A method for simulating short circuit fault in lithium ion battery

Abstract

The application discloses a lithium ion battery internal short circuit fault simulation method, comprising the following steps: S1, establishing a lithium ion battery single particle lumped parameter estimation model, and estimating the dynamics and transfer attribute parameters of a lithium ion battery to be simulated by using a control equation; S2, constructing an electrochemical-thermal coupling 3D model and setting a control equation thereof; S3, substituting the dynamics and transfer attribute parameters of the simulated lithium ion battery into the constructed electrochemical-thermal coupling 3D model, simulating the electrothermal behavior of the lithium ion battery under different fault types based on the control equation, and realizing internal short circuit fault simulation. The application solves the defects of the existing fault simulation scheme in simulation accuracy, calculation rapidity and application universality, establishes an internal short circuit fault electrochemical-thermal coupling 3D model, and provides simulation data basis for an internal short circuit fault detection method.

Description

Technical Field

[0001] This invention belongs to the field of lithium-ion battery electrothermal simulation technology, specifically relating to a method for simulating internal short-circuit faults in lithium batteries. Background Technology

[0002] Lithium-ion batteries, with their high energy density, long cycle life, and lack of memory effect, have been widely used in energy storage systems, electronic products, and various electromechanical equipment. However, the safety risks associated with lithium-ion batteries have become increasingly prominent in recent years. As the specific energy of lithium-ion batteries gradually increases, the thickness of the separator decreases while the thickness of the electrode material increases. Internal short circuits have gradually become the most common cause of safety accidents in lithium-ion batteries. Broadly speaking, an internal short circuit refers to the phenomenon where the positive and negative electrode materials come into direct contact after the separator inside the battery is damaged by mechanical extrusion, foreign object puncture, or high-temperature melting, forming an electrical connection and causing discharge. This is a key link in the development of mechanical abuse, electrical abuse, and thermal abuse towards battery thermal runaway. If an internal short circuit is not detected in its early stages, the resistive heat generated by the short circuit will cause a large accumulation of localized heat in the battery over time. The exothermic decomposition reaction accelerates at high temperatures, causing thermal runaway in individual cells and even spreading to adjacent cells, ultimately leading to serious safety accidents such as fires and explosions. Therefore, internal short circuits have become a major cause of operational accidents in lithium-ion battery energy storage systems, seriously threatening safe production.

[0003] Currently, scholars have conducted in-depth research on the causes and triggering mechanisms of internal short-circuit faults, and have developed several numerical simulation technology schemes. However, the simulation modeling of internal short-circuit faults in lithium-ion batteries is a complex multi-factor coupling process. The academic community has not yet reached a consensus on how to simplify the electrochemical mechanisms and control equations in the numerical simulation model while ensuring that the simulated electrothermal characteristics are close to the actual engineering situation.

[0004] Electrochemical-thermal coupled simulation models of internal short-circuit faults can be cross-validated with simulated triggering experiments of internal short-circuit faults, compensating for the shortcomings of some simulated triggering experiments in controlling different types of internal short-circuit faults or obtaining some monitoring data. However, it should be recognized that internal short-circuit faults are a complex multi-factor coupled process, and its numerical simulation inevitably involves simplifications in certain mechanisms and control equations. Newman, Doyle, and Fuller et al. established an electrochemical-thermal coupled model, the basic form of which is a pseudo-two-dimensional (P2D) battery model based on first-principles calculations. This model has been experimentally validated for many years and is currently the most widely used simplified internal short-circuit model in academia. Through the thermal balance equation, the heat generation rate and various parameters of the P2D model can be converted into a 3D electro-thermal coupled simulation model, on which the electrochemical-thermal characteristics of battery internal short-circuit faults are simulated and verified.

[0005] There are two technical approaches to establishing internal short-circuit fault models based on 3D electrochemical-thermal coupling models. Zavalis established a needle-puncture electrochemical-thermal coupling model using steel needles as internal short-circuit pathways. By reasonably setting various electrochemical parameters of the steel needles, the local current density and electrolyte concentration distribution of lithium-ion batteries under internal short-circuit fault conditions can be simulated. However, this model has a large computational load and is generally only used for simple calculations of 2D models. Zhang and Wang extended Zavalis' 2D model to 3D and established a temperature field simulation model for internal short-circuit faults in lithium-ion batteries. However, in Zhang and Wang's simplified model, short-circuit heat generation is regarded as resistive heat generation, and internal short-circuit heat generation is attributed to the external short-circuit Joule heat generated by the lithium-ion battery through the steel needle channel, assuming that all heat generation occurs inside the battery.

[0006] Based on this, existing simulations of internal short-circuit faults in lithium-ion batteries have the following drawbacks:

[0007] 1) Simulation modeling of internal short-circuit faults in lithium-ion batteries is a complex multi-factor coupled process. Existing fault simulation modeling methods cannot simplify the electrochemical mechanisms and control equations in the numerical simulation model while ensuring that the simulated electrothermal characteristics are close to the actual engineering situation. The simulation solution speed for internal short-circuit faults of large-capacity lithium-ion batteries used in engineering is slow and the calculation error is large.

[0008] 2) Most existing methods focus on single-layer electrodes for small-capacity lithium-ion batteries (0.5-2Ah) and are limited to local areas with internal short circuits, resulting in low accuracy in simulating large-capacity lithium-ion batteries.

[0009] 3) Existing simulation modeling methods for internal short-circuit faults in lithium-ion batteries are difficult to obtain the dynamics and transfer properties of the tested object. Generally, empirical estimation methods are used, and the simulation results deviate from the actual engineering situation. Summary of the Invention

[0010] To address the aforementioned shortcomings in existing technologies, this invention provides a lithium-ion battery internal short-circuit fault simulation method that solves the problems of simulation accuracy, computational speed, and wide applicability in fault simulation schemes.

[0011] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: a method for simulating internal short-circuit faults in lithium-ion batteries, comprising the following steps:

[0012] S1. Establish a lumped parameter estimation model for a single lithium-ion battery particle, and use its governing equations to estimate the dynamic and transport property parameters of the lithium-ion battery to be simulated.

[0013] S2. Construct an electrochemical-thermal coupled 3D model and set its governing equations;

[0014] S3. Substitute the kinetic and transport property parameters of the simulated lithium-ion battery into the constructed electrochemical-thermal coupled 3D model. Based on its control equation, simulate the electrothermal behavior of the lithium-ion battery under different fault conditions to realize the simulation of internal short-circuit fault.

[0015] Furthermore, in step S1, the input parameters of the lumped parameter estimation model include the battery capacity, voltage, initial state of charge, and measured open-circuit voltage and SOC of the lithium-ion battery to be simulated, and the output parameter is the ohmic overpotential η at a 1C rate. IR,1C The charge exchange current J0 and the diffusion time constant τ;

[0016] The governing equations in the lumped parameter estimation model include the Ohmic potential drop process equation represented by the lumped solution resistance term in the electrolyte, the potential loss equation caused by the single-particle diffusion process, the charge state equation of the particle surface, and the voltage loss equation caused by concentration overpotential.

[0017] Furthermore, in the lumped parameter estimation model, the equation for the Ohmic potential drop process is:

[0018]

[0019]

[0020] In the formula, η IR For ohmic overpotential, η IR,1C I is the ohmic overpotential corresponding to a 1C rate. cell For external current, Q cell,0 η represents battery capacity, s represents time in seconds; act The total voltage loss caused by the charge transfer process on the positive and negative electrodes is R, the molar gas constant is F, the Faraday constant is T, the temperature is asinh(·) is the inverse hyperbolic sine function, and J0 is the dimensionless charge exchange current.

[0021] The potential loss equation caused by the single-particle diffusion process is:

[0022]

[0023] In the formula, τ is the diffusion time constant, SOC is the state of charge, and t is time. For divergence;

[0024] The equation of state for the charge on the particle surface is:

[0025]

[0026] In the formula, SOC average The average state of charge is represented by Π, where π is π and X is the particle radius.

[0027] The equation for voltage loss due to concentration overpotential is:

[0028] η conc =E OCV (SOC surface )-E OCV (SOC average )

[0029] In the formula, η conc E is the voltage loss caused by concentration overpotential. OCV (·) represents the open-circuit voltage, SOC. surface The charge state of the particle surface at X=1.

[0030] Furthermore, in step S2, the geometry of the electrochemical-thermal coupled 3D model includes a cuboid electrode core, an aluminum shell, and electrode tabs, and the influence of the edge curvature of the square wound electrode core on the electrochemical reaction is not considered.

[0031] The electrochemical-thermal coupled 3D model employs a combination of a local P2D electrochemical model and a global 3D thermal model to simulate electrothermal behavior under different fault conditions.

[0032] Furthermore, in step S3, the governing equations of the electrochemical-thermal coupled 3D model include the average heat generation power conversion equation from the P2D electrochemical model to the 3D thermal model, and the electrochemical reaction governing equations of the lithium-ion battery cell.

[0033] Among them, the electrochemical reaction control equations of a lithium-ion battery cell include the potential control equation, the electrolyte potential control equation, the charge transport process equation in the electrode core, the liquid phase lithium-ion balance control equation in the electrolyte, the thermal balance equation, the electrochemical reaction rate equation, the internal short-circuit current equation, the internal short-circuit reaction equation, and the parameter effectiveness correction equation.

[0034] Furthermore, the average heat generation power conversion equation from the P2D electrochemical model to the 3D thermal model is as follows:

[0035]

[0036]

[0037] In the formula, Q 3D Q P2D The heat generation power of the 3D thermal model and the P2D electrochemical model are respectively. The thickness of the current collector electrode for the positive electrode is [missing information]. L represents the thickness of the current collector electrode for the negative electrode. + L represents the thickness of the positive electrode sheet. - L represents the thickness of the negative electrode sheet.SEI r represents the electrode thickness of the SEI film. P2D r is the radius of the P2D electrochemical model. nail Let ρ be the radius of the metal wire. p For the P2D electrochemical model density, L i Let ρ be the thickness of the i-th layer in the 3D thermal model. i Let C be the density of the i-th layer in the 3D thermal model. p Let C be the specific heat capacity of the i-th layer in the 3D thermal model. p,i Let k be the specific heat capacity of the i-th layer in the P2D electrochemical model. p For the thermal conductivity of the 3D thermal model, k T,i Let be the thermal conductivity of the i-th layer in the P2D electrochemical model.

[0038] Furthermore, the potential control equation is as follows:

[0039]

[0040] In the formula, Let σ be the divergence. eff For effective conductivity, φ s For solid-state potential, j Li This is the current loss due to the reaction of the lithium battery;

[0041] The governing equation for the electrolyte potential is:

[0042]

[0043] In the formula, Let κ be the divergence, φ be the chemical reaction rate, and φ be the scalar divergence. e For liquid phase potential, κ D c is the rate of a liquid-phase chemical reaction. e j represents the concentration of the liquid-phase reactants. Li This is the current loss due to the reaction of the lithium battery;

[0044] Equation of charge transport process in the electrode core:

[0045]

[0046] In the formula, c S Where is the concentration of the solid-phase reactant, r is the radius of the electrode core, and D is the polarity. S denoted as the diffusion coefficient of lithium ions in the porous electrode, and t as the radial coordinate of the porous electrode;

[0047] The governing equation for the liquid-phase lithium-ion balance in the electrolyte is:

[0048]

[0049] In the formula, ε e Let t be the liquid phase porosity, t be the radial coordinate of the porous electrode, and c be the liquid phase porosity.e This refers to the concentration of the liquid-phase reactants. Let D be the divergence. e Let be the electrolyte diffusion coefficient. Let j be the lithium-ion transfer coefficient. Li The current loss in a lithium battery reaction is F, where F is the Faraday constant.

[0050] The heat balance equation is:

[0051]

[0052] Q P2D =Q rev +Q pol +Q TR +Q ISC

[0053] In the formula, ρ is density, and c p Let T be the specific heat capacity of the homogeneous mass, T be the temperature, and t be the time. Let Q be the divergence, k be the thermal conductivity, and Q be the thermal conductivity. P2D Q represents the heat generation power of the P2D electrochemical model. rev Q represents the heat production power of the reversible reaction in the P2D electrochemical model. pol Q represents the polarization heat generation power of the P2D electrochemical model. TR Q represents the thermal runaway heat generation power of the P2D electrochemical model. ISC The internal short-circuit heat generation power of the P2D electrochemical model;

[0054] The electrochemical reaction rate equation is:

[0055]

[0056]

[0057] In the formula, j Li For lithium battery reaction current loss, a s α is the active surface area per unit volume of the particle. a and α c All are transfer coefficients of the electrode reaction, i0 is the surface density of the electrode exchange current, η is the overpotential of the electrode reaction, R is the molar gas constant, F is the Faraday constant, T is the temperature, and φ is the transfer coefficient of the electrode reaction. s For solid-state potential, φ e R is the liquid phase potential, U is the electrical potential, and R is the liquid phase potential. SEI The resistivity per unit area of ​​the SEI film;

[0058] The equation for the internal short-circuit current is:

[0059] I ISC =-ΔΦ S / R ISC =∫iS dA=N·A·i S

[0060] In the formula, I ISC Internal short-circuit current, ΔΦ S R is the solid potential gradient corresponding to the cross-sectional area of ​​the internal short-circuit path. ISC i is the equivalent resistance of the internal short-circuit path. S Here, A is the resistivity per unit area of ​​the SEI film, A is the core area, and N is the number of layers in the wound electrode.

[0061] The internal short-circuit reaction equation is:

[0062] ΔH TR =M·C P1 ·ΔT

[0063] In the formula, ΔH TR Let M be the enthalpy of thermal runaway, M be the mass of the electrode core, and C be the enthalpy of thermal runaway. P1 ΔT is the specific heat capacity of the core as an average value, and ΔT is the temperature difference between the highest temperature of the single cell and the thermal runaway initiation temperature.

[0064] The parameter validity correction equation is:

[0065] σ eff =σε s κ eff =κε e

[0066]

[0067]

[0068] In the formula, σ eff σ is the effective conductivity, ε is the conductivity, and σ is the conductivity. s κ represents the solid phase porosity. eff Let κ be the effective chemical reaction rate, and ε be the chemical reaction rate. e For liquid phase porosity, D is the effective electrolyte diffusion coefficient. e Let be the electrolyte diffusion coefficient. To correct for chemical reaction rates, R is the molar gas constant, T is the temperature, and F is the Faraday constant. Here, is the lithium-ion transfer coefficient, d is the simplified interlayer distance, and f is... ± The positive and negative electrode reaction rates, c e This represents the concentration of the liquid-phase reactants.

[0069] Further, step S4 specifically includes:

[0070] S41. Limit the electrochemical simulation values ​​to the local P2D region of the battery around the internal short circuit point in the geometry of the electrochemical-thermal coupled 3D model, and use it as a local model of internal short circuit fault.

[0071] Among them, the local model of internal short-circuit fault corresponds to the P2D electrochemical model, and the overall geometric structure of the electrochemical-thermal coupled 3D model corresponds to the 3D thermal model.

[0072] S42. Substitute the dynamics and transfer parameters of the lithium-ion battery to be simulated into the local model of internal short-circuit fault.

[0073] S43. Simulate the internal short circuit process in the local model of internal short circuit fault. Based on the principle of heat transfer, describe the thermal balance of the battery based on the electrochemical reaction control equation, and calculate the average heat generation rate of the local model of internal short circuit fault.

[0074] S44. Convert the calculated average heat generation rate from the P2D electrochemical model to the 3D thermal model, and calculate the average heat generation power of the battery cell.

[0075] S45. Based on the calculated average heat production power, quantitatively adjust the parameters of the numerical model corresponding to the 3D thermal model according to the Arrhenius formula, and feed them back into the P2D electrochemical model.

[0076] S46. Repeat steps S42 to S45. By adjusting and transferring the thermal balance parameters, the electrochemical-thermal coupling process is realized, thereby simulating the electrothermal behavior of lithium-ion batteries under different fault conditions and realizing the simulation of internal short-circuit faults.

[0077] The beneficial effects of this invention are as follows:

[0078] (1) This invention estimates parameters based on charge-discharge cycle monitoring data of individual battery cells. The obtained model parameters meet the requirements of engineering applications, balancing high simulation accuracy with low computational complexity. It can use limited monitoring data to solve the dynamics and transport properties of lithium-ion batteries, thereby setting the initial conditions of batteries in complex numerical simulation models and achieving better simulation application results.

[0079] (2) The method of obtaining the dynamic and transfer property parameters of lithium-ion batteries by means of lumped parameter estimation model in this invention reduces the modeling difficulty but increases the model error compared with the traditional method of obtaining model parameters based on experience or manufacturer's instructions. This invention estimates parameters based on the charge and discharge cycle monitoring data of individual battery cells. The obtained model parameters meet the requirements of engineering applications and take into account both high simulation accuracy and low computational complexity.

[0080] (3) This invention reasonably simplifies the model geometry and constructs a multi-scale electrochemical-thermal coupled model. It employs a 3D electrochemical-thermal coupled model, coupling local electrochemical models with a global thermal model to simulate the electrothermal behavior of faulty batteries under different fault types and series-parallel configurations. Compared to traditional full-size electrochemical-thermal coupled models, this invention significantly reduces modeling and simulation difficulty while ensuring simulation accuracy, overcoming the shortcomings of traditional methods such as high computational load, difficult modeling, and limited applicability to actual internal short-circuit fault modeling. Attached Figure Description

[0081] Figure 1 The flowchart of the lithium-ion battery internal short-circuit fault simulation method provided by the present invention is shown.

[0082] Figure 2 This is a schematic diagram of the electrochemical-thermal coupling 3D model provided by the present invention.

[0083] Figure 3 This is a schematic diagram of the coupling method of the electrochemical-thermal coupling 3D model provided by the present invention. Detailed Implementation

[0084] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0085] Before describing specific embodiments of the present invention, to make the solution of the present invention clearer and more complete, the definitions of abbreviations and key terms appearing in the present invention will first be explained:

[0086] Lithium-ion batteries: Lithium-ion batteries are a type of rechargeable battery that primarily functions by the movement of lithium ions between the positive and negative electrodes. During charging and discharging, Li... + Intercalation and deintercalation back and forth between the two electrodes: During charging, Li + The lithium is extracted from the positive electrode and inserted into the negative electrode through the electrolyte, putting the negative electrode in a lithium-rich state; the opposite occurs during discharge.

[0087] Internal short circuit fault: An internal short circuit fault refers to the phenomenon where the positive and negative electrode materials come into direct contact after the battery's internal separator is damaged by mechanical extrusion, foreign object puncture, or high-temperature melting, forming an electrical connection and conducting discharge.

[0088] Electrochemical-thermal coupled 3D model: An electrochemical-thermal coupled model for lithium-ion batteries. This model can simulate the electrothermal behavior of lithium-ion batteries under internal short-circuit fault conditions and extract the electrothermal characteristics and fault features of the battery during the evolution of internal short-circuit faults.

[0089] In this embodiment of the invention, in order to fully understand the electrothermal and fault characteristics of the battery during the evolution of internal short-circuit faults, and to lay a solid research foundation for the design of experimental schemes and fault detection of internal short-circuit faults in lithium-ion batteries, it is necessary to establish an electro-thermal coupling simulation model of the lithium-ion battery energy storage system. This model simulates different types of internal short-circuit faults, such as aluminum-copper short circuit, copper-positive electrode short circuit-positive electrode-negative electrode short circuit, and aluminum-negative electrode short circuit. The evolution of the internal short circuit during the evolution of internal short-circuit faults is described by the electrolyte concentration distribution and the internal temperature field distribution of the lithium-ion battery.

[0090] This invention constructs a single-particle lumped parameter estimation model for lithium-ion batteries and a multi-scale electrochemical-thermal coupling model for wound lithium-ion batteries. The former is used to estimate the kinetics and transport properties of lithium-ion batteries, while the latter is used to simulate the electrothermal behavior of multilayer wound batteries under four types of internal short-circuit fault conditions.

[0091] Based on this, embodiments of the present invention provide a method for simulating internal short-circuit faults in lithium-ion batteries, such as... Figure 1 As shown, it includes the following steps:

[0092] S1. Establish a lumped parameter estimation model for a single lithium-ion battery particle, and use its governing equations to estimate the dynamic and transport property parameters of the lithium-ion battery to be simulated.

[0093] S2. Construct and set its governing equations;

[0094] S3. Substitute the kinetic and transport property parameters of the simulated lithium-ion battery into the constructed electrochemical-thermal coupled 3D model. Based on its control equation, simulate the electrothermal behavior of the lithium-ion battery under different fault conditions to realize the simulation of internal short-circuit fault.

[0095] In this embodiment of the invention, the lithium-ion battery energy storage system can be considered a "black box" whose internal parameters cannot be precisely obtained. For example, the battery capacity decay characteristics over time, the battery open-circuit voltage at different SOCs, the ohmic overpotential at different currents, the activation overpotential of the electrode surface, and the particle diffusion time constant. Some parameters can be obtained based on experience or the manufacturer's specifications, while others, such as kinetic and transport properties, are closely related to the performance of individual battery cells and cannot be directly obtained.

[0096] To utilize limited monitoring data to solve for the basic parameters of lithium-ion batteries and set the initial conditions for batteries in complex numerical simulation models, step S1 of this embodiment of the invention establishes a lumped parameter estimation model for a single lithium-ion battery particle. Its input parameters include the battery capacity, voltage, initial state of charge, and measured open-circuit voltage and SOC of the lithium-ion battery to be simulated. The output parameter is the ohmic overpotential η at a 1C rate. IR,1C The model assumes that the battery is controlled by a diffusion process in one electrode, ignores the concentration gradient and local potential in the electrolyte, and simplifies the model by taking the lumped form of the resistance term in the electrolyte. The parameters and input / output values ​​of the model are shown in Table 1.

[0097] Table 1: Input and Output Parameters of the Lumped Parameter Estimation Model

[0098]

[0099] In this embodiment of the invention, the governing equations in the lumped parameter estimation model include the Ohmic potential drop process equation represented by the lumped solution resistance term in the electrolyte, the potential loss equation caused by the single-particle diffusion process, the charge state equation of the particle surface, and the voltage loss equation caused by concentration overpotential.

[0100] Specifically, the equation for the ohmic potential drop process represented by the lumped solution resistance term in the electrolyte is:

[0101]

[0102]

[0103] In the formula, η IR For ohmic overpotential, η IR,1C I is the ohmic overpotential corresponding to a 1C rate. cell For external current, Q cell,0 η represents battery capacity, s represents time in seconds; act The total voltage loss caused by the charge transfer process on the positive and negative electrodes is R, the molar gas constant is F, the Faraday constant is T, the temperature is asinh(·) is the inverse hyperbolic sine function, and J0 is the dimensionless charge exchange current.

[0104] Based on Fick's diffusion theory, the potential loss caused by single-particle diffusion is solved separately in an additional dimension where the particle length is 1. Using a spherical symmetric form, the potential loss equation is obtained as follows:

[0105]

[0106] In the formula, τ is the diffusion time constant, SOC is the state of charge, and t is time. For divergence;

[0107] The above equation represents the average particle controlling the motor reaction. The surface and center of the particle correspond to X=1 and X=0, respectively, and the corresponding boundary conditions are:

[0108]

[0109] In the formula, N shape =3 (spherical particles), SOC0 is the initial state of charge of the battery, SOC surface The charge state of the particle surface at X=1;

[0110] Integrating over the particle in spherical coordinates yields the following equation of state for the charged surface of the particle:

[0111]

[0112] In the formula, SOC average The average state of charge is represented by Π, where π is π and X is the particle radius.

[0113] The equation for voltage loss due to concentration overpotential is:

[0114] η conc =E OCV (SOC surface )-E OCV (SOC average )

[0115] In the formula, η conc E is the voltage loss caused by concentration overpotential. OCV (·) represents the open-circuit voltage, SOC. surface The charge state of the particle surface at X=1.

[0116] In this embodiment of the invention, after considering the above factors, the accuracy of the estimated kinetic and transfer property parameters is verified by estimating the battery voltage; wherein, the battery voltage E cell The formula for estimation is:

[0117] E cell =E OCV (SOC average )+η IR +η act +η conc

[0118] In this embodiment of the invention, an electrochemical-thermal coupled 3D model is constructed based on the kinetic and transport property parameters of the lithium-ion battery obtained by the lumped parameter estimation model. This model simulates a rectangular wound lithium-ion battery, in which the electrodes of the lithium-ion battery are wound and stacked on the core shaft. The thickness of a single electrode layer is generally tens of micrometers, and the length and width are tens of centimeters. Using a full-size lithium-ion battery model to simulate the internal short-circuit electrothermal process requires a large amount of computation. Therefore, this invention reasonably simplifies the model geometry and constructs a multi-scale electrochemical-thermal coupled model.

[0119] Based on this, the geometric structure of the electrochemical-thermal coupled 3D model provided in step S2 of the present invention includes a cuboid electrode core (such as... Figure 2 As shown in (a), the electrode core is 155 mm long in the x-direction, 125 mm wide in the y-direction, and has a single-layer thickness of 180 μm in the Z-direction (magnified 100 times along the Z-axis). It consists of an aluminum shell and electrode tabs, and the effect of the edge curvature of the square wound electrode core on the electrochemical reaction is not considered. Figure 2 (c) shows a schematic diagram of the series and parallel connection of lithium-ion battery modules. The diagram shows that #1 and #2 are connected in parallel and then connected in series with #3, #4 and #5. In the experiment, the batteries are connected in series in this form to form a battery module, and the individual cells are numbered sequentially as series #1, #2 and #3; the battery module is formed in the form of 2P2S first in parallel and then in series, and the individual cells are numbered sequentially as parallel #1, #2, #3 and #4. Figure 1 The fork and rhombus shapes represent the positions of the temperature probe and voltage probe, respectively, for monitoring temperature and voltage.

[0120] In the embodiments of this invention, the three-dimensional (3D) model of the cell unit's geometric structure of the above-mentioned electrochemical-thermal coupling 3D model is as follows: Figure 2 As shown in (d), the electrode core is formed by stacking multiple layers of electrode sheets, separated by a single layer of thin wall, and wound around the core shaft three full turns. The thickness of each layer of electrode sheets and the material used are as follows:

[0121] 1) Positive current collector: Aluminum;

[0122] 2) Porous cathode electrode: L + =45μm, LiFePO4;

[0123] 3) Diaphragm: L SEI =40μm, PE;

[0124] 4) Porous anode electrode: L - =50μm, LixC6 MCMB;

[0125] 5) Negative electrode current collector: Copper;

[0126] 6) The gap between the aluminum shell and the electrode core is filled with electrolyte: LiPF6, 3:7:3EC:DMC:EMC.

[0127] In this embodiment of the invention, the electrochemical-thermal coupled 3D model adopts a method of coupling a local P2D electrochemical model and a global 3D thermal model to simulate the electrothermal behavior under different fault types.

[0128] Specifically, to simplify calculations, such as Figure 2 As shown in (b), the electrochemical numerical simulation of the internal short-circuit fault is limited to a local P2D region of the battery with a radius of 25 mm around the internal short-circuit point, and a thermal balance equation is used to couple the 3D thermal model with the electrochemical P2D model. Figure 2 (b) The single-layer internal short circuit local model within the box shows that, by using a penetrating diaphragm to connect the variable resistance metal wires of each layer, four types of internal short circuit faults are simulated. A step function is used to set the on / off time to simulate soft / hard short circuits. When t = 0, the conductivity of the wire is set to a very low value (equivalent insulation). At t = 1s, a smooth step function is used to raise it to the maximum conductivity (equivalent short circuit), which continues until the short circuit temperature stabilizes (t = 30s). The on / off resistance of the variable resistance metal wire in the aluminum-negative and aluminum-copper internal short circuits is 4.5 / 5kΩ, and the on / off resistance of the metal wire in the copper-positive and positive-negative internal short circuits is 100 / 5kΩ.

[0129] In the embodiments of the present invention, the size and computational mesh diagram of the local model of the internal short-circuit fault are shown in 2(b) and (d). The mesh near the short-circuit point and the metal wire is refined to ensure the computational convergence of the simulation model under large variable gradient.

[0130] In step S3 of this embodiment of the invention, the governing equations of the electrochemical-thermal coupled 3D model include the average heat generation power conversion equation from the P2D electrochemical model to the 3D thermal model, and the electrochemical reaction governing equations of the lithium-ion battery cell.

[0131] Among them, the electrochemical reaction control equations of a lithium-ion battery cell include the potential control equation, the electrolyte potential control equation, the charge transport process equation in the electrode core, the liquid phase lithium-ion balance control equation in the electrolyte, the thermal balance equation, the electrochemical reaction rate equation, the internal short-circuit current equation, the internal short-circuit reaction equation, and the parameter effectiveness correction equation.

[0132] Specifically, the average heat generation power conversion equation from the P2D electrochemical model to the 3D thermal model is as follows:

[0133]

[0134]

[0135] In the formula, Q 3D Q P2D The heat generation power of the 3D thermal model and the P2D electrochemical model are respectively. The thickness of the current collector electrode for the positive electrode is [missing information]. L represents the thickness of the current collector electrode for the negative electrode. + L represents the thickness of the positive electrode sheet. - L represents the thickness of the negative electrode sheet. SEI r represents the electrode thickness of the SEI film. P2D r is the radius of the P2D electrochemical model. nail Let ρ be the radius of the metal wire. p For the P2D electrochemical model density, L i Let ρ be the thickness of the i-th layer in the 3D thermal model. i Let C be the density of the i-th layer in the 3D thermal model. p Let C be the specific heat capacity of the i-th layer in the 3D thermal model. p,i Let k be the specific heat capacity of the i-th layer in the P2D electrochemical model. p For the thermal conductivity of the 3D thermal model, k T,i Let be the thermal conductivity of the i-th layer in the P2D electrochemical model.

[0136] The governing equations for the electrochemical reactions of a single lithium-ion battery cell are as follows:

[0137] The governing equation for the electric potential, as described by Ohm's law, is:

[0138]

[0139] In the formula, Let σ be the divergence. eff For effective conductivity, φ s For solid-state potential, j Li This is the current loss due to the reaction of the lithium battery;

[0140] The governing equation for the electrolyte potential is:

[0141]

[0142] In the formula, Let κ be the divergence, φ be the chemical reaction rate, and φ be the scalar divergence. e For liquid phase potential, κ D c is the rate of a liquid-phase chemical reaction. e j represents the concentration of the liquid-phase reactants. Li This is the current loss due to the reaction of the lithium battery;

[0143] Equation of charge transport process in the electrode core:

[0144]

[0145] In the formula, c SWhere is the concentration of the solid-phase reactant, r is the radius of the electrode core, and D is the polarity. S denoted as the diffusion coefficient of lithium ions in the porous electrode, and t as the radial coordinate of the porous electrode;

[0146] The governing equation for the liquid-phase lithium-ion balance in the electrolyte is:

[0147]

[0148] In the formula, ε e Let t be the liquid phase porosity, t be the radial coordinate of the porous electrode, and c be the liquid phase porosity. e This refers to the concentration of the liquid-phase reactants. Let D be the divergence. e Let be the electrolyte diffusion coefficient. Let j be the lithium-ion transfer coefficient. Li The current loss in a lithium battery reaction is F, where F is the Faraday constant.

[0149] The heat balance equation is:

[0150]

[0151] Q P2D =Q rev +Q pol +Q TR +Q ISC

[0152]

[0153] Q pol =j Li (φ s -φ e -U)

[0154]

[0155]

[0156]

[0157]

[0158] In the formula, ρ is density, and c p Let T be the specific heat capacity of the homogeneous mass, T be the temperature, and t be the time. Let Q be the divergence, k be the thermal conductivity, and Q be the thermal conductivity. P2D Q represents the heat generation power of the P2D electrochemical model. rev Q represents the heat production power of the reversible reaction in the P2D electrochemical model. pol Q represents the polarization heat generation power of the P2D electrochemical model. TR Q represents the thermal runaway heat generation power of the P2D electrochemical model. ISCThe internal short-circuit heat generation power of the P2D electrochemical model;

[0159] The electrochemical reaction rate at the electrode / electrolyte interface was quantified using the Bultler-Volmer equation. The electrochemical reaction rate equation is as follows:

[0160]

[0161]

[0162] In the formula, j Li For lithium battery reaction current loss, a s α is the active surface area per unit volume of the particle. a and α c All are transfer coefficients of the electrode reaction, i0 is the surface density of the electrode exchange current, η is the overpotential of the electrode reaction, R is the molar gas constant, F is the Faraday constant, T is the temperature, and φ is the transfer coefficient of the electrode reaction. s For solid-state potential, φ e R is the liquid phase potential, U is the electrical potential, and R is the liquid phase potential. SEI The resistivity per unit area of ​​the SEI film;

[0163] Assuming the internal short circuit is an instantaneous and discrete electrochemical process, after the internal short circuit occurs, a continuous internal short circuit path exists within the battery cell. The internal short circuit current equation described using Ohm's law is:

[0164] I ISC =-ΔΦ S / R ISC =∫i S dA=N·A·i S

[0165] In the formula, I ISC Internal short-circuit current, ΔΦ S R is the solid potential gradient corresponding to the cross-sectional area of ​​the internal short-circuit path. ISC i is the equivalent resistance of the internal short-circuit path. S Here, A is the resistivity per unit area of ​​the SEI film, A is the core area, and N is the number of layers in the wound electrode.

[0166] Based on the internal short-circuit reaction process described in the adiabatic thermal runaway experiment, the corresponding enthalpy of thermal runaway is calculated, where the internal short-circuit reaction equation is:

[0167] ΔH TR =M·C P1 ·ΔT

[0168] In the formula, ΔH TR Let M be the enthalpy of thermal runaway, M be the mass of the electrode core, and C be the enthalpy of thermal runaway. P1 ΔT is the specific heat capacity of the core as an average value, and ΔT is the temperature difference between the highest temperature of the single cell and the thermal runaway initiation temperature.

[0169] In summary, the average heat production power and average potential of the 3D thermal model calculated from the electrochemical reaction governing equations are as follows:

[0170]

[0171]

[0172] The validity correction equations for the above parameters are as follows:

[0173] σ eff =σε s κ eff =κε e

[0174]

[0175]

[0176] In the formula, σ eff σ is the effective conductivity, ε is the conductivity, and σ is the conductivity. s κ represents the solid phase porosity. eff Let κ be the effective chemical reaction rate, and ε be the chemical reaction rate. e For liquid phase porosity, D is the effective electrolyte diffusion coefficient. e Let be the electrolyte diffusion coefficient. To correct for chemical reaction rates, R is the molar gas constant, T is the temperature, and F is the Faraday constant. Here, is the lithium-ion transfer coefficient, d is the simplified interlayer distance, and f is... ± The positive and negative electrode reaction rates, c e This represents the concentration of the liquid-phase reactants.

[0177] The effective conductivity of the electrodes and electrolyte is determined by σ. eff =σε s κ eff =κε e The effective diffusion coefficient of the electrolyte is described by... The effective diffusion conductivity is described by describe.

[0178] The model dissipates heat through air convection, with the convective heat transfer coefficient set at 5 W·m⁻¹ under natural convection cooling conditions. -2 ·K -1 The thermal boundary conditions of a lithium-ion battery cell with air are described using Newton's law of cooling.

[0179]

[0180] In the formula, T ambFor ambient temperature, T ∞ λ is the surface temperature of the battery; λ is the thermal conductivity of the lithium-ion battery casing; and n represents the normal direction of the battery surface.

[0181] The above governing equations describe the key electrochemical processes in the electro-thermal coupling model of internal short-circuit faults in lithium-ion batteries. Figure 3 Based on the coupling mode of the electrochemical-thermal coupling model of the above-mentioned governing equations, step S4 of this embodiment of the invention specifically includes:

[0182] S41. Limit the electrochemical simulation values ​​to the local P2D region of the battery around the internal short circuit point in the geometry of the electrochemical-thermal coupled 3D model, and use it as a local model of internal short circuit fault.

[0183] Among them, the local model of internal short-circuit fault corresponds to the P2D electrochemical model, and the overall geometric structure of the electrochemical-thermal coupled 3D model corresponds to the 3D thermal model.

[0184] S42. Substitute the dynamics and transfer parameters of the lithium-ion battery to be simulated into the local model of internal short-circuit fault.

[0185] S43. Simulate the internal short circuit process in the local model of internal short circuit fault. Based on the principle of heat transfer, describe the thermal balance of the battery based on the electrochemical reaction control equation, and calculate the average heat generation rate of the local model of internal short circuit fault.

[0186] S44. Convert the calculated average heat generation rate from the P2D electrochemical model to the 3D thermal model, and calculate the average heat generation power of the battery cell.

[0187] S45. Based on the calculated average heat production power, quantitatively adjust the parameters of the numerical model corresponding to the 3D thermal model according to the Arrhenius formula, and feed them back into the P2D electrochemical model.

[0188] S46. Repeat steps S42 to S45. By adjusting and transferring the thermal balance parameters, the electrochemical-thermal coupling process is realized, thereby simulating the electrothermal behavior of lithium-ion batteries under different fault conditions and realizing the simulation of internal short-circuit faults.

[0189] The numerical model's thermal balance parameters include density, specific heat capacity, and thermal conductivity, taking into account the heat conduction and heat loss of the current collector, electrode core, and casing in the battery cell.

[0190] In this embodiment, based on Figure 3 The coupling method shown is according to The calculated heat production rate was converted from the P2D model to the 3D model, according to the formula... The density, specific heat capacity, and thermal conductivity of the numerical model were adjusted to fully account for the heat conduction and heat loss of the current collector, electrode core, and casing in the battery cell. The electrode core was treated as homogeneous when calculating heat conduction.

[0191] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0192] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for simulating internal short-circuit faults in lithium-ion batteries, characterized in that, Includes the following steps: S1. Establish a lumped parameter estimation model for a single lithium-ion battery particle, and use its governing equations to estimate the dynamic and transport property parameters of the lithium-ion battery to be simulated. S2. Construct an electrochemical-thermal coupled 3D model and set its governing equations; S3. Substitute the dynamics and transport properties parameters of the simulated lithium-ion battery into the constructed electrochemical-thermal coupled 3D model. Based on its control equation, simulate the electrothermal behavior of the lithium-ion battery under different fault conditions to realize the simulation of internal short circuit fault. In step S3, the governing equations of the electrochemical-thermal coupled 3D model include the average heat generation power conversion equation from the P2D electrochemical model to the 3D thermal model, and the electrochemical reaction governing equations of the lithium-ion battery cell. Among them, the electrochemical reaction control equations of lithium-ion battery cells include the potential control equation, the electrolyte potential control equation, the charge transport process equation in the electrode core, the liquid phase lithium-ion balance control equation in the electrolyte, the thermal balance equation, the electrochemical reaction rate equation, the internal short-circuit current equation, the internal short-circuit reaction equation, and the parameter effectiveness correction equation. The average heat production power conversion equation from the P2D electrochemical model to the 3D thermal model is as follows: In the formula, Q 3D , Q P2D The heat generation power of the 3D thermal model and the P2D electrochemical model are respectively. The thickness of the current collector electrode for the positive electrode is [missing information]. The thickness of the current collector electrode for the negative electrode is [missing information]. The thickness of the positive electrode sheet. The thickness of the negative electrode sheet. The electrode thickness of the SEI film is [missing information]. The radius of the P2D electrochemical model is... Where is the radius of the metal wire. For P2D electrochemical model density, For the 3D thermal model i Layer thickness, For the 3D thermal model i Layer density, For the 3D thermal model i Specific heat capacity of the layer Let i be the specific heat capacity of the i-th layer in the P2D electrochemical model. Thermal conductivity for 3D thermal models For the P2D electrochemical model i Layer thermal conductivity; Step S4 specifically involves: S41. Limit the electrochemical simulation values ​​to the local P2D region of the battery around the internal short circuit point in the geometry of the electrochemical-thermal coupled 3D model, and use it as a local model of internal short circuit fault. Among them, the local model of internal short-circuit fault corresponds to the P2D electrochemical model, and the overall geometric structure of the electrochemical-thermal coupled 3D model corresponds to the 3D thermal model. S42. Substitute the dynamics and transfer parameters of the lithium-ion battery to be simulated into the local model of internal short-circuit fault. S43. Simulate the internal short circuit process in the local model of internal short circuit fault. Based on the principle of heat transfer, describe the thermal balance of the battery based on the electrochemical reaction control equation, and calculate the average heat generation rate of the local model of internal short circuit fault. S44. Convert the calculated average heat generation rate from the P2D electrochemical model to the 3D thermal model, and calculate the average heat generation power of the battery cell. S45. Based on the calculated average heat production power, quantitatively adjust the parameters of the numerical model corresponding to the 3D thermal model according to the Arrhenius formula, and feed them back into the P2D electrochemical model. S46. Repeat steps S42 to S45. By adjusting and transferring the thermal balance parameters, the electrochemical-thermal coupling process is realized, thereby simulating the electrothermal behavior of lithium-ion batteries under different fault conditions and realizing the simulation of internal short-circuit faults.

2. The lithium-ion battery internal short-circuit fault simulation method according to claim 1, characterized in that, In step S1, the input parameters of the lumped parameter estimation model include the battery capacity, voltage, initial state of charge, and measured open-circuit voltage and SOC of the lithium-ion battery to be simulated, and the output parameter is the ohmic overpotential at 1C rate. Charge exchange current and diffusion time constant ; The governing equations in the lumped parameter estimation model include the Ohmic potential drop process equation represented by the lumped solution resistance term in the electrolyte, the potential loss equation caused by the single-particle diffusion process, the charge state equation of the particle surface, and the voltage loss equation caused by concentration overpotential.

3. The lithium-ion battery internal short-circuit fault simulation method according to claim 2, characterized in that, In the lumped parameter estimation model, the equation for the Ohmic potential drop process is: In the formula, This is an ohmic overpotential. This is the ohmic overpotential corresponding to a 1C rate. For external current, , For battery capacity, The unit of time is seconds; This refers to the lumped voltage loss caused by the charge transfer process on the positive and negative electrodes. The molar gas constant, It is Faraday's constant. For temperature, It is an inverse hyperbola sine function. It is a dimensionless charge exchange current; The potential loss equation caused by the single-particle diffusion process is: In the formula, The diffusion time constant is In a charged state, For time, For divergence; The equation of state for the charge on the particle surface is: In the formula, The average state of charge, For π, Where the particle radius is; The equation for voltage loss due to concentration overpotential is: In the formula, The voltage loss is due to concentration overpotential. Open circuit voltage, for X =1 represents the charged state of the particle surface.

4. The lithium-ion battery internal short-circuit fault simulation method according to claim 2, characterized in that, In step S2, the geometry of the electrochemical-thermal coupled 3D model includes a cuboid electrode core, an aluminum shell, and electrode tabs, without considering the influence of the edge curvature of the square wound electrode core on the electrochemical reaction. The electrochemical-thermal coupled 3D model employs a combination of a local P2D electrochemical model and a global 3D thermal model to simulate electrothermal behavior under different fault conditions.

5. The lithium-ion battery internal short-circuit fault simulation method according to claim 1, characterized in that, The potential control equation is: In the formula, For divergence, For effective conductivity, For solid-state potential, This is the current loss due to the reaction of the lithium battery; The governing equation for the electrolyte potential is: In the formula, For divergence, For chemical reaction rate, The liquid phase potential, For liquid-phase chemical reaction rate, This refers to the concentration of the liquid-phase reactants. This is the current loss due to the reaction of the lithium battery; Equation of charge transport process in the electrode core: In the formula, This represents the concentration of the solid-phase reactants. The radius of the pole core, The diffusion coefficient of lithium ions in the porous electrode is given. The radial coordinates of the porous electrode; The governing equation for the liquid-phase lithium-ion balance in the electrolyte is: In the formula, For liquid phase porosity, Let be the radial coordinate of the porous electrode. This refers to the concentration of the liquid-phase reactants. For divergence, Let be the electrolyte diffusion coefficient. This represents the lithium-ion transfer coefficient. For lithium battery reaction current loss, F It is Faraday's constant; The heat balance equation is: In the formula, For density, For homogeneous specific heat capacity, For temperature, For time, For divergence, Thermal conductivity, The heat generation power of the P2D electrochemical model, The heat production power of the reversible reaction in the P2D electrochemical model. The polarization heat generation power of the P2D electrochemical model. The thermal runaway heat generation power of the P2D electrochemical model. The internal short-circuit heat generation power of the P2D electrochemical model; The electrochemical reaction rate equation is: In the formula, For lithium battery reaction current loss, This represents the active surface area per unit volume of the particles. and All are transfer coefficients of the electrode reaction. i 0 represents the surface density of the electrode exchange current. This is the overpotential of the electrode reaction. The molar gas constant, It is Faraday's constant. For temperature, For solid-state potential, The liquid phase potential, Potential, The resistivity per unit area of ​​the SEI film; The equation for the internal short-circuit current is: In the formula, Internal short-circuit current, This represents the solid potential gradient corresponding to the cross-sectional area of ​​the internal short-circuit path. The equivalent resistance of the internal short-circuit path. The resistivity per unit area of ​​the SEI film. The core area is This represents the number of stacked layers of the wound electrode. The internal short-circuit reaction equation is: In the formula, For thermal runaway enthalpy, For the quality of the core, The specific heat capacity of the electrode core is considered to be the average value. This is the temperature difference between the highest temperature of the single unit and the thermal runaway initiation temperature. The parameter validity correction equation is: In the formula, For effective conductivity, For electrical conductivity, For solid phase porosity, For an effective chemical reaction rate, For chemical reaction rate, For liquid phase porosity, For the effective electrolyte diffusion coefficient, Let be the electrolyte diffusion coefficient. To correct the rate of chemical reaction, The molar gas constant, For temperature, It is Faraday's constant. This represents the lithium-ion transfer coefficient. For simplified inter-layer spacing, The positive and negative electrode reaction rates are... This represents the concentration of the liquid-phase reactants.

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