Thermal runaway adjusting method and device for energy storage battery cabin

Abstract

The invention provides an energy storage battery cabin thermal runaway adjusting method and device, and the method comprises the steps: obtaining an initial heat distribution parameter of an energy storage battery cabin according to an operation environment; obtaining a first heat distribution parameter for real-time data processing based on interference suppression on the initial heat distribution parameter; according to stored historical data, trend prediction is carried out on the first heat distribution parameters, a thermal runaway risk assessment result of the energy storage battery cabin is obtained, and feedback adjustment is carried out on the operation environment of the energy storage battery cabin based on the thermal runaway risk assessment result. Through carrying out trend prediction on the first heat distribution parameter, the accuracy of thermal runaway monitoring of the energy storage battery cabin is greatly improved; according to the thermal runaway risk assessment result, feedback adjustment is carried out on the operation environment of the energy storage battery cabin, it is ensured that the energy storage battery cabin can operate within the safe temperature range, then the operation stability of the energy storage battery cabin is improved to the maximum extent, and therefore the thermal runaway adjustment method and device for the energy storage battery cabin have wide applicability.

Description

Technical Field

[0001] The present application relates to the field of energy storage design and application technology, and in particular to a method and device for regulating thermal runaway of an energy storage battery compartment. Background Art

[0002] Energy storage battery compartments are usually based on lithium-ion battery settings. Thermal runaway is one of the main risks faced by lithium-ion batteries. When short circuits, overcharges, over-discharges, etc. occur inside the battery, a large amount of heat will be generated rapidly, causing the battery temperature to rise sharply, which in turn causes fires or even explosions. On the other hand, the operating environment of the energy storage battery compartment is often complex and changeable. Special environments such as high altitudes, low temperatures, and strong winds and sand will place more stringent requirements on the monitoring and regulation of thermal runaway. Therefore, how to conduct real-time temperature monitoring of the energy storage battery compartment, so as to promptly detect abnormal temperature nodes, and adaptively predict the trend of the thermal distribution of the energy storage battery compartment according to changes in the external environment, thereby ensuring that the energy storage battery compartment operates within a safe temperature range, is a technical problem that needs to be solved urgently by technicians in this field.

[0003] It should be noted that the above introduction to the technical background is only for the convenience of providing a clear and complete description of the technical solutions of the present application and for the convenience of understanding by those skilled in the art. It cannot be considered that the above technical solutions are well known to those skilled in the art simply because they are described in the background technology section of the present application. Summary of the invention

[0004] The embodiments of the present application provide a method and device for regulating thermal runaway of an energy storage battery compartment.

[0005] The first embodiment of the present application proposes a method for regulating thermal runaway of an energy storage battery compartment, comprising:

[0006] According to the operating environment, the initial thermal distribution parameters of the energy storage battery compartment are obtained;

[0007] Based on interference suppression of the initial thermal distribution parameters, obtaining first thermal distribution parameters for real-time data processing;

[0008] According to the stored historical data, a trend forecast is performed on the first heat distribution parameter to obtain a thermal runaway risk assessment result of the energy storage battery compartment, and based on the thermal runaway risk assessment result, feedback adjustment is performed on the operating environment of the energy storage battery compartment.

[0009] The second embodiment of the present application proposes a thermal runaway regulating device for an energy storage battery compartment, comprising:

[0010] A first acquisition module, the first acquisition module is used to obtain initial thermal distribution parameters of the energy storage battery compartment according to the operating environment;

[0011] a second acquisition module, the second acquisition module being used to acquire first heat distribution parameters for real-time data processing based on interference suppression of the initial heat distribution parameters;

[0012] A prediction module, the prediction module is used to perform trend prediction on the first heat distribution parameter according to the stored historical data, and obtain a thermal runaway risk assessment result of the energy storage battery compartment;

[0013] A regulation module, wherein the regulation module is used to perform feedback regulation on the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result.

[0014] The third aspect embodiment of the present application proposes an electronic device, comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the energy storage battery compartment thermal runaway regulation method proposed in the first aspect embodiment of the present application.

[0015] The fourth aspect embodiment of the present application proposes a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device can execute the method proposed in the first aspect embodiment of the present application.

[0016] The fifth aspect embodiment of the present application proposes a computer program product, including a computer program, which implements the method proposed in the first aspect embodiment of the present application when executed by a processor in a communication device.

[0017] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:

[0018] According to the stored historical data, the trend of the first heat distribution parameter obtained for real-time data processing is predicted, and the thermal runaway risk assessment result of the energy storage battery compartment is obtained, thereby greatly improving the accuracy of thermal runaway monitoring of the energy storage battery compartment; and according to the thermal runaway risk assessment result, the operating environment of the energy storage battery compartment is feedback-adjusted to ensure that the energy storage battery compartment can operate within a safe temperature range, thereby maximizing the stability of the operation of the energy storage battery compartment, and thus the energy storage battery compartment thermal runaway adjustment method and device have wide applicability.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0021] Figure 1A schematic flow chart of a thermal runaway regulation method for an energy storage battery compartment provided in an embodiment of the present application;

[0022] Figure 2 A schematic flow chart of another method for regulating thermal runaway of an energy storage battery compartment provided in an embodiment of the present application;

[0023] Figure 3 A schematic diagram of the structure of a thermal runaway regulating device for an energy storage battery compartment provided in an embodiment of the present application;

[0024] Figure 4 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of the structure of another electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0027] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0028] It should be understood that, although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present application, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at..." or "when..." or "in response to determination".

[0029] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0030] It should be noted that the energy storage battery compartment thermal runaway regulation method provided in any embodiment of the present application can be executed alone, or in combination with possible implementation methods in other embodiments, or in combination with any technical solution in the relevant technology.

[0031] The following describes a method and device for regulating thermal runaway of an energy storage battery compartment according to an embodiment of the present application with reference to the accompanying drawings.

[0032] Figure 1 A schematic diagram of a thermal runaway regulation method for an energy storage battery compartment provided in an embodiment of the present application. Figure 1 As shown, the method includes but is not limited to the following steps:

[0033] S101, obtaining initial thermal distribution parameters of the energy storage battery compartment according to the operating environment.

[0034] In a feasible implementation, the initial thermal distribution parameters of the energy storage battery compartment are affected by factors such as the battery type, cabin design, operating environment, and configuration of the thermal management system. Since the batteries used in the energy storage battery compartment include lithium-ion batteries, lead-acid batteries, etc., different types of batteries have different thermal characteristics (thermal characteristics include thermal capacity, internal resistance, heat generation during charging and discharging, etc.). The cabin size, shape, and internal structure of the energy storage battery compartment will affect air flow and heat distribution. The operating environment includes factors such as temperature, humidity, altitude, and windy and sandy weather. For example, in a high temperature environment, the initial temperature in the energy storage battery compartment is high; in a high humidity environment, the performance of the battery and the efficiency of thermal management will be restricted. The configuration of the thermal management system includes the setting of the heat dissipation method, the setting of the cooling capacity and the setting of the air volume. The heat dissipation method includes natural heat dissipation, forced air cooling, liquid cooling and phase change direct cooling. Different heat dissipation methods will affect the initial heat distribution and temperature control effect in the energy storage battery compartment. According to the heat generation and heat dissipation requirements of the energy storage battery compartment, the air conditioner can be appropriately added to adjust the cooling capacity. The air volume is usually set by a fan. The air volume generated by the fan should meet the airflow requirements inside the battery module to ensure that the heat can be effectively dissipated.

[0035] Furthermore, since the initial heat distribution parameters are affected by many factors, their specific values ​​need to be measured and calculated according to the actual situation. According to the ambient temperature and the thermal insulation performance of the energy storage battery compartment, the initial temperature in the battery compartment may be close to or slightly higher than the ambient temperature. In the initial state, since no charging and discharging operations are performed, the temperature distribution in the battery compartment is relatively uniform; as the energy storage battery compartment operates, local temperature differences may occur due to the influence of the compartment structure and heat dissipation method; in the initial state, the heat flow in the energy storage battery compartment is mainly caused by the ambient temperature and the heat transfer of the compartment wall, and the specific value needs to be calculated based on parameters such as the heat transfer coefficient, heat exchange area and temperature difference.

[0036] Furthermore, the initial temperature distribution parameters can be obtained by measuring the temperature of the energy storage battery compartment in the actual operating environment. For example, the temperature sensor, infrared imager and other equipment can be used for measurement. After the measurement, the energy storage battery compartment can be numerically simulated by thermal simulation to obtain the initial thermal distribution parameters. The numerical simulation by thermal simulation requires relatively accurate model parameters and boundary conditions.

[0037] S102, based on interference suppression of initial thermal distribution parameters, obtaining first thermal distribution parameters for real-time data processing.

[0038] In a feasible implementation, the initial heat distribution parameters obtained from step S101 include the distribution of temperature values ​​in space or time. It is necessary to check and remove abnormal values, missing values ​​or noise data (which can be done by statistical methods, such as mean filtering, median filtering, etc., or by threshold setting based on physical principles. The specific operation will not be repeated here), and then perform data standardization. In the process of interference suppression, it is usually necessary to perform interference source analysis, including identifying interference sources that may be introduced into the heat distribution data, such as external heat sources, sensor errors, data transmission errors, etc. Filtering operations are also required. If high-frequency noise is to be removed, low-pass filtering can be used to retain the main trend of heat distribution; Kalman filtering can also be used to estimate the true state of heat distribution while suppressing noise and interference; for noise in a specific frequency band, wavelet transform can also be used. Specifically, the filtering operation method should be selected according to the usage scenario. On the other hand, according to the characteristics of the interference, an appropriate algorithm can also be designed or selected for interference suppression. As an example, a statistical method, such as threshold monitoring, can be used; a model-based method, such as state estimation, can also be used; statistics and models can also be used in combination.

[0039] After interference suppression, prediction models such as time series analysis and machine learning models can also be used to predict future thermal distribution trends. According to application requirements, the first thermal distribution parameters of the rod are extracted from the data after interference suppression, and the first thermal distribution parameters include average temperature, maximum temperature, temperature gradient, heat flux, etc. These parameters can accurately reflect the current thermal distribution state and are used for subsequent real-time policy or control.

[0040] S103, performing trend prediction on the first heat distribution parameter according to the stored historical data, obtaining a thermal runaway risk assessment result of the energy storage battery compartment, and performing feedback adjustment on the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result.

[0041] In a feasible implementation, the stored historical data is composed of the first thermal distribution parameters at the previous moment. In order to distinguish it from the first thermal distribution parameters at the current moment, the historical data can be characterized by the second thermal distribution parameters. From the stored second thermal distribution parameters, features that are highly correlated with the first thermal distribution parameters at the current moment and used for real-time data processing are extracted, and the features include parameters such as average temperature and maximum temperature. Then, according to the data features and prediction requirements of the second thermal distribution parameters, a suitable prediction model is selected. The prediction model can be a time series model, including a differential autoregressive moving average model, a long short-term memory network, a gated recurrent unit, etc. Then, the prediction model is trained with the historical data (i.e., the second thermal distribution parameters), and the prediction performance is optimized by adjusting the model parameters.

[0042] Then substitute the first heat distribution parameter into the prediction model, output the prediction result, and map the prediction result to the defined risk level according to the safety requirements of the energy storage battery compartment to obtain the thermal runaway risk assessment result of the energy storage battery compartment. According to the thermal runaway risk assessment result, specify the corresponding operating environment adjustment strategy, such as adjusting the working mode of the cooling system, optimizing the battery layout, limiting the charging and discharging power, etc. And convert the adjustment strategy into specific control instructions, and adjust the operating environment of the energy storage battery compartment in real time through the control instructions. At the same time, it is also necessary to continuously monitor the operating status of the energy storage battery compartment, evaluate the results of the feedback adjustment, and adjust the adjustment strategy according to actual needs. After the feedback adjustment operation is completed, the first heat distribution parameter is incorporated into the historical data for optimization and updating of the prediction model.

[0043] In summary, based on the stored historical data, the trend of the first heat distribution parameter obtained for real-time data processing is predicted, and the thermal runaway risk assessment result of the energy storage battery compartment is obtained, thereby greatly improving the accuracy of thermal runaway monitoring of the energy storage battery compartment; and based on the thermal runaway risk assessment result, the operating environment of the energy storage battery compartment is feedback-adjusted to ensure that the energy storage battery compartment can operate within a safe temperature range, thereby maximizing the operating stability of the energy storage battery compartment, and therefore the energy storage battery compartment thermal runaway adjustment method and device have wide applicability.

[0044] Figure 2 A schematic diagram of another method for regulating thermal runaway of an energy storage battery compartment provided in an embodiment of the present application. Figure 2 As shown, the method includes but is not limited to the following steps:

[0045] S201, identifying the operating environment of the energy storage battery compartment and obtaining environmental parameters.

[0046] For further details of step S201, please refer to the relevant contents in the above embodiment, which will not be repeated here.

[0047] S202, performing infrared imaging scanning on the energy storage battery compartment according to the environmental parameters to obtain initial thermal distribution parameters of the energy storage battery compartment.

[0048] In a feasible implementation, the environmental parameters are subjected to principal component analysis to obtain the first parameter that affects the thermal distribution of the energy storage battery compartment. It should be noted that it is necessary to clarify which environmental parameters may be related to the thermal distribution of the energy storage battery compartment, and these parameters include temperature, humidity, wind speed, internal layout of the battery compartment, battery arrangement, cooling efficiency, etc. However, in the actual application of principal component analysis, only numerical data can be processed. Specifically, the covariance matrix of the standardized environmental parameters is obtained; the eigenvalues ​​and eigenvectors of the covariance matrix are calculated, and these eigenvalues ​​and eigenvectors are used to determine the principal components; the principal components are selected according to the size of the eigenvalues, and the first principal component corresponds to the largest eigenvalue, which explains the maximum variation in the data; the loads of each environmental parameter on the first principal component (i.e., the value in the eigenvector) are checked, and the larger the absolute value of the load, the greater the contribution of the parameter to the first principal component; according to the loads of each parameter on the first principal component, it can be determined which environmental parameter is the first parameter that affects the thermal distribution of the energy storage battery compartment.

[0049] After obtaining the first parameter, the thermophysical parameters of the energy storage battery compartment material are obtained, which are key factors in evaluating the thermal management performance of the energy storage battery compartment and ensuring the safe operation of the battery. These parameters may include thermal conductivity, specific heat capacity, thermal expansion coefficient, etc., which describe the characteristics of the material in terms of heat transfer, heat storage and thermal deformation.

[0050] Then, a thermal model of the energy storage battery compartment is established based on the first parameter and the thermophysical parameters. Furthermore, a three-dimensional geometric model of the energy storage battery compartment can be obtained based on a fluid dynamics analysis operation, wherein the continuity equation, Bernoulli equation, or Navier-Stokes equation in fluid dynamics can be used for analysis, and the specific analysis process is not repeated here; based on the three-dimensional geometric model, boundary conditions and initial conditions are determined; based on the first parameter, thermophysical parameters, boundary conditions, and initial conditions, a thermal simulation analysis is performed on the energy storage battery compartment to obtain a thermal model of the energy storage battery compartment.

[0051] Therefore, according to the thermal model, the energy storage battery compartment is scanned by infrared imaging to obtain the initial thermal distribution parameters of the energy storage battery compartment.

[0052] For further details of step S202, please refer to the relevant contents in the above embodiment, which will not be repeated here.

[0053] S203, based on interference suppression of the initial heat distribution parameters, obtaining first heat distribution parameters for real-time data processing.

[0054] In a feasible implementation, interference sources that affect the thermal distribution accuracy of the energy storage battery compartment are identified from the initial thermal distribution parameters; an interference suppression strategy is determined based on the interference sources; and interference suppression is performed on the initial thermal distribution parameters based on the interference suppression strategy to obtain first thermal distribution parameters for real-time data processing.

[0055] For further details of step S203, please refer to the relevant contents in the above embodiment, which will not be repeated here.

[0056] S204, performing trend prediction on the first heat distribution parameter according to the stored historical data, obtaining a thermal runaway risk assessment result of the energy storage battery compartment, and performing feedback adjustment on the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result.

[0057] In a feasible implementation, historical data related to the first heat distribution parameter is obtained from the operation database of the energy storage battery compartment; the historical data is preprocessed to obtain the second heat distribution parameter; and the prediction model is determined according to the prediction demand and the data characteristics of the second heat distribution parameter. Furthermore, the environmental factors affecting the second heat distribution parameter are obtained; according to the environmental factors, the second heat distribution parameter is feature extracted to obtain the first feature, wherein the feature extraction can obtain useful features, such as trends and periodic changes in time series, etc.; the first feature is feature transformed to obtain the second feature, wherein the feature expression ability can be enhanced and redundancy can be reduced through mathematical transformation (such as logarithmic transformation, difference, etc.) or machine learning.

[0058] Then, according to the prediction needs and the second feature, the prediction model is determined, wherein the prediction target, prediction time range and prediction accuracy requirements are determined according to the usage scenario; the data characteristics of the second feature (including data type, data volume, data quality, etc.) are obtained, various factors that may affect the thermal physical parameters of the energy storage battery compartment material (such as temperature, pressure, material composition, etc.) are analyzed, and the correlation between each factor and the thermal physical factor parameters is explored to determine which factors can be used as input variables of the prediction model. Furthermore, the prediction model can be set up using a time series model, a regression model, a machine learning model, etc., and the specific setting process will not be repeated here.

[0059] The first heat distribution parameter is then substituted into the prediction model for trend prediction to obtain a thermal runaway risk assessment result of the energy storage battery compartment.

[0060] Furthermore, based on the thermal runaway risk assessment results, feedback adjustment is performed on the operating environment of the energy storage battery compartment. Specifically, as an example, an adjustment strategy is determined based on the thermal runaway risk assessment results; according to the adjustment strategy, the environmental perception data of the energy storage battery compartment is monitored in real time, and based on the monitoring results, feedback adjustment is performed on the operating environment of the energy storage battery compartment. More specifically, according to the adjustment strategy, the temperature, humidity, carbon monoxide concentration and smoke concentration of the energy storage battery compartment are monitored to obtain the monitoring results; according to the monitoring results, the ventilation and heat dissipation of the energy storage battery compartment are controlled, and when the environmental parameters of the energy storage battery compartment exceed the set warning threshold, the energy storage battery compartment is subjected to emergency treatment, wherein the emergency treatment includes cutting off the power supply of the energy storage battery compartment, fire response to the energy storage battery compartment, etc.

[0061] For further details of step S204, please refer to the relevant contents in the above embodiment, which will not be repeated here.

[0062] In summary, based on the stored historical data, the trend of the first heat distribution parameter obtained for real-time data processing is predicted, and the thermal runaway risk assessment result of the energy storage battery compartment is obtained, thereby greatly improving the accuracy of thermal runaway monitoring of the energy storage battery compartment; and based on the thermal runaway risk assessment result, the operating environment of the energy storage battery compartment is feedback-adjusted to ensure that the energy storage battery compartment can operate within a safe temperature range, thereby maximizing the operating stability of the energy storage battery compartment, and therefore the energy storage battery compartment thermal runaway adjustment method and device have wide applicability.

[0063] Figure 3 This is a schematic diagram of the structure of a thermal runaway control device for an energy storage battery compartment provided in an embodiment of the present application. Figure 3 As shown, the energy storage battery compartment thermal runaway regulating device 300 includes:

[0064] A first acquisition module 301, the first acquisition module 301 is used to obtain initial thermal distribution parameters of the energy storage battery compartment according to the operating environment;

[0065] A second acquisition module 302, the second acquisition module 302 is used to acquire first heat distribution parameters for real-time data processing based on interference suppression of the initial heat distribution parameters;

[0066] A prediction module 303, which is used to perform trend prediction on the first heat distribution parameter according to the stored historical data, and obtain a thermal runaway risk assessment result of the energy storage battery compartment;

[0067] The regulating module 304 is used to perform feedback regulation on the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result.

[0068] Figure 4 The present invention is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0069] like Figure 4 As shown, the electronic device 400 includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a memory 406 to a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0070] The following components are connected to the I / O interface 405: a memory 406 including a hard disk, etc.; and a communication part 407 including a network interface card such as a LAN (Local Area Network) card, a modem, etc., and the communication part 407 performs communication processing via a network such as the Internet; a drive 408 is also connected to the I / O interface 405 as needed.

[0071] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 407. When the computer program is executed by the processor 401, the above-mentioned functions defined in the method of the present application are executed.

[0072] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory including instructions, and the instructions can be executed by the processor 401 of the electronic device 400 to complete the above method. Optionally, the storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0073] In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0074] Figure 5 It is a schematic diagram of the structure of another electronic device provided according to an embodiment of the present application. Figure 5 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application. Figure 5 As shown, the electronic device 500 includes a processor 501 and a memory 502. The memory 502 is used to store program codes, and the processor 501 is connected to the memory 502 to read the program codes from the memory 502 to implement the thermal runaway regulation method of the energy storage battery compartment in the above embodiment.

[0075] Optionally, the number of processors 501 may be one or more.

[0076] Optionally, the electronic device may further include an interface 503, and the number of the interface 503 may be multiple. The interface 503 may be connected to an application program and may receive data from an external device such as a sensor.

[0077] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0078] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for regulating thermal runaway of an energy storage battery compartment, characterized in that: include: According to the operating environment, the initial thermal distribution parameters of the energy storage battery compartment are obtained; Based on interference suppression of the initial thermal distribution parameters, obtaining first thermal distribution parameters for real-time data processing; According to the stored historical data, a trend forecast is performed on the first heat distribution parameter to obtain a thermal runaway risk assessment result of the energy storage battery compartment, and based on the thermal runaway risk assessment result, feedback adjustment is performed on the operating environment of the energy storage battery compartment.

2. The method according to claim 1, characterized in that The obtaining of initial thermal distribution parameters of the energy storage battery compartment according to the operating environment includes: Identify the operating environment of the energy storage battery compartment and obtain environmental parameters; According to the environmental parameters, an infrared imaging scan is performed on the energy storage battery compartment to obtain initial thermal distribution parameters of the energy storage battery compartment.

3. The method according to claim 2, characterized in that The step of performing infrared imaging scanning on the energy storage battery compartment according to the environmental parameters to obtain initial thermal distribution parameters of the energy storage battery compartment includes: Performing principal component analysis on the environmental parameters to obtain a first parameter that affects the thermal distribution of the energy storage battery compartment; Obtain the thermal physical parameters of energy storage battery compartment materials; Establishing a thermal model of the energy storage battery compartment according to the first parameter and the thermophysical property parameter; According to the thermal model, an infrared imaging scan is performed on the energy storage battery compartment to obtain initial thermal distribution parameters of the energy storage battery compartment.

4. The method according to claim 3, characterized in that The step of establishing a thermal model of the energy storage battery compartment according to the first parameter and the thermophysical property parameter includes: Based on the fluid dynamics analysis operation, a three-dimensional geometric model of the energy storage battery compartment is obtained; Determining boundary conditions and initial conditions according to the three-dimensional geometric model; According to the first parameter, the thermophysical property parameter, the boundary condition and the initial condition, a thermal simulation analysis is performed on the energy storage battery compartment to obtain a thermal model of the energy storage battery compartment.

5. The method according to claim 1, characterized in that The obtaining of the first heat distribution parameter for real-time data processing based on interference suppression of the initial heat distribution parameter comprises: From the initial heat distribution parameters, identifying interference sources that affect the heat distribution accuracy of the energy storage battery compartment; Determining an interference suppression strategy according to the interference source; According to the interference suppression strategy, interference suppression is performed on the initial heat distribution parameters to obtain first heat distribution parameters for real-time data processing.

6. The method according to claim 1, characterized in that The step of performing trend prediction on the first heat distribution parameter according to the stored historical data to obtain a thermal runaway risk assessment result of the energy storage battery compartment includes: Acquiring historical data related to the first heat distribution parameter from an operation database of the energy storage battery compartment; Preprocessing the historical data to obtain a second heat distribution parameter; Determining a prediction model according to the prediction demand and the data characteristics of the second heat distribution parameter; The first heat distribution parameter is substituted into the prediction model for trend prediction to obtain a thermal runaway risk assessment result of the energy storage battery compartment.

7. The method according to claim 6, characterized in that Determining a prediction model according to the prediction demand and the data characteristics of the second heat distribution parameter includes: Acquiring environmental factors that affect the second heat distribution parameter; According to the environmental factor, feature extraction is performed on the second heat distribution parameter to obtain a first feature; Performing feature transformation on the first feature to obtain a second feature; A prediction model is determined according to the prediction requirements and the second characteristic.

8. The method according to claim 1, characterized in that The feedback adjustment of the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result includes: Determining a regulation strategy according to the thermal runaway risk assessment result; According to the adjustment strategy, the environmental perception data of the energy storage battery compartment is monitored in real time, and based on the monitoring results, the operating environment of the energy storage battery compartment is feedback-adjusted.

9. The method according to claim 8, characterized in that According to the adjustment strategy, the environmental perception data of the energy storage battery compartment is monitored in real time, and based on the monitoring results, the operating environment of the energy storage battery compartment is feedback-adjusted, including: According to the adjustment strategy, the temperature, humidity, carbon monoxide concentration and smoke concentration of the energy storage battery compartment are monitored to obtain monitoring results; According to the monitoring results, the ventilation and heat dissipation of the energy storage battery compartment are controlled, and when the environmental parameters of the energy storage battery compartment exceed the set warning threshold, the energy storage battery compartment is subjected to emergency treatment.

10. A thermal runaway regulating device for an energy storage battery compartment, characterized in that: include: A first acquisition module, the first acquisition module is used to obtain initial thermal distribution parameters of the energy storage battery compartment according to the operating environment; a second acquisition module, the second acquisition module being used to acquire first heat distribution parameters for real-time data processing based on interference suppression of the initial heat distribution parameters; A prediction module, the prediction module is used to perform trend prediction on the first heat distribution parameter according to the stored historical data, and obtain a thermal runaway risk assessment result of the energy storage battery compartment; A regulation module, wherein the regulation module is used to perform feedback regulation on the operating environment of the energy storage battery compartment based on the thermal runaway risk assessment result.

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