Battery cell safety prediction method and apparatus, device, and medium

Abstract

The present application provides a battery cell safety prediction method and apparatus, a device, and a medium. The method comprises: determining a first environment parameter, and executing a first thermal runaway operation on a target battery cell on the basis of the first environment parameter until thermal runaway of the target battery cell occurs; acquiring a first state parameter of the target battery cell; determining a target heat generation model; performing three-dimensional modeling on the structure of a battery; executing a second thermal runaway operation on the established model; on the basis of the target heat generation model, acquiring a second state parameter during the second thermal runaway operation; and determining the safety of a target battery pack. A target heat generation model is determined by means of an actual thermal runaway operation, and the safety of a target battery pack is determined on the basis of the target heat generation model by means of a thermal runaway simulation operation, thereby saving test costs and simplifying a battery cell safety prediction system. Additionally, the method reduces the requirements of mechanism modeling for basic data, and thus improves the efficiency and accuracy of battery cell safety prediction.

Description

Cell safety prediction methods, devices, equipment and media

[0001] This application claims priority to Chinese Patent Application No. 202410684615.4, filed on May 29, 2024, entitled “Method, Apparatus, Device and Medium for Predicting Battery Cell Safety”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to battery testing technology, and more particularly to a method, apparatus, equipment and medium for predicting the safety of battery cells. Background Technology

[0003] All battery and energy storage system products require overcharge testing to verify their safety performance. Proper design of batteries and battery packs can prevent thermal runaway that may occur when batteries are overcharged, thereby reducing the likelihood of serious safety incidents such as fires or explosions.

[0004] Whether a battery pack will experience thermal runaway during overcharging is related to the overcharging performance of individual cells and the battery pack's structural design. Before overcharging testing, the battery pack's overcharging performance can be estimated. If the estimation results indicate a high risk of thermal runaway, the design can be adjusted in a timely manner, reducing the material and time costs incurred by using actual materials for trial and error, thus improving R&D efficiency.

[0005] However, current estimation methods require accurate information on material composition and reaction conditions for modeling, and the resulting systems are complex, leading to low estimation efficiency. Therefore, a new method for predicting battery cell safety is needed to simplify the system and improve its efficiency.

[0006] Summary of the Invention

[0007] This application provides a method, apparatus, device, and medium for predicting the safety of battery cells, in order to solve the problem that current battery cell safety estimation schemes require accurate acquisition of material composition and reaction conditions for modeling, and the corresponding system has a complex structure, resulting in low estimation efficiency.

[0008] In a first aspect, this application provides a method for predicting the safety of battery cells, the method comprising:

[0009] A first environmental parameter of the target area is determined, and a first thermal runaway operation is performed on the target cell based on the first environmental parameter until the target cell experiences thermal runaway; and, during the execution of the first thermal runaway operation, a first state parameter of the target cell is acquired.

[0010] The target battery cell is at a preset overcharge level;

[0011] Based on the first state parameter, a target heat generation model corresponding to each target cell is determined; wherein, the target heat generation model is used to indicate the heat generation of each target cell under preset operating parameters;

[0012] A structural model of the target battery pack is established, and a second thermal runaway operation is performed on the structural model; and, during the execution of the second thermal runaway operation, a second state parameter of each target cell is determined according to each target heat generation model.

[0013] The safety of the target battery pack is determined based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

[0014] As an optional implementation, the first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition that the target area is kept in an insulation state;

[0015] The method further includes determining a first environmental parameter of the target area and performing a first thermal runaway operation on the target cell based on the first environmental parameter until the target cell experiences thermal runaway.

[0016] Perform a charging operation on the target cells until each target cell is fully charged.

[0017] Determine multiple first measurement points associated with the target battery cell;

[0018] The first measuring point is used to obtain the temperature parameters of each target battery cell;

[0019] And, the step of determining the first environmental parameters of the target area, and performing a first thermal runaway operation on the target cell based on the first environmental parameters, until the target cell experiences thermal runaway, includes:

[0020] Determine the first environmental parameters of the target area, and perform a first thermal runaway operation on the target cell based on the first environmental parameters;

[0021] Based on the temperature parameters corresponding to each of the first measuring points, determine whether the target cell has experienced thermal runaway.

[0022] If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

[0023] As an optional implementation, the first state parameters include one or more of the cell surface temperature, charging current, and cell voltage; the target heat generation model includes a target overcharge model; and determining the target heat generation model corresponding to each target cell based on the first state parameters includes:

[0024] Based on the first state parameter, establish a single cell overcharge model corresponding to each target cell, and determine the third state parameter in each single cell overcharge model.

[0025] The single-cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell.

[0026] Parameter optimization is performed on each of the third state parameters to obtain target state parameters, and target overcharge models corresponding to each target cell are determined based on the target state parameters and the overcharge models of each individual cell.

[0027] As an optional implementation, the step of optimizing each of the third state parameters to obtain the target state parameters includes:

[0028] Determine the target limits and target orders of magnitude for each of the third state parameters;

[0029] Based on the target order of magnitude of each of the third state parameters, determine the gradient of the state parameter change corresponding to each of the third state parameters;

[0030] Within the target limit, parameter adjustments are performed on each of the third state parameters according to the state parameter change gradient corresponding to each of the third state parameters;

[0031] Under different values ​​of the third state parameters, the measured value of the cell surface temperature corresponding to each target cell is determined, and the calculated value of the cell surface temperature corresponding to each target cell is obtained by calculating the single cell overcharge model.

[0032] The first thermal runaway initiation temperature is determined based on the measured value, the second thermal runaway initiation temperature is determined based on the calculated value, the difference between the thermal runaway initiation temperatures is determined based on the first thermal runaway initiation temperature and the second thermal runaway initiation temperature, and the sum of squares of the difference is determined based on the measured value and the calculated value.

[0033] The candidate parameter values ​​for the third state parameter are determined under the condition that the sum of squares of the difference is less than a preset sum of squares threshold, and / or the difference in thermal runaway initiation temperature is less than a preset difference threshold, and the target state parameter is determined from the candidate parameter values.

[0034] As an optional implementation, establishing a structural model of the target battery pack and performing a second thermal runaway operation on the structural model includes:

[0035] The electrical component structure and mechanical component structure of the target battery pack are determined, and a structural model of the target battery pack is established based on the electrical component structure and the mechanical component structure.

[0036] The electrical component structure includes a battery cell structure and a connector bus structure;

[0037] Based on the target overcharge model of each target cell, a first heat generation model corresponding to the cell structure is established; and, the ohmic heat generation corresponding to the connecting busbar structure is determined, and a second heat generation model is established; and, the convective heat transfer coefficient and radiative emissivity corresponding to the mechanical component structure are determined, and a third heat generation model is established.

[0038] Based on the target charging time and target charging current, the structural model is simulated to overcharge in order to perform a second thermal runaway operation and determine the thermal runaway conditions;

[0039] The thermal runaway condition is associated with the first heat generation model, the second heat generation model, and the third heat generation model, and is used to indicate the thermophysical conditions corresponding to the preset safety requirements for the safety of the target battery pack.

[0040] Secondly, this application provides a cell safety prediction device, the device comprising:

[0041] The determination module is used to determine the first environmental parameters of the target area;

[0042] The processing module is configured to perform a first thermal runaway operation on the target cell according to the first environmental parameters until the target cell experiences thermal runaway; and to acquire the first state parameters of the target cell during the execution of the first thermal runaway operation.

[0043] The processing module is further configured to determine a target heat generation model corresponding to each of the target cells based on the first state parameters; wherein the target heat generation model is used to indicate the heat generation of each of the target cells under preset operating parameters;

[0044] The processing module is further configured to establish a structural model of the target battery pack and perform a second thermal runaway operation on the structural model; and, during the execution of the second thermal runaway operation, determine the second state parameters of each target cell according to each target heat generation model.

[0045] The processing module is further configured to determine the safety of the target battery pack based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

[0046] As an optional implementation, the first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition that the target area is kept in an insulation state;

[0047] The processing module is further configured to, before the determining module determines the first environmental parameters of the target area,

[0048] Perform a charging operation on the target cells until each target cell is fully charged.

[0049] Determine multiple first measurement points associated with the target battery cell;

[0050] The first measuring point is used to obtain the temperature parameters of each target battery cell;

[0051] And, the specific method by which the processing module performs a first thermal runaway operation on the target cell according to the first environmental parameters after the determining module determines the first environmental parameters of the target area, until the target cell experiences thermal runaway, includes:

[0052] Determine the first environmental parameters of the target area, and perform a first thermal runaway operation on the target cell based on the first environmental parameters;

[0053] Based on the temperature parameters corresponding to each of the first measuring points, determine whether the target cell has experienced thermal runaway.

[0054] If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

[0055] As an optional implementation, the first state parameter includes one or more of the cell surface temperature, charging current, and cell voltage; the target heat generation model includes a target overcharge model; and the processing module determines the specific method of the target heat generation model corresponding to each target cell based on the first state parameter, including:

[0056] Based on the first state parameter, establish a single cell overcharge model corresponding to each target cell, and determine the third state parameter in each single cell overcharge model.

[0057] The single-cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell.

[0058] Parameter optimization is performed on each of the third state parameters to obtain target state parameters, and target overcharge models corresponding to each target cell are determined based on the target state parameters and the overcharge models of each individual cell.

[0059] As an optional implementation, the processing module optimizes each of the third state parameters to obtain the target state parameters in the following ways:

[0060] Determine the target limits and target orders of magnitude for each of the third state parameters;

[0061] Based on the target order of magnitude of each of the third state parameters, determine the gradient of the state parameter change corresponding to each of the third state parameters;

[0062] Within the target limit, parameter adjustments are performed on each of the third state parameters according to the state parameter change gradient corresponding to each of the third state parameters;

[0063] Under different values ​​of the third state parameters, the measured value of the cell surface temperature corresponding to each target cell is determined, and the calculated value of the cell surface temperature corresponding to each target cell is obtained by calculating the single cell overcharge model.

[0064] The first thermal runaway initiation temperature is determined based on the measured value, the second thermal runaway initiation temperature is determined based on the calculated value, the difference between the thermal runaway initiation temperatures is determined based on the first thermal runaway initiation temperature and the second thermal runaway initiation temperature, and the sum of squares of the difference is determined based on the measured value and the calculated value.

[0065] The candidate parameter values ​​for the third state parameter are determined under the condition that the sum of squares of the difference is less than a preset sum of squares threshold, and / or the difference in thermal runaway initiation temperature is less than a preset difference threshold, and the target state parameter is determined from the candidate parameter values.

[0066] As an optional implementation, the processing module establishes a structural model of the target battery pack and specifies the method for performing a second thermal runaway operation on the structural model, including...

[0067] The electrical component structure and mechanical component structure of the target battery pack are determined, and a structural model of the target battery pack is established based on the electrical component structure and the mechanical component structure.

[0068] The electrical component structure includes a battery cell structure and a connector bus structure;

[0069] Based on the target overcharge model of each target cell, a first heat generation model corresponding to the cell structure is established; and, the ohmic heat generation corresponding to the connecting busbar structure is determined, and a second heat generation model is established; and, the convective heat transfer coefficient and radiative emissivity corresponding to the mechanical component structure are determined, and a third heat generation model is established.

[0070] Based on the target charging time and target charging current, the structural model is simulated to overcharge in order to perform a second thermal runaway operation and determine the thermal runaway conditions;

[0071] The thermal runaway condition is associated with the first heat generation model, the second heat generation model, and the third heat generation model, and is used to indicate the thermophysical conditions corresponding to the preset safety requirements for the safety of the target battery pack.

[0072] Thirdly, this application also provides an electronic device, comprising:

[0073] At least one processor; and

[0074] A memory communicatively connected to the at least one processor; wherein,

[0075] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method as described in the first aspect.

[0076] Fourthly, this application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0077] The cell safety prediction method, apparatus, equipment, and medium provided in this application determine first environmental parameters and perform a first thermal runaway operation on a target cell based on these parameters until thermal runaway occurs. During this process, first state parameters of the target cell are acquired. Based on these first state parameters, a target heat generation model is determined, and a three-dimensional model of the battery structure is created. A second thermal runaway operation is then performed based on the three-dimensional model. During the second thermal runaway operation, second state parameters are acquired based on the previously determined target heat generation model. The safety of the target battery pack can be determined based on these second state parameters. Therefore, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, testing costs are saved, the cell safety prediction system is simplified, and the requirements for basic data in mechanism modeling are reduced. In summary, this method improves the efficiency and accuracy of cell safety prediction. Attached Figure Description

[0078] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0079] Figure 1 is a flowchart illustrating a cell safety prediction method disclosed in an embodiment of the present invention;

[0080] Figure 2 is a schematic diagram of the structure of a battery cell safety prediction device disclosed in an embodiment of the present invention;

[0081] Figure 3 is a schematic diagram of the structure of a battery cell safety prediction electronic device disclosed in an embodiment of the present invention.

[0082] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0083] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0084] All battery and energy storage system products require overcharge testing to verify their safety performance. Proper design of batteries and battery packs can prevent thermal runaway that may occur when batteries are overcharged, thereby reducing the likelihood of serious safety incidents such as fires or explosions.

[0085] Whether a battery pack will experience thermal runaway during overcharging is related to the overcharging performance of individual cells and the battery pack's structural design. Before overcharging testing, the battery pack's overcharging performance can be estimated. If the estimation results indicate a high risk of thermal runaway, the design can be adjusted in a timely manner, reducing the material and time costs incurred by using actual materials for trial and error, thus improving R&D efficiency.

[0086] However, current estimation methods require accurate information on material composition and reaction conditions for modeling, and the resulting systems are complex, leading to low estimation efficiency. Therefore, a new method for predicting battery cell safety is needed to simplify the system and improve its efficiency.

[0087] The technical concept of this application lies in determining a first environmental parameter and performing a first thermal runaway operation on a target battery cell based on the first environmental parameter until thermal runaway occurs. During this process, the first state parameter of the target battery cell is acquired. Based on the first state parameter, a target heat generation model is determined, and a three-dimensional model of the battery structure is created. A second thermal runaway operation is then performed based on the three-dimensional model. During the second thermal runaway operation, a second state parameter is acquired based on the previously determined target heat generation model. The safety of the target battery pack can be determined based on the second state parameter. Therefore, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, testing costs are saved, the battery cell safety prediction system is simplified, and the requirements for basic data in mechanism modeling are reduced. In summary, this method improves the efficiency and accuracy of battery cell safety prediction.

[0088] Example 1

[0089] Please refer to Figure 1, which is a flowchart illustrating a cell safety prediction method disclosed in an embodiment of the present invention. As shown in Figure 1, the method includes:

[0090] S101. Determine the first environmental parameters of the target area, and perform a first thermal runaway operation on the target cell based on the first environmental parameters until the target cell experiences thermal runaway; and, during the execution of the first thermal runaway operation, acquire the first state parameters of the target cell.

[0091] The target battery cell structure includes multiple target battery cells and corresponding mechanical and electrical connection devices. In the subsequent structural modeling process, a corresponding structural model needs to be established based on the actual structure of the target battery cells. In this application, thermal runaway of the target battery cell can be determined based on the propagation phenomenon of thermal runaway occurring in several target battery cells.

[0092] During the first thermal runaway operation, it is necessary to ensure that the target cell experiences thermal runaway. This can be achieved by recording the first state parameters of the target cell during the charging to thermal runaway process. If the target cell does not experience thermal runaway under the current environmental conditions, the first environmental parameters need to be adjusted to ensure that the target cell experiences thermal runaway. For details, please refer to the relevant descriptions of other implementation methods.

[0093] Meanwhile, before performing thermal runaway operation on each target cell, each target cell needs to be charged to an overcharged state of more than full charge. Each target cell is in a preset overcharged state. In subsequent implementation methods, there are some related parameters that are associated with this overcharged state. For details, please refer to the corresponding implementation method.

[0094] S102. Determine the target heat generation model corresponding to each target cell based on the first state parameters; wherein, the target heat generation model is used to indicate the heat generation of each target cell under preset operating parameters.

[0095] The target heat generation model can include an electrochemical reaction heat generation model and a decomposition reaction heat generation model, which will be described in detail in other embodiments. It should be noted that, given that the exact convective heat transfer coefficient and radiative emissivity of a single battery cell are known, the method provided in this application is not strictly limited to an adiabatic environment and can be carried out in an isothermal or variable-temperature environment at any temperature. In this case, the target heat generation model needs to consider actual thermophysical phenomena, and the complexity of the model will increase.

[0096] S103. Establish a structural model of the target battery pack and perform a second thermal runaway operation on the structural model; and, during the execution of the second thermal runaway operation, determine the second state parameters of each target cell based on each target heat generation model.

[0097] The structural model, as mentioned above, is a three-dimensional model obtained in modeling software based on multiple target cells and corresponding mechanical and electrical connection devices. It is used to simulate the actual target battery pack structure and to perform a second thermal runaway operation on the structural model. During the process, the corresponding state parameters are obtained based on the aforementioned target heat generation model, thereby saving the cost of cell safety testing and simplifying the system structure.

[0098] S104. Determine the safety of the target battery pack based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

[0099] The second state parameter may include one or more of the following: the temperature distribution of each target cell, the rate of temperature change on at least one preset cell surface on each target cell, and the overall temperature distribution and rate of temperature change of the target battery pack. This can determine the thermal runaway status of the target cell, thereby enabling the testing of the safety of each target cell and the target battery pack as a whole.

[0100] As an optional implementation, the first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition of maintaining an insulation state in the target area;

[0101] The method further includes determining the first environmental parameters of the target area, and performing a first thermal runaway operation on the target cell based on the first environmental parameters until thermal runaway occurs in the target cell.

[0102] Perform a charging operation on the target cells until each target cell is fully charged;

[0103] It should be understood that after charging to full charge, each target cell needs to be further charged to a preset overcharge state, depending on the specific application scenario.

[0104] Multiple first measurement points associated with the target battery cells are identified; wherein, the first measurement points are used to obtain the temperature parameters of each target battery cell;

[0105] And, determine the first environmental parameters of the target area, and based on the first environmental parameters, perform a first thermal runaway operation on the target cell until the target cell experiences thermal runaway, including:

[0106] Determine the first environmental parameters of the target area, and perform the first thermal runaway operation on the target cell based on the first environmental parameters;

[0107] Based on the temperature parameters corresponding to each first measuring point, determine whether the target cell has experienced thermal runaway.

[0108] If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

[0109] As can be seen, in this embodiment, the target cell is pre-charged to full charge before the first thermal runaway operation, and multiple first measurement points for obtaining temperature parameters are determined to complete the preliminary preparation for the first thermal runaway operation. At the same time, an adiabatic environment is created for the first thermal runaway operation based on the determined first environmental parameters. The first thermal runaway operation is performed on the target cell in the adiabatic environment, and the first environmental parameters are adjusted according to the actual state of the target cell during the first thermal runaway operation until the target cell actually experiences thermal runaway.

[0110] This ensures the effectiveness and practicality of the first thermal runaway operation. During this operation, relevant parameters of the target cell during charging to the point of overcharging and thermal runaway can be successfully obtained, providing effective basic data for the target heat generation model. In summary, the target heat generation model can be determined through a single actual thermal runaway operation, and then the safety of the target battery pack can be determined based on the target heat generation model through a simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanistic modeling, thus improving the overall efficiency and accuracy of cell safety prediction.

[0111] As an optional implementation, the first state parameters include one or more of the cell surface temperature, charging current, and cell voltage. The target heat generation model includes a target overcharge model. Based on the first state parameters, a target heat generation model corresponding to each target cell is determined, including:

[0112] Based on the first state parameters, establish a single cell overcharge model corresponding to each target cell, and determine the third state parameters in each single cell overcharge model.

[0113] Among them, the single cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell.

[0114] Parameter optimization is performed on each third state parameter to obtain the target state parameter. Based on the target state parameter and the overcharge model of each individual cell, the target overcharge model corresponding to each target cell is determined.

[0115] In this embodiment, a single-cell overcharge model for each target cell can be established using the first state parameter. A third state parameter requiring optimization is then determined within this single-cell overcharge model. Based on the data characteristics of the third state parameter, a corresponding optimization process is executed to obtain the target state parameters, thereby determining the target overcharge model. This improves the effectiveness and efficiency of establishing the target overcharge model. The target heat generation model can be determined through a single actual thermal runaway operation, and the safety of the target battery pack can be determined based on the target overcharge model through a single simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanism modeling, thus improving the overall efficiency and accuracy of cell safety prediction.

[0116] As an optional implementation, parameter optimization is performed on each third state parameter to obtain the target state parameters, including:

[0117] Determine the target limits and target order of magnitude for each third state parameter;

[0118] Based on the target order of magnitude of each third state parameter, determine the gradient of the state parameter change corresponding to each third state parameter;

[0119] Within the target boundary, parameter adjustments are performed on each third state parameter based on the gradient of the state parameter change corresponding to each third state parameter.

[0120] Under different values ​​of each third state parameter, the measured value of the cell surface temperature corresponding to each target cell is determined, as well as the calculated value of the cell surface temperature corresponding to each target cell obtained from the single cell overcharge model.

[0121] The first thermal runaway initiation temperature is determined based on the measured value, the second thermal runaway initiation temperature is determined based on the calculated value, the difference between the first and second thermal runaway initiation temperatures is determined based on the first and second thermal runaway initiation temperatures, and the sum of squares of the difference is determined based on the measured and calculated values.

[0122] Under the condition that the sum of squares of the difference is less than a preset sum of squares threshold and / or the difference in thermal runaway initiation temperature is less than a preset difference threshold, the alternative parameter values ​​for the third state parameter are determined, and the target state parameter is determined from the alternative parameter values.

[0123] It should be noted that the aforementioned difference in thermal runaway initiation temperatures and the sum of squared differences are only optional screening criteria. In practical applications, any indicator that can measure the difference between the first and second thermal runaway initiation temperatures can be used as a screening criterion. Furthermore, within the target boundary, the process of adjusting the parameters of each third state parameter based on the gradient of the state parameter change corresponding to each third state parameter is essentially a grid optimization process. While simple to apply, it may contain some errors. In scenarios with higher accuracy requirements, other optimization models can be applied for parameter optimization.

[0124] In this embodiment, the optimization gradient is determined by the parameter limits and order-of-magnitude distribution of the third state parameter. Each third state parameter is changed according to the corresponding gradient. The measured value of the target cell surface temperature and the calculated value of the target cell surface temperature obtained by the single cell overcharge model are determined by the grid optimization method under different values ​​of the third state parameter. The first thermal runaway initiation temperature and the second thermal runaway initiation temperature are determined based on the measured value and the calculated value, thereby obtaining the candidate parameters of the third state parameter. The target state parameter is then selected from the candidate parameters to determine the target overcharge model.

[0125] This improves the effectiveness and efficiency of the target overcharge model. The target heat generation model can be determined through an actual thermal runaway operation, and the safety of the target battery pack can be determined based on the target overcharge model through a simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanism modeling, thus improving the overall efficiency and accuracy of cell safety prediction.

[0126] As an optional implementation, a structural model of the target battery pack is established, and a second thermal runaway operation is performed on the structural model, including...

[0127] Determine the electrical and mechanical component structures of the target battery pack, and establish a structural model of the target battery pack based on the electrical and mechanical component structures;

[0128] The electrical component structure includes the battery cell structure and the connector structure;

[0129] Based on the target overcharge model of each target cell, a first heat generation model corresponding to the cell structure is established; and, the ohmic heat generation corresponding to the connecting bus structure is determined, and a second heat generation model is established; and, the convective heat transfer coefficient and radiative emissivity corresponding to the mechanical component structure are determined, and a third heat generation model is established.

[0130] Based on the target charging time and target charging current, the structural model is simulated to overcharge in order to perform a second thermal runaway operation and determine the thermal runaway conditions;

[0131] The thermal runaway condition is associated with the first heat generation model, the second heat generation model, and the third heat generation model, and is used to indicate the thermophysical conditions corresponding to the preset safety requirements for the safety of the target battery pack.

[0132] This implementation model the actual structure of the target battery cell and determines the corresponding heat generation formula and thermal runaway conditions. During the simulation of overcharging based on the target charging time and current, and the execution of the second thermal runaway operation, second state parameters can be obtained from the determined target heat generation model. These second state parameters can then be used to determine the safety of the target battery pack. Therefore, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, this method saves testing costs, simplifies the battery cell safety prediction system, and reduces the requirements for basic data in mechanism modeling. In summary, it improves the efficiency and accuracy of battery cell safety prediction.

[0133] In one application scenario, the solution provided in this application first overcharges a single battery cell to a certain cutoff voltage under adiabatic conditions using different currents. Then, radiant heating is gradually applied to the cell until thermal runaway occurs, with battery voltage, current, and surface temperature recorded throughout the process. Based on the individual cell measurements, the electrochemical heat generation and decomposition side reaction heat generation during overcharging are calculated, i.e., the aforementioned electrochemical reaction heat generation model and decomposition reaction heat generation model. The electrochemical reaction rate is an exponentially related function to the battery's state of charge during overcharging and the decomposition reaction rate. The decomposition side reaction rate follows the Arrhenius equation, and the reactant concentration of the decomposition side reaction is related to the proportion of active material inside the cell, the decomposition side reaction rate, and the overcharged battery's state of charge. This couples the electrochemical reaction with the decomposition reaction. The parameters in the equations can be automatically solved by an optimization algorithm. When the difference between the measured and calculated temperature rise on the cell surface is less than a set value, an optimal set of equation parameters is selected from a set of parameters that meet the conditions. Subsequently, a 3D model of the battery pack can be built in finite element method (FEM) software based on the actual design. Each individual cell can be assigned the heat generated as it changes with the state of charge and temperature of the overcharged battery. Using current as input, the overcharging process in actual testing is simulated, increasing the state of charge and temperature of the cells within the battery pack, and accelerating electrochemical and decomposition reactions. When thermal runaway propagation occurs in the cells of the battery pack, it indicates a fire risk during the overcharge test, requiring design adjustments. One criterion for determining thermal runaway propagation is that multiple cells successively experience thermal runaway, and the temperature rise rate reaches a preset threshold under the current operating conditions, with the duration exceeding a preset judgment time. If no thermal runaway propagation occurs, a physical experiment can be conducted directly based on the design to verify whether a fire will occur, thereby determining safety.

[0134] Specifically, in a battery pack composed of multiple cells with preset parameters, a current of I is applied. C In the scenario where overcharge testing might lead to thermal runaway, the method in this application can be implemented in the following form:

[0135] Under adiabatic conditions, an overcharge and heating test was conducted on a single battery cell.

[0136] Once the battery is fully charged, multiple temperature measurement points are placed on its surface. The battery is then placed in a device that creates an insulated environment. After the temperature measurement data stabilizes and there is no heat exchange between the battery cell and the surrounding environment (i.e., the temperature distribution inside and outside the battery cell and inside the device is uniform and stable), overcharging is performed according to the charging and cutoff conditions set based on the predicted demand.

[0137] If thermal runaway occurs during overcharging, no further heating is required. If thermal runaway does not occur after overcharging, the internal temperature of the insulation device is gradually increased at a certain temperature gradient. Once the surface temperature of the battery cell equals and stabilizes with the set temperature of the insulation device, the temperature of the insulation device is further increased until thermal runaway occurs in the battery cell.

[0138] The surface temperature of the battery cell, the charging current, and the voltage of the battery cell were recorded throughout the test.

[0139] If the exact convective heat transfer coefficient and radiative emissivity of a single battery cell are known, the test can be conducted outside of an adiabatic environment, either in a constant or variable temperature environment at any temperature.

[0140] In addition, the overcharge condition can be replaced with various electrical parameters such as constant / changing current and constant / changing power, depending on the actual situation. This application uses overcharge as an example for illustration, but it should not be limited in this respect.

[0141] Next, an overcharge model of a single battery cell can be established in finite element analysis software. Based on the data obtained in the previous step, the formula for calculating heat generation can be derived.

[0142] The expressions for the heat generation of the overcharge reaction are shown in equations (1) to (3):

[0143] Q c =ρ*H c *R c Equation (3)

[0144] Among them, R c For the overcharge reaction rate, A c E is the pre-exponential factor for the overcharge reaction. a_c R is the activation energy for the overcharge reaction. const Here, T is the molar gas constant, and c is the thermodynamic temperature. c The volume fraction of the reactive substance in the overcharge reaction is given, t0 is the overcharge duration, and c is the volume fraction of the reactive substance in the overcharge reaction. act The ratio of the core volume to the cell volume, I is the overcharge current, Ah is the rated capacity of the battery, and R is the rated capacity of the battery. de Q represents the decomposition reaction rate. c For the heat production rate of the overcharge reaction, H c This is the enthalpy of the overcharge reaction.

[0145] The expressions for the heat production of the decomposition reaction are shown in equations (4) to (6):

[0146] Q de =ρ*Hde *R de Equation (6)

[0147] Among them, A de E is the pre-exponential factor for the decomposition reaction. a_de The activation energy for the decomposition reaction is c. de Q represents the volume fraction of the overcharge reactive substance. de For the heat production rate of the decomposition reaction, H de This is the enthalpy of the decomposition reaction.

[0148] The expression for the ohmic heat generation during charging is shown in equation (7):

[0149] Q ohm =I 2 *R0 Equation (7)

[0150] Among them, Q ohm R0 is the ohmic heat generation rate, and R0 is the DC internal resistance of the cell when the SOC is at the preset condition. The change in internal resistance caused by overcharging is reflected by the heat generation rate of the overcharging reaction.

[0151] Since the battery cell is placed in an insulated environment, the heat dissipation is 0.

[0152] Using a multi-parameter optimization method, within the possible upper and lower bounds of the target parameter, and with the cutoff condition that the sum of the squares of the differences between the simulated temperature calculation results and the measured results at different locations of the battery cell is less than a certain value, the most matching target parameter A is searched. de A c H de E a_c E a_de Because these five parameters differ significantly in magnitude, the step size variation rate of each parameter needs to be constrained when setting the optimization algorithm to facilitate faster acquisition of matching results.

[0153] In addition to minimizing the sum of the squares of the differences between the calculated and measured values, it is also necessary to control the difference between the calculated and measured thermal runaway initiation temperatures (when the cell temperature rise rate is greater than a preset temperature rise rate threshold) to be less than a certain value.

[0154] Subsequently, an overcharge thermal runaway model of the battery pack can be established in finite element method (FE) software. This model can then predict whether thermal runaway will occur during the overcharging process and the heat conduction process after overcharging has stopped.

[0155] Based on the actual battery pack design, a 3D model of the battery pack, including cells, connectors, and other structural components, is established. Thermoelectric coupling is used to characterize the ohmic heat generation at the connector locations. For each cell, based on the obtained target parameters, its own overcharge and decomposition reaction heat generation is independently set, indicating that the reaction heat of each cell is determined by its own temperature and the volume fraction of active material. The charging time of the battery pack is equal to the measured result of a single cell reaching the overcharge cutoff condition under the given charging current.

[0156] At the locations where the battery pack comes into contact with the outside environment, the appropriate convective heat transfer coefficient and radiative emissivity are set according to the actual conditions.

[0157] If the battery pack does not experience thermal runaway after overcharging, whether the heat exchange in the environment exceeds the heat generated by the ongoing decomposition reaction is a crucial condition for whether thermal runaway will occur. Because the cells in the central position of the battery pack are surrounded by other cells, the heat they generate is difficult to dissipate to the outside, making it more likely that cells in this position will experience thermal runaway earlier than those in other positions.

[0158] The calculation results determine whether the battery pack design can ensure safety during overcharging.

[0159] In the battery pack model, probes are placed at preset locations for each cell to obtain the calculated temperature rise rate at each cell, checking for thermal runaway or its propagation (if adjacent cells also subsequently experience thermal runaway). If thermal runaway or its propagation occurs, it indicates a risk in the current design, requiring adjustment. If not, actual testing can be conducted for physical verification.

[0160] This embodiment determines a first environmental parameter and performs a first thermal runaway operation on the target cell based on the first environmental parameter until thermal runaway occurs. During this process, the first state parameter of the target cell is acquired. Then, based on the first state parameter, a target heat generation model is determined, and a three-dimensional model of the battery structure is performed. A second thermal runaway operation is then performed based on the three-dimensional model. During the second thermal runaway operation, a second state parameter is acquired based on the previously determined target heat generation model. Based on the second state parameter, the safety of the target battery pack can be determined. Thus, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, testing costs are saved, the cell safety prediction system is simplified, and the requirements for basic data in mechanism modeling are reduced. In summary, this method improves the efficiency and accuracy of cell safety prediction.

[0161] Example 2

[0162] This invention also provides a cell safety prediction device to implement the aforementioned method. Please refer to Figure 2, which is a schematic diagram of the structure of a cell safety prediction device disclosed in this invention. As shown in Figure 2, the device includes:

[0163] Module 31 is used to determine the first environmental parameters of the target area;

[0164] Processing module 32 is used to perform a first thermal runaway operation on the target cell according to the first environmental parameters until the target cell experiences thermal runaway; and to acquire the first state parameters of the target cell during the execution of the first thermal runaway operation.

[0165] The processing module 32 is further configured to determine the target heat generation model corresponding to each target cell based on the first state parameters; wherein the target heat generation model is used to indicate the heat generation of each target cell under preset operating parameters;

[0166] The processing module 32 is also used to establish a structural model of the target battery pack and perform a second thermal runaway operation on the structural model; and, during the execution of the second thermal runaway operation, to determine the second state parameters of each target cell based on each target heat generation model.

[0167] The processing module 32 is also used to determine the safety of the target battery pack based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

[0168] By determining the first environmental parameters and performing a first thermal runaway operation on the target cell based on these parameters until thermal runaway occurs, the first state parameters of the target cell are acquired during this process. Based on these parameters, a target heat generation model is determined, and a 3D model of the battery structure is created. A second thermal runaway operation is then performed based on this model. During the second thermal runaway operation, the second state parameters are acquired using the previously determined target heat generation model. Based on these second state parameters, the safety of the target battery pack can be determined. Therefore, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, testing costs are saved, the cell safety prediction system is simplified, and the requirements for basic data in mechanism modeling are reduced. In summary, this method improves the efficiency and accuracy of cell safety prediction.

[0169] As an optional implementation, the first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition of maintaining an insulation state in the target area;

[0170] Processing module 32 is also configured to, before determining the first environmental parameters of the target area by determining module 31,

[0171] Perform a charging operation on the target cells until each target cell is fully charged;

[0172] Identify multiple first measurement points associated with the target battery cell;

[0173] The first measuring point is used to obtain the temperature parameters of each target cell;

[0174] And, after determining the first environmental parameters of the target area by the determining module 31, the processing module 32 performs a first thermal runaway operation on the target cell according to the first environmental parameters until the target cell experiences thermal runaway, including the following specific methods:

[0175] Determine the first environmental parameters of the target area, and perform the first thermal runaway operation on the target cell based on the first environmental parameters;

[0176] Based on the temperature parameters corresponding to each of the first measuring points, determine whether the target cell has experienced thermal runaway.

[0177] If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

[0178] By pre-charging the target cell to full charge before the first thermal runaway operation and identifying multiple first measurement points for acquiring temperature parameters, preparations for the first thermal runaway operation are completed. Simultaneously, based on the determined first environmental parameters, an adiabatic environment is created for the first thermal runaway operation. The first thermal runaway operation is then performed on the target cell within this adiabatic environment. The first environmental parameters are adjusted based on the actual state of the target cell during the first thermal runaway operation until the target cell actually experiences thermal runaway. This ensures the effectiveness and practicality of the first thermal runaway operation process. During the first thermal runaway operation, relevant parameters of the target cell during charging to the point of overcharging and thermal runaway can be successfully acquired, providing effective basic data for the target heat generation model. In summary, the target heat generation model can be determined through an actual thermal runaway operation, and then the safety of the target battery pack can be determined based on the target heat generation model through a simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanistic modeling, thus improving the overall efficiency and accuracy of cell safety prediction.

[0179] As an optional implementation, the first state parameters include one or more of the cell surface temperature, charging current, and cell voltage. The target heat generation model includes a target overcharge model. The processing module 32 determines the specific method of the target heat generation model corresponding to each target cell based on the first state parameters, including:

[0180] Based on the first state parameters, establish a single cell overcharge model corresponding to each target cell, and determine the third state parameters in each single cell overcharge model.

[0181] Among them, the single cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell.

[0182] Parameter optimization is performed on each third state parameter to obtain the target state parameter. Based on the target state parameter and the overcharge model of each individual cell, the target overcharge model corresponding to each target cell is determined.

[0183] By using the first state parameters, an overcharge model for each target cell can be established. Within this model, a third state parameter requiring optimization is determined. Based on the data characteristics of the third state parameter, a corresponding optimization process is executed to obtain the target state parameters, thereby determining the target overcharge model. This improves the effectiveness and efficiency of establishing the target overcharge model. The target heat generation model can be determined through a single actual thermal runaway operation, and the safety of the target battery pack can be determined based on the target overcharge model through a simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanism modeling, thus improving the overall efficiency and accuracy of cell safety prediction.

[0184] As an optional implementation, the processing module 32 optimizes each third state parameter to obtain the target state parameter in the following ways:

[0185] Determine the target limits and target order of magnitude for each third state parameter;

[0186] Based on the target order of magnitude of each third state parameter, determine the gradient of the state parameter change corresponding to each third state parameter;

[0187] Within the target boundary, parameter adjustments are performed on each third state parameter based on the gradient of the state parameter change corresponding to each third state parameter.

[0188] Under different values ​​of each third state parameter, the measured value of the cell surface temperature corresponding to each target cell is determined, as well as the calculated value of the cell surface temperature corresponding to each target cell obtained from the single cell overcharge model.

[0189] The first thermal runaway initiation temperature is determined based on the measured value, the second thermal runaway initiation temperature is determined based on the calculated value, the difference between the first and second thermal runaway initiation temperatures is determined based on the first and second thermal runaway initiation temperatures, and the sum of squares of the difference is determined based on the measured and calculated values.

[0190] Under the condition that the sum of squares of the difference is less than a preset sum of squares threshold and / or the difference in thermal runaway initiation temperature is less than a preset difference threshold, the alternative parameter values ​​for the third state parameter are determined, and the target state parameter is determined from the alternative parameter values.

[0191] By analyzing the parameter limits and magnitude distribution of the third state parameters, an optimization gradient is determined. Based on this gradient, each third state parameter is modified. Through grid optimization, the measured surface temperature of the target cell under different values ​​of the third state parameters, along with the calculated surface temperature obtained from the single-cell overcharge model, are determined. Based on the measured and calculated values, the first and second thermal runaway initiation temperatures are determined, thus obtaining candidate parameters for the third state parameters. The target state parameters are then selected from these candidate parameters to determine the target overcharge model. This improves the effectiveness and efficiency of establishing the target overcharge model. The target heat generation model can be determined through a single actual thermal runaway operation, and the safety of the target battery pack can be determined through a simulated thermal runaway operation. This saves testing costs, simplifies the cell safety prediction system, and reduces the requirements for basic data in mechanism modeling, thereby improving the overall efficiency and accuracy of cell safety prediction.

[0192] As an optional implementation, the processing module 32 establishes a structural model of the target battery pack and specifies the method for performing the second thermal runaway operation on the structural model, including...

[0193] Determine the electrical and mechanical component structures of the target battery pack, and establish a structural model of the target battery pack based on the electrical and mechanical component structures;

[0194] The electrical component structure includes the battery cell structure and the connector structure;

[0195] Based on the target overcharge model of each target cell, a first heat generation model corresponding to the cell structure is established; and, the ohmic heat generation corresponding to the connecting bus structure is determined, and a second heat generation model is established; and, the convective heat transfer coefficient and radiative emissivity corresponding to the mechanical component structure are determined, and a third heat generation model is established.

[0196] Based on the target charging time and target charging current, the structural model is simulated to overcharge in order to perform a second thermal runaway operation and determine the thermal runaway conditions;

[0197] The thermal runaway condition is associated with the first heat generation model, the second heat generation model, and the third heat generation model, and is used to indicate the thermophysical conditions corresponding to the preset safety requirements for the safety of the target battery pack.

[0198] By modeling the actual structure of the target battery cell and determining the corresponding heat generation formula and thermal runaway conditions, and simulating overcharging based on the target charging time and current, a second thermal runaway operation is performed. During this process, second state parameters can be obtained from the determined target heat generation model, and the safety of the target battery pack can be determined based on these parameters. Therefore, by determining the target heat generation model through one actual thermal runaway operation and then determining the safety of the target battery pack through one simulated thermal runaway operation, testing costs are saved, the battery cell safety prediction system is simplified, and the requirements for basic data in mechanism modeling are reduced. In summary, this method improves the efficiency and accuracy of battery cell safety prediction.

[0199] Example 3

[0200] This application also provides an electronic device, including:

[0201] At least one processor; and

[0202] A memory that is communicatively connected to at least one processor; wherein,

[0203] The memory stores instructions that can be executed by at least one processor to enable the at least one processor to perform the method as in any embodiment.

[0204] This application also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method as described in any of the embodiments.

[0205] Please refer to Figure 3, which is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. As shown in Figure 3, the electronic device may include:

[0206] The device includes a processor 291 and a memory 292 storing executable program code; it may also include a communication interface 293 and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via the bus 294. The communication interface 293 can be used for information transmission. The processor 291 is coupled to the memory 292, and the processor 291 can call logical instructions (executable program code) in the memory 292 to execute the method of any of the above embodiments.

[0207] Furthermore, the logic instructions in the aforementioned memory 292 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0208] The memory 292, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, thereby implementing the methods in the above-described method embodiments.

[0209] The memory 292 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 292 may include high-speed random access memory and may also include non-volatile memory.

[0210] This invention also provides a computer-readable storage medium storing computer-executable instructions, which, when invoked, are used to implement the method in any of the embodiments.

[0211] This invention also discloses a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform the steps of the method described in any embodiment.

[0212] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0213] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including 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 storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0214] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0215] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for predicting the safety of battery cells, characterized in that, The method includes: A first environmental parameter of the target area is determined, and a first thermal runaway operation is performed on the target cell based on the first environmental parameter until the target cell experiences thermal runaway; and, during the execution of the first thermal runaway operation, a first state parameter of the target cell is acquired. The target battery cell is at a preset overcharge level; Based on the first state parameter, a target heat generation model corresponding to each target cell is determined; wherein, the target heat generation model is used to indicate the heat generation of each target cell under preset operating parameters; A structural model of the target battery pack is established, and a second thermal runaway operation is performed on the structural model; and, during the execution of the second thermal runaway operation, a second state parameter of each target cell is determined according to each target heat generation model. The safety of the target battery pack is determined based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

2. The method according to claim 1, characterized in that, The first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition that the target area is kept in an insulation state; The method further includes determining a first environmental parameter of the target area and performing a first thermal runaway operation on the target cell based on the first environmental parameter until the target cell experiences thermal runaway. Perform a charging operation on the target cells until each target cell is fully charged. Determine multiple first measurement points associated with the target battery cell; The first measuring point is used to obtain the temperature parameters of each target battery cell; And, the step of determining the first environmental parameters of the target area, and performing a first thermal runaway operation on the target cell based on the first environmental parameters, until the target cell experiences thermal runaway, includes: Determine the first environmental parameters of the target area, and perform a first thermal runaway operation on the target cell based on the first environmental parameters; Based on the temperature parameters corresponding to each of the first measuring points, determine whether the target cell has experienced thermal runaway. If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

3. The method according to claim 1, characterized in that, The first state parameters include one or more of the cell surface temperature, charging current, and cell voltage. The target heat generation model includes a target overcharge model. Determining the target heat generation model corresponding to each target cell based on the first state parameters includes: Based on the first state parameter, an overcharge model for each target cell is established, and a third state parameter is determined in each cell overcharge model; wherein, the cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell. Parameter optimization is performed on each of the third state parameters to obtain target state parameters, and target overcharge models corresponding to each target cell are determined based on the target state parameters and the overcharge models of each individual cell.

4. The method according to claim 3, characterized in that, The step of optimizing each of the third state parameters to obtain the target state parameters includes: Determine the target limits and target orders of magnitude for each of the third state parameters; Based on the target order of magnitude of each of the third state parameters, determine the gradient of the state parameter change corresponding to each of the third state parameters; Within the target limit, parameter adjustments are performed on each of the third state parameters according to the state parameter change gradient corresponding to each of the third state parameters; Under different values ​​of the third state parameters, the measured value of the cell surface temperature corresponding to each target cell is determined, and the calculated value of the cell surface temperature corresponding to each target cell is obtained by calculating the single cell overcharge model. The first thermal runaway initiation temperature is determined based on the measured value, the second thermal runaway initiation temperature is determined based on the calculated value, the difference between the thermal runaway initiation temperatures is determined based on the first thermal runaway initiation temperature and the second thermal runaway initiation temperature, and the sum of squares of the difference is determined based on the measured value and the calculated value. The candidate parameter values ​​for the third state parameter are determined under the condition that the sum of squares of the difference is less than a preset sum of squares threshold, and / or the difference in thermal runaway initiation temperature is less than a preset difference threshold, and the target state parameter is determined from the candidate parameter values.

5. The method according to claim 3, characterized in that, The step of establishing a structural model of the target battery pack and performing a second thermal runaway operation on the structural model includes: establishing a structural model of the target battery pack and performing a second thermal runaway operation on the structural model, including: The electrical component structure and mechanical component structure of the target battery pack are determined, and a structural model of the target battery pack is established based on the electrical component structure and the mechanical component structure. The electrical component structure includes a battery cell structure and a connector bus structure; Based on the target overcharge model of each target cell, a first heat generation model corresponding to the cell structure is established; And, determine the ohmic heat generation corresponding to the connecting row structure and establish a second heat generation model; and determine the convective heat transfer coefficient and radiative emissivity corresponding to the mechanical component structure and establish a third heat generation model; Based on the target charging time and target charging current, the structural model is simulated to overcharge in order to perform a second thermal runaway operation and determine the thermal runaway conditions; The thermal runaway condition is associated with the first heat generation model, the second heat generation model, and the third heat generation model, and is used to indicate the thermophysical conditions corresponding to the preset safety requirements for the safety of the target battery pack.

6. A battery cell safety prediction device, characterized in that, The device includes: The determination module is used to determine the first environmental parameters of the target area; The processing module is configured to perform a first thermal runaway operation on the target cell according to the first environmental parameters until the target cell experiences thermal runaway; and to acquire the first state parameters of the target cell during the execution of the first thermal runaway operation. The processing module is further configured to determine a target heat generation model corresponding to each of the target cells based on the first state parameters; wherein the target heat generation model is used to indicate the heat generation of each of the target cells under preset operating parameters; The processing module is further configured to establish a structural model of the target battery pack and perform a second thermal runaway operation on the structural model; and, during the execution of the second thermal runaway operation, determine the second state parameters of each target cell according to each target heat generation model. The processing module is further configured to determine the safety of the target battery pack based on the second state parameter; wherein the second state parameter is used to indicate the thermal runaway status of each target cell.

7. The apparatus according to claim 6, characterized in that, The first environmental parameter includes an insulation parameter, which is used to indicate the environmental parameters under the condition that the target area is kept in an insulation state; The processing module is further configured to, before the determining module determines the first environmental parameters of the target area, Perform a charging operation on the target cells until each target cell is fully charged. Determine multiple first measurement points associated with the target battery cell; The first measuring point is used to obtain the temperature parameters of each target battery cell; And, the specific method by which the processing module performs a first thermal runaway operation on the target cell according to the first environmental parameters after the determining module determines the first environmental parameters of the target area, until the target cell experiences thermal runaway, includes: Determine the first environmental parameters of the target area, and perform a first thermal runaway operation on the target cell based on the first environmental parameters; Based on the temperature parameters corresponding to each of the first measuring points, determine whether the target cell has experienced thermal runaway. If the target cell does not experience thermal runaway, the first environmental parameter is adjusted according to the preset environmental parameter change gradient until the target cell experiences thermal runaway.

8. The apparatus according to claim 6, characterized in that, The first state parameters include one or more of the cell surface temperature, charging current, and cell voltage. The target heat generation model includes a target overcharge model. The processing module determines the specific method of the target heat generation model corresponding to each target cell based on the first state parameters, including: Based on the first state parameter, establish a single cell overcharge model corresponding to each target cell, and determine the third state parameter in each single cell overcharge model. The single-cell overcharge model includes an electrochemical reaction heat generation model and a decomposition reaction heat generation model, and the third state parameter is related to the degree of overcharge of the corresponding cell. Parameter optimization is performed on each of the third state parameters to obtain target state parameters, and target overcharge models corresponding to each target cell are determined based on the target state parameters and the overcharge models of each individual cell.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-5.

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