Thermal runaway early warning system for lithium iron phosphate energy storage battery cabinet

Abstract

The invention discloses a lithium iron phosphate energy storage battery cabinet thermal runaway early warning system, relates to the technical field of battery cabinet safety management, solves the problems of inaccurate monitoring and monitoring delay of a current lithium iron phosphate energy storage battery cabinet thermal runaway early warning mode, and comprises a data transmission module, a battery analysis module and an abnormity analysis module, the data transmission module is used as an information interaction channel between the battery cabinet terminal and the management platform; the battery analysis module is used for carrying out real-time current monitoring and real-time voltage monitoring on the energy storage batteries stored in the battery cabinet terminal, and if the battery cabinet terminal is abnormal, the battery analysis module sends an abnormal alarm to the management platform; and the abnormity analysis module is used for calculating an abnormity index corresponding to the battery cabinet terminal according to the real-time state information, and then judging an abnormal condition of the battery cabinet terminal through the abnormity index of the battery cabinet terminal. According to the invention, timely early warning and accurate early warning of the thermal runaway condition of the lithium iron phosphate energy storage battery cabinet are realized based on the multi-source data.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermal runaway warning for battery cabinets, and in particular to a thermal runaway warning system for a lithium iron phosphate energy storage battery cabinet. Background Art

[0002] Energy storage battery cabinets are devices used to store and manage electrical energy. They usually contain multiple battery cells, which are reasonably laid out and designed to ensure safe and efficient storage and release of electrical energy. Battery cabinets are widely used in scenarios such as the storage of renewable energy such as solar energy and wind energy, power load regulation, and backup power supply for power systems. It is usually equipped with a monitoring system for real-time detection of battery temperature, pressure, voltage and other parameters to ensure that the battery operates within a safe range. It also has safety designs such as fire prevention, explosion prevention, and heat dissipation to avoid accidents caused by battery abnormalities or thermal runaway. The efficiency, reliability and safety of energy storage battery cabinets are important guarantees for their application areas.

[0003] In the prior art, the energy storage batteries inside the battery cabinet are often judged to be abnormal based on single data such as temperature or gas concentration. The single data judgment method cannot fully reflect the health status of the energy storage batteries inside the battery cabinet. At the same time, the data does not change significantly at the beginning of the abnormality of the energy storage battery, there is a detection lag, and it is impossible to judge the abnormal charging and discharging problem of the energy storage battery; To this end, the present invention proposes a thermal runaway early warning system for a lithium iron phosphate energy storage battery cabinet. Summary of the invention

[0004] The purpose of the present invention is to propose a thermal runaway warning system for a lithium iron phosphate energy storage battery cabinet to solve the problems raised in the above background technology.

[0005] The technical problems to be solved by the present invention are: How to achieve timely and accurate warning of thermal runaway of lithium iron phosphate energy storage battery cabinets based on multi-source data.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: Thermal runaway warning system based on lithium iron phosphate energy storage battery cabinet, including data acquisition module, data transmission module, battery analysis module, abnormal analysis module, database module, battery cabinet terminal and management platform; The data acquisition module is used to collect the real-time status information of the battery cabinet terminal, and send the real-time status information of the battery cabinet terminal to the management platform and the battery analysis module through the data transmission module after adding a timestamp; The data transmission module is used as an information exchange channel between the battery cabinet terminal and the management platform; The battery analysis module is used to perform real-time current monitoring and real-time voltage monitoring on the energy storage batteries stored in the battery cabinet terminal. If no operation is performed or the battery cabinet terminal is detected to be abnormal, the battery analysis module will send an abnormal alarm to the management platform. When the management platform receives an abnormality alarm issued by the battery analysis module, the management platform starts the abnormality analysis module and sends the real-time status information of the battery cabinet terminal to the abnormality analysis module; The database module is used to store the maximum safety pressure threshold, normal pressure value, maximum safety gas concentration threshold and normal gas concentration value of the battery cabinet terminal; the abnormal analysis module is used to calculate the abnormal index corresponding to the battery cabinet terminal according to the real-time status information, and then judge the abnormal situation of the battery cabinet terminal through the abnormal index of the battery cabinet terminal.

[0007] Furthermore, the real-time status information includes real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data of the battery cabinet terminal. The real-time gas concentration data is the real-time hydrogen fluoride concentration generated when the lithium iron phosphate battery burns.

[0008] Furthermore, the data transmission module includes a lora control unit, a data checking unit and a data uplink unit. The working process of the data transmission module is as follows: Step S1, the data acquisition module sends the real-time status information corresponding to the battery cabinet terminal to the lora control unit; Step S2, the lora control unit decodes the real-time status information, and then matches and merges the real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data corresponding to the decoded real-time status information with the battery cabinet terminal ID, and records the matched and merged real-time status information as the first message data, and sends the first message data to the data inspection unit at the same time; Step S3, the data checking unit performs an integrity check on the first message data, records the first message data that passes the integrity check as a second uplink message, and sends the second uplink message to the data uplink unit; The data uplink unit checks the integrity of the first message data by using CRC verification, and if there is repeated first message data in the first message data, the repeated first message data is merged.

[0009] Furthermore, the working process of the data transmission module also includes: Step S4, the data uplink unit encapsulates the second uplink message into a standard format, and then sends the encapsulated second uplink message to the management platform; Step S5, the management personnel sends the control message to the data uplink unit through the management platform; Step S6, the data uplink unit generates downlink message data according to the control message, and sends the downlink message data to the data checking unit; Step S7, the data checking unit performs an integrity check on the downlink message data, and then sends the downlink message data that passes the integrity check to the lora control unit; Step S8: The lora control unit obtains control message data based on the downlink message data that passes the integrity check, and sends the control message data to the battery cabinet terminal.

[0010] Furthermore, the working process of the battery analysis module is as follows: Step P1, obtaining the real-time current data Ii and the real-time voltage data Vi in the real-time status information according to the timestamp, i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step P2, calculating the real-time current threshold interval according to the real-time current data; Step P3: when the real-time current data is within the real-time current threshold range, the next step is entered; when the real-time current data is outside the real-time current threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform; Step P4, calculating the real-time voltage threshold interval according to the real-time voltage data; Step P5, when the real-time voltage data is within the real-time voltage threshold range, no operation is performed; when the real-time voltage data is outside the real-time voltage threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform.

[0011] Furthermore, the calculation process of the real-time current threshold interval is: The real-time current mean DLJ and the real-time current standard deviation DLB corresponding to the real-time current data are calculated according to the formula. The real-time current mean calculation formula is as follows: ; The real-time current standard deviation formula is as follows: ; Among them, the real-time current threshold interval is specifically: [DLJ-DLB, DLJ+DLB]; The calculation process of the real-time voltage threshold interval is: The real-time voltage mean DYJ and the real-time voltage standard deviation DYB corresponding to the real-time voltage data are calculated according to the formula. The real-time voltage mean calculation formula is as follows: ; The real-time voltage standard deviation formula is as follows: ; The real-time voltage threshold interval is specifically: [DYJ-DYB, DYJ+DYB].

[0012] Furthermore, the analysis process of the abnormal analysis module is as follows: Step R1, calculating the temperature abnormality value YCW according to the real-time temperature data in the real-time status information; Step R2, calculating the pressure abnormality value YCY according to the real-time pressure data in the real-time status information; Step R3, calculating the gas concentration abnormality value YCQ according to the real-time gas concentration data in the real-time status information; Step R4, using a formula to calculate the battery cabinet terminal abnormality index according to the temperature abnormality value, the pressure abnormality value and the gas concentration abnormality value, the formula is as follows: DCY=w1×YCW+w2×YCY+w3×YCQ, where w1, w2 and w3 are weight coefficients with fixed values, and w1>w2>w3; Step R5, when the abnormality index of the battery cabinet terminal is less than or equal to the second abnormality index threshold, the abnormality analysis module sends a third alarm message to the management platform, and then the management platform keeps monitoring the battery cabinet terminal; When the abnormal index of the battery cabinet terminal is less than or equal to the first abnormal index threshold and greater than the second abnormal index threshold, the abnormal analysis module sends a second alarm message to the management platform, and the management platform notifies the staff to check the battery cabinet terminal; When the abnormality index of the battery cabinet terminal is greater than the first abnormality index threshold, the abnormality analysis module sends a first alarm message to the management platform, and the management platform cuts off the power supply of the battery cabinet terminal, and the staff repairs the battery cabinet terminal at the same time; wherein the first abnormality index threshold is greater than the second abnormality index threshold.

[0013] Furthermore, the calculation process of the temperature anomaly value is: Step R11, obtaining the real-time temperature data Ti in the real-time status information according to the timestamp, where i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step R12, calculating the real-time temperature threshold interval according to the real-time temperature data; Specifically, the real-time temperature mean WDJ and the real-time temperature standard deviation WDB corresponding to the real-time current data are calculated according to the formulas. The real-time current mean calculation formula is as follows: ; The real-time current standard deviation formula is as follows: ; The real-time current threshold is specifically: [WDJ-WDB, WDJ+WDB]; Step R13, when the real-time temperature data is within the real-time temperature threshold range, the energy storage battery corresponding to the battery cabinet terminal is normal, and the temperature abnormality value is zero; when the real-time current data is outside the real-time current threshold range, the energy storage battery corresponding to the battery cabinet terminal is abnormal, and the temperature abnormality value is YCW.

[0014] Furthermore, the calculation process of the pressure anomaly value is as follows; Step R21, obtaining the maximum safety pressure threshold ZDY and normal pressure value ZCY corresponding to the battery cabinet terminal in the database module, and obtaining the real-time pressure data SSY of the battery cabinet terminal; Step R22, calculate the abnormal pressure value YCY of the battery cabinet terminal by the formula, the specific formula is as follows: YCY=|SSY-ZCY| / (ZDY-ZCY).

[0015] Furthermore, the calculation process of the gas concentration anomaly value is as follows; Step R31, obtaining the maximum safe gas concentration threshold ZDQ and normal gas concentration value ZCQ corresponding to the battery cabinet terminal in the database module, and obtaining the real-time gas concentration data SSQ of the battery cabinet terminal; Step R32, compare the real-time gas concentration data SSQ of the battery cabinet terminal with the normal gas concentration value ZCQ. If the real-time gas concentration data SSQ is less than the normal gas concentration value ZCQ, no operation is performed; if the real-time gas concentration data SSQ is greater than or equal to the normal gas concentration value ZCQ, proceed to the next step; Step R33, calculate the abnormal gas concentration value YCQ of the battery cabinet terminal through the formula, the specific formula is as follows: YCQ=(SSQ-ZCQ) / (ZDQ-ZCQ).

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention first collects the real-time status information of the battery cabinet terminal, and sends the collected real-time status information to the battery analysis module through the data transmission module. The battery analysis module performs real-time current monitoring and real-time voltage monitoring on the energy storage battery stored in the battery cabinet terminal to achieve preliminary detection of the lithium iron phosphate energy storage battery cabinet; 2. When an abnormal condition is initially detected, the present invention sends the real-time status information of the battery cabinet terminal to the abnormal analysis module. At the same time, combined with the maximum safety pressure threshold, normal pressure value, maximum safety gas concentration threshold and normal gas concentration value of the battery cabinet terminal, the abnormal analysis module calculates the abnormal index corresponding to the battery cabinet terminal according to the real-time status information, and judges the abnormal condition of the battery cabinet terminal based on the abnormal index of the battery cabinet terminal. The present invention realizes timely and accurate early warning of thermal runaway of lithium iron phosphate energy storage battery cabinets based on multi-source data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0018] Figure 1 is the overall system block diagram of the present invention; Figure 2 This is an example diagram of the process of uploading data by the data transmission module in the present invention; Figure 3 This is an example diagram of the process of sending instructions by the management platform in the present invention; Figure 4 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In one embodiment, see Figure 1-Figure 3 As shown, the technical solution provided by the present invention is: a thermal runaway warning system for a lithium iron phosphate energy storage battery cabinet, including a data acquisition module, a data transmission module, a battery analysis module, an abnormality analysis module, a database module, a battery cabinet terminal and a management platform; In a specific implementation, the management platform is wirelessly connected to a plurality of battery cabinet terminals, and the battery cabinet terminals are used to store energy storage batteries and charge the devices to be charged connected to the battery cabinet terminals through the energy storage batteries; It should be specifically noted that the energy storage battery includes lead-acid batteries, lithium-ion batteries, sodium-sulfur batteries, etc. In this embodiment, lithium iron phosphate batteries are preferably used as energy storage batteries.

[0021] In this embodiment, the data acquisition module is used to collect the real-time status information of the battery cabinet terminal, and add a timestamp to the real-time status information of the battery cabinet terminal and send it to the management platform and the battery analysis module through the data transmission module; It should be specifically stated that the real-time status information includes the real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data of the battery cabinet terminal. The real-time gas concentration data is specifically the real-time hydrogen fluoride concentration generated when the lithium iron phosphate battery is burned; the timestamp represents the data of the real-time status data at any time, usually a character sequence that uniquely identifies the time at a certain moment; In specific implementation, the data acquisition module is a collection component deployed in the battery cabinet terminal, which collects real-time status information of the battery cabinet terminal in real time, wherein the collection component includes a gas sensor, a temperature sensor, a pressure sensor, a current sensor, a voltage sensor and a timer; The data transmission module serves as an information interaction channel between the battery cabinet terminal and the management platform, wherein the data transmission module includes a lora control unit, a data checking unit and a data uplink unit; It should be specifically noted that the data transmission module uses Lora technology for data transmission. Lora is a low-power, long-distance wireless communication technology that is suitable for transmitting low-data-volume sensor information without stable network coverage; like Figure 2-Figure 3 As shown, the working process of the data transmission module is as follows: Step S1, the data acquisition module sends the real-time status information corresponding to the battery cabinet terminal to the lora control unit; Step S2, the lora control unit decodes the real-time status information, and then matches and merges the real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data corresponding to the decoded real-time status information with the battery cabinet terminal ID, and records the matched and merged real-time status information as the first message data, and sends the first message data to the data inspection unit at the same time; It should be specifically noted that the battery cabinet terminal ID is the unique identity authentication of the battery cabinet terminal, and one battery cabinet terminal ID uniquely corresponds to one battery cabinet terminal; Step S3, the data checking unit performs an integrity check on the first message data, records the first message data that passes the integrity check as a second uplink message, and sends the second uplink message to the data uplink unit; Specifically, the data uplink unit checks the integrity of the first message data by using CRC verification, and if there is repeated first message data in the first message data, merges the repeated first message data; It should be specifically noted that CRC verification is an existing mature technology and a commonly used error detection method to ensure that data is not damaged during transmission or storage; Step S4, the data uplink unit encapsulates the second uplink message into a standard format, and then sends the encapsulated second uplink message to the management platform; Step S5, the management personnel sends the control message to the data uplink unit through the management platform; It should be explained that the control message is a control instruction sent by the management personnel or users to the collection component corresponding to the data collection module through the management platform; Step S6, the data uplink unit generates downlink message data according to the control message, and sends the downlink message data to the data checking unit; Step S7, the data checking unit performs an integrity check on the downlink message data, and then sends the downlink message data that passes the integrity check to the lora control unit; Step S8: The lora control unit obtains control message data based on the downlink message data that passes the integrity check, and sends the control message data to the battery cabinet terminal.

[0022] Furthermore, the battery analysis module is used to perform real-time current monitoring and real-time voltage monitoring on the energy storage batteries stored in the battery cabinet terminal. The process of real-time current monitoring and real-time voltage monitoring is as follows: Step P1, obtaining the real-time current data Ii and the real-time voltage data Vi in the real-time status information according to the timestamp, i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step P2, calculating the real-time current threshold interval according to the real-time current data; Specifically, the real-time current mean DLJ and the real-time current standard deviation DLB corresponding to the real-time current data are calculated according to the formulas. The real-time current mean calculation formula is as follows: ; The real-time current standard deviation formula is as follows: ; Among them, the real-time current threshold interval is specifically: [DLJ-DLB, DLJ+DLB]; Step P3: when the real-time current data is within the real-time current threshold range, the next step is entered; when the real-time current data is outside the real-time current threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform; Step P4, calculating the real-time voltage threshold interval according to the real-time voltage data; Specifically, the real-time voltage mean value DYJ and the real-time voltage standard deviation DYB corresponding to the real-time voltage data are calculated according to the formulas. The real-time voltage mean value calculation formula is as follows: ; The real-time voltage standard deviation formula is as follows: ; Among them, the real-time voltage threshold range is specifically: [DYJ-DYB, DYJ+DYB] Step P5, when the real-time voltage data is within the real-time voltage threshold range, no operation is performed; when the real-time voltage data is outside the real-time voltage threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform.

[0023] As a further solution of this embodiment, when the management platform receives an abnormality alarm issued by the battery analysis module, the management platform starts the abnormality analysis module and sends the real-time status information of the battery cabinet terminal to the abnormality analysis module; The abnormal analysis module is connected to a database module, which stores the maximum safety pressure threshold, normal pressure value, maximum safety gas concentration threshold and normal gas concentration value of the battery cabinet terminal; the abnormal analysis module is used to calculate the abnormal index corresponding to the battery cabinet terminal according to the real-time status information, and then judge the abnormal situation of the battery cabinet terminal according to the abnormal index of the battery cabinet terminal. The analysis process of the abnormal analysis module is as follows: Step R1, calculating the temperature abnormality value according to the real-time temperature data in the real-time status information; Step R11, obtaining the real-time temperature data Ti in the real-time status information according to the timestamp, where i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step R12, calculating the real-time temperature threshold interval according to the real-time temperature data; Specifically, the real-time temperature mean WDJ and the real-time temperature standard deviation WDB corresponding to the real-time current data are calculated according to the formulas. The real-time current mean calculation formula is as follows: ; The real-time current standard deviation formula is as follows: ; The real-time current threshold is specifically: [WDJ-WDB, WDJ+WDB]; Step R13, when the real-time temperature data is within the real-time temperature threshold range, the energy storage battery corresponding to the battery cabinet terminal is normal, and the temperature abnormality value is zero; when the real-time current data is outside the real-time current threshold range, the energy storage battery corresponding to the battery cabinet terminal is abnormal, and the temperature abnormality value is YCW; Step R2, calculating the pressure abnormality value according to the real-time pressure data in the real-time status information; Step R21, obtaining the maximum safety pressure threshold ZDY and normal pressure value ZCY corresponding to the battery cabinet terminal in the database module, and obtaining the real-time pressure data SSY of the battery cabinet terminal; Step R22, calculate the abnormal pressure value YCY of the battery cabinet terminal by the formula, the specific formula is as follows: YCY=|SSY-ZCY| / (ZDY-ZCY); Step R3, calculating the gas concentration abnormality value according to the real-time gas concentration data in the real-time status information; Step R31, obtaining the maximum safe gas concentration threshold ZDQ and normal gas concentration value ZCQ corresponding to the battery cabinet terminal in the database module, and obtaining the real-time gas concentration data SSQ of the battery cabinet terminal; Step R32, compare the real-time gas concentration data SSQ of the battery cabinet terminal with the normal gas concentration value ZCQ. If the real-time gas concentration data SSQ is less than the normal gas concentration value ZCQ, no operation is performed; if the real-time gas concentration data SSQ is greater than or equal to the normal gas concentration value ZCQ, proceed to the next step; Step R33, calculate the abnormal gas concentration value YCQ of the battery cabinet terminal through the formula, the specific formula is as follows: YCQ=(SSQ-ZCQ) / (ZDQ-ZCQ); Step R4, using a formula to calculate the battery cabinet terminal abnormality index according to the temperature abnormality value, the pressure abnormality value and the gas concentration abnormality value, the formula is as follows: DCY=w1×YCW+w2×YCY+w3×YCQ, where w1, w2 and w3 are weight coefficients with fixed values, and w1>w2>w3; Step R5, when the abnormality index of the battery cabinet terminal is less than or equal to the second abnormality index threshold, the abnormality analysis module sends a third alarm message to the management platform, and then the management platform keeps monitoring the battery cabinet terminal; when the abnormality index of the battery cabinet terminal is less than or equal to the first abnormality index threshold and greater than the second abnormality index threshold, the abnormality analysis module sends a second alarm message to the management platform, and the management platform notifies the staff to check the battery cabinet terminal; when the abnormality index of the battery cabinet terminal is greater than the first abnormality index threshold, the abnormality analysis module sends a first alarm message to the management platform, and the management platform cuts off the power supply of the battery cabinet terminal, and the staff repairs the battery cabinet terminal; wherein, the first abnormality index threshold is greater than the second abnormality index threshold.

[0024] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0025] In another embodiment, if Figure 4 As shown, based on another concept of the same invention, a thermal runaway warning method for a lithium iron phosphate energy storage battery cabinet is proposed, and the specific method is as follows: Step S1, collecting real-time status information of the battery cabinet terminal and adding a timestamp to the real-time status information of the battery cabinet terminal; Step S2, real-time current monitoring and real-time voltage monitoring of the energy storage batteries stored in the battery cabinet terminal are performed. If the monitoring result of the battery cabinet terminal is abnormal, an abnormal alarm is issued and further analysis is performed; Step S3, obtaining the maximum safety pressure threshold, normal pressure value, maximum safety gas concentration threshold and normal gas concentration value of the battery cabinet terminal; Step S4, calculating the abnormality index corresponding to the battery cabinet terminal in combination with the real-time status information, and then judging the abnormality of the battery cabinet terminal by the abnormality index.

[0026] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet is characterized by: Including data acquisition module, data transmission module, battery analysis module, abnormal analysis module, database module, battery cabinet terminal and management platform; The data acquisition module is used to collect the real-time status information of the battery cabinet terminal, and send the real-time status information of the battery cabinet terminal to the management platform and the battery analysis module through the data transmission module after adding a timestamp; The data transmission module is used as an information exchange channel between the battery cabinet terminal and the management platform; The battery analysis module is used to perform real-time current monitoring and real-time voltage monitoring on the energy storage batteries stored in the battery cabinet terminal. If no operation is performed or the battery cabinet terminal is detected to be abnormal, the battery analysis module will send an abnormal alarm to the management platform. When the management platform receives an abnormality alarm issued by the battery analysis module, the management platform starts the abnormality analysis module and sends the real-time status information of the battery cabinet terminal to the abnormality analysis module; The database module is used to store the maximum safety pressure threshold, normal pressure value, maximum safety gas concentration threshold and normal gas concentration value of the battery cabinet terminal; the abnormal analysis module is used to calculate the abnormal index corresponding to the battery cabinet terminal according to the real-time status information, and then judge the abnormal situation of the battery cabinet terminal through the abnormal index of the battery cabinet terminal.

2. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 1 is characterized in that: The real-time status information includes real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data of the battery cabinet terminal. The real-time gas concentration data is the real-time hydrogen fluoride concentration generated when the lithium iron phosphate battery burns.

3. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 2 is characterized in that: The data transmission module includes a lora control unit, a data checking unit and a data uplink unit. The working process of the data transmission module is as follows: Step S1, the data acquisition module sends the real-time status information corresponding to the battery cabinet terminal to the lora control unit; Step S2, the lora control unit decodes the real-time status information, and then matches and merges the real-time temperature data, real-time gas concentration data, real-time current data, real-time voltage data and real-time pressure data corresponding to the decoded real-time status information with the battery cabinet terminal ID, and records the matched and merged real-time status information as the first message data, and sends the first message data to the data inspection unit at the same time; Step S3, the data checking unit performs an integrity check on the first message data, records the first message data that passes the integrity check as a second uplink message, and sends the second uplink message to the data uplink unit; The data uplink unit checks the integrity of the first message data by using CRC verification, and if there is repeated first message data in the first message data, the repeated first message data is merged.

4. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 3 is characterized in that: The working process of the data transmission module also includes: Step S4, the data uplink unit encapsulates the second uplink message into a standard format, and then sends the encapsulated second uplink message to the management platform; Step S5, the management personnel sends the control message to the data uplink unit through the management platform; Step S6, the data uplink unit generates downlink message data according to the control message, and sends the downlink message data to the data checking unit; Step S7, the data checking unit performs an integrity check on the downlink message data, and then sends the downlink message data that passes the integrity check to the lora control unit; Step S8: The lora control unit obtains control message data based on the downlink message data that passes the integrity check, and sends the control message data to the battery cabinet terminal.

5. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 2 is characterized in that: The working process of the battery analysis module is as follows: Step P1, obtaining the real-time current data Ii and the real-time voltage data Vi in the real-time status information according to the timestamp, i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step P2, calculating the real-time current threshold interval according to the real-time current data; Step P3: when the real-time current data is within the real-time current threshold range, proceed to the next step; When the real-time current data is outside the real-time current threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform; Step P4, calculating the real-time voltage threshold interval according to the real-time voltage data; Step P5, when the real-time voltage data is within the real-time voltage threshold range, no operation is performed; when the real-time voltage data is outside the real-time voltage threshold range, the battery cabinet terminal is abnormal, and the battery analysis module sends an abnormal alarm to the management platform.

6. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 5 is characterized in that: The calculation process of the real-time current threshold interval is: The real-time current mean DLJ and the real-time current standard deviation DLB corresponding to the real-time current data are calculated according to the formula. The real-time current mean calculation formula is as follows: ； The real-time current standard deviation formula is as follows: ； Among them, the real-time current threshold interval is specifically: [DLJ-DLB, DLJ+DLB]; The calculation process of the real-time voltage threshold interval is: The real-time voltage mean DYJ and the real-time voltage standard deviation DYB corresponding to the real-time voltage data are calculated according to the formula. The real-time voltage mean calculation formula is as follows: ； The real-time voltage standard deviation formula is as follows: ； The real-time voltage threshold interval is specifically: [DYJ-DYB, DYJ+DYB].

7. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 5, characterized in that: The analysis process of the abnormal analysis module is as follows: Step R1, calculating the temperature abnormality value YCW according to the real-time temperature data in the real-time status information; Step R2, calculating the pressure abnormality value YCY according to the real-time pressure data in the real-time status information; Step R3, calculating the gas concentration abnormality value YCQ according to the real-time gas concentration data in the real-time status information; Step R4, using a formula to calculate the battery cabinet terminal abnormality index according to the temperature abnormality value, the pressure abnormality value and the gas concentration abnormality value, the formula is as follows: DCY=w1×YCW+w2×YCY+w3×YCQ, where w1, w2 and w3 are weight coefficients with fixed values, and w1>w2>w3; Step R5, when the abnormality index of the battery cabinet terminal is less than or equal to the second abnormality index threshold, the abnormality analysis module sends a third alarm message to the management platform, and then the management platform keeps monitoring the battery cabinet terminal; When the abnormal index of the battery cabinet terminal is less than or equal to the first abnormal index threshold and greater than the second abnormal index threshold, the abnormal analysis module sends a second alarm message to the management platform, and the management platform notifies the staff to check the battery cabinet terminal; When the abnormality index of the battery cabinet terminal is greater than the first abnormality index threshold, the abnormality analysis module sends a first alarm message to the management platform, and the management platform cuts off the power supply of the battery cabinet terminal, and the staff repairs the battery cabinet terminal at the same time; wherein the first abnormality index threshold is greater than the second abnormality index threshold.

8. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 7 is characterized in that: The calculation process of temperature anomaly value is: Step R11, obtaining the real-time temperature data Ti in the real-time status information according to the timestamp, where i=1, 2, ..., n, n is a positive integer, and i represents the timestamp number; Step R12, calculating the real-time temperature threshold interval according to the real-time temperature data; Specifically, the real-time temperature mean WDJ and the real-time temperature standard deviation WDB corresponding to the real-time current data are calculated according to the formulas. The real-time current mean calculation formula is as follows: ； The real-time current standard deviation formula is as follows: ； The real-time current threshold is specifically: [WDJ-WDB, WDJ+WDB]; Step R13, when the real-time temperature data is within the real-time temperature threshold range, the energy storage battery corresponding to the battery cabinet terminal is normal, and the temperature abnormality value is zero; when the real-time current data is outside the real-time current threshold range, the energy storage battery corresponding to the battery cabinet terminal is abnormal, and the temperature abnormality value is YCW.

9. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 7, characterized in that: The calculation process of pressure anomaly value is as follows; Step R21, obtaining the maximum safety pressure threshold ZDY and normal pressure value ZCY corresponding to the battery cabinet terminal in the database module, and obtaining the real-time pressure data SSY of the battery cabinet terminal; Step R22, calculate the abnormal pressure value YCY of the battery cabinet terminal by the formula, the specific formula is as follows: YCY=|SSY-ZCY| / (ZDY-ZCY).

10. The thermal runaway warning system for lithium iron phosphate energy storage battery cabinet according to claim 7, characterized in that: The calculation process of gas concentration anomaly value is as follows; Step R31, obtaining the maximum safe gas concentration threshold ZDQ and normal gas concentration value ZCQ corresponding to the battery cabinet terminal in the database module, and obtaining the real-time gas concentration data SSQ of the battery cabinet terminal; Step R32, compare the real-time gas concentration data SSQ of the battery cabinet terminal with the normal gas concentration value ZCQ. If the real-time gas concentration data SSQ is less than the normal gas concentration value ZCQ, no operation is performed; if the real-time gas concentration data SSQ is greater than or equal to the normal gas concentration value ZCQ, proceed to the next step; Step R33, calculate the abnormal gas concentration value YCQ of the battery cabinet terminal through the formula, the specific formula is as follows: YCQ=(SSQ-ZCQ) / (ZDQ-ZCQ).

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