Thermal runaway simulation method and device of battery and storage medium

Abstract

The invention provides a thermal runaway simulation method and device of a battery and a storage medium. The thermal runaway simulation method of the battery comprises the following steps: acquiring a battery simulation model of a target battery; performing adiabatic thermal runaway simulation test on the battery simulation model by using the three-dimensional simulation model of the acceleration calorimeter to obtain thermal runaway characteristic data of the battery simulation model; and based on the thermal runaway characteristic data, generating a thermal runaway heat source model of the target battery, and performing thermal runaway simulation processing on the target battery by using the thermal runaway heat source model. According to the embodiment of the invention, the three-dimensional simulation model of the acceleration calorimeter is utilized to carry out the adiabatic thermal runaway simulation test on the battery simulation model to obtain the thermal runaway characteristic data, so that the thermal runaway characteristic data is prevented from being obtained by adopting an actual test mode, the thermal runaway characteristic data is not influenced by external factors in the actual test, and the thermal runaway characteristic data can be accurately measured. Therefore, the accuracy of the thermal runaway heat source model is improved, and the accurate restoration of the real thermal runaway process is realized.

Description

Technical Field

[0001] This application relates to the field of battery technology, specifically to a method, apparatus, and storage medium for simulating thermal runaway of a battery. Background Technology

[0002] The thermal runaway characteristics of a battery are crucial for assessing its thermal safety capabilities, making the acquisition of more accurate thermal runaway characteristic data of great value.

[0003] In related technologies, thermal runaway simulation models can be used to simulate the thermal runaway of batteries. However, current thermal runaway simulation models have low accuracy and do not accurately reproduce the real thermal runaway process. Summary of the Invention

[0004] The embodiments of this application provide a method, apparatus, and storage medium for simulating thermal runaway of a battery, aiming to improve the accuracy of thermal runaway-related models.

[0005] In a first aspect, embodiments of this application provide a method for simulating thermal runaway of a battery, the method comprising:

[0006] Obtain the battery simulation model of the target battery;

[0007] Using a three-dimensional simulation model of an accelerating calorimeter, an adiabatic thermal runaway simulation test was conducted on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model.

[0008] Based on the thermal runaway characteristic data, a thermal runaway heat source model of the target battery is generated, and the thermal runaway heat source model is used to simulate the thermal runaway of the target battery.

[0009] In the embodiments of this application, the three-dimensional simulation model of the accelerating calorimeter is used to perform adiabatic thermal runaway simulation tests on the battery simulation model to obtain thermal runaway characteristic data. This avoids the need to obtain thermal runaway characteristic data through actual testing. In this way, the thermal runaway characteristic data will not be affected by external factors during actual testing, and will therefore be more accurate, thereby improving the accuracy of the thermal runaway heat source model and achieving accurate reproduction of the real thermal runaway process.

[0010] In one embodiment, the process of using a three-dimensional simulation model of an accelerating calorimeter to perform adiabatic thermal runaway simulation tests on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model includes:

[0011] The battery simulation model is placed into the three-dimensional simulation model of the accelerated calorimeter;

[0012] The three-dimensional simulation model of the accelerated calorimeter is controlled to heat the battery simulation model according to a preset temperature rise strategy.

[0013] After the heating treatment is completed, the battery temperature rise rate of the battery simulation model is determined;

[0014] Based on the battery temperature rise rate, the thermal runaway characteristic data of the battery simulation model are determined.

[0015] In the embodiments of this application, the three-dimensional simulation model of the accelerating calorimeter and the battery simulation model are used to conduct simulation tests of adiabatic thermal runaway, avoiding the actual test of adiabatic thermal runaway. Therefore, the thermal runaway characteristic data obtained from the simulation test will not be affected by external factors, thus making it more accurate.

[0016] In one embodiment, determining the thermal runaway characteristic data of the battery simulation model based on the battery temperature rise rate includes:

[0017] Obtain the self-heating threshold pre-associated with the battery simulation model;

[0018] If the battery temperature rise rate is greater than the self-heating threshold, the current battery temperature of the battery simulation model is obtained and used as the self-heating start temperature.

[0019] Based on the self-heating onset temperature, the thermal runaway characteristic data of the battery simulation model are determined.

[0020] In the embodiments of this application, the self-heating onset temperature is determined based on the comparison between the battery temperature rise rate and the self-heating threshold. Since the self-heating onset temperature is determined based on the battery simulation model, the influence of external factors can be avoided, thus making it more accurate.

[0021] In one embodiment, generating a thermal runaway heat source model of the target battery based on the thermal runaway characteristic data includes:

[0022] Multiple heat source test samples are obtained, wherein the heat source test samples include at least one of the positive electrode, negative electrode, separator, and electrolyte of the target battery;

[0023] Determine the sample heat generation amount for each of the heat source test samples;

[0024] Based on the heat generation of the sample, the target heat source sample is determined among the multiple heat source test samples;

[0025] Based on the target heat source sample and the thermal runaway characteristic data, a thermal runaway heat source model for the target battery is generated.

[0026] In the embodiments of this application, the main heat source during thermal runaway is screened from multiple heat source test samples using the sample heat generation amount, and used to generate a thermal runaway heat source model that conforms to the real situation, so that the thermal runaway heat source model can be more accurate.

[0027] In one embodiment, determining the sample heat generation amount of each of the heat source test samples includes:

[0028] The heat flow curve of each heat source test sample was measured using a differential scanning calorimeter.

[0029] Based on the heat flow curve, the sample heat generation of the corresponding heat source test sample is determined.

[0030] In the embodiments of this application, a heat flow curve is obtained by measuring a differential scanning calorimeter, thereby determining the amount of heat generated in the sample and achieving accurate measurement of the amount of heat generated in the sample.

[0031] In one embodiment, determining the target heat source sample among a plurality of heat source test samples based on the sample heat generation includes:

[0032] A first test sample is determined from a plurality of heat source test samples, the first test sample including the positive electrode, negative electrode, separator and electrolyte of the target battery;

[0033] Among the multiple heat source test samples, the heat source test sample other than the target reference sample is used as the second test sample;

[0034] Determine the ratio of the heat generated by each second test sample to the heat generated by the first test sample;

[0035] Based on a comparison of the ratios between multiple second test samples, the target heat source sample is determined among the multiple second test samples.

[0036] In the embodiments of this application, the target heat source sample among multiple second test samples is determined by comparing the ratio of the sample heat generation amount of each second test sample to the sample heat generation amount of the first test sample, thereby achieving accurate identification of the main heat source during thermal runaway.

[0037] In one embodiment, generating a thermal runaway heat source model of the target battery based on the target heat source sample and the thermal runaway characteristic data includes:

[0038] The heat source equation for generating the target heat source sample includes the correlation between the heat of reaction, enthalpy of reaction, mass of reactants, decomposition rate of reactant concentration, and formation rate of reactant concentration of the heat source formed by the target heat source sample.

[0039] Based on the heat source equation and the thermal runaway characteristic data, a thermal runaway heat source model of the target battery is generated, wherein the thermal runaway initiation temperature of the thermal runaway heat source model is determined based on the self-heating initiation temperature of the battery simulation model in the thermal runaway characteristic data.

[0040] In the embodiments of this application, the thermal runaway initiation temperature of the thermal runaway heat source model is determined based on the self-heating initiation temperature of the battery simulation model, and combined with the heat source equation of the target heat source sample, the determined thermal runaway heat source model can be made more accurate.

[0041] In one embodiment, the heat source equation further includes a pre-exponential factor and an activation energy parameter whose values ​​are to be determined. The step of generating a thermal runaway heat source model for the target battery based on the heat source equation and the thermal runaway characteristic data includes:

[0042] Determine the peak temperature of the exothermic peak in the heat flux curve of the target heat source sample;

[0043] Based on the peak temperature of the exothermic peak and the temperature rise rate of the heat flow curve of the target heat source sample, a fitting process is performed to obtain a fitting equation.

[0044] Based on the fitted equation, the values ​​of the pre-exponential factor and the activation energy parameter are determined;

[0045] Based on the values ​​of the pre-exponential factor and the activation energy parameter, the heat source equation, and the thermal runaway characteristic data, a thermal runaway heat source model for the target battery is generated.

[0046] In the embodiments of this application, the thermal runaway heat source model of the target battery is accurately described by the pre-exponential factor and activation energy parameter, so that the thermal runaway heat source model can accurately reproduce the real thermal runaway process of the target battery.

[0047] Secondly, embodiments of this application provide a battery thermal runaway simulation device, the battery thermal runaway simulation device comprising:

[0048] The acquisition module is used to acquire the battery simulation model of the target battery;

[0049] The simulation module is used to perform adiabatic thermal runaway simulation tests on the battery simulation model using the three-dimensional simulation model of the accelerating calorimeter, and to obtain thermal runaway characteristic data of the battery simulation model.

[0050] The generation module is used to generate a thermal runaway heat source model of the target battery based on the thermal runaway characteristic data, so as to use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0051] Thirdly, embodiments of this application provide a battery thermal runaway simulation device, the battery thermal runaway simulation device including a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the battery thermal runaway simulation method as described in any of the preceding claims.

[0052] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program configured to be executed by a processor to implement the thermal runaway simulation method for a battery as described in any of the preceding claims.

[0053] Fifthly, embodiments of this application provide a computer program product, including a computer program or instructions, which are executed by a processor to implement the thermal runaway simulation method for a battery as described in any of the preceding claims.

[0054] The beneficial effects of the embodiments of this application are as follows:

[0055] In the embodiments of this application, the three-dimensional simulation model of the accelerating calorimeter is used to perform adiabatic thermal runaway simulation tests on the battery simulation model to obtain thermal runaway characteristic data. This avoids the need to obtain thermal runaway characteristic data through actual testing. In this way, the thermal runaway characteristic data will not be affected by external factors during actual testing, and will therefore be more accurate, thereby improving the accuracy of the thermal runaway heat source model and achieving accurate reproduction of the real thermal runaway process. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a schematic flowchart of an embodiment of the battery thermal runaway simulation method provided in this application;

[0058] Figure 2 This is an example graph showing the battery temperature change curve and the measured temperature change curve of the target battery during the simulation test of the battery simulation model provided in the embodiments of this application for adiabatic thermal runaway.

[0059] Figure 3 This is an example diagram showing the simulation results and actual test results of thermal runaway of the target battery provided in the embodiments of this application;

[0060] Figure 4This is an example diagram of the heat flow curves of the target heat source sample provided in the embodiments of this application at multiple different preset temperature rise rates;

[0061] Figure 5 This is an example diagram of the fitting process for the dynamic parameters in the Kissinger equation provided in an embodiment of this application;

[0062] Figure 6 This is an example diagram provided by an embodiment of this application, showing the corresponding values ​​or ranges of some parameters in the thermal runaway heat source model for different heat sources of thermal runaway.

[0063] Figure 7 This is a schematic diagram of an embodiment of the battery thermal runaway simulation device provided in this application;

[0064] Figure 8 This is a schematic diagram of an embodiment of the thermal runaway simulation device for batteries provided in this application.

[0065] in, Figure 2 , Figure 3 , Figure 4 as well as Figure 5 It is a color image so that different objects in the image can be distinguished by using different colors. Detailed Implementation

[0066] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. In addition, in the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0067] This application provides a method, device, and storage medium for simulating thermal runaway in batteries. It utilizes a three-dimensional simulation model of an accelerating calorimeter to perform adiabatic thermal runaway simulation tests on the battery simulation model, obtaining thermal runaway characteristic data. This avoids obtaining thermal runaway characteristic data through actual testing, thus preventing the data from being affected by external factors during actual testing (such as human error, battery detachment from thermocouples, and lower instrument accuracy), resulting in more accurate data. This improves the accuracy of the thermal runaway heat source model and achieves accurate reconstruction of the real thermal runaway process. For specific details, please refer to the following description.

[0068] Firstly, embodiments of this application provide a method for simulating thermal runaway of a battery. Specifically, refer to... Figure 1 , Figure 1This is a schematic flowchart of an embodiment of a method for simulating thermal runaway in a battery. Figure 1 The thermal runaway simulation method for this battery may include:

[0069] 101. Obtain the battery simulation model of the target battery.

[0070] In the embodiments of this application, the target battery refers to the battery that requires thermal runaway simulation, such as an LFP (LiFePO4, lithium iron phosphate) battery. The battery simulation model of the target battery refers to a simulation model in a three-dimensional simulation space that maintains consistency with the target battery in terms of structure, size, material, and performance, for simulation testing. The battery simulation model can be created using three-dimensional simulation software.

[0071] 102. Using the three-dimensional simulation model of the accelerating calorimeter, the adiabatic thermal runaway simulation test of the battery simulation model was carried out to obtain the thermal runaway characteristic data of the battery simulation model.

[0072] In the embodiments of this application, the Accelerating Rate Calorimeter (ARC) is a high-precision thermal analysis instrument that can assess the thermal decomposition behavior and safety risks of chemical substances by monitoring sample temperature, pressure, and thermodynamic parameters in real time in an adiabatic environment. The three-dimensional simulation model of the ARC refers to a simulation model in a three-dimensional simulation space that maintains consistency with the ARC in terms of structure, size, function, and performance, for use in simulation testing. The three-dimensional simulation model of the ARC can be created using three-dimensional simulation software.

[0073] In the embodiments of this application, the simulation test of adiabatic thermal runaway is carried out in the aforementioned three-dimensional simulation space. That is, simulation technology is used to simulate the adiabatic thermal runaway test of the target battery by an accelerated calorimeter, thereby avoiding the influence of external factors on the test results during actual testing and making the test results more accurate.

[0074] The test results of the adiabatic thermal runaway simulation test, i.e., the thermal runaway characteristic data of the battery simulation model. The thermal runaway characteristic data may include, for example, the battery temperature change curve over time during thermal runaway, and the self-heating initiation temperature of the battery simulation model during thermal runaway. The battery temperature change curve over time may include, for example:

[0075]

[0076] The temperature change curve of the cavity over time in the three-dimensional simulation model of the accelerated calorimeter can include, for example:

[0077]

[0078] In this model, the subscript 'arc' represents the 3D simulation model of the accelerating calorimeter, the subscript 'bat' represents the battery simulation model, and h, A, M, C, and T represent the convection coefficient, surface area, mass, specific heat capacity, and temperature, respectively. a This indicates the ambient temperature of the three-dimensional simulation model of the accelerating calorimeter.

[0079] 103. Based on thermal runaway characteristic data, generate a thermal runaway heat source model for the target battery, and use the thermal runaway heat source model to simulate thermal runaway of the target battery.

[0080] In the embodiments of this application, the thermal runaway heat source model of the target battery refers to a functional model used to describe the heat source conditions when the target battery experiences thermal runaway. Using the thermal runaway heat source model to simulate the thermal runaway of the target battery involves simulating the impact of the heat source conditions on the battery simulation model of the target battery, thereby obtaining the thermal runaway simulation results. The thermal runaway simulation results may include, for example, the temperature, morphology, and properties of materials at various locations within the target battery.

[0081] As can be seen from the above embodiments of this application, the three-dimensional simulation model of the accelerating calorimeter is used to conduct adiabatic thermal runaway simulation tests on the battery simulation model to obtain thermal runaway characteristic data. This avoids obtaining thermal runaway characteristic data through actual testing, thus the thermal runaway characteristic data is not affected by external factors during actual testing, and is therefore more accurate, thereby improving the accuracy of the thermal runaway heat source model and achieving accurate reproduction of the real thermal runaway process. Compared with actual testing, simulation testing can also reduce the testing cost and time of thermal runaway and improve the testing efficiency. The thermal runaway simulation results obtained using the thermal runaway heat source model are unique and are not affected by the external environment. In addition, the establishment of the thermal runaway heat source model can quickly analyze the thermal runaway characteristics of batteries of the same system, greatly improving production efficiency.

[0082] In some embodiments of this application, the specific process of simulation testing for adiabatic thermal runaway is described. Specifically, using a three-dimensional simulation model of an accelerating calorimeter, an adiabatic thermal runaway simulation test is performed on a battery simulation model to obtain thermal runaway characteristic data of the battery simulation model. This process may include: placing the battery simulation model into the three-dimensional simulation model of the accelerating calorimeter to simulate the operation of placing the target battery into the accelerating calorimeter during actual testing; controlling the three-dimensional simulation model of the accelerating calorimeter to heat the battery simulation model according to a preset temperature rise strategy, which can be the temperature rise strategy of the accelerating calorimeter during actual adiabatic thermal runaway testing; waiting for a preset time after the heating treatment to allow the temperature of the three-dimensional simulation model of the accelerating calorimeter to be consistent with that of the battery simulation model and reach thermal equilibrium, and determining the battery temperature rise rate of the battery simulation model during the waiting period; and determining the thermal runaway characteristic data of the battery simulation model based on the battery temperature rise rate, thereby completing the adiabatic thermal runaway simulation test.

[0083] In some embodiments of this application, determining the thermal runaway characteristic data of the battery simulation model based on the battery temperature rise rate may include: obtaining a self-heating threshold pre-associated with the battery simulation model, which is a threshold pre-set for the battery temperature rise rate, i.e., the detection sensitivity used to detect whether the battery simulation model is self-heating; if the battery temperature rise rate is greater than the self-heating threshold, it indicates that the battery temperature rise rate is large, which is the battery temperature rise caused by self-heating during thermal runaway of the battery simulation model. Therefore, the current battery temperature of the battery simulation model can be obtained and used as the self-heating start temperature; the thermal runaway characteristic data of the battery simulation model is determined based on the self-heating start temperature. For example, the thermal runaway characteristic data may include the self-heating start temperature, a segment of the battery temperature change curve of the battery simulation model over time (e.g., a segment after the time point where the self-heating start temperature is located), etc.

[0084] In some embodiments of this application, the above-described temperature rise strategy is illustrated. Specifically, the temperature rise strategy includes a pre-set heating termination temperature (e.g., 50°C) and a temperature gradient (e.g., 5°C). During the heating process of the battery simulation model according to the temperature rise strategy, after the battery simulation model is placed into the three-dimensional simulation model of the accelerating calorimeter, the three-dimensional simulation model of the accelerating calorimeter is first controlled to heat at a preset first temperature rate (e.g., 0.00357°C / second) so that the cavity temperature of the three-dimensional simulation model of the accelerating calorimeter is greater than or equal to the heating termination temperature. Then, the three-dimensional simulation model of the accelerating calorimeter is controlled to continue heating at a preset second temperature rate (e.g., 0.00714°C / second) so that the current battery temperature of the battery simulation model is greater than or equal to the heating termination temperature. At this point, the three-dimensional simulation model of the accelerating calorimeter is controlled to stop heating, i.e., the heating process ends.

[0085] After the heating process is completed, a preset time (e.g., 40 minutes) is allowed to be waited for the 3D simulation model of the accelerated calorimeter to reach the same temperature and thermal equilibrium as the battery simulation model. During this waiting period, the battery temperature rise rate of the battery simulation model is determined. If a battery temperature rise rate greater than or equal to the self-heating threshold (e.g., 0.0003℃ / second) exists within the preset time, it indicates that the battery simulation model has begun to self-heat. Therefore, the current battery temperature of the battery simulation model can be obtained and used as the self-heating initiation temperature, thereby determining the thermal runaway characteristics data of the battery simulation model. Subsequent heating of the 3D simulation model using the accelerated calorimeter is no longer necessary.

[0086] If the battery temperature rise rate is less than the self-heating threshold within a preset time period, the sum of the heating termination temperature and the temperature gradient is used as the updated heating termination temperature. Then, the process returns to controlling the three-dimensional simulation model of the accelerated calorimeter to heat at a preset first temperature rate so that the cavity temperature of the three-dimensional simulation model of the accelerated calorimeter is greater than or equal to the updated heating termination temperature. This process continues until a battery temperature rise rate greater than or equal to the self-heating threshold exists within the preset time period, thus obtaining the thermal runaway characteristic data of the battery simulation model.

[0087] In some embodiments of this application, reference is made to Figure 2 , Figure 2 An example graph showing the battery temperature change curve during adiabatic thermal runaway simulation test of a battery simulation model and the measured temperature change curve of the target battery. Figure 2 In the simulation test of adiabatic thermal runaway, the battery temperature change curve of the battery simulation model is shown as the dashed line "simulation," while the measured temperature change curve of the target battery is shown as the solid line "test." It can be seen that the simulation test results of the battery simulation model under adiabatic thermal runaway are basically consistent with the measured results of the target battery, indicating that the simulation test results are valid.

[0088] In some embodiments of this application, since there are numerous physical changes and chemical reactions in the target battery during thermal runaway, and the heat source situation is complex, the main heat sources during thermal runaway can be screened from the target battery and used to generate a thermal runaway heat source model to simplify the thermal runaway heat source model. Specifically, generating a thermal runaway heat source model of the target battery based on thermal runaway characteristic data may include: obtaining multiple heat source test samples, wherein the heat source test samples refer to samples that need to be tested to determine whether they are the main heat sources during thermal runaway. The heat source test samples include at least one of the target battery's positive electrode (Pos, Positive), negative electrode (neg, Negative), separator (sep, Separator), and electrolyte (ele, Electrolyte). Multiple heat source test samples may be, for example, negative electrode, negative electrode + positive electrode + separator, negative electrode + electrolyte, positive electrode + positive electrode + separator, negative electrode + electrolyte, positive electrode + positive electrode + separator, negative electrode + electrolyte, positive electrode + negative electrode + separator, negative electrode + positive electrode + separator, negative electrode + ... Examples of heat source test samples include: electrode + electrolyte, electrolyte, negative electrode + positive electrode + separator + electrolyte, etc.; determine the sample heat generation amount of each heat source test sample; based on the sample heat generation amount, determine the target heat source sample among multiple heat source test samples, for example, multiple heat source test samples can be ranked from large to small according to the sample heat generation amount, and the top-ranked preset number of heat source test samples can be used as target heat source samples; based on the target heat source sample and thermal runaway characteristic data, generate a thermal runaway heat source model of the target battery, so that the target heat source sample can be used as the main heat source during thermal runaway, so as to generate a thermal runaway heat source model that conforms to the real situation, and the thermal runaway heat source model can be more accurate.

[0089] In some embodiments of this application, the method for determining the sample heat generation is described. Specifically, determining the sample heat generation of each heat source test sample may include: using a differential scanning calorimeter (DSC), each heat source test sample is made into a coin cell (button cell) for measurement, and the heat flow curve of each heat source test sample is obtained. The differential scanning calorimeter is used to measure the relationship between temperature and heat flow related to the internal thermal transformation of the material. Therefore, the heat flow curve may include, for example, the relationship between the heat flow rate of the corresponding heat source test sample and the temperature. Based on the heat flow curve, the sample heat generation of the corresponding heat source test sample is determined. For example, the sample heat generation of the corresponding heat source test sample can be determined by identifying the area of ​​the exothermic peak in the heat flow curve and then determining the sample heat generation of the corresponding heat source test sample based on the area of ​​the exothermic peak. The specific calculation process can be referred to related technologies and is not limited here.

[0090] In some embodiments of this application, the method for determining the target heat source sample is described. Specifically, determining the target heat source sample among multiple heat source test samples based on the sample heat generation can include: determining a first test sample among the multiple heat source test samples, wherein the first test sample represents a reference standard for the other heat source test samples, for example, the first test sample may include the positive electrode, negative electrode, separator, and electrolyte of the target battery, that is, the first test sample includes all components of the other heat source test samples; among the multiple heat source test samples, heat source test samples other than the target reference sample are used as second test samples; determining the ratio of the sample heat generation of each second test sample to the sample heat generation of the first test sample, the ratio being, for example, a percentage; and determining the target heat source sample among the multiple second test samples based on a comparison of the ratios of the multiple second test samples, thereby making the determined target heat source sample more accurate.

[0091] In some embodiments of this application, examples of the sample heat generation of multiple second test samples and the above-mentioned ratios are shown in Table 1 below:

[0092] Table 1

[0093] Second test sample Sample heat generation (joules per gram) The above ratio negative electrode 490 83％ positive electrode 40 7％ Negative electrode + Positive electrode + Separator 190 32％ negative electrode + electrolyte 890 151％ Positive electrode + electrolyte 200 34％ electrolyte 202 34％

[0094] The heat generation of the first test sample can be, for example, 590 joules per gram.

[0095] In some embodiments of this application, determining a target heat source sample from among multiple second test samples based on a comparison of ratios among multiple second test samples may include: determining a third test sample and a fourth test sample from among the multiple second test samples, wherein the components in the fourth test sample are increased relative to the components in the third test sample, and at least one component is added; determining the difference between the ratio of the third test sample and the ratio of the fourth test sample; if the difference is greater than a preset difference threshold, it indicates that the difference is large, and the increased components in the fourth test sample relative to the third test sample have a greater impact on the heat generation, thus the fourth test sample can be determined as the target heat source sample, thereby making the determined target heat source sample more accurate.

[0096] Taking the data shown in Table 1 as an example, it can be seen that in multiple second test samples, the aforementioned ratio for the negative electrode is 83%, while the aforementioned ratio for the negative electrode + electrolyte is 151%, showing a significant difference between the two ratios. Furthermore, the aforementioned ratio for the positive electrode is 7%, while the aforementioned ratio for the positive electrode + electrolyte is 34%, indicating that the electrolyte has a significant impact on heat generation during thermal runaway. Therefore, the negative electrode + electrolyte, positive electrode + electrolyte, and electrolyte samples can be used as target heat source samples, respectively.

[0097] In some embodiments of this application, generating a thermal runaway heat source model for a target battery based on a target heat source sample and thermal runaway characteristic data may include: generating a heat source equation for the target heat source sample, the heat source equation including the correlation between the reaction heat term, reaction enthalpy term, reactant mass term, decomposition rate of reactant concentration, and formation rate of reactant concentration of the heat source formed by the target heat source sample, wherein the specific formula of the heat source equation can be set according to the target heat source sample, and the formula form of the heat source equation for the target heat source sample may also be different when different target heat source samples exist. If multiple target heat source samples exist at the same time, the heat source equation for each target heat source sample can be generated separately; generating a thermal runaway heat source model for the target battery based on the heat source equation and thermal runaway characteristic data, wherein the thermal runaway initiation temperature of the thermal runaway heat source model is determined based on the self-heating initiation temperature of the battery simulation model in the thermal runaway characteristic data, for example, the self-heating initiation temperature can be directly used as the thermal runaway initiation temperature of the thermal runaway heat source model, thereby using the thermal runaway initiation temperature as a constraint condition for the thermal runaway heat source model, making the thermal runaway heat source model more refined and accurate.

[0098] In some embodiments of this application, heat source equations are described by way of example. Specifically, heat source equations may include:

[0099]

[0100] Among them, Q x (t) represents the reaction heat of the heat source formed by the target heat source sample, ΔH x For the enthalpy of reaction, m x Mass of reactants The decomposition rate is the concentration of reactants. The regeneration rate of reactant concentration is T(t), where T(t) is the battery temperature in the battery simulation model. onset，x This is the thermal runaway initiation temperature. (C) x，0 This represents the normalized initial concentration of the reactants. A x Let nx,1 and nx,2 be the pre-exponential factors whose values ​​are to be determined, exp be the natural exponential function, and E be the reaction order. a,x Let be the activation energy parameter whose value is to be determined, and R be the gas constant. x (t) represents the reaction correction term, which can be set based on actual needs and is not limited here.

[0101] The thermal runaway heat source model provided above has been applied in practice, and its simulation results for thermal runaway of the target battery are basically consistent with the actual thermal runaway test results. Therefore, the accuracy of the thermal runaway heat source model can meet the actual needs and achieve accurate reproduction of the real thermal runaway process.

[0102] In some embodiments of this application, reference is made to Figure 3 , Figure 3 This is an example graph showing the simulation results and experimental results of thermal runaway for the target battery. Figure 3 In the figure, the simulated thermal runaway results of the target battery are shown as dashed lines (simulation), while the measured thermal runaway results are shown as solid lines (test). It can be seen that the simulated and measured thermal runaway results are in good agreement, and the constructed thermal runaway heat source model can accurately describe the characteristics of thermal runaway occurring in the target battery in the accelerating calorimeter.

[0103] In some embodiments of this application, the pre-exponential factor and activation energy parameter to be determined in the heat source equation can be determined based on the heat flow curve of the target heat source sample. Specifically, generating a thermal runaway heat source model of the target battery based on the heat source equation and thermal runaway characteristic data may include: determining the peak temperature of the exothermic peak in the heat flow curve of the target heat source sample, for example, by referring to... Figure 4 , Figure 4 This is an example graph showing the heat flow curves of a target heat source sample at multiple preset temperature rise rates, such as 5, 10, 15, and 20 °C / min. Figure 4 It can be seen that each heat flow curve has three distinct peaks ①, ②, and ③. According to the thermal runaway chain reaction, ①, ②, and ③ correspond to the decomposition of the SEI (solid electrolyte interface), the reaction between the negative electrode and the electrolyte, and the reaction of PVDF (polyvinylidene difluoride), respectively. The temperature of each peak is the exothermic peak temperature. Based on the exothermic peak temperature and the temperature rise rate of the heat flow curve of the target heat source sample, a fitting process is performed to obtain a fitting equation. Based on the fitting equation, the values ​​of the pre-exponential factor and activation energy parameter are determined. According to the heat source equation, the values ​​of the pre-exponential factor and activation energy parameter, and the thermal runaway characteristic data, a thermal runaway heat source model of the target battery is generated. For example, by substituting the values ​​of the pre-exponential factor and activation energy parameter into the heat source equation, and combining the constraints based on the thermal runaway characteristic data, the generated thermal runaway heat source model can be made more refined and accurate.

[0104] The fitting process can be implemented using the Kissinger equation, which may include, for example:

[0105]

[0106] Where ln represents the natural logarithm, β represents the temperature rise rate of the heat flux curve, and T p The peak temperature of the exothermic peak in the heat flux curve is represented by A, which represents the pre-exponential factor, and E represents the peak temperature of the exothermic peak. a R represents the activation energy parameter, and R represents the gas constant.

[0107] Reference Figure 5 , Figure 5 This is an example plot showing the fitting treatment of the kinetic parameters (i.e., pre-exponential factors and activation energy parameters) in the Kissinger equations. Figure 5 The x-coordinates of the four coordinate points are the reciprocals of the peak temperatures of the exothermic peaks of the four heat flux curves (i.e., 1 / T). p The ordinates of the four coordinate points are respectively the ordinates of the four heat flux curves. from Figure 5 It can be seen that these four coordinate points are basically on the same straight line. Therefore, the slope of the line equation (i.e., -E) can be obtained by fitting the line. a / R) and intercept (i.e. This allows us to determine the pre-exponential factor A and the activation energy parameter E. a .

[0108] In some embodiments of this application, in the heat source equation, Q x (t) represents the reaction heat of the heat source formed by the target heat source sample. To determine the thermal runaway heat source model, it is necessary to determine... Where, ΔH x It can be determined from the heat flux profile, for example, based on the area of ​​the exothermic peak (i.e., the integral of the peak value in the heat flux profile). E a A and m can be determined based on the fitting process of the Kissinger equation described above. x This refers to the mass of the heat source components, i.e., the battery's design parameters. Other parameters in the thermal runaway heat source model include... Figure 6 As shown, Figure 6 The diagram shows the corresponding values ​​or ranges of other parameters in the thermal runaway heat source model for different heat sources of thermal runaway.

[0109] Secondly, referring to Figure 7 Based on the battery thermal runaway simulation method described in the above embodiments, this application provides a battery thermal runaway simulation device 700, which is used to execute the steps in any embodiment of the battery thermal runaway simulation method described above. For example, the battery thermal runaway simulation device 700 may include:

[0110] The acquisition module 701 is used to acquire the battery simulation model of the target battery;

[0111] Simulation module 702 is used to perform adiabatic thermal runaway simulation tests on the battery simulation model using the three-dimensional simulation model of the accelerating calorimeter, and obtain thermal runaway characteristic data of the battery simulation model.

[0112] The generation module 703 is used to generate a thermal runaway heat source model of the target battery based on thermal runaway characteristic data, so as to use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0113] Thirdly, embodiments of this application provide a battery thermal runaway simulation device, which integrates any of the battery thermal runaway simulation devices provided in the embodiments of this application. The battery thermal runaway simulation device includes a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the battery thermal runaway simulation method as described in any of the above embodiments, for example:

[0114] Obtain a battery simulation model of the target battery; use the three-dimensional simulation model of the accelerating calorimeter to conduct adiabatic thermal runaway simulation test on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model; based on the thermal runaway characteristic data, generate a thermal runaway heat source model of the target battery, and use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0115] Fourthly, embodiments of this application provide a battery thermal runaway simulation device, which integrates any of the battery thermal runaway simulation devices provided in embodiments of this application. For example... Figure 8 As shown, it illustrates a schematic diagram of the structure of the battery thermal runaway simulation device involved in the embodiments of this application. Specifically:

[0116] The thermal runaway simulation device for this battery may include components such as a processor 801 with one or more processing cores, a memory 802 with one or more computer-readable storage media, a power supply 803, and an input unit 804. Those skilled in the art will understand that... Figure 8 The battery thermal runaway simulation device structure shown does not constitute a limitation on the battery thermal runaway simulation device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0117] The processor 801 is the control center of the battery thermal runaway simulation device. It connects to various parts of the device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 802, and by calling data stored in the memory 802, it performs various functions and processes data of the battery thermal runaway simulation device, thereby providing overall monitoring of the device. Optionally, the processor 801 may include one or more processing cores; preferably, it may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may not be integrated into the processor 801.

[0118] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the battery thermal runaway simulation device, etc. In addition, the memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0119] The battery thermal runaway simulation device also includes a power supply 803 that supplies power to the various components. Preferably, the power supply 803 can be logically connected to the processor 801 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 803 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0120] The thermal runaway simulation device for the battery may also include an input unit 804, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0121] Although not shown, the battery thermal runaway simulation device may also include a display unit, etc., which will not be described in detail here. Specifically, in the embodiments of this application, the processor 801 in the battery thermal runaway simulation device loads the executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 runs the application programs stored in the memory 802 to realize various functions, such as:

[0122] Obtain a battery simulation model of the target battery; use the three-dimensional simulation model of the accelerating calorimeter to conduct adiabatic thermal runaway simulation test on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model; based on the thermal runaway characteristic data, generate a thermal runaway heat source model of the target battery, and use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0123] Fifthly, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc. The computer-readable storage medium stores a computer program configured to be executed by a processor to implement the battery thermal runaway simulation method as described in any of the preceding claims, for example:

[0124] Obtain a battery simulation model of the target battery; use the three-dimensional simulation model of the accelerating calorimeter to conduct adiabatic thermal runaway simulation test on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model; based on the thermal runaway characteristic data, generate a thermal runaway heat source model of the target battery, and use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0125] Sixthly, embodiments of this application provide a computer program product, including a computer program or instructions, which are executed by a processor to implement the battery thermal runaway simulation method as described in any of the preceding claims, for example:

[0126] Obtain a battery simulation model of the target battery; use the three-dimensional simulation model of the accelerating calorimeter to conduct adiabatic thermal runaway simulation test on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model; based on the thermal runaway characteristic data, generate a thermal runaway heat source model of the target battery, and use the thermal runaway heat source model to perform thermal runaway simulation processing on the target battery.

[0127] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for simulating thermal runaway of a battery, characterized in that, The method for simulating thermal runaway of the battery includes: Obtain the battery simulation model of the target battery; Using a three-dimensional simulation model of an accelerating calorimeter, an adiabatic thermal runaway simulation test was conducted on the battery simulation model to obtain thermal runaway characteristic data of the battery simulation model. Based on the thermal runaway characteristic data, a thermal runaway heat source model of the target battery is generated, and the thermal runaway heat source model is used to simulate the thermal runaway of the target battery.

2. The method for simulating thermal runaway of a battery as described in claim 1, characterized in that, The three-dimensional simulation model using an accelerating calorimeter is used to conduct adiabatic thermal runaway simulation test on the battery simulation model, obtaining thermal runaway characteristic data of the battery simulation model, including: The battery simulation model is placed into the three-dimensional simulation model of the accelerated calorimeter; The three-dimensional simulation model of the accelerated calorimeter is controlled to heat the battery simulation model according to a preset temperature rise strategy. After the heating treatment is completed, the battery temperature rise rate of the battery simulation model is determined; Based on the battery temperature rise rate, the thermal runaway characteristic data of the battery simulation model are determined.

3. The battery thermal runaway simulation method as described in claim 2, characterized in that, The step of determining the thermal runaway characteristic data of the battery simulation model based on the battery temperature rise rate includes: Obtain the self-heating threshold pre-associated with the battery simulation model; If the battery temperature rise rate is greater than the self-heating threshold, the current battery temperature of the battery simulation model is obtained and used as the self-heating start temperature. Based on the self-heating onset temperature, the thermal runaway characteristic data of the battery simulation model are determined.

4. The method for simulating thermal runaway of a battery as described in claim 1, characterized in that, The step of generating a thermal runaway heat source model for the target battery based on the thermal runaway characteristic data includes: Multiple heat source test samples are obtained, wherein the heat source test samples include at least one of the positive electrode, negative electrode, separator, and electrolyte of the target battery; Determine the sample heat generation amount for each of the heat source test samples; Based on the heat generation of the sample, the target heat source sample is determined among the multiple heat source test samples; Based on the target heat source sample and the thermal runaway characteristic data, a thermal runaway heat source model for the target battery is generated.

5. The method for simulating thermal runaway of a battery as described in claim 4, characterized in that, Determining the sample heat generation amount of each heat source test sample includes: The heat flow curve of each heat source test sample was measured using a differential scanning calorimeter. Based on the heat flow curve, the sample heat generation of the corresponding heat source test sample is determined.

6. The method for simulating thermal runaway of a battery as described in claim 4, characterized in that, The step of determining the target heat source sample among multiple heat source test samples based on the sample heat generation includes: A first test sample is determined from a plurality of heat source test samples, the first test sample including the positive electrode, negative electrode, separator and electrolyte of the target battery; Among the multiple heat source test samples, the heat source test sample other than the target reference sample is used as the second test sample; Determine the ratio of the heat generated by each second test sample to the heat generated by the first test sample; Based on a comparison of the ratios between multiple second test samples, the target heat source sample is determined among the multiple second test samples.

7. The method for simulating thermal runaway of a battery as described in claim 4, characterized in that, The step of generating a thermal runaway heat source model for the target battery based on the target heat source sample and the thermal runaway characteristic data includes: The heat source equation for generating the target heat source sample includes the correlation between the heat of reaction, enthalpy of reaction, mass of reactants, decomposition rate of reactant concentration, and formation rate of reactant concentration of the heat source formed by the target heat source sample. Based on the heat source equation and the thermal runaway characteristic data, a thermal runaway heat source model of the target battery is generated, wherein the thermal runaway initiation temperature of the thermal runaway heat source model is determined based on the self-heating initiation temperature of the battery simulation model in the thermal runaway characteristic data.

8. The method for simulating thermal runaway of a battery as described in claim 7, characterized in that, The heat source equation also includes a pre-exponential factor and activation energy parameter whose values ​​are to be determined. The step of generating a thermal runaway heat source model for the target battery based on the heat source equation and the thermal runaway characteristic data includes: Determine the peak temperature of the exothermic peak in the heat flux curve of the target heat source sample; Based on the peak temperature of the exothermic peak and the temperature rise rate of the heat flow curve of the target heat source sample, a fitting process is performed to obtain a fitting equation. Based on the fitted equation, the values ​​of the pre-exponential factor and the activation energy parameter are determined; Based on the values ​​of the pre-exponential factor and the activation energy parameter, the heat source equation, and the thermal runaway characteristic data, a thermal runaway heat source model for the target battery is generated.

9. A battery thermal runaway simulation device, characterized in that, The battery thermal runaway simulation device includes a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the battery thermal runaway simulation method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program configured to be executed by a processor to implement the thermal runaway simulation method for the battery as described in any one of claims 1 to 8.

Images