy of the prediction of the remaining life of the storage battery, and further improving the ability to master the danger of the storage battery. Description of the Drawings

[0039] Figure 1 It is a schematic diagram of the overall process of the storage battery safety control method based on remote monitoring of the present invention;

[0040] Figure 2 It is a schematic diagram of step S2 of the storage battery safety control method based on remote monitoring of the present invention;

[0041] Figure 3 It is a schematic diagram of the overall framework of the storage battery safety control system based on remote monitoring of the present invention;

[0042] Figure 4 It is a schematic diagram of the electronic device of the present invention. Detailed implementation manners

[0043] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way limits the present application and its application or use.

[0044] Embodiment 1

[0045] To solve the technical problems raised in the background art: when the prior art prevents battery fires, it is unable to comprehensively evaluate the battery operation electrical signal data and operation temperature data, resulting in the inability to accurately analyze the degree of battery operation abnormality. Furthermore, it is unable to predict the remaining life of the battery through the accurately obtained change rate of the battery operation abnormality degree, reducing the accuracy of the remaining life prediction of the battery and thus reducing the ability to master the danger of the battery; the present invention provides a preferred embodiment: as Figure 1 - Figure 2 shown, a battery safety control method based on remote monitoring, which includes the following specific steps:

[0046] S1. The data acquisition module acquires the operation data of the battery during the operation of the battery, and simultaneously obtains the operation temperature data of the battery;

[0047] In this embodiment, the specific steps for the data acquisition module to acquire the operation data of the battery during the operation of the battery and simultaneously obtain the operation temperature data of the battery are as follows:

[0048] S11. Collect the voltage change data curve and current change data curve during the operation of the battery through the power information acquisition terminal, and store them in the first storage component;

[0049] S12. Set a plurality of temperature acquisition points on the surface of the battery, and collect the temperature data of the temperature acquisition points on the surface of the battery through the temperature acquisition terminal, and store them in the second storage component;

[0050] S2. Import the operation data of the battery acquired during the operation of the battery into the operation abnormality analysis model for operation abnormality analysis;

[0051] Importing the current and voltage data during the operation of the battery acquired into the operation abnormality analysis model for analysis is a reasonable and necessary practice;

[0052] Current and voltage are key parameters for measuring the health and performance of a battery. Under normal operating conditions, a battery will have a stable current-voltage curve. Any abnormal fluctuations deviating from this curve may indicate potential problems with the battery. By real-time monitoring of current and voltage data, an operation anomaly analysis model can detect early fault signs of the battery in a timely manner, such as overcharging, over-discharging, internal short circuit, etc. This information is crucial for implementing preventive maintenance and can avoid battery performance degradation and even safety accidents.

[0053] As a power supply component for many critical systems, the reliability of a battery directly affects the stability of the entire system. For example, in fields such as data centers and communication base stations, battery failures may lead to service interruptions. Through the anomaly analysis model, problems can be identified in advance and measures can be taken to improve the overall reliability of the system.

[0054] Timely analysis of current and voltage data can reduce safety risks caused by battery failures and at the same time reduce economic losses caused by emergency repairs or battery replacements. Therefore, from the perspectives of safety, economy, and maintenance, it is very reasonable to import the current and voltage data of the battery into the operation anomaly analysis model for anomaly analysis.

[0055] In this embodiment, importing the operation data of the battery during the operation process collected into the operation anomaly analysis model for operation anomaly analysis includes the following specific steps:

[0056] S21. Obtain the voltage change data curve and current change data curve during the battery operation within the monitoring period. Divide the monitoring period evenly into several monitoring time segments, where the duration of the monitoring time segment is from 1 s to 3 s. Obtain the average voltage change data curve of each monitoring time segment and import it into the voltage anomaly value calculation formula to calculate the voltage anomaly value. The voltage anomaly value calculation formula is:

[0057] where a is the voltage difference amplitude ratio coefficient, N is the number of monitoring time segments in the monitoring period, Vi is the average voltage value of the i-th monitoring time segment, and Vm is the voltage standard value of the i-th monitoring time segment.

[0058] S22. Obtain the current change data curve within the monitoring period. Import the current change data within the monitoring period into the current anomaly value calculation formula to calculate the current anomaly value. The current anomaly value calculation formula is: where T is the duration of the monitoring period, dt is the time integral, It is the current output value at time t, and its is the current output standard value at time t.

[0059] S23. Obtain the voltage anomaly value and current anomaly value within the monitoring period, and import them into the operating anomaly analysis value calculation formula to calculate the operating anomaly analysis value of the monitoring period. Among them, the operating anomaly analysis value calculation formula is: XY = λXV + (1 - λ)XI, where λ is the voltage anomaly proportion coefficient;

[0060] S3. Import the operating anomaly analysis result and the obtained operating temperature data of the storage battery into the storage battery anomaly analysis model to analyze the anomaly degree of the storage battery;

[0061] In this embodiment, importing the operating anomaly analysis result and the obtained operating temperature data of the storage battery into the storage battery anomaly analysis model to analyze the anomaly degree of the storage battery includes the following specific steps:

[0062] S31. Obtain the temperature data of each monitoring point on the surface of the storage battery at the end moment of the monitoring period, and import the temperature data of each monitoring point on the surface of the storage battery at the end moment of the monitoring period into the temperature anomaly analysis value calculation formula to calculate the temperature anomaly analysis value. Among them, the temperature anomaly analysis value calculation formula is: where m is the number of monitoring points, Tj is the temperature value of the jth monitoring point, Tjm is the median of the temperature safety range of the jth monitoring point, Tjmax is the maximum value of the temperature safety range of the jth monitoring point, and Tjmin is the minimum value of the temperature safety range of the jth monitoring point;

[0063] S32. Substitute the calculated operating anomaly analysis value and temperature anomaly analysis value within the monitoring period into the storage battery anomaly degree analysis value calculation formula to calculate the storage battery anomaly degree analysis value. Among them, the storage battery anomaly degree analysis value calculation formula is:

[0064] XZ = (λXV + (1 - λ)XI + 1) × exp(XT), where exp() is the exponential power of the natural constant e;

[0065] S4. Import the analyzed anomaly degree of the storage battery and the service time of the storage battery into the storage battery remaining life prediction model to predict the remaining life of the storage battery;

[0066] In this embodiment, importing the analyzed anomaly degree of the storage battery and the service time of the storage battery into the storage battery remaining life prediction model to predict the remaining life of the storage battery includes the following specific contents:

[0067] Obtain the analysis value of the abnormal degree of the battery in the current monitoring period and the analysis value of the abnormal degree of the battery in the previous monitoring period. Compare the analysis value of the abnormal degree of the battery in the current monitoring period with the analysis value of the abnormal degree of the battery in the previous monitoring period. If the analysis value of the abnormal degree of the battery in the current monitoring period is less than or equal to the analysis value of the abnormal degree of the battery in the previous monitoring period, no life prediction is performed. If the analysis value of the abnormal degree of the battery in the current monitoring period is greater than the analysis value of the abnormal degree of the battery in the previous monitoring period, life prediction is performed, and substitute it into the battery remaining life prediction formula to calculate the remaining life of the battery. Among them, the battery remaining life prediction formula is: Among them, XZM is the set abnormal degree analysis threshold, XZ(Tt-1) is the analysis value of the abnormal degree of the battery in the previous monitoring period, and t s is the monitoring period duration;

[0068] S5. Perform battery operation warning according to the battery remaining life prediction result;

[0069] In this embodiment, performing battery operation warning according to the battery remaining life prediction result includes the following specific contents: Compare the calculated battery remaining life prediction value with the set battery remaining life threshold. If the battery remaining life prediction value is greater than the set battery remaining life threshold, no battery maintenance warning is issued to the maintenance personnel. If the battery remaining life prediction value is less than or equal to the set battery remaining life threshold, a battery maintenance warning is issued to the maintenance personnel to remind the maintenance personnel to maintain the battery. Here, it should be noted that the set battery remaining life threshold is set according to the habits of the maintenance personnel and is at least one day.

[0070] Here, it should be noted that the value-taking methods of the voltage difference amplitude ratio coefficient, the voltage abnormality ratio coefficient, and the abnormal degree analysis threshold are as follows: Collect 5000 groups of battery operation data during the operation of the battery, and at the same time obtain the battery operation temperature data, and at the same time count the battery failure time. Substitute the battery operation data during the operation of the battery and the obtained battery operation temperature data into the battery remaining life prediction formula to calculate the remaining life of the battery. Substitute the battery failure time and the battery remaining life into the fitting software to obtain the values of the voltage difference amplitude ratio coefficient, the voltage abnormality ratio coefficient, and the abnormal degree analysis threshold that are most in line with the failure time judgment accuracy rate;

[0071] It should be noted that in this embodiment, the advantages of this embodiment compared with the prior art are as follows: The operation data of the storage battery during operation is collected by the data collection module, and at the same time, the operation temperature data of the storage battery is obtained. The operation data of the storage battery during operation collected is imported into the operation anomaly analysis model for operation anomaly analysis. The operation anomaly analysis result and the obtained operation temperature data of the storage battery are imported into the storage battery anomaly degree analysis model for storage battery anomaly degree analysis. The analyzed storage battery anomaly degree and the storage battery usage time are imported into the storage battery remaining life prediction model for storage battery remaining life prediction. According to the storage battery remaining life prediction result, a storage battery operation warning is carried out. The present invention comprehensively evaluates the storage battery operation electrical signal data and operation temperature data, and then accurately analyzes the storage battery operation anomaly degree. The remaining life of the storage battery is predicted through the accurately obtained change rate of the storage battery operation anomaly degree, improving the accuracy of the storage battery remaining life prediction, and further improving the ability to master the danger of the storage battery.

[0072] Embodiment 2

[0073] As Figure 3 shown, a storage battery safety control system based on remote monitoring is implemented based on the above-mentioned storage battery safety control method based on remote monitoring. The data collection module is used to collect the operation data of the storage battery during operation and obtain the operation temperature data of the storage battery at the same time;

[0074] The operation anomaly analysis module is used to import the operation data of the storage battery during operation collected into the operation anomaly analysis model for operation anomaly analysis;

[0075] The storage battery anomaly degree analysis module is used to import the operation anomaly analysis result and the obtained operation temperature data of the storage battery into the storage battery anomaly degree analysis model for storage battery anomaly degree analysis;

[0076] The storage battery remaining life prediction module is used to import the analyzed storage battery anomaly degree and the storage battery usage time into the storage battery remaining life prediction model for storage battery remaining life prediction;

[0077] The warning module is used to carry out a storage battery operation warning according to the storage battery remaining life prediction result;

[0078] The control module is used to control the operation of the data collection module, the operation anomaly analysis module, the storage battery anomaly degree analysis module, the storage battery remaining life prediction module and the warning module.

[0079] Embodiment 3

[0080] This embodiment provides an electronic device, such as Figure 4As shown, it includes: a processor and a memory, where the memory stores a computer program that can be called by the processor;

[0081] The processor executes the above-mentioned battery safety control method based on remote monitoring by calling the computer program stored in the memory.

[0082] This electronic device can have relatively large differences due to different configurations or performances, and can include one or more processors and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the battery safety control method based on remote monitoring provided by the above method embodiment. This electronic device can also include other components for implementing device functions. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for input and output of data. This embodiment will not be elaborated here.

[0083] Embodiment 4

[0084] This embodiment provides a computer-readable storage medium, on which a rewritable computer program is stored;

[0085] When the computer program runs on a computer device, it causes the computer device to execute the above-mentioned battery safety control method based on remote monitoring.

[0086] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a compact disc read-only memory, magnetic tapes, floppy disks, and optical data storage devices, etc.

[0087] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

Claims

1. A battery safety control method based on remote monitoring, characterized in that: It includes the following specific steps: The data acquisition module collects the operating data of the battery during the operation of the battery, and obtains the operating temperature data of the battery at the same time; Importing the collected operation data of the battery during the operation of the battery into the operation abnormality analysis model to perform operation abnormality analysis; Importing the abnormal operation analysis results and the acquired battery operation temperature data into the battery abnormality analysis model to perform battery abnormality degree analysis; The abnormality degree of the battery and the battery usage time obtained by the analysis are introduced into the battery remaining life prediction model to predict the remaining battery life; Performing a battery operation warning according to the battery remaining life prediction result; importing the collected battery operation data during the battery operation process into the operation abnormality analysis model for operation abnormality analysis includes the following specific steps: The voltage change data curve and current change data curve during the battery operation within the monitoring period are obtained, and the monitoring period is evenly divided into several monitoring time periods. The average voltage change data curve of each monitoring time period is obtained and imported into the voltage abnormal value calculation formula to calculate the voltage abnormal value. The voltage abnormal value calculation formula is: Wherein, a is the voltage phase difference ratio, N is the number of monitoring time periods in the monitoring cycle, Vi is the voltage average value of the i-th monitoring time period, and Vm is the voltage standard value of the i-th monitoring time period; The current change data curve within the monitoring period is obtained, and the current change data within the monitoring period is imported into the current abnormal value calculation formula to calculate the current abnormal value, wherein the current abnormal value calculation formula is: Wherein, T is the monitoring cycle duration, dt is the time integral, It is the current output value at time t, and its is the current output standard value at time t; The voltage abnormality value and current abnormality value within the monitoring period are obtained, and the operation abnormality analysis value calculation formula is imported to calculate the operation abnormality analysis value of the monitoring period, wherein the operation abnormality analysis value calculation formula is: XY=λXV+(1-λ)XI, wherein λ is the voltage abnormality ratio coefficient.

2. The battery safety control method based on remote monitoring according to claim 1, characterized in that: The step of importing the operation abnormality analysis result and the acquired operation temperature data of the battery into the battery abnormality analysis model to perform battery abnormality degree analysis includes the following specific steps: The temperature data of each monitoring point on the battery surface at the end of the monitoring period is obtained, and the temperature data of each monitoring point on the battery surface at the end of the monitoring period is imported into the temperature anomaly analysis value calculation formula to calculate the temperature anomaly analysis value, wherein the temperature anomaly analysis value calculation formula is: Wherein, m is the number of monitoring points, Tj is the temperature value of the j-th monitoring point, Tjm is the median value of the temperature safety range of the j-th monitoring point, Tjmax is the maximum value of the temperature safety range of the j-th monitoring point, and Tjmin is the minimum value of the temperature safety range of the j-th monitoring point; Substitute the calculated operation abnormality analysis value and temperature abnormality analysis value within the monitoring period into the battery abnormality degree analysis value calculation formula to calculate the battery abnormality degree analysis value, wherein the battery abnormality degree analysis value calculation formula is: XZ=(λXV+(1-λ)XI+1)×exp(XT), where exp() is the exponential power of the natural constant e.

3. The battery safety control method based on remote monitoring according to claim 2, characterized in that: The method of importing the analyzed battery abnormality degree and battery usage time into the battery remaining life prediction model to predict the battery remaining life includes the following specific contents: Obtain the calculated battery abnormality analysis value of the current monitoring cycle and the battery abnormality analysis value of the previous monitoring cycle, and compare the battery abnormality analysis value of the current monitoring cycle with the battery abnormality analysis value of the previous monitoring cycle. If the battery abnormality analysis value of the current monitoring cycle is less than or equal to the battery abnormality analysis value of the previous monitoring cycle, no life estimation is performed. If the battery abnormality analysis value of the current monitoring cycle is greater than the battery abnormality analysis value of the previous monitoring cycle, life estimation is performed and substituted into the battery remaining life prediction formula to calculate the battery remaining life, wherein the battery remaining life prediction formula is: Among them, XZM is the set abnormality analysis threshold, XZ(Tt-1) is the battery abnormality analysis value of the previous monitoring cycle, and ts is the duration of the monitoring cycle.

4. The battery safety control method based on remote monitoring as claimed in claim 3, characterized in that: The battery operation warning based on the battery remaining life prediction result includes the following specific contents: comparing the calculated battery remaining life prediction value with the set battery remaining life threshold value; if the battery remaining life prediction value is greater than the set battery remaining life threshold value, no battery maintenance warning is issued to the maintenance personnel; if the battery remaining life prediction value is less than or equal to the set battery remaining life threshold value, a battery maintenance warning is issued to the maintenance personnel to remind the maintenance personnel to maintain the battery.

5. The battery safety control method based on remote monitoring according to claim 4, characterized in that: The specific steps of the data acquisition module collecting the operating data of the battery during the operation of the battery and obtaining the operating temperature data of the battery are as follows: The voltage change data curve and the current change data curve during the operation of the battery are collected by the power information collection terminal, and stored in the first storage component; A plurality of temperature collection points are arranged on the surface of the battery, and the temperature data of the temperature collection points on the surface of the battery are collected by the temperature collection terminal and stored in the second storage component.

6. A battery safety control system based on remote monitoring, which is implemented based on the battery safety control method based on remote monitoring as claimed in any one of claims 1 to 5, characterized in that: Specifically include: The data acquisition module is used to collect the operating data of the battery during the operation of the battery and obtain the operating temperature data of the battery; An operation abnormality analysis module is used to import the operation data of the battery collected during the operation of the battery into the operation abnormality analysis model to perform operation abnormality analysis; A battery abnormality degree analysis module is used to import the operation abnormality analysis results and the acquired battery operation temperature data into the battery abnormality analysis model to perform battery abnormality degree analysis; A battery remaining life prediction module is used to import the analyzed battery abnormality and battery usage time into the battery remaining life prediction model to predict the battery remaining life; An early warning module is used to provide a battery operation early warning based on the battery remaining life prediction result; The control module is used for controlling the operation of the data acquisition module, the operation abnormality analysis module, the battery abnormality degree analysis module, the battery remaining life prediction module and the early warning module.

7. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the battery safety control method based on remote monitoring as described in any one of claims 1 to 5 by calling the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the battery safety control method based on remote monitoring as described in any one of claims 1 to 5.

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