An electric vehicle whole vehicle thermal runaway simulation method and system, and a storage device

Abstract

The present application relates to the technical field of whole vehicle thermal runaway, in particular to a kind of electric vehicle whole vehicle thermal runaway simulation method, system and storage device, including the required simulation of the power battery corresponding one-dimensional model of power battery is constructed;According to the one-dimensional model of power battery, set the various thermal runaway trigger operating conditions corresponding to the power battery, and under different thermal runaway trigger operating conditions, simulate the power battery thermal runaway simulation test, and calculate the battery thermal runaway data corresponding to the power battery under thermal runaway;Battery thermal runaway data is fitted and processed, corresponding fitting curve is formed, and the fitting curve is written as a preset format file;The three-dimensional model corresponding to the whole vehicle is constructed;According to three-dimensional model, battery thermal runaway data and the fitting curve written as a preset format file, the calculation of the simulation test of the whole vehicle thermal runaway corresponding to electric vehicle is carried out, and the corresponding whole vehicle thermal runaway simulation analysis result corresponding to electric vehicle is obtained.

Description

Technical Field

[0001] This invention relates to the field of vehicle thermal runaway technology, specifically to a method, system, and storage device for simulating thermal runaway in electric vehicles. Background Technology

[0002] Safety is a key factor in the widespread adoption of electric vehicles, and thermal runaway of the power battery is a major risk affecting electric vehicle safety. Thermal runaway can not only lead to battery performance degradation but also trigger fires or explosions, threatening the safety of passengers and the surrounding environment. Therefore, research on thermal runaway in electric vehicles is crucial.

[0003] Traditional simulations of thermal runaway in electric vehicles mainly employ real-world testing methods. However, electric vehicle testing is large-scale, involves complex testing scenarios, is uncontrollable, and is costly.

[0004] To address the aforementioned issues, existing electric vehicle thermal runaway simulations employ simulation methods. While simulation significantly reduces experimental costs and enhances the adaptability of the experimental process, existing simulation methods often fail to fully consider the specific structure of the power battery, chemical reaction mechanisms, and complex heat transfer processes, resulting in low simulation prediction accuracy and an inability to accurately reflect the actual situation.

[0005] Therefore, there is an urgent need for a method, system, and storage device for simulating thermal runaway of electric vehicles, which can achieve high accuracy and precision in simulating thermal runaway of electric vehicles. Summary of the Invention

[0006] One of the objectives of this invention is to provide a method, system, and storage device for simulating thermal runaway of an electric vehicle, which can achieve high accuracy and precision in simulating thermal runaway of an electric vehicle.

[0007] To achieve the above objectives, a method for simulating thermal runaway of an electric vehicle is provided, comprising the following steps:

[0008] S1. Based on the actual battery cell model and cell parameters corresponding to the power battery to be simulated, construct a one-dimensional model of the power battery corresponding to the power battery to be simulated based on the various model components in the battery library.

[0009] S2. Based on the one-dimensional model of the power battery corresponding to the power battery to be simulated, set up various thermal runaway triggering conditions for the power battery, and simulate the thermal runaway simulation test of the power battery under different thermal runaway triggering conditions, and calculate the battery thermal runaway data corresponding to the power battery under thermal runaway; the battery thermal runaway data includes heat generation data and gas generation data.

[0010] S3. Fit the heat production data and gas production data to form the corresponding fitting curve, and compile the fitting curve into a preset format file.

[0011] S4. Based on the actual results and dimensions of the electric vehicle where the power battery is installed, construct a three-dimensional model of the entire vehicle.

[0012] S5. Based on the three-dimensional model of the vehicle, the thermal runaway data of the power battery under thermal runaway, and the fitting curve compiled into a preset format file, perform simulation tests on the thermal runaway of the electric vehicle and obtain the simulation analysis results of the thermal runaway of the electric vehicle.

[0013] The technical principles and effects of this solution are as follows: Based on the actual battery cell model and parameters, and various model components in the battery library, a one-dimensional model of the required power battery is constructed. This method ensures that the battery model accurately reflects the physical and chemical characteristics of the actual battery. It can quickly construct corresponding models for different types of batteries (such as lithium-ion and lithium iron phosphate), demonstrating strong adaptability. After completing the construction of the one-dimensional power battery model, various thermal runaway triggering conditions are set. By setting multiple thermal runaway triggering conditions, including overcharge, over-discharge, short circuit, and external heating, the simulation ensures that all possible extreme situations are covered. Thermal runaway simulation experiments are conducted under different conditions to obtain detailed heat generation and gas generation data, providing rich basic data for subsequent analysis.

[0014] Then, the heat generation and gas generation data are fitted to form a fitting curve, ensuring that the data is smooth and representative. The fitting curve is compiled into a preset format file, which facilitates import into the 3D vehicle simulation model, improving the efficiency and consistency of data processing.

[0015] Subsequently, based on the actual structure and dimensions of the electric vehicle with the power battery installed, a three-dimensional model of the entire vehicle was constructed to ensure that the simulation environment was as close to reality as possible. Combining the thermal runaway data and fitted curves of the power battery, simulation experiments were conducted to calculate the thermal runaway of the entire electric vehicle, achieving the coupling of battery thermal runaway gas generation and vehicle combustion. The final simulation analysis results of the entire vehicle's thermal runaway provide a comprehensive safety assessment.

[0016] This solution fully considers the battery's structure and heat transfer mechanism by combining a one-dimensional model of the power battery, a three-dimensional model of the vehicle, and a preset format file corresponding to the power battery. It not only realizes the simulation of thermal runaway across the entire chain from individual battery cells to the whole vehicle level, but also improves the realism of the vehicle thermal runaway simulation and significantly enhances the prediction accuracy of the vehicle thermal runaway simulation. In other words, it can achieve high accuracy and precision in the simulation of thermal runaway of electric vehicles.

[0017] Furthermore, the thermal runaway triggering conditions corresponding to the power battery set in S2 include:

[0018] Under various thermal runaway triggering conditions, the thermal properties, initial conditions, and thermal runaway triggering conditions of the positive and negative electrode materials, electrolyte, and separator in the power battery are defined. The thermal properties include thermal conductivity and specific heat capacity; the initial conditions include temperature and pressure; and the thermal runaway triggering conditions include the application of a temperature boundary.

[0019] Beneficial effects: In this scheme, by precisely setting the thermal property parameters of the power battery, the simulation results are ensured to realistically reflect the thermal behavior of the battery under different operating conditions. Uniform initial conditions ensure comparability and consistency between different simulation tests. Diverse triggering conditions cover almost all possible extreme operating conditions, ensuring the simulation results have broad applicability.

[0020] Furthermore, S3 includes:

[0021] S30. Based on the heat generation data and gas generation data of the power battery under different thermal runaway triggering conditions, identify the gas components and corresponding temperature data released by the power battery under thermal runaway under different thermal runaway triggering conditions.

[0022] S31. Based on the identified gas component data and corresponding temperature data under a certain thermal runaway triggering condition, identify and classify each gas component and its corresponding temperature data, and fit the gas production rate-reaction temperature curve corresponding to each gas component.

[0023] S32. Based on the fitted gas production rate-reaction temperature curve for each gas component, compile the corresponding gas production rate-reaction temperature curve into a UDF file corresponding to a certain thermal runaway triggering condition.

[0024] Beneficial Effects: This approach correlates identified gas components with their corresponding temperature data, ensuring that the generation of each gas matches the temperature conditions at which it occurs. This provides a deeper understanding of the gas generation mechanism during battery thermal runaway and helps identify potential safety risks. Appropriate mathematical models (such as polynomial fitting and exponential fitting) are used to fit the relationship between the gas generation rate and reaction temperature for each gas component, forming a gas generation rate-reaction temperature curve. The fitted gas generation rate-reaction temperature curves for each gas component are then compiled into user-defined function (UDF) files for easy import into Fluent or other simulation software. UDF files can be directly applied to whole-vehicle thermal runaway simulations, reducing data conversion and processing time and improving simulation efficiency.

[0025] Furthermore, S5 includes:

[0026] S50. Based on the constructed three-dimensional model of the vehicle, define the combustible materials corresponding to each component of the vehicle in the three-dimensional model.

[0027] S51. Divide the three-dimensional model after defining the combustible material into computational domain meshes to form the computational domain meshes corresponding to the three-dimensional model.

[0028] S52. Based on the preset physical model calculation formula, calculate the physical model corresponding to each computing domain grid.

[0029] S53. Based on the UDF file under a certain thermal runaway triggering condition, define the thermal runaway boundary conditions of the whole vehicle corresponding to the three-dimensional model;

[0030] S54. After defining the corresponding vehicle thermal runaway boundary conditions, perform simulation tests on the vehicle thermal runaway corresponding to the electric vehicle, and obtain the simulation analysis results of the vehicle thermal runaway corresponding to the electric vehicle under the corresponding thermal runaway triggering conditions.

[0031] Beneficial Effects: In this scheme, by defining the combustible materials of each component of the vehicle in the 3D model, dividing the computational domain mesh, determining the physical model, and establishing the thermal runaway boundary conditions for the entire vehicle, the simulation model is ensured to realistically reflect the combustion characteristics of each component, improving the reliability of the simulation results. Simultaneously, the division of the computational domain mesh balances computational efficiency and accuracy, reducing unnecessary waste of computational resources. It helps capture subtle changes in complex structures, improving simulation accuracy. A suitable physical model is calculated, ensuring that the simulation results accurately reflect the actual situation.

[0032] Furthermore, the formula for calculating the minimum grid size in each computational domain grid corresponding to the three-dimensional model in S51 is as follows:

[0033]

[0034] In the formula, Q is the heat release rate of the fire source; g is the acceleration due to gravity; ρ ∞ For air density, c p T is the specific heat capacity of air. ∞ The ambient air temperature.

[0035] Beneficial effects: By considering multiple dimensions, the calculation of the minimum mesh size is made more scientific and reliable, and the subtle differences in the simulation of thermal runaway of the whole vehicle are captured quickly, thus improving the accuracy of the simulation results.

[0036] Furthermore, the preset physical model calculation formula is as follows:

[0037]

[0038] In the formula, ρ is the gas density, V is the velocity vector, V=(u,v,w), t is the simulation time, p is the pressure, g is the gravitational acceleration, T is the viscous stress tensor, and h is the specific enthalpy; Let Y be a volumetric heat source, q be the radiative heat flux vector, Φ be the dissipation function, and Y be the volumetric heat source. i D represents the mass fraction of component i; i Let be the diffusion coefficient of component i; The percentage of a component generated or consumed per unit volume is given by T, where T is the gas temperature; R is the universal gas constant, and M is the molecular weight of the gas. i Let be the molecular weight of component i.

[0039] Beneficial effects: Through calculations using physical models, complex physical phenomena such as turbulence, combustion, and heat transfer can be captured, improving the accuracy of simulation results. Precise modeling of multiphysics fields ensures that simulations can capture critical thermal runaway phenomena, identify potential safety hazards in advance, and provide important basis for designing safer and more reliable electric vehicles.

[0040] The present invention also provides a simulation system for thermal runaway of an electric vehicle, using the above-described simulation method for thermal runaway of an electric vehicle.

[0041] The present invention also provides a thermal runaway simulation storage medium for electric vehicles, wherein a computer program is stored on the storage medium, and the computer program, when executed by a processor, implements the aforementioned thermal runaway simulation method for electric vehicles. Attached Figure Description

[0042] Figure 1 This is a flowchart of the electric vehicle thermal runaway simulation method in Embodiment 1 of the present invention;

[0043] Figure 2 This is a simulated distribution diagram of the thermal runaway smoke from the entire vehicle at a certain moment in Embodiment 1 of the present invention. Detailed Implementation

[0044] The following detailed description illustrates the specific implementation method:

[0045] Example 1

[0046] A simulation method for thermal runaway of an electric vehicle, basically as follows: Figure 1 As shown, it includes the following steps:

[0047] S1. Based on the actual battery cell model and parameters corresponding to the power battery to be simulated, and based on the various model components in the battery library, construct a one-dimensional model of the power battery to be simulated. In this embodiment, the one-dimensional model of the power battery includes key components such as battery cell, electrolyte, positive and negative electrodes, and separator.

[0048] S2. Based on the one-dimensional model of the power battery corresponding to the power battery to be simulated, set various thermal runaway triggering conditions for the power battery, and simulate the thermal runaway simulation test of the power battery under different thermal runaway triggering conditions, and calculate the battery thermal runaway data corresponding to the power battery under thermal runaway; the battery thermal runaway data includes heat generation data and gas generation data; in this embodiment, the heat generation data and gas generation data are used as boundary conditions for the whole vehicle thermal runaway simulation, but these data need to be rewritten.

[0049] The thermal runaway triggering conditions corresponding to the power battery set in S2 include:

[0050] Under various thermal runaway triggering conditions, the thermophysical parameters, initial conditions, and thermal runaway triggering conditions corresponding to the positive and negative electrode materials, electrolyte, and separator in the power battery are defined. The thermophysical parameters include thermal conductivity and specific heat capacity; the initial conditions include temperature and pressure; and the thermal runaway triggering conditions include the application of a temperature boundary. In this embodiment, the corresponding thermal runaway triggering conditions can also be simulated by combining the corresponding electrochemical model, thermal model, and chemical reaction kinetic model of the power battery.

[0051] S3. Fit the heat production data and gas production data to form the corresponding fitting curve, and compile the fitting curve into a preset format file.

[0052] S3 includes:

[0053] S30. Based on the heat generation data and gas generation data of the power battery under different thermal runaway triggering conditions, identify the gas components and corresponding temperature data released by the power battery under thermal runaway under different thermal runaway triggering conditions.

[0054] S31. Based on the identified gas component data and corresponding temperature data under a certain thermal runaway triggering condition, identify and classify each gas component and its corresponding temperature data, and fit the gas production rate-reaction temperature curve corresponding to each gas component.

[0055] S32. Based on the fitted gas generation rate-reaction temperature curve corresponding to each gas component, compile the corresponding gas generation rate-reaction temperature curve into a UDF file corresponding to a certain thermal runaway triggering condition. In this embodiment, in order to make the corresponding heat generation data and gas generation data serve as boundary conditions for three-dimensional vehicle thermal runaway simulation, it is necessary to identify each gas component corresponding to each thermal runaway triggering condition and associate the corresponding temperature with the gas component to form a gas generation rate-reaction temperature curve corresponding to each gas component, and then compile it into a UDF file suitable for three-dimensional vehicle thermal runaway simulation under the corresponding thermal runaway triggering condition.

[0056] S4. Based on the actual results and dimensions of the electric vehicle with the power battery installed, construct a three-dimensional model of the entire vehicle. In this embodiment, during the modeling process of the three-dimensional model of the entire vehicle, the relevant parts of the vehicle body should be simplified to adapt to the working conditions of the simulation software. Note that flammable parts, such as the power battery, seats, interior, and tires, should be retained.

[0057] S5. Based on the three-dimensional model of the vehicle, the thermal runaway data of the power battery under thermal runaway, and the fitting curve compiled into a preset format file, perform simulation tests on the thermal runaway of the electric vehicle and obtain the simulation analysis results of the thermal runaway of the electric vehicle.

[0058] S5 includes:

[0059] S50. Based on the constructed 3D model of the entire vehicle, define the combustible materials corresponding to each component of the vehicle in the 3D model. In this embodiment, common combustible materials inside the vehicle include plastics, fabrics, natural leather, rubber, etc.; among which, plastic parts can be further subdivided into polyethylene plastics, polyurethane plastics, etc. Different materials have different properties and different combustion conditions. Find the corresponding material in the corresponding material library for definition or directly define its parameters. Of course, in practical applications, to simplify the geometric model, similar combustible materials with gaps are simplified into continuous watertight bodies, and non-combustible materials are merged into continuous watertight bodies for simulation.

[0060] S51. Divide the three-dimensional model after defining the combustible material into computational domain meshes to form various computational domain meshes corresponding to the three-dimensional model. In this embodiment, in order to balance the requirements of ensuring the accuracy of the simulation and reducing the number of meshes, multiple computational domains are also generated when dividing the computational domain meshes, such as atmospheric environment, polyethylene rate, and polyurethane plastic. The VOF method is used to assign materials to the computational domains other than atmospheric environment to complete phase boundary capture.

[0061] The formula for calculating the minimum grid size in each computational domain grid corresponding to the three-dimensional solid model in S51 is as follows:

[0062]

[0063] In the formula, Q is the heat release rate of the fire source; g is the acceleration due to gravity; ρ ∞ For air density, c p T is the specific heat capacity of air. ∞ The ambient air temperature.

[0064] S52. Based on the preset physical model calculation formula, calculate the physical model corresponding to each computing domain grid.

[0065] The preset physical model calculation formula is as follows:

[0066]

[0067]

[0068] In the formula, ρ is the gas density, V is the velocity vector, V=(u,v,w), t is the simulation time, p is the pressure, g is the gravitational acceleration, T is the viscous stress tensor, and h is the specific enthalpy; Let Y be a volumetric heat source, q be the radiative heat flux vector, Φ be the dissipation function, and Y be the volumetric heat source. i D represents the mass fraction of component i; i Let be the diffusion coefficient of component i; The percentage of a component generated or consumed per unit volume is given by T, where T is the gas temperature; R is the universal gas constant, and M is the molecular weight of the gas. i Let be the molecular weight of component i. In this embodiment, during the actual simulation, the gas generation result of the one-dimensional simulation of battery thermal runaway is used as the boundary condition for the three-dimensional simulation of the whole vehicle. The finite element analysis then involves the combustion propagation of thermal runaway gas generation and the combustion propagation of combustibles in the whole vehicle. This involves not only gas-phase combustion but also the entire process of solid combustion—melting-pyrolysis-gas-phase combustion. Therefore, a suitable physical model needs to be set. Specifically, for the simulation of gas-phase combustion, a finite rate model (Species Transport) is used. In this model, the chemical reaction mechanism can be customized, and the combustion mechanism is generally simplified before use. The reaction rate, as a source term, is calculated in the chemical component transport equation using the Arrhenius equation or the eddy dissipation model.

[0069] The simulation of solid combustion involves the process of melting, pyrolysis, and gas-phase combustion. The entire process of solid combustible combustion within the vehicle is simulated using the melting-solidification model, the Lee model, the VOF multiphase flow model, and the finite-rate model. Specifically, the VOF multiphase flow model is used to capture phase boundaries and distinguish solid fuel regions. Based on the melting-solidification model, the momentum source term of the solid fuel region is frozen, giving it solid-phase properties. The Lee evaporation model is used to simulate the pyrolysis of solid materials to obtain gas-phase fuel, and the finite-rate model is used to simulate gas-phase combustion. Figure 2 This is a simulated distribution diagram of the thermal runaway smoke from the entire vehicle at a certain moment.

[0070] S53. Based on the UDF file under a certain thermal runaway triggering condition, define the thermal runaway boundary conditions of the whole vehicle corresponding to the three-dimensional model;

[0071] S54. After defining the corresponding vehicle thermal runaway boundary conditions, perform simulation tests on the vehicle thermal runaway corresponding to the electric vehicle, and obtain the simulation analysis results of the vehicle thermal runaway corresponding to the electric vehicle under the corresponding thermal runaway triggering conditions.

[0072] This embodiment also discloses an electric vehicle thermal runaway simulation system, which uses the above-described electric vehicle thermal runaway simulation method.

[0073] This embodiment also discloses a thermal runaway simulation storage medium for electric vehicles, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the aforementioned thermal runaway simulation method for electric vehicles.

[0074] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, based on the guidance provided in this application, improve and implement this solution in combination with their own capabilities. Some typical well-known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for simulating thermal runaway of an electric vehicle, characterized in that: Includes the following steps: S1. Based on the actual battery cell model and cell parameters corresponding to the power battery to be simulated, construct a one-dimensional model of the power battery corresponding to the power battery to be simulated based on the various model components in the battery library. S2. Based on the one-dimensional model of the power battery corresponding to the power battery to be simulated, set up various thermal runaway triggering conditions for the power battery, and simulate the thermal runaway simulation test of the power battery under different thermal runaway triggering conditions, and calculate the battery thermal runaway data corresponding to the power battery under thermal runaway; the battery thermal runaway data includes heat generation data and gas generation data. S3. Fit the heat production data and gas production data to form the corresponding fitting curve, and compile the fitting curve into a preset format file. S3 includes: S30. Based on the heat generation data and gas generation data of the power battery under different thermal runaway triggering conditions, identify the gas components and corresponding temperature data released by the power battery under thermal runaway under different thermal runaway triggering conditions. S31. Based on the identified gas component data and corresponding temperature data under a certain thermal runaway triggering condition, identify and classify each gas component and its corresponding temperature data, and fit the gas production rate-reaction temperature curve corresponding to each gas component. S32. Based on the fitted gas production rate-reaction temperature curve corresponding to each gas component, compile the corresponding gas production rate-reaction temperature curve into a UDF file corresponding to a certain thermal runaway triggering condition. S4. Based on the actual results and dimensions of the electric vehicle where the power battery is installed, construct a three-dimensional model of the entire vehicle. S5. Based on the three-dimensional model of the vehicle, the thermal runaway data of the power battery under thermal runaway, and the fitting curve compiled into a preset format file, perform simulation test calculations on the thermal runaway of the electric vehicle and obtain the simulation analysis results of the thermal runaway of the electric vehicle. S5 includes: S50. Based on the constructed three-dimensional model of the vehicle, define the combustible materials corresponding to each component of the vehicle in the three-dimensional model. S51. Divide the three-dimensional model after defining the combustible material into computational domain meshes to form the computational domain meshes corresponding to the three-dimensional model. S52. Based on the preset physical model calculation formula, calculate the physical model corresponding to each computational domain grid; the preset physical model calculation formula includes the continuity equation, momentum equation, energy conservation equation, component transport equation and multi-component ideal gas equation of state. S53. Based on the UDF file under a certain thermal runaway triggering condition, define the thermal runaway boundary conditions of the whole vehicle corresponding to the three-dimensional model; S54. After defining the corresponding vehicle thermal runaway boundary conditions, perform simulation tests on the vehicle thermal runaway corresponding to the electric vehicle, and obtain the simulation analysis results of the vehicle thermal runaway corresponding to the electric vehicle under the corresponding thermal runaway triggering conditions.

2. The method for simulating thermal runaway of an electric vehicle according to claim 1, characterized in that: The thermal runaway triggering conditions corresponding to the power battery set in S2 include: Under various thermal runaway triggering conditions, the thermal properties, initial conditions, and thermal runaway triggering conditions of the positive and negative electrode materials, electrolyte, and separator in the power battery are defined. The thermal properties include thermal conductivity and specific heat capacity; the initial conditions include temperature and pressure; and the thermal runaway triggering conditions include the application of a temperature boundary.

3. The method for simulating thermal runaway of an electric vehicle according to claim 2, characterized in that: The formula for calculating the minimum grid size in each computational domain grid corresponding to the three-dimensional solid model in S51 is as follows: In the formula, The rate of heat release from the heat source; It is the acceleration due to gravity. air density, The specific heat capacity of air, The ambient air temperature.

4. The method for simulating thermal runaway of an electric vehicle according to claim 3, characterized in that: The preset physical model calculation formula is as follows: In the formula, For gas density, It is a velocity vector. = (u, v, w), where t is the simulation time, p is the pressure, g is the gravitational acceleration, T is the viscous stress tensor, and h is the specific enthalpy; Let q be the volumetric heat source and q be the radiative heat flux vector. Let be the dissipation function. The mass fraction of component i; Let be the diffusion coefficient of component i; Here, T represents the rate of formation or consumption of the component per unit volume, T is the gas temperature, R is the universal gas constant, and M is the gas molecular weight. Let be the molecular weight of component i.

5. A simulation system for thermal runaway of an electric vehicle, characterized in that: A simulation method for thermal runaway of an electric vehicle using any one of claims 1 to 4.

6. A thermal runaway simulation storage medium for an electric vehicle, wherein a computer program is stored on the storage medium, characterized in that: When the computer program is executed by the processor, it implements a simulation method for thermal runaway of an electric vehicle as described in any one of claims 1 to 4.

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