A battery module anti-re-ignition control system for an electrochemical energy storage station

Abstract

The present application provides a battery module anti-rekindling control system for an electrochemical energy storage station, which relates to the technical field of battery module monitoring. It monitors the concentration of thermal runaway gas in the battery module; determines the concentration growth characteristics corresponding to the thermal runaway gas of the battery module according to the concentration data, and determines the module smoldering factor of the battery module based on the concentration growth characteristics; collects the real-time temperature data of the battery module, extracts the temperature trend characteristics of the battery module from the corresponding real-time temperature data, and uses the temperature trend characteristics to predict the rekindling of the battery module to obtain the rekindling prediction temperature of the battery module; obtains the opening degrees of the fire extinguishing agent injection valves and the ventilation valves at the positions where each battery module is located, and adjusts the corresponding opening degrees of the fire extinguishing agent injection valves and the ventilation valves according to the corresponding module smoldering factors and rekindling prediction temperatures. The technical solution of the present application can adaptively adjust the fire extinguishing agent injection and ventilation systems to improve the overall response ability of the anti-rekindling control system.

Description

Technical Field

[0001] This application relates to the technical field of battery module monitoring. More specifically, this application relates to a battery module anti-re-ignition control system for an electrochemical energy storage station. Background Art

[0002] The anti-re-ignition control system of an electrochemical energy storage station aims to ensure that the battery module can timely identify and respond to potential fire risks during operation by integrating advanced monitoring technologies and automated control strategies, thereby reducing the possibility of re-ignition. The core of this system includes real-time data monitoring, fire extinguishing agent spraying, ventilation control, and emergency response mechanisms. By deploying temperature sensors, voltage monitoring devices, and gas detectors, the system can monitor the re-ignition state of the battery module in real time. When abnormal conditions are detected, it automatically adjusts the opening of the fire extinguishing agent spraying valve and combines the adjustment of the ventilation valve to ensure the safety of the internal and external environments of the battery module.

[0003] During the implementation of this anti-re-ignition control system, the adjustment of the fire extinguishing agent spraying and ventilation systems requires extremely high sensitivity and response speed. In high-temperature or abnormal situations, the system needs to quickly respond to activate the fire extinguishing device or increase ventilation to avoid potential fire spread. However, excessive spraying or ventilation may cause other safety hazards. Therefore, how to adaptively adjust the fire extinguishing agent spraying and ventilation systems based on the thermal runaway gas concentration and temperature data of the battery module to improve the overall response ability of the anti-re-ignition control system is a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a battery module anti-re-ignition control system for an electrochemical energy storage station, which can adaptively adjust the fire extinguishing agent spraying and ventilation systems based on the thermal runaway gas concentration and temperature data of the battery module to improve the overall response ability of the anti-re-ignition control system.

[0005] This application provides a battery module anti-re-ignition control system for an electrochemical energy storage station, and the control system includes:

[0006] A gas concentration monitoring module for monitoring the thermal runaway gas concentration of each battery module in the electrochemical energy storage station;

[0007] A smoldering feature extraction module for determining the concentration growth feature corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station according to the monitored concentration data of the thermal runaway gas, and determining the module smoldering factor of each battery module in the electrochemical energy storage station based on the concentration growth feature corresponding to the thermal runaway gas of each battery module;

[0008] A re-ignition temperature prediction module, which is used to collect the real-time temperature data of each battery module in the electrochemical energy storage station, extract the temperature trend characteristics of each battery module from the corresponding real-time temperature data, and use the corresponding temperature trend characteristics to perform re-ignition prediction on each battery module to obtain the re-ignition predicted temperature of each battery module;

[0009] A valve opening control module, which is used to obtain the opening degrees of the fire extinguishing agent injection valves and the ventilation valves at the positions where each battery module is located, and adjust the opening degrees of the corresponding fire extinguishing agent injection valves and the ventilation valves according to the corresponding module smoldering factors and re-ignition predicted temperatures.

[0010] In this embodiment, a gas detector is used to monitor the concentration of thermal runaway gas in each battery module of the electrochemical energy storage station.

[0011] In this embodiment, determining the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station according to the monitored concentration data of the thermal runaway gas specifically includes:

[0012] For each battery module in the electrochemical energy storage station, fitting the monitored concentration data of the thermal runaway gas of the battery module to obtain the concentration fitting curve of the thermal runaway gas of the battery module;

[0013] Extracting the growth characteristics from the concentration fitting curve to obtain the concentration growth characteristics corresponding to the thermal runaway gas of the battery module, and further obtaining the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station.

[0014] In this embodiment, extracting the growth characteristics from the concentration fitting curve to obtain the concentration growth characteristics corresponding to the thermal runaway gas of the battery module specifically includes:

[0015] Segmenting the concentration fitting curve to obtain multiple concentration curve segments;

[0016] Respectively determining the concentration growth rate corresponding to each concentration curve segment;

[0017] Determining the concentration growth characteristics corresponding to the thermal runaway gas of the battery module through all the concentration growth rates.

[0018] In this embodiment, determining the module smoldering factor of each battery module in the electrochemical energy storage station based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module specifically includes:

[0019] For each battery module in the electrochemical energy storage station, obtaining the volume fractions of various gases in the thermal runaway gas of the battery module;

[0020] Determine the module smoldering factor of the battery module according to the concentration growth characteristics of the thermal runaway gas corresponding to the battery module and the volume fractions of various gases in the thermal runaway gas of the battery module, and then obtain the module smoldering factors of each battery module in the electrochemical energy storage station.

[0021] In this embodiment, the real-time temperature data of each battery module in the electrochemical energy storage station is collected by a temperature sensor.

[0022] In this embodiment, extracting the temperature trend characteristics of each battery module from the corresponding real-time temperature data specifically includes:

[0023] For the real-time temperature data of each battery module, draw the temperature curve of the battery module according to the real-time temperature data;

[0024] Perform feature extraction on the temperature curve to obtain the temperature trend characteristics of the battery module, and then obtain the temperature trend characteristics of each battery module.

[0025] In this embodiment, using the corresponding temperature trend characteristics to predict afterburning of each battery module to obtain the afterburning prediction temperature of each battery module specifically includes:

[0026] Obtain a pre-trained simulation software for afterburning prediction of battery modules;

[0027] Input the temperature trend characteristics corresponding to each battery module into the simulation software for afterburning prediction, and then obtain the afterburning prediction temperature of each battery module.

[0028] In this embodiment, obtain the opening degrees of the fire extinguishing agent injection valves and the ventilation valves at the positions of each battery module through an angle sensor.

[0029] In this embodiment, adjusting the opening degrees of the corresponding fire extinguishing agent injection valves and ventilation valves according to the corresponding module smoldering factor and afterburning prediction temperature specifically includes:

[0030] For each battery module, when the module smoldering factor of the battery module exceeds a preset threshold, increase the opening degree of the ventilation valve and continuously spray the fire extinguishing agent;

[0031] When the module smoldering factor of the battery module is lower than the preset threshold, keep the opening degree of the ventilation valve;

[0032] When the afterburning prediction temperature of the battery module exceeds a preset safety value, increase the opening degree of the fire extinguishing agent injection valve and extend the fire extinguishing agent spraying time;

[0033] When the afterburning prediction temperature of the battery module is lower than the preset safety value, keep the opening degree of the fire extinguishing agent injection valve.

[0034] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0035] The gas concentration monitoring module monitors the thermal runaway gas concentration of each battery module in the electrochemical energy storage station; the smoldering characteristic extraction module determines the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station based on the monitored concentration data of the thermal runaway gas, and determines the module smoldering factor of each battery module in the electrochemical energy storage station based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module; the re-ignition temperature prediction module collects the real-time temperature data of each battery module in the electrochemical energy storage station, extracts the temperature trend characteristics of each battery module from the corresponding real-time temperature data, and uses the corresponding temperature trend characteristics to perform re-ignition prediction on each battery module to obtain the re-ignition prediction temperature of each battery module; the valve opening control module obtains the opening degrees of the fire extinguishing agent injection valves and the ventilation valves at the positions where each battery module is located, and adjusts the opening degrees of the fire extinguishing agent injection valves and the ventilation valves respectively according to the module smoldering factor and the re-ignition prediction temperature of the battery module.

[0036] Thus, in this application, the fire extinguishing agent injection and ventilation systems can be adaptively adjusted based on the thermal runaway gas concentration and temperature data of the battery module; among them, by monitoring the concentration change of the thermal runaway gas in real time, potential fire re-ignition risks can be identified in a timely manner, and the calculation of the module smoldering factor can quantify the safety risks of each battery module; then, by monitoring the temperature data in real time and extracting the temperature trend characteristics, the abnormal temperature rise trend of the battery module can be identified in a timely manner, and potential re-ignition risks can be warned early. The calculation of the re-ignition prediction temperature can help identify which battery modules are at higher re-ignition risks, so as to preferentially monitor and protect the high-risk battery modules; finally, by obtaining the valve opening data in real time and adjusting the ventilation and fire extinguishing strategies in a timely manner based on the module smoldering factor and the re-ignition prediction temperature, the abnormal conditions of the battery module can be effectively responded to, the re-ignition risk can be reduced, and the overall response efficiency and effect can be improved.

[0037] In summary, the technical solution adopted in this application can adaptively adjust the fire extinguishing agent injection and ventilation systems based on the thermal runaway gas concentration and temperature data of the battery module to improve the overall response ability of the anti-re-ignition control system. Description of the Drawings

[0038] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a module structure diagram of a battery module anti-re-ignition control system for an electrochemical energy storage station provided according to the present application;

[0040] Figure 2 It is a schematic flow diagram for determining the module smoldering factors of each battery module provided according to the present application;

[0041] Figure 3 It is a schematic flow diagram for extracting the temperature trend characteristics of each battery module provided according to the present application. Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with 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. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0043] The embodiment of the present application provides a battery module anti-re-ignition control system for an electrochemical energy storage station. Its core is to monitor the thermal runaway gas concentration of each battery module in the electrochemical energy storage station through a gas concentration monitoring module; the smoldering feature extraction module determines the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station based on the monitored concentration data of the thermal runaway gas, and determines the module smoldering factors of each battery module in the electrochemical energy storage station based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module; the re-ignition temperature prediction module collects the real-time temperature data of each battery module in the electrochemical energy storage station, extracts the temperature trend characteristics of each battery module from the corresponding real-time temperature data, and uses the corresponding temperature trend characteristics to perform re-ignition prediction on each battery module to obtain the re-ignition prediction temperature of each battery module; the valve opening control module obtains the opening degrees of the fire extinguishing agent injection valves and ventilation valves at the positions where each battery module is located, and adjusts the opening degrees of the corresponding fire extinguishing agent injection valves and ventilation valves according to the corresponding module smoldering factors and re-ignition prediction temperatures. The present application adopts the above technical solutions to adaptively adjust the fire extinguishing agent injection and ventilation systems according to the thermal runaway gas concentration and temperature data of the battery modules, so as to improve the overall response ability of the anti-re-ignition control system.

[0044] To better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1As shown in the figure, this is a module structure diagram of a battery module anti-re-ignition control system for an electrochemical energy storage station according to an embodiment of the present application. The processing system includes: a gas concentration monitoring module 100, a smoldering feature extraction module 200, a re-ignition temperature prediction module 300, and a valve opening control module 400, which are described as follows:

[0045] The gas concentration monitoring module 100 is used to monitor the thermal runaway gas concentration of each battery module in the electrochemical energy storage station.

[0046] It should be noted that in the present application, the thermal runaway gas mainly refers to hydrogen, methane, ethylene, and carbon monoxide. Specifically, in implementation, the thermal runaway gas concentration of each battery module in the electrochemical energy storage station can be monitored through a gas detector. A gas detector is installed at the position of each battery module in the electrochemical energy storage station, and this gas detector can monitor a variety of thermal runaway gases in real time.

[0047] The smoldering feature extraction module 200 is used to determine the concentration growth feature corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station based on the monitored concentration data of the thermal runaway gas, and determine the module smoldering factor of each battery module in the electrochemical energy storage station based on the concentration growth feature corresponding to the thermal runaway gas of each battery module.

[0048] In this embodiment, the following method can be specifically adopted to determine the concentration growth feature corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station based on the monitored concentration data of the thermal runaway gas, that is:

[0049] For each battery module in the electrochemical energy storage station, the monitored concentration data of the thermal runaway gas of the battery module is fitted to obtain the concentration fitting curve of the thermal runaway gas of the battery module;

[0050] The growth feature of the concentration is extracted from the concentration fitting curve to obtain the concentration growth feature corresponding to the thermal runaway gas of the battery module, and then the concentration growth feature corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station is obtained.

[0051] In specific implementation, first, for each battery module in the electrochemical energy storage station, the concentration data of the thermal runaway gas of the monitored battery module can be fitted, that is, the linear regression method is used to fit the concentration data of the thermal runaway gas, so as to obtain the concentration fitting curve of the thermal runaway gas of the battery module. This concentration fitting curve can accurately reflect the change trend of the thermal runaway gas concentration over time. Then, the growth characteristics can be extracted from the concentration fitting curve to obtain the concentration growth characteristics corresponding to the thermal runaway gas of the battery module. Through the above method, the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station can be obtained. This concentration growth characteristic is a characteristic used to represent the growth trend fluctuation of the thermal runaway gas concentration.

[0052] In this embodiment, to extract the growth characteristics from the concentration fitting curve to obtain the concentration growth characteristics corresponding to the thermal runaway gas of the battery module, the following method can be specifically adopted, that is:

[0053] Segment the concentration fitting curve to obtain multiple concentration curve segments;

[0054] Determine the concentration growth rate corresponding to each concentration curve segment respectively;

[0055] Determine the concentration growth characteristics corresponding to the thermal runaway gas of the battery module through all the concentration growth rates.

[0056] In specific implementation, first, the concentration fitting curve can be segmented according to the characteristics of the concentration fitting curve, that is, the inflection points in the concentration fitting curve can be identified, and the concentration fitting curve can be divided into different paragraphs according to the slope change, so as to obtain multiple concentration curve segments. Then, the concentration growth rate corresponding to each concentration curve segment can be determined, that is, the slope of the concentration curve segment is calculated, and this slope is used as the concentration growth rate corresponding to the concentration curve segment, so as to obtain the concentration growth rate corresponding to each concentration curve segment. This concentration growth rate is used to represent the growth rate of the thermal runaway gas concentration in the corresponding time period. Finally, the concentration growth characteristics corresponding to the thermal runaway gas of the battery module determined through all the concentration growth rates is to use the standard deviation of all the concentration growth rates as the concentration growth characteristics corresponding to the thermal runaway gas of the battery module.

[0057] Preferably, in this embodiment, based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module, the module smoldering factor of each battery module in the electrochemical energy storage station is determined. Refer to Figure 2 As shown in the figure, which is a schematic flow chart for determining the module smoldering factor of each battery module in some embodiments of the present application. In this embodiment, the module smoldering factor of each battery module can be determined by the following steps:

[0058] First, in step S21, for each battery module in the electrochemical energy storage station, obtain the volume fractions of various gases in the thermal runaway gas of the battery module;

[0059] Then, in step S22, determine the module smoldering factor of the battery module according to the concentration growth characteristics corresponding to the thermal runaway gas of the battery module and the volume fractions of various gases in the thermal runaway gas of the battery module, and then obtain the module smoldering factors of each battery module in the electrochemical energy storage station.

[0060] When specifically implemented, first, for each battery module in the electrochemical energy storage station, to obtain the volume fractions of various gases in the thermal runaway gas of the battery module, a gas detector can be used to monitor the components of the thermal runaway gas released by the battery module in real time, and record the volume fractions of the main thermal runaway gases (i.e., hydrogen, methane, ethylene, and carbon monoxide); then, the module smoldering factor of the battery module can be determined according to the concentration growth characteristics corresponding to the thermal runaway gas of the battery module and the volume fractions of various gases in the thermal runaway gas of the battery module. This module smoldering factor represents the probability of smoldering conditions existing in the battery module. The larger this module smoldering factor, the greater the possibility of smoldering conditions existing, and the greater the possibility of afterburning of this battery module. In actual implementation, the module smoldering factor of the battery module can be determined according to the following formula: Where, represents the module smoldering factor of the i-th battery module, represents the weighted average of the volume fractions of various gases in the thermal runaway gas of the i-th battery module, represents the concentration growth characteristics corresponding to the thermal runaway gas of the i-th battery module, and represent empirical weight coefficients. Through the above method, the module smoldering factors of each battery module in the electrochemical energy storage station can be obtained.

[0061] It should be noted that by monitoring the concentration change of the thermal runaway gas in real time, potential fire afterburning risks can be identified in a timely manner, and the calculation of the module smoldering factor can quantify the safety risks of each battery module, helping managers to prioritize high-risk modules, thereby optimizing resource allocation and safety management strategies.

[0062] The afterburning temperature prediction module 300 is used to collect the real-time temperature data of each battery module in the electrochemical energy storage station, extract the temperature trend characteristics of each battery module from the corresponding real-time temperature data, and use the corresponding temperature trend characteristics to perform afterburning prediction on each battery module to obtain the afterburning prediction temperature of each battery module.

[0063] During specific implementation, real-time temperature data of each battery module in the electrochemical energy storage station is collected through a temperature sensor; temperature sensors are installed at key positions of each battery module and connected to the control system to ensure that the control system can read and store the temperature data in real time. Set the acquisition frequency of the temperature data, usually at intervals of one second or shorter, to ensure that the temperature changes of the battery module can be captured in a timely manner.

[0064] Preferably, in this embodiment, temperature trend characteristics of each battery module are extracted from the corresponding real-time temperature data. Refer to Figure 3 As described, this figure is a schematic flowchart of extracting temperature trend characteristics of each battery module in some embodiments of this application. The temperature trend characteristics of each battery module can be extracted in the following steps in this embodiment:

[0065] First, in step S31, for the real-time temperature data of each battery module, a temperature curve of the battery module is plotted based on the real-time temperature data;

[0066] Then, in step S32, feature extraction is performed on the temperature curve to obtain the temperature trend characteristics of the battery module, and thus the temperature trend characteristics of each battery module are obtained.

[0067] During specific implementation, first, for the real-time temperature data of each battery module, a temperature curve of the battery module can be plotted based on the real-time temperature data, that is, with time as the horizontal axis and the real-time temperature data of each battery module as the vertical axis, a temperature curve of each battery module is plotted. Data visualization tools (such as Matplotlib, Plotly, etc.) can be used to generate a temperature curve graph to clearly display the temperature changes; then, feature extraction is performed on the temperature curve, that is, the overall slope of the temperature curve is calculated, and the overall slope is used as the temperature trend characteristic of the battery module. This temperature trend characteristic is used to represent the characteristic of the overall temperature trend change of the battery module. Through the above method, the temperature trend characteristics of each battery module can be obtained.

[0068] In this embodiment, the corresponding temperature trend characteristics are used to perform reignition prediction on each battery module, and the reignition prediction temperature of each battery module can be obtained in the following specific way, that is:

[0069] Obtain a pre-trained simulation software for reignition prediction of battery modules;

[0070] Input the temperature trend characteristics corresponding to each battery module into the simulation software for reignition prediction, and thus the reignition prediction temperature of each battery module is obtained.

[0071] In specific implementation, first, obtain the simulation software for predicting the afterburning of battery modules, ensuring that the software is fully trained and has the ability to predict the afterburning of battery modules. Then, organize the temperature trend features extracted from each battery module into a format suitable for inputting into the simulation software, and perform standardization processing on the temperature trend features according to the requirements of the simulation software. Thus, input the organized temperature trend features into the simulation software one by one, start the simulation software, run the afterburning prediction model, and calculate based on the input temperature trend features to obtain the afterburning prediction temperature of each battery module. This afterburning prediction temperature is the temperature that the battery module may reach after afterburning predicted through prediction.

[0072] It should be noted that real-time monitoring of temperature data and extraction of temperature trend features can promptly identify the abnormal temperature rise trend of battery modules and early warning of potential afterburning risks. The calculation of the afterburning prediction temperature can help identify which battery modules face higher afterburning risks, and managers can better evaluate the safety status of each battery module, so as to prioritize the monitoring and protection of high-risk battery modules and optimize resource allocation.

[0073] The valve opening control module 400 is used to obtain the opening degrees of the fire extinguishing agent injection valves and ventilation valves at the positions where each battery module is located, and adjust the opening degrees of the corresponding fire extinguishing agent injection valves and ventilation valves according to the corresponding module smoldering factors and afterburning prediction temperatures.

[0074] In specific implementation, the opening degrees of the fire extinguishing agent injection valves and ventilation valves at the positions where each battery module is located can be obtained through an angle sensor. In this application, the selected angle sensor is an inclination sensor, which can accurately measure the opening and closing angles of the fire extinguishing agent injection valve and ventilation valve, and then connect the angle sensor to the control system to ensure that the angle data can be read in real time.

[0075] In this embodiment, adjusting the opening degrees of the corresponding fire extinguishing agent injection valves and ventilation valves according to the corresponding module smoldering factors and afterburning prediction temperatures can be specifically implemented in the following way, that is:

[0076] For each battery module, when the module smoldering factor of the battery module exceeds the preset threshold, increase the opening degree of the ventilation valve and continuously spray the fire extinguishing agent;

[0077] When the module smoldering factor of the battery module is lower than the preset threshold, keep the opening degree of the ventilation valve;

[0078] When the afterburning prediction temperature of the battery module exceeds the preset safety value, increase the opening degree of the fire extinguishing agent injection valve and extend the fire extinguishing agent spraying time;

[0079] When the afterburning prediction temperature of the battery module is lower than the preset safety value, keep the opening degree of the fire extinguishing agent injection valve.

[0080] In specific implementation, first, the threshold of the module smoldering factor of each battery module can be set according to historical data and safety standards, and the safety value of the re-ignition prediction temperature of the battery module can be set according to historical data to ensure safe operation. Then, continuously monitor the module smoldering factor and the re-ignition prediction temperature of each battery module to ensure the timeliness and accuracy of the data. Furthermore, for each battery module, when the module smoldering factor exceeds the preset threshold, increase the opening degree of the ventilation valve to promote air circulation, reduce the concentration of thermal runaway gas in the battery module, and continuously spray the fire extinguishing agent to prevent thermal runaway. When the module smoldering factor is lower than the preset threshold, keep the opening degree of the ventilation valve to maintain the current ventilation state and avoid waste of resources caused by excessive ventilation. When the re-ignition prediction temperature exceeds the preset safety value, increase the opening degree of the fire extinguishing agent spraying valve to quickly spray the fire extinguishing agent and extend the fire extinguishing agent spraying time to reduce the temperature of the battery module and prevent re-ignition. When the re-ignition prediction temperature is lower than the preset safety value, keep the opening degree of the fire extinguishing agent spraying valve to ensure the use efficiency of the fire extinguishing agent and avoid unnecessary spraying.

[0081] It should be noted that by obtaining the valve opening data in real time and adjusting the ventilation and fire extinguishing strategies in a timely manner based on the module smoldering factor and the re-ignition prediction temperature, the abnormal conditions of the battery module can be effectively responded to, the re-ignition risk can be reduced, and the overall response efficiency and effect can be improved.

[0082] Thus, it can be seen that in this application, the fire extinguishing agent spraying and ventilation systems can be adaptively adjusted according to the thermal runaway gas concentration and temperature data of the battery module. Among them, by real-time monitoring the change of the thermal runaway gas concentration, the potential fire re-ignition risk can be identified in a timely manner, and the calculation of the module smoldering factor can quantify the safety risks of each battery module. Then, by real-time monitoring the temperature data and extracting the temperature trend characteristics, the abnormal temperature rise trend of the battery module can be identified in a timely manner, and the potential re-ignition risk can be warned early. The calculation of the re-ignition prediction temperature can help identify which battery modules are at a higher re-ignition risk, so as to preferentially monitor and protect the high-risk battery modules. Finally, by obtaining the valve opening data in real time and adjusting the ventilation and fire extinguishing strategies in a timely manner based on the module smoldering factor and the re-ignition prediction temperature, the abnormal conditions of the battery module can be effectively responded to, the re-ignition risk can be reduced, and the overall response efficiency and effect can be improved.

[0083] In summary, the technical solution adopted in this application can adaptively adjust the fire extinguishing agent spraying and ventilation systems according to the thermal runaway gas concentration and temperature data of the battery module to improve the overall response ability of the anti-re-ignition control system.

[0084] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or means for realizing the functions specified in multiple blocks.

[0085] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0086] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, commodity or device including the element.

Claims

1. A battery module anti-re-ignition control system for an electrochemical energy storage station, characterized in that, The control system includes: A gas concentration monitoring module for monitoring the thermal runaway gas concentration of each battery module in the electrochemical energy storage station; A smoldering characteristic extraction module for determining the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station according to the monitored concentration data of the thermal runaway gas. For each battery module in the electrochemical energy storage station, the concentration data of the thermal runaway gas of the monitored battery module is fitted to obtain the concentration fitting curve of the thermal runaway gas of the battery module; the growth characteristics are extracted from the concentration fitting curve to obtain the concentration growth characteristics corresponding to the thermal runaway gas of the battery module, and then the concentration growth characteristics corresponding to the thermal runaway gas of each battery module in the electrochemical energy storage station are obtained. Among them, the concentration fitting curve is segmented to obtain multiple concentration curve segments; the concentration growth rate corresponding to each concentration curve segment is determined respectively; the concentration growth characteristics corresponding to the thermal runaway gas of the battery module are determined through all the concentration growth rates. Among them, the standard deviation of all the concentration growth rates is used as the concentration growth characteristics corresponding to the thermal runaway gas of the battery module; based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module, the module smoldering factor of each battery module in the electrochemical energy storage station is determined. Among them, determining the module smoldering factor of each battery module in the electrochemical energy storage station based on the concentration growth characteristics corresponding to the thermal runaway gas of each battery module specifically includes: For each battery module in the electrochemical energy storage station, obtain the volume fraction of various gases in the thermal runaway gas of the battery module; Determine the module smoldering factor of the battery module according to the concentration growth characteristics corresponding to the thermal runaway gas of the battery module and the volume fraction of various gases in the thermal runaway gas of the battery module, and then obtain the module smoldering factor of each battery module in the electrochemical energy storage station. Among them, the module smoldering factor of the battery module is determined according to the following formula: α i = k1 * C i + k2 * R i Among them, α i represents the module smoldering factor of the i-th battery module, C i represents the weighted average of the volume fractions of various gases in the thermal runaway gas of the i-th battery module, R i represents the concentration growth characteristic corresponding to the thermal runaway gas of the i-th battery module, and k1 and k2 represent empirical weight coefficients; A re-ignition temperature prediction module for collecting the real-time temperature data of each battery module in the electrochemical energy storage station, extracting the temperature trend characteristics of each battery module from the corresponding real-time temperature data, and using the corresponding temperature trend characteristics to perform re-ignition prediction on each battery module to obtain the re-ignition prediction temperature of each battery module; A valve opening control module for obtaining the opening degrees of the fire extinguishing agent injection valves and the ventilation valves at the positions where each battery module is located, and adjusting the corresponding opening degrees of the fire extinguishing agent injection valves and the ventilation valves according to the corresponding module smoldering factors and the re-ignition prediction temperatures.

2. The battery module anti-rekindling control system for an electrochemical energy storage station according to claim 1, characterized in that, Monitor the thermal runaway gas concentration of each battery module in the electrochemical energy storage station through a gas detector.

3. The battery module anti-re-ignition control system for an electrochemical energy storage station according to claim 1, wherein Collect the real-time temperature data of each battery module in the electrochemical energy storage station through a temperature sensor.

4. The battery module anti-re-ignition control system for an electrochemical energy storage station according to claim 1, characterized in that, Extracting the temperature trend characteristics of each battery module from the corresponding real-time temperature data specifically includes: For the real-time temperature data of each battery module, draw the temperature curve of the battery module according to the real-time temperature data; Extract the characteristics from the temperature curve to obtain the temperature trend characteristics of the battery module, and then obtain the temperature trend characteristics of each battery module.

5. The battery module anti-rekindling control system for an electrochemical energy storage station according to claim 1, characterized in that, Using the corresponding temperature trend features to conduct afterburning prediction for each battery module, and obtaining the afterburning prediction temperature of each battery module specifically includes: Obtain a pre-trained simulation software for afterburning prediction of battery modules; Input the temperature trend features corresponding to each battery module into the simulation software for afterburning prediction, and then obtain the afterburning prediction temperature of each battery module.

6. The battery module anti-rekindling control system for an electrochemical energy storage station according to claim 1, characterized in that, Obtain the opening degrees of the fire extinguishing agent injection valves and ventilation valves at the positions where each battery module is located through an angle sensor.

7. The battery module anti-re-ignition control system for an electrochemical energy storage station according to claim 1, characterized in that, Adjust the corresponding opening degrees of the fire extinguishing agent injection valves and ventilation valves according to the corresponding module smoldering factor and afterburning prediction temperature, specifically including: For each battery module, when the module smoldering factor of the battery module exceeds a preset threshold, increase the opening degree of the ventilation valve and continuously inject the fire extinguishing agent; When the module smoldering factor of the battery module is lower than the preset threshold, keep the opening degree of the ventilation valve; When the afterburning prediction temperature of the battery module exceeds a preset safety value, increase the opening degree of the fire extinguishing agent injection valve and extend the fire extinguishing agent injection time; When the afterburning prediction temperature of the battery module is lower than the preset safety value, keep the opening degree of the fire extinguishing agent injection valve.

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