A battery acupuncture thermal runaway simulation method, device and medium

Abstract

The present invention provides a battery acupuncture thermal runaway simulation method, device and medium, the method comprising: using an internal short circuit equivalent circuit model, a charge state estimation model, an electrochemical model, a rare substance transfer model and a thermal runaway model as control equations of a lithium battery geometric simulation model; iteratively solving the control equations of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; using the battery thermal runaway simulation data to predict the thermal behavior of the lithium battery; in this way, using the internal short circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the rare substance transfer model and the thermal runaway model as the control equations of the lithium battery geometric simulation model is equivalent to considering the coupling effects of the electric field, the chemical field and the thermal field at the same time, so that the electrochemical reaction inside the battery and the transfer process of ions and electrons can be accurately simulated, and the temperature change of the lithium battery geometric simulation model can be determined, thereby improving the accuracy of the prediction of the thermal runaway diffusion of the lithium battery.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery acupuncture thermal runaway simulation method, device, and medium. Background Art

[0002] As a widely used energy storage and power device, lithium-ion batteries play an important role in electric vehicles, portable electronic devices, and energy storage systems due to their high energy density, long service life, no memory effect, and fast charge and discharge. However, lithium-ion batteries are prone to internal short circuits under abuse conditions, such as high temperature, overcharging, and puncture, which can lead to thermal runaway. Thermal runaway can not only cause a sharp drop in battery performance, but may even cause fires or explosions, posing a major threat to personal safety and property.

[0003] It can be seen that internal short circuit of the battery is one of the main reasons for thermal runaway of lithium batteries. Especially during the acupuncture process, the invasion of the needle will cause a variety of short circuit modes inside the battery (such as direct short circuit of positive and negative active materials, short circuit of positive active materials-negative current collector, etc.), which will not only affect the magnitude of the short circuit current, but also change the heat distribution and temperature gradient inside the battery. However, the existing simulation methods are difficult to fully reflect the complex changes inside the battery during the acupuncture process.

[0004] Therefore, in order to more accurately simulate the thermal runaway process of lithium-ion batteries with internal short circuits caused by needle puncture, it is necessary to develop a thermal runaway simulation method based on the characteristics of internal short circuits caused by needle puncture, so as to accurately predict and analyze the thermal runaway diffusion process of lithium-ion batteries from internal short circuit to thermal runaway in a real environment. Summary of the invention

[0005] In response to the problems existing in the prior art, the embodiments of the present invention provide a battery puncture thermal runaway simulation method, device and medium to solve or partially solve the technical problem that the simulation method in the prior art cannot fully reflect the internal changes of the lithium battery during the puncture process, and thus cannot accurately predict the thermal runaway spread of the lithium battery.

[0006] A first aspect of the present invention provides a battery thermal runaway simulation method, the method comprising:

[0007] Constructing an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model, and a thermal runaway model; using the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model, and the thermal runaway model as control equations of a lithium battery geometric simulation model;

[0008] When the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, it triggers the iterative solution of the control equation of the lithium battery geometric simulation model to obtain the battery thermal runaway simulation data; the internal short circuit equivalent circuit model is used to provide the short circuit current required for each iterative solution;

[0009] The battery thermal runaway simulation data is used to predict the thermal behavior of the lithium battery in a real environment.

[0010] In the above scheme, the internal short-circuit equivalent circuit model includes: a short-circuit current determination model, a battery terminal voltage determination model and a battery internal resistance determination model; wherein,

[0011] The short-circuit current determination model is:

[0012] The battery terminal voltage determination model is: V(t)=U(SOC)-I short ×R cell ;

[0013] The battery internal resistance determination model is: in,

[0014] The V(t) is the terminal voltage of the geometric simulation model of the lithium battery; the U(SOC) is the open circuit voltage of the geometric simulation model of the lithium battery; the I short is the short-circuit current of the lithium battery geometric simulation model; cell is the internal resistance of the geometric simulation model of the lithium battery; short is the internal resistance of the probe geometric model; cell,ref is the reference resistance value of the lithium battery geometric simulation model at a reference temperature; ξ(T) is a resistance compensation function, and T is the temperature of the lithium battery geometric simulation model at the current iteration.

[0015] In the above scheme, the state of charge estimation model is: in,

[0016] The ISC cond is a step function, the T c is the melting point of the diaphragm of the lithium battery geometric simulation model, T is the temperature of the current iteration of the lithium battery geometric simulation model, and A ec is the pre-exponential factor of the electrochemical reaction, the E ec is the short-circuit activation energy, C is the capacity of the lithium battery geometric simulation model, R is the ideal gas constant, and exp is an exponential function.

[0017] In the above scheme, the electrochemical model includes: the Arrhenius equation, the reaction rate equation and the electrochemical reaction heat generation equation for describing the relationship between the chemical reaction rate constant and the temperature; wherein,

[0018] The Arrhenius equation is:

[0019] The reaction rate equation is: CR = M × [C] n ;

[0020] The electrochemical reaction heat generation equation is: Q exo =CR×ΔH; where

[0021] M is the reaction rate constant, exp is the exponential function, and A ec is the pre-exponential factor of the electrochemical reaction, the E ec is the short-circuit activation energy, R is the ideal gas constant, T is the temperature of the current iteration of the lithium battery geometry simulation model, CR is the reaction rate, C is the lithium ion concentration, n is the reaction order, and Q exo is the electrochemical reaction heat, and ΔH is the unit molar reaction heat.

[0022] In the above scheme, the dilute species transfer model is: in,

[0023] The C is the lithium ion concentration, the D is the diffusion coefficient, is the rate of change of the lithium ion concentration over time, is the second-order derivative of the lithium ion concentration in space.

[0024] In the above scheme, the thermal runaway model includes: a total heat generation model, a total heat dissipation model and a battery temperature determination model; wherein,

[0025] The total heat generation model is:

[0026] The total heat dissipation model is: Q diss =Q rad +Q conv ;

[0027] The battery temperature determination model is: in,

[0028] The Q gen is the total heat generation of the lithium battery geometric simulation model, the Q exo is the electrochemical reaction heat, the Q cell is the Joule heat generated by the internal resistance of the lithium battery geometric simulation model, and the Q ISCis the Joule heat generated by the internal short circuit of the lithium battery geometric simulation model, and the Q diss is the total heat dissipation of the lithium battery geometric simulation model, the Q conv Thermal convection heat, the Q rad is the heat radiation heat, ρ is the battery density of the lithium battery geometric simulation model, ▽ is the gradient operator, and C p is the specific heat capacity, T is the temperature of the current iteration of the lithium battery geometric simulation model, λ is the battery thermal conductivity, and T d is the decomposition temperature.

[0029] In the above scheme, the battery thermal runaway simulation data includes: the temperature and terminal voltage of the geometric simulation model of the lithium battery; the control equation of the geometric simulation model of the lithium battery is iteratively solved to obtain the battery thermal runaway simulation data, including:

[0030] For each iteration, the temperature of the lithium battery geometric simulation model after the previous iteration and the state of charge of the lithium battery geometric simulation model after the previous iteration are obtained; the short-circuit current corresponding to the lithium battery geometric simulation model in the current iteration and the internal resistance of the lithium battery geometric simulation model in the current iteration are determined according to the temperature of the lithium battery geometric simulation model after the previous iteration, the state of charge of the lithium battery geometric simulation model after the previous iteration and the internal short-circuit equivalent circuit model;

[0031] Determine the electrochemical reaction heat according to the temperature of the lithium battery geometric simulation model after the previous iteration, the electrochemical model and the dilute species transfer model, and determine the current temperature of the lithium battery geometric simulation model corresponding to the current iteration according to the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, the electrochemical reaction heat and the thermal runaway model;

[0032] Determine the current state of charge of the lithium battery geometric simulation model at the current iteration according to the current temperature of the lithium battery geometric simulation model corresponding to the current iteration, the short-circuit current corresponding to the lithium battery geometric simulation model at the current iteration, and the state of charge estimation model;

[0033] The terminal voltage of the lithium battery geometric simulation model of the current iteration is determined according to the current state of charge, the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, and the state of charge-open circuit voltage curve function; wherein,

[0034] In the first iteration, the state of charge of the lithium battery geometric simulation model and the temperature of the lithium battery geometric simulation model are preset.

[0035] In the above scheme, the method of determining the terminal voltage of the current iteration of the geometric simulation model of the lithium battery according to the current state of charge, the short-circuit current corresponding to the geometric simulation model of the lithium battery in the current iteration, the internal resistance of the geometric simulation model of the lithium battery in the current iteration, and the state of charge-open circuit voltage curve includes:

[0036] Substituting the current state of charge into the state of charge-open circuit voltage curve function to obtain the open circuit voltage of the lithium battery geometric simulation model of the current iteration;

[0037] The short-circuit current corresponding to the current iteration of the geometric simulation model of the lithium battery, the internal resistance of the current iteration of the geometric simulation model of the lithium battery, and the open-circuit voltage are substituted into the battery terminal voltage determination model to obtain the terminal voltage of the current iteration of the geometric simulation model of the lithium battery.

[0038] A second aspect of the present invention provides a battery acupuncture thermal runaway simulation device, the device comprising:

[0039] A construction unit is used to construct an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model and a thermal runaway model; the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model are used as control equations of a lithium battery geometric simulation model;

[0040] A solving unit is used to trigger iterative solving of the control equation of the lithium battery geometric simulation model when the probe model penetrates into the interior of the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, so as to obtain the battery thermal runaway simulation data; the internal short circuit equivalent circuit model is used to provide the short circuit current required for each iterative solution;

[0041] The prediction unit is used to predict the thermal behavior of the lithium battery in a real environment by using the battery thermal runaway simulation data.

[0042] According to a third aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

[0043] The present invention provides a battery acupuncture thermal runaway simulation method, device and medium, the method comprising: constructing an internal short circuit equivalent circuit model, a charge state estimation model, an electrochemical model, a rare substance transfer model and a thermal runaway model; using the internal short circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the rare substance transfer model and the thermal runaway model as control equations of a lithium battery geometric simulation model; when the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, triggering iterative solution of the control equations of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; the internal short circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the rare substance transfer model and the thermal runaway model are used as control equations of a lithium battery geometric simulation model; when the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, triggering iterative solution of the control equations of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; The equivalent circuit model is used to provide the short-circuit current required for each iterative solution; the battery thermal runaway simulation data is used to predict the thermal behavior of the lithium battery in a real environment; in this way, during the simulation, the internal short-circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model are used as the control equations of the lithium battery geometric simulation model, which is equivalent to taking into account the coupling effects of the electric field, the chemical field and the thermal field at the same time. Therefore, the electrochemical reactions inside the battery and the transfer process of ions and electrons can be accurately simulated, and the temperature changes of the lithium battery geometric simulation model can be more accurately determined, thereby improving the accuracy of the prediction of the thermal runaway diffusion of the lithium battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0045] Figure 1 A schematic diagram of the process of a battery acupuncture thermal runaway simulation method according to an embodiment of the present invention is shown;

[0046] Figure 2 A schematic diagram showing the coupling principle of an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a rare species transfer model, and a thermal runaway model according to an embodiment of the present invention is shown;

[0047] Figure 3 A schematic diagram of a state of charge-open circuit voltage curve according to an embodiment of the present invention is shown;

[0048] Figure 4 A schematic diagram showing the arrangement of temperature probe points inside an experimental lithium battery according to an embodiment of the present invention is shown;

[0049] Figure 5 A schematic diagram of a thermal runaway temperature curve corresponding to a 50% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 3 mm is shown;

[0050] Figure 6 A schematic diagram of a thermal runaway voltage curve corresponding to a 50% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 3 mm is shown;

[0051] Figure 7 A schematic diagram of a thermal runaway temperature curve corresponding to a 25% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 3 mm is shown;

[0052] Figure 8 A schematic diagram of a thermal runaway voltage curve corresponding to a 25% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 3 mm is shown;

[0053] Fig. 9 A schematic diagram of a thermal runaway temperature curve corresponding to a 50% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 6 mm is shown;

[0054] Fig.10 A schematic diagram of a thermal runaway voltage curve corresponding to a 50% SOC lithium battery geometric simulation model when the diameter of the probe model according to an embodiment of the present invention is 6 mm is shown;

[0055] Fig.11 A schematic structural diagram of a battery puncture thermal runaway simulation device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0056] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0057] The present invention provides a battery acupuncture thermal runaway simulation method, such as Figure 1 As shown, the method mainly includes the following steps:

[0058] S110, constructing an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model and a thermal runaway model; using the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model as control equations of a lithium battery geometric simulation model.

[0059] Before constructing the internal short circuit equivalent circuit model, charge state estimation model, electrochemical model, dilute species transfer model and thermal runaway model, it is necessary to construct a lithium battery geometric simulation model according to the actual size and actual parameters of each battery component. The actual size and parameter values ​​of each battery component are shown in Table 1:

[0060] Table 1

[0061]

[0062] Then, an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model and a thermal runaway model are constructed. The internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model are used as the control equations of the lithium battery geometric simulation model. The battery thermal runaway process can be simulated subsequently according to the control equations.

[0063] In the present invention, the internal short-circuit equivalent circuit model includes: a short-circuit current determination model, a battery terminal voltage determination model and a battery internal resistance determination model; wherein,

[0064] The short-circuit current determination model is shown in formula (1):

[0065]

[0066] The battery terminal voltage determination model is shown in formula (2):

[0067] V(t)=U(SOC)-I short ×R cell (2)

[0068] The battery internal resistance determination model is shown in formula (3):

[0069] R cell =R cell,ref ×ξ(T) (3)

[0070]

[0071] Wherein, V(t) is the terminal voltage of the geometric simulation model of the lithium battery; U(SOC) is the terminal voltage of the geometric simulation model of the lithium battery; I short is the short-circuit current of the lithium battery geometry simulation model; R cell is the internal resistance of the lithium battery geometry simulation model; R short is the internal resistance of the probe geometry model; R cell,ref is the reference resistance value of the lithium battery geometry simulation model at the reference temperature, which is 1 mΩ; ξ(T) is the resistance compensation function, which is used to compensate for the resistance drop caused by the increase in temperature, and T is the temperature of the current iteration of the lithium battery geometry simulation model.

[0072] Specifically, it is assumed that all parts of the lithium battery geometric simulation model have the same thermophysical properties and that the thermophysical properties do not change over time. At the same time, the material is isotropic and directly runs through the geometric center of the battery. The model ignores the electrochemical heat of the battery.

[0073] When the internal short circuit occurs, the overall temperature of the battery increases significantly, and the ion diffusion coefficient increases exponentially, resulting in a decrease in the internal resistance of the battery. Considering the temperature dependence of the internal resistance of the battery, assuming that the internal resistance of the battery decreases exponentially, the internal resistance of the lithium battery geometric simulation model can be determined based on the above battery internal resistance model.

[0074] During the internal short circuit process, the state of charge (SOC) of the lithium battery geometric simulation model will change due to the self-discharge of the short circuit point and the increase in the overall temperature of the battery. Then, the SOC of the lithium battery geometric simulation model can be determined based on the state of charge estimation model.

[0075] The state of charge estimation model is shown in formula (5):

[0076]

[0077] Among them, ISC cond is a step function, when ISC cond When T >1, it means that the entire geometric simulation model of the lithium battery is in an internal short circuit; c is the melting point of the diaphragm of the lithium battery geometry simulation model, which is 444.15K; T is the temperature of the current iteration of the lithium battery geometry simulation model, A ec is the pre-exponential factor of the electrochemical reaction, E ec is the short-circuit activation energy, C is the capacity of the lithium battery geometry simulation model, R is the ideal gas constant (molar gas constant), and exp is the exponential function.

[0078] As the temperature inside the lithium battery geometry simulation model rises, the chemical reaction rate inside the battery will also speed up, thus affecting the generation of heat. The electrochemical model includes: the Arrhenius equation used to describe the relationship between the chemical reaction rate constant and temperature, the reaction rate equation, and the electrochemical reaction heat generation equation;

[0079] The Arrhenius equation is shown in formula (7):

[0080]

[0081] M is the reaction rate constant, which determines the speed of a chemical reaction.

[0082] Based on the Arrhenius equation, the reaction rate equation can be determined. The reaction rate equation describes the change of reactant concentration (such as lithium ions) over time. The reaction rate equation is shown in formula (8):

[0083] CR=M×[C] n (8)

[0084] Electrochemical reactions are accompanied by the generation or absorption of heat. Therefore, in the battery thermal runaway simulation, the electrochemical reaction heat needs to be determined. The electrochemical reaction heat generation equation is shown in formula (9):

[0085] Q exo =CR×ΔH (9)

[0086] Where M is the reaction rate constant, exp is the exponential function, and A ec is the pre-exponential factor of the electrochemical reaction, E ec is the short-circuit activation energy, R is the ideal gas constant, which is about 8.314 J / (mol K); T is the temperature of the current iteration of the lithium battery geometry simulation model, CR is the reaction rate, C is the lithium ion concentration, n is the reaction order (can be pre-set), Q exo is the electrochemical reaction heat, and ΔH is the unit molar reaction heat.

[0087] During the electrochemical reaction, it is also necessary to simulate the diffusion process of reactants inside the battery through a dilute species transfer model to achieve heterogeneous simulation of the battery thermal runaway reaction. The dilute species transfer model is the Fick diffusion equation, as shown in formula (10):

[0088]

[0089] C is the lithium ion concentration, and D is the diffusion coefficient, which is a constant representing the ease with which lithium ions diffuse in a particular medium; is the rate of change of lithium ion concentration over time, is the second-order derivative of lithium ion concentration in space, which describes the rate of change of lithium ion concentration in space.

[0090] The heat generated by the electrochemical reaction is calculated in the electrochemical model based on the reaction rate and the unit molar reaction heat, and this heat will be input into the solid heat transfer model as a heat source term. As the exothermic process progresses, the lithium ion concentration will also change. The change in lithium ion concentration calculated in the dilute species transfer model will be fed back to the electrochemical model, affecting the calculation of the reaction rate, thereby coupling the electrochemical model and the dilute species transfer model.

[0091] When the geometric simulation model of the lithium battery is punctured (the probe is inserted into the battery), a short circuit occurs inside, and the positive and negative active materials are interconnected electronically, resulting in a high current density locally and causing a local temperature rise. The impact of the local temperature rise is very significant. If the temperature exceeds the critical value, the electrolyte may begin to decompose and react exothermically, causing the temperature to rise and thus cause thermal runaway.

[0092] After the internal short circuit heat generation occurs in the geometric simulation model of the lithium battery, the temperature at the puncture site rises sharply, causing the solid electrolyte interface (SEI) formed on the surface of the battery's negative electrode to decompose. When the SEI film decomposes, the negative electrode loses protection, and the lithium ions embedded in the negative electrode react with the electrolyte. As the temperature continues to rise, the diaphragm begins to melt, and the positive electrode reacts with the electrolyte, accompanied by the occurrence of self-induced thermal runaway of the electrolyte. After that, the negative electrode reacts with the binder, causing the electrolyte to catch fire, causing the battery to burn, and thus causing thermal runaway.

[0093] Then the thermal runaway model includes: total heat generation model, total heat dissipation model and battery temperature determination model;

[0094] The total heat generation model is shown in formula (11):

[0095]

[0096] In formula (11), if the temperature of the current iteration of the lithium battery geometry simulation model is lower than the critical temperature 473.15K, the internal active substances will not decompose and no decomposition reaction heat Q will be generated. e ; When the temperature of the lithium battery geometry simulation model reaches 473.15K, the internal active substances begin to decompose, and the decomposition reaction heat of the active substances themselves is Q e :

[0097]

[0098] The total heat dissipation model is shown in formula (14):

[0099] Q diss =Q rad +Q conv (14)

[0100] The battery temperature determination model is shown in formula (15):

[0101]

[0102] Q rad =ε×σ×(T 4 -T 4 amb ) (16)

[0103]

[0104] Q conv =h×A×(TT amb ) (19)

[0105] Among them, Q genis the total heat generation of the lithium battery geometry simulation model, Q exo is the electrochemical reaction heat, Q cell is the Joule heat generated by the internal resistance of the lithium battery geometry simulation model, Q ISC is the Joule heat generated by the internal short circuit of the lithium battery geometry simulation model, Q diss is the total heat dissipation of the lithium battery geometry simulation model, Q conv Convection heat, Q rad is the heat radiation heat, ρ is the battery density of the lithium battery geometric simulation model, ▽ is the gradient operator, C p is the specific heat capacity, T is the temperature of the current iteration of the lithium battery geometry simulation model, λ is the battery thermal conductivity, and T d is the decomposition temperature, A e is the pre-exponential factor of the decomposition reaction, E e is the activation energy of the decomposition reaction, H e is the heat released by decomposition of unit mass of electrolyte, W e The total electrolyte content, ε is the emissivity of the geometric simulation model of the lithium battery, σ is the Stefan-Boltzmann constant, T amb is the ambient temperature, h is the air convection heat transfer coefficient, and A is the heat transfer area. d It can be set according to the actual situation of the battery, for example, it can be set to 473.15K.

[0106] S111, when the probe model penetrates into the geometric simulation model of the lithium battery to simulate the thermal runaway caused by the internal short circuit of the battery, it triggers the iterative solution of the control equation of the geometric simulation model of the lithium battery to obtain the battery thermal runaway simulation data; the internal short circuit equivalent circuit model is used to provide the short circuit current required for each iterative solution.

[0107] The present invention can insert the probe model into the interior of the lithium battery geometric simulation model to cause a short circuit, thereby simulating the thermal runaway phenomenon caused by the short circuit inside the battery. The process of simulating and analyzing thermal runaway is equivalent to the process of solving the above control equations, and the solution needs to be implemented through multiple iterations based on a preset time step.

[0108] At each iteration, Figure 2 As shown, the internal short circuit equivalent circuit model 21 can simulate the internal short circuit phenomenon of the battery caused by the probe piercing the interior of the lithium battery geometric simulation model, and output the corresponding short circuit current I short ; Determine the internal resistance R of the lithium battery geometry simulation model according to the short-circuit current and the temperature of the lithium battery geometry simulation model cell , the short-circuit current I short And the internal resistance R of the lithium battery geometry simulation model cell is input into the state of charge estimation model 22; at the same time, the short-circuit current I shortInput to the state of charge estimation model 22 .

[0109] The temperature of the last iteration of the lithium battery geometry simulation model, the electrochemical model 23 and the dilute species transfer model 24 are used to determine the electrochemical reaction heat of the lithium battery geometry simulation model, and the electrochemical reaction heat is transferred to the thermal runaway model 25.

[0110] Thermal runaway model 25 uses the short-circuit current I short , the internal resistance R of the lithium battery geometric simulation model cell The total heat of the lithium battery geometric simulation model is determined by the heat of the electrochemical reaction; the temperature T of the current iteration of the lithium battery geometric simulation model is determined according to the total heat; and the temperature T is transferred to the state of charge estimation model 22.

[0111] The state of charge estimation model 22 is based on the temperature T and the short-circuit current I short Output the current state of charge of the lithium battery geometric simulation model; the internal short-circuit equivalent circuit model 21 determines the terminal voltage of the current iteration lithium battery geometric simulation model according to the current state of charge and the state of charge-open circuit voltage curve.

[0112] This is equivalent to taking into account the coupling effects of electric field, chemical field and thermal field at the same time during simulation. Therefore, the electrochemical reactions, ion and electron transfer processes inside the battery can be accurately simulated, and the temperature changes of the geometric simulation model of the lithium battery can be more accurately determined, thereby improving the accuracy of the prediction of thermal runaway diffusion of lithium batteries.

[0113] Among them, in each iteration, the temperature used in the battery internal resistance model in the current iteration is the temperature of the lithium battery geometric simulation model determined after the previous iteration. In the first iteration, an initial temperature and an initial SOC are set for the lithium battery geometric simulation model.

[0114] In one embodiment, the battery thermal runaway simulation data includes: the temperature and terminal voltage of the lithium battery geometric simulation model; the control equation of the lithium battery geometric simulation model is iteratively solved to obtain the battery thermal runaway simulation data, including:

[0115] For each iteration, the temperature of the lithium battery geometric simulation model after the previous iteration and the state of charge of the lithium battery geometric simulation model after the previous iteration are obtained; the short-circuit current corresponding to the lithium battery geometric simulation model in the current iteration and the internal resistance of the lithium battery geometric simulation model in the current iteration are determined according to the temperature of the lithium battery geometric simulation model after the previous iteration, the state of charge of the lithium battery geometric simulation model after the previous iteration and the internal short-circuit equivalent circuit model;

[0116] Determine the electrochemical reaction heat according to the temperature, electrochemical model and dilute species transfer model of the lithium battery geometric simulation model after the previous iteration, and determine the current temperature of the lithium battery geometric simulation model corresponding to the current iteration according to the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, the electrochemical reaction heat and the thermal runaway model;

[0117] Determine the current state of charge of the lithium battery geometric simulation model of the current iteration according to the current temperature of the lithium battery geometric simulation model corresponding to the current iteration, the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, and the state of charge estimation model;

[0118] The terminal voltage of the current iteration lithium battery geometric simulation model is determined according to the current state of charge, the short-circuit current corresponding to the current iteration lithium battery geometric simulation model, the internal resistance of the current iteration lithium battery geometric simulation model, and the state of charge-open circuit voltage curve function; wherein,

[0119] In the first iteration, the state of charge of the lithium battery geometry simulation model and the temperature of the lithium battery geometry simulation model are preset.

[0120] Specifically, taking the first iteration as an example, in the first iteration, the initial SOC of the lithium battery geometric simulation model is preset, for example, the initial SOC may be 50%; the initial temperature of the lithium battery geometric simulation model is also preset, for example, the initial temperature may be 298.15K.

[0121] Based on the initial temperature, the internal resistance of the lithium battery geometric simulation model at the first iteration can be determined using formulas (3) and (4); then the open circuit voltage of the lithium battery geometric simulation model can be determined based on the initial SOC and the state of charge-open circuit voltage curve; finally, based on the internal resistance of the lithium battery geometric simulation model, the open circuit voltage, and the internal resistance of the probe model (known value), the short-circuit current corresponding to the first iteration can be determined using formula (1). Among them, the state of charge-open circuit voltage curve can be as follows Figure 3 shown.

[0122] Based on the initial temperature, the electrochemical reaction heat is determined using equations (7) to (9).

[0123] The short-circuit current and the internal resistance of the lithium battery geometric simulation model are fed back to the thermal runaway model. The thermal runaway model combines the electrochemical reaction heat, the short-circuit circuit and the internal resistance of the lithium battery geometric simulation model, and uses formula (15) to determine the current temperature of the lithium battery geometric simulation model of the first iteration. The current temperature and short-circuit current are fed back to the state of charge estimation model, and the SOC corresponding to the first iteration is determined based on formula (5). The open circuit voltage of the lithium battery geometric simulation model after the first iteration can be determined based on the SOC corresponding to the first iteration and the state of charge-open circuit voltage curve; finally, the terminal voltage of the lithium battery geometric simulation model after the first iteration is determined based on the open circuit voltage of the lithium battery geometric simulation model after the first iteration and formula (2).

[0124] In each subsequent iteration, the temperature and SOC of the lithium battery geometric simulation model determined in the previous iteration can be further calculated in the same manner as above, and the temperature and terminal voltage of the lithium battery geometric simulation model after each iteration can be finally obtained; that is, the battery thermal runaway simulation data is finally obtained.

[0125] S112, predicting the thermal behavior of the lithium battery in a real environment using the battery thermal runaway simulation data.

[0126] After the battery thermal runaway simulation data is determined, a first curve showing the terminal voltage changing with time and a second curve showing the temperature changing with time can be fitted based on the battery thermal runaway simulation data. The terminal voltage trend can be determined according to the first curve and the temperature spread trend can be determined according to the second curve. The thermal behavior of the lithium battery in a real environment can be predicted based on the terminal voltage trend and the temperature spread trend.

[0127] Furthermore, in order to ensure the simulation accuracy of the battery puncture thermal runaway model and improve the accuracy of battery thermal runaway prediction, the thermal runaway simulation of the lithium battery geometric simulation model was performed at 50% SOC and 25% SOC respectively, and the simulation results were compared with the actual puncture test results.

[0128] In the needle puncture test, the extreme physical damage that the battery may suffer in the real environment was simulated, that is, a steel nail with a diameter of 3mm was used to directly penetrate the center of the battery at a speed of 4mm / s. This operation quickly triggered the thermal runaway reaction inside the battery, causing the temperature inside the battery to rise sharply, accompanied by flames and the release of harmful gases. Once the thermal runaway phenomenon starts, it will quickly spread to other areas of the battery, posing a serious threat to the safety of the entire battery.

[0129] Among them, thermocouple temperature detection points were symmetrically arranged at 20mm, 40mm, 60mm, 80mm, and 100mm away from the acupuncture point as the temperature measurement points in the actual experiment. Figure 4 As shown, the experimental temperature measurement points include: TL 1TL 2 TL 3 TL 4 TL 5 ,TR 1 ,TR 2 ,TR 3 ,TR 4 ,TR 5 Similarly, the same probe points are set at the corresponding positions of the lithium battery geometric simulation model as temperature measurement points during simulation.

[0130] When performing thermal runaway simulation, when the diameter of the probe model is 3 mm, the thermal runaway temperature curve corresponding to the 50% SOC lithium battery geometry simulation model is as follows: Figure 5 As shown, the thermal runaway voltage curve is as follows Figure 6 shown.

[0131] exist Figure 5 In the 50% SOC lithium battery geometric simulation model, the temperature of the TL1 probe point (the probe point 20 mm away from the needle puncture center) reaches a maximum temperature of 1413K at 8s, while the experimental temperature reaches a maximum temperature of 997K at 18s.

[0132] The temperature of the TL3 probe point (60 mm from the puncture center) of the 50% SOC lithium battery geometric simulation model reached a maximum temperature of 1124 K at 16 seconds, while the experimental temperature reached a maximum temperature of 1075 K at 23 seconds. The simulated thermal runaway propagation rate was 7.3 mm / s, while the experimental propagation rate was 8.9 mm / s. The propagation rates were similar, and the temperature rise and temperature drop trends were roughly the same. Figure 5 The simulation TL1 in the simulation is the geometric simulation model of the lithium battery with 50% SOC TL 1 Simulated temperature curve at the probe point, Figure 5 The simulation TL3 in the simulation is a 50% SOC lithium battery geometry simulation model TL 3 Simulated temperature curve at the probe point, Figure 5 The experiment TL1 is a lithium battery TL with a SOC of 50%. 1 Experimental temperature curve at the probe point, Figure 5 The experiment TL3 is a lithium battery TL with a SOC of 50%. 3 Experimental temperature curve at the probe point.

[0133] exist Figure 6 In the figure, before the acupuncture began, the terminal voltage values ​​of the 50% SOC lithium battery geometric simulation model and the experiment were both 3.7V. After the acupuncture began, the terminal voltage of the experiment dropped to 1.06V at 8.4 seconds, while the terminal voltage of the model dropped to 1.06V at 4.1 seconds. Then, the terminal voltage of the experiment dropped to 0V at 14 seconds, while the terminal voltage of the model dropped to 0V at 7 seconds. The voltage drop trend and time of the model are roughly consistent with the experimental data. Figure 6 The experimental code refers to the voltage curve corresponding to the actual experimental process, and the simulation code refers to the voltage curve corresponding to the simulation process.

[0134] When performing thermal runaway simulation, when the diameter of the probe model is 3 mm, the thermal runaway temperature curve corresponding to the 25% SOC lithium battery geometry simulation model is as follows: Figure 7 As shown, the thermal runaway voltage curve is as follows Figure 8 shown.

[0135] from Figure 7 It can be seen that the temperature of the TL1 probe point (the probe point 20 mm away from the puncture center) of the 25% SOC lithium battery geometric simulation model reaches a maximum temperature of 952K at 20s, while the experimental temperature reaches a maximum temperature of 1036K at 22s.

[0136] The temperature of the TL3 probe point (60 mm from the puncture center) of the 25% SOC lithium battery geometric simulation model reached a maximum temperature of 655 K at 21 seconds, while the experimental temperature reached a maximum temperature of 863 K at 23 seconds. The simulated thermal runaway propagation rate was 6.9 mm / s, while the experimental propagation rate was 8.0 mm / s. The propagation rates were similar, and the temperature rise and temperature drop trends were roughly the same. Figure 7 The simulation TL1 in the simulation is the geometric simulation model of the lithium battery with 25% SOC TL 1 Simulated temperature curve at the probe point, Figure 7 The simulation TL3 in the simulation is a 25% SOC lithium battery geometry simulation model TL 3 Simulated temperature curve at the probe point, Figure 7 The experiment TL1 is a lithium battery TL with a SOC of 25%. 1 Experimental temperature curve at the probe point, Figure 7 The experiment TL3 is a lithium battery TL with a SOC of 25%. 3 Experimental temperature curve at the probe point.

[0137] from Figure 8 It can be seen that before the acupuncture began, the terminal voltage values ​​of the 25% SOC lithium battery geometry simulation model and the experiment were both 3.5V. After the acupuncture began, the terminal voltage of the experiment dropped to 1.17V at 9.8 seconds, while the terminal voltage of the model dropped to 1.17V at 7.1 seconds. Then, the terminal voltage of the experiment dropped to 0V at 16 seconds, while the terminal voltage of the model dropped to 0V at 12 seconds. The voltage drop trend and time of the model are roughly consistent with the experimental data. Figure 8 The experimental code refers to the voltage curve corresponding to the actual experimental process, and the simulation code refers to the voltage curve corresponding to the simulation process.

[0138] Furthermore, the present invention is further verified by puncturing a 50% SOC lithium battery geometric simulation model with a probe model of 6 mm. When the diameter of the probe model is 6 mm, the thermal runaway temperature curve corresponding to the 50% SOC lithium battery geometric simulation model is as follows: Fig. 9 As shown, the thermal runaway voltage curve is as follows Fig.10 shown.

[0139] Fig. 9 In the figure, the temperature of the TL1 probe point (the probe point 20 mm away from the puncture center) of the 50% SOC lithium battery geometric simulation model reaches a maximum temperature of 1173K at 6s, while the experimental temperature reaches a maximum temperature of 1084K at 18s.

[0140] The temperature of the TL3 probe point (60 mm from the puncture center) of the 50% SOC lithium battery geometric simulation model reached a maximum temperature of 1306 K at 11 seconds, while the experimental temperature reached a maximum temperature of 1028 K at 25 seconds. Fig. 9 From the slope of the curve in , we can get the simulated thermal runaway propagation rate of 9.8 mm / s, while the experimental propagation rate is 10.0 mm / s. The propagation rates are similar, and the temperature rise and temperature drop trends are roughly the same.

[0141] Fig. 9 The simulation TL1 in the simulation is the geometric simulation model of the lithium battery with 50% SOC TL 1 Simulated temperature curve at the probe point, Fig. 9 The simulation TL3 in the simulation is a 50% SOC lithium battery geometry simulation model TL 3 Simulated temperature curve at the probe point, Fig. 9 The experiment TL1 is a lithium battery TL with a SOC of 50%. 1 Experimental temperature curve at the probe point, Fig. 9 The experiment TL3 is a lithium battery TL with a SOC of 50%. 3 Experimental temperature curve at the probe point.

[0142] from Fig.10 It can be seen that before the acupuncture began, the terminal voltage values ​​of the 20% SOC lithium battery geometry simulation model and the experiment were both 3.7V. After the acupuncture began, the terminal voltage of the experiment dropped to 1.4V at 6 seconds, while the terminal voltage of the model dropped to 1.4V at 4 seconds. Then, the terminal voltage of the experiment dropped to 0V at 13 seconds, while the terminal voltage of the model dropped to 0V at 8 seconds. The voltage drop trend and time of the model are roughly consistent with the experimental data. Fig.10 The experimental code refers to the voltage curve corresponding to the actual experimental process, and the simulation code refers to the voltage curve corresponding to the simulation process.

[0143] Since the geometric simulation model of lithium batteries of the present invention mainly focuses on the internal short circuit process of a single battery, and the experimental process has many uncertain factors, including battery gas production, combustion, etc., which leads to the time to reach the highest temperature and the highest temperature are not completely consistent, but the thermal runaway propagation rate and the maximum temperature rise time error are within the corresponding threshold range. This comparison still demonstrates the ability of the geometric control model of lithium batteries of the present invention to simulate the thermal runaway behavior of the battery. During simulation, the present invention uses the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute material transfer model and the thermal runaway model as the control equations of the geometric simulation model of lithium batteries, which is equivalent to taking into account the coupling of electric field, chemical field and thermal field at the same time. Therefore, the electrochemical reaction inside the battery, the transfer process of ions and electrons can be accurately simulated, and the temperature change of the geometric simulation model of lithium batteries can be determined more accurately, thereby improving the accuracy of the prediction of thermal runaway diffusion of lithium batteries.

[0144] Based on the same inventive concept as in the above-mentioned embodiment, this embodiment also provides a battery acupuncture thermal runaway simulation device, such as Fig.11 As shown, the device comprises:

[0145] A construction unit 110 is used to construct an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model, and a thermal runaway model; and the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model, and the thermal runaway model are used as control equations of a lithium battery geometric simulation model;

[0146] The solving unit 111 is used to iteratively solve the control equation of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; the internal short-circuit equivalent circuit model is used to provide the short-circuit current required for each iterative solution to simulate the short-circuit phenomenon caused by the probe piercing the interior of the lithium battery geometric simulation model;

[0147] The prediction unit 112 is used to predict the thermal behavior of the lithium battery in a real environment by using the battery thermal runaway simulation data.

[0148] Since the device introduced in the embodiment of the present invention is a device used to implement the battery acupuncture thermal runaway simulation method of the embodiment of the present invention, based on the method introduced in the embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the device, so it is not repeated here. All devices used in the method of the embodiment of the present invention belong to the scope of protection of the present invention.

[0149] Based on the same inventive concept, this embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the methods described above are implemented.

[0150] Through one or more embodiments of the present invention, the present invention has the following beneficial effects or advantages:

[0151] The present invention provides a battery acupuncture thermal runaway simulation method, device and medium, the method comprising: constructing an internal short circuit equivalent circuit model, a charge state estimation model, an electrochemical model, a rare substance transfer model and a thermal runaway model; using the internal short circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the rare substance transfer model and the thermal runaway model as control equations of a lithium battery geometric simulation model; when the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, triggering iterative solution of the control equations of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; the internal short circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the rare substance transfer model and the thermal runaway model are used as control equations of a lithium battery geometric simulation model; when the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, triggering iterative solution of the control equations of the lithium battery geometric simulation model to obtain battery thermal runaway simulation data; The equivalent circuit model is used to provide the short-circuit current required for each iterative solution; the battery thermal runaway simulation data is used to predict the thermal behavior of the lithium battery in a real environment; in this way, during the simulation, the internal short-circuit equivalent circuit model, the charge state estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model are used as the control equations of the lithium battery geometric simulation model, which is equivalent to taking into account the coupling effects of the electric field, the chemical field and the thermal field at the same time. Therefore, the electrochemical reactions inside the battery and the transfer process of ions and electrons can be accurately simulated, and the temperature changes of the lithium battery geometric simulation model can be more accurately determined, thereby improving the accuracy of the prediction of the thermal runaway diffusion of the lithium battery.

[0152] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0153] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A battery acupuncture thermal runaway simulation method, characterized in that: The method comprises: Constructing an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model, and a thermal runaway model; using the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model, and the thermal runaway model as control equations of a lithium battery geometric simulation model; When the probe model penetrates into the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, it triggers the iterative solution of the control equation of the lithium battery geometric simulation model to obtain the battery thermal runaway simulation data; the internal short circuit equivalent circuit model is used to provide the short circuit current required for each iterative solution; The battery thermal runaway simulation data is used to predict the thermal behavior of the lithium battery in a real environment.

2. The method according to claim 1, characterized in that The internal short-circuit equivalent circuit model includes: a short-circuit current determination model, a battery terminal voltage determination model and a battery internal resistance determination model; wherein, The short-circuit current determination model is: The battery terminal voltage determination model is: V(t)=U(SOC)-I short ×R cell ; The battery internal resistance determination model is: R cell =R cell,ref ×ξ(T), in, The V(t) is the terminal voltage of the geometric simulation model of the lithium battery; the U(SOC) is the open circuit voltage of the geometric simulation model of the lithium battery; the I short is the short-circuit current of the lithium battery geometric simulation model; cell is the internal resistance of the geometric simulation model of the lithium battery; short is the internal resistance of the probe geometric model; cell,ref is the reference resistance value of the lithium battery geometric simulation model at a reference temperature; ξ(T) is a resistance compensation function, and T is the temperature of the lithium battery geometric simulation model at the current iteration.

3. The method according to claim 1, characterized in that The state of charge estimation model is: in, The ISC cond is a step function, the T c is the melting point of the diaphragm of the lithium battery geometric simulation model, T is the temperature of the lithium battery geometric simulation model in the current iteration, and A ec is the pre-exponential factor of the electrochemical reaction, the E ec is the short-circuit activation energy, C is the capacity of the lithium battery geometric simulation model, R is the ideal gas constant, and exp is an exponential function.

4. The method according to claim 1, characterized in that The electrochemical model includes: the Arrhenius equation, the reaction rate equation and the electrochemical reaction heat generation equation for describing the relationship between the chemical reaction rate constant and the temperature; wherein, The Arrhenius equation is: The reaction rate equation is: CR = M × [C] n ; The electrochemical reaction heat generation equation is: Q exo =CR×ΔH; where M is the reaction rate constant, exp is the exponential function, and A ec is the pre-exponential factor of the electrochemical reaction, the E ec is the short-circuit activation energy, R is the ideal gas constant, T is the temperature of the current iteration of the lithium battery geometry simulation model, CR is the reaction rate, C is the lithium ion concentration, n is the reaction order, and Q exo is the electrochemical reaction heat, and ΔH is the unit molar reaction heat.

5. The method according to claim 1, characterized in that The dilute species transfer model is: in, The C is the lithium ion concentration, the D is the diffusion coefficient, is the rate of change of the lithium ion concentration over time, is the second-order derivative of the lithium ion concentration in space.

6. The method according to claim 1, characterized in that The thermal runaway model includes: a total heat generation model, a total heat dissipation model and a battery temperature determination model; wherein, The total heat generation model is: The total heat dissipation model is: Q diss =Q rad +Q conv ; The battery temperature determination model is: in, The Q gen is the total heat generation of the lithium battery geometric simulation model, the Q exo is the electrochemical reaction heat, the Q cell is the Joule heat generated by the internal resistance of the lithium battery geometric simulation model, and the Q ISC is the Joule heat generated by the internal short circuit of the lithium battery geometric simulation model, and the Q e is the heat of decomposition reaction, the Q diss is the total heat dissipation of the lithium battery geometric simulation model, and the Q conv Thermal convection heat, the Q rad is the heat radiation heat, ρ is the battery density of the lithium battery geometric simulation model, is the gradient operator, the C p is the specific heat capacity, T is the temperature of the current iteration of the lithium battery geometric simulation model, λ is the battery thermal conductivity, and T d is the decomposition temperature.

7. The method according to claim 1, characterized in that The battery thermal runaway simulation data includes: the temperature and terminal voltage of the lithium battery geometric simulation model; the control equation of the lithium battery geometric simulation model is iteratively solved to obtain the battery thermal runaway simulation data, including: For each iteration, the temperature of the lithium battery geometric simulation model after the previous iteration and the state of charge of the lithium battery geometric simulation model after the previous iteration are obtained; the short-circuit current corresponding to the lithium battery geometric simulation model in the current iteration and the internal resistance of the lithium battery geometric simulation model in the current iteration are determined according to the temperature of the lithium battery geometric simulation model after the previous iteration, the state of charge of the lithium battery geometric simulation model after the previous iteration and the internal short-circuit equivalent circuit model; Determine the electrochemical reaction heat according to the temperature of the lithium battery geometric simulation model after the previous iteration, the electrochemical model and the dilute species transfer model, and determine the current temperature of the lithium battery geometric simulation model corresponding to the current iteration according to the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, the electrochemical reaction heat and the thermal runaway model; Determine the current state of charge of the lithium battery geometric simulation model at the current iteration according to the current temperature of the lithium battery geometric simulation model corresponding to the current iteration, the short-circuit current corresponding to the lithium battery geometric simulation model at the current iteration, and the state of charge estimation model; The terminal voltage of the lithium battery geometric simulation model of the current iteration is determined according to the current state of charge, the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, and the state of charge-open circuit voltage curve function; wherein, In the first iteration, the state of charge of the lithium battery geometric simulation model and the temperature of the lithium battery geometric simulation model are preset.

8. The method according to claim 7, characterized in that The determining the terminal voltage of the lithium battery geometric simulation model of the current iteration according to the current state of charge, the short-circuit current corresponding to the lithium battery geometric simulation model of the current iteration, the internal resistance of the lithium battery geometric simulation model of the current iteration, and the state of charge-open circuit voltage curve includes: Substituting the current state of charge into the state of charge-open circuit voltage curve function to obtain the open circuit voltage of the lithium battery geometric simulation model of the current iteration; The short-circuit current corresponding to the current iteration of the geometric simulation model of the lithium battery, the internal resistance of the current iteration of the geometric simulation model of the lithium battery, and the open-circuit voltage are substituted into the battery terminal voltage determination model to obtain the terminal voltage of the current iteration of the geometric simulation model of the lithium battery.

9. A battery acupuncture thermal runaway simulation device, characterized in that: The device comprises: A construction unit is used to construct an internal short circuit equivalent circuit model, a state of charge estimation model, an electrochemical model, a dilute species transfer model and a thermal runaway model; the internal short circuit equivalent circuit model, the state of charge estimation model, the electrochemical model, the dilute species transfer model and the thermal runaway model are used as control equations of a lithium battery geometric simulation model; A solving unit is used to trigger iterative solving of the control equation of the lithium battery geometric simulation model when the probe model penetrates into the interior of the lithium battery geometric simulation model to simulate the thermal runaway caused by the internal short circuit of the battery, so as to obtain the battery thermal runaway simulation data; the internal short circuit equivalent circuit model is used to provide the short circuit current required for each iterative solution; The prediction unit is used to predict the thermal behavior of the lithium battery in a real environment by using the battery thermal runaway simulation data.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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