Hard package lithium battery structure design method and related equipment

Abstract

The invention discloses a hard package lithium battery structure design method and related equipment, and aims to provide a practical tool for lithium battery structure design. According to the method, the optimization of the assembly clearance in the hard package lithium battery design is realized by taking meeting the thermal abuse safety standard as a design target. Firstly, a standard thermal abuse condition is established, and a safety target is established for structural design of the lithium battery; secondly, establishing a lithium battery state evaluation model, giving a solving method, and providing a critical moment analysis kernel for the structural design of the lithium battery; and constructing a lithium battery structure design model again, and solving to obtain an optimal structure design parameter meeting the thermal abuse safety standard. The method is clear in solving process steps, does not involve complex finite element or algorithm programming, is easy to master by engineers, and has good engineering applicability; second-level solving efficiency and robust convergence are guaranteed theoretically; and the optimal assembly clearance can be obtained, so that the lithium battery just meets the thermal abuse safety standard, and a precision basis is provided for safety design.

Description

Technical Field

[0001] The present invention relates to the field of lithium battery safety design, and in particular to a hard-pack lithium battery structure design method and related equipment. Background Art

[0002] Lithium-ion batteries account for more than 97% of the market in the power and energy storage fields due to their high energy density, low self-discharge rate and no memory effect. However, the safety of lithium batteries has always been a challenge. Especially under thermal abuse conditions, the solid electrolyte interface (SEI) on the battery anode decomposes, releasing heat and gas, causing the internal temperature and pressure to rise. The temperature increase will intensify the electrochemical reaction, forming a vicious cycle. To avoid this situation, hard-pack batteries are designed with a pressure relief mechanism. When the pressure exceeds a threshold, the pressure relief valve opens to release high-temperature, flammable gases. For battery packs composed of large-scale lithium batteries, a single lithium battery will heat the adjacent batteries when a pressure relief event occurs, causing thermal runaway to spread, which may cause the battery pack to burn and cause accidents. In order to ensure the safety of lithium batteries in service, many government agencies and international organizations around the world have issued a series of battery safety assessment standards, such as UN 38.3, IEC 62133, and GB / T 31241. These standards specify the thermal abuse test requirements for lithium-ion batteries. The thermal abuse test conditions are similar in each standard and are usually used as mandatory test items for battery manufacturers.

[0003] To meet the safety standards of thermal abuse, the optimal design of lithium battery structure is an important way. For example, if the assembly gap in the structural design parameters is too large, it may cause the lithium battery cell to slide and rub in the shell, inducing short circuit and spontaneous combustion; if the value is too small, the critical moment of pressure relief will be earlier than the end moment of thermal abuse conditions, that is, it will not meet the safety standards of thermal abuse. In order to improve the performance and service safety of lithium batteries, researchers have developed a series of important theories and methods for lithium battery safety design. For example, CN202111349288.X discloses a design method for lithium battery expansion space and a device for designing lithium battery expansion space. CN202110808163.2 discloses a simulation analysis method for cylindrical lithium battery structure design. CN202110639563.5 discloses a lithium battery thermal management design method, system, and terminal based on critical heat transfer coefficient. CN202110130622.6 discloses a design method for negative electrode sheet and lithium battery. CN202010104945.3 discloses a lithium battery temperature control method with non-independent thermal design. CN201911253420.X provides a design simulation method for the welding shape of a lithium battery. CN201911112246.7 discloses a design method, system, safety valve and battery for the opening pressure of a lithium battery safety valve. CN201810757329.0 discloses a design method for lithium battery system test conditions based on operating probability characteristics. The above progress shows that it has become a general consensus to improve the performance and safety of lithium batteries from the perspective of structural design. However, there are few reports on the research of lithium battery structural design methods for thermal abuse conditions.

[0004] The challenge is that the evaluation of the state of lithium batteries under thermal abuse conditions involves complex electrochemical and thermodynamic processes, and the state simulation model itself faces challenges in efficiency and convergence. The solution to the structural design of lithium batteries involves nested optimization of simulation models, that is, the outer layer searches for the optimal structural design parameters, and the inner layer solves the state simulation model. The simulation model describes a strongly nonlinear dynamic process, most of which are based on multi-field coupled finite element methods. A single solution is very time-consuming and difficult to converge. The optimization model of the nested simulation model is even more challenging in terms of solution efficiency and convergence. To this end, in view of the structural design problem of lithium batteries, a structural design model suitable for general engineers is established, and an efficient and robust solution method is proposed, which has important engineering significance for improving the performance and safety of lithium batteries. Summary of the invention

[0005] The present invention overcomes the shortcomings of the prior art and provides a hard-pack lithium battery structure design method and related equipment. The method takes meeting the thermal abuse safety standard as the design goal, searches for the optimal assembly gap of the hard-pack lithium battery, and provides a practical tool for optimizing the lithium battery structure design. First, a standard thermal abuse condition is established to establish a safety target for the lithium battery structure design; secondly, a lithium battery state assessment model is established, and a solution method is given to provide a critical moment analysis kernel for the lithium battery structure design; and again, a lithium battery structure design model is constructed to solve the optimal structural design parameters that meet the thermal abuse safety standard.

[0006] To achieve the above purpose, the present invention proposes a hard-pack lithium battery structure design method, which adopts the following technical solutions:

[0007] Step 1: Establish thermal abuse conditions for lithium batteries.

[0008] Step 2: Establish a lithium battery status assessment model.

[0009] Step 3: Solve the lithium battery state assessment model.

[0010] Step 4: Solve for the optimal structural design parameters.

[0011] Furthermore, in step 1, establishing thermal abuse conditions for lithium batteries means hanging a fully charged lithium battery in a hot box with circulating air convection under standard atmospheric pressure, heating the ambient temperature to 403±2K at a rate of 5K per minute, and then keeping it warm for 30 minutes. The thermal abuse condition lasts 3060 seconds, including 1260 seconds of heating time and 1800 seconds of insulation time. If the lithium battery does not experience a pressure relief event under thermal abuse conditions, it is deemed to meet the thermal abuse safety standards.

[0012] Furthermore, in step 2, the process of establishing a lithium battery status assessment model is as follows.

[0013] Step 2.1: Establish the electrochemical sub-model.

[0014] The heat generation equation of lithium batteries under thermal abuse conditions is written as formula (1):

[0015] Q(t)=m A *(h D *v D (t)+h R *v R (t)).

[0016] t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance. D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction. D(t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment.

[0017] The reaction rate of SEI decomposition is expressed as formula (2):

[0018] v D (t) = -dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))).

[0019] f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K). D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D (t) is derived with respect to time. exp represents the exponential operator. The reaction rate of SEI regeneration is expressed as formula (3):

[0020] v R (t) = -dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t))).

[0021] f R Represents the frequency factor of SEI regeneration. x R (t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t). y(t) increases synchronously with x R (t) is reduced and written as formula (4):

[0022] dy / dt=-dx R / dt.

[0023] dy / dt represents the time derivative of y(t).

[0024] The gas production rate is synchronized with the reaction rate, which can be expressed as formula (5):

[0025] dm G / dt=γD *v D (t)+γ R *v R (t)

[0026] dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment. D represents the gas generation coefficient of SEI decomposition, γ R Represents the gas generation coefficient of SEI regeneration.

[0027] Step 2.2: Establish a thermodynamic sub-model. The thermodynamic sub-model includes the heat transfer equation and the gas state equation. The heat transfer equation is derived as equation (6):

[0028] 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt.

[0029] T A (t) represents the current ambient temperature, and dT / dt represents the time derivative of T(t). According to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7):

[0030] T A (t)=298+t / 12,0s≤t<1260s; T A (t)=403,t≥1260s.

[0031] R G represents the conduction thermal resistance from the cell to the casing, which can be expressed as formula (8):

[0032] R G =δ / (K G *A).

[0033] δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity. R A represents the convection thermal resistance from the case to the environment, which is expressed as formula (9):

[0034] R A =1 / (h A *A).

[0035] h A represents the convective heat transfer coefficient. C represents the heat capacity of the battery cell, which can be expressed as formula (10):

[0036] C=c*m B .

[0037] c represents the specific heat capacity of the battery cell, and mB represents the mass of the battery cell.

[0038] The gas state equation is derived as equation (11):

[0039] δ*A*P(t)=R C *m G (t)*T(t).

[0040] P(t) represents the gas pressure at the current moment, R C Represents the gas constant. m G The initial value of (t) is written as formula (12):

[0041] m G 0 =δ*A*P 0 / (R C *T 0 ).

[0042] P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0 =0.103MPa, T 0 =298K.

[0043] The integrated formula (1)-formula (12) forms a lithium battery state assessment model. The input parameters include static parameters and dynamic variable initial values. The static variables are active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (h A ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ). The initial values ​​of the state variables include x D 0 、x R 0 ,y 0 .x D 0 Represents x D The initial value of (t), x R 0 Represents x R The output is t * , t *represents the critical moment when the critical condition is satisfied. The critical condition is P(t)≥P * , P * Indicates the pressure relief valve threshold.

[0044] Furthermore, in step 3, the process of solving the lithium battery state assessment model is as follows.

[0045] Step 3.1: Input parameter assignment. Collect the initial values ​​of static parameters and dynamic variables as input parameters for solving the lithium battery state assessment model.

[0046] Step 3.2: Given solution parameters. Given dt, dt represents the time step of the equal time period discretization method. Given k = 1, k represents the time period sequence number. Given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 Represents the initial value of the dimensionless thickness increment of SEI.

[0047] Step 3.3: Update state variables, including time, ambient temperature, fraction of lithium ions contained in SEI, fraction of lithium ions embedded in SEI, and dimensionless thickness of SEI. Calculate t k :

[0048] t k =k*dt,

[0049] t k Indicates the time of the current period. k Substitute into formula (7) and calculate T A k , T A k Indicates the ambient temperature of the current period. Calculate x D k :

[0050] x D k =x D k-1 +dx D k-1 ,

[0051] x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the fraction of lithium ions contained in SEI in the previous period. Calculate x R k :

[0052] x R k =x R k-1 +dx R k-1 ,

[0053] x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 represents the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period. Calculate y k :

[0054] y k =y k-1 +dy k-1 ,

[0055] y k represents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 Represents the dimensionless thickness increment of SEI in the previous period.

[0056] Step 3.4: Construct static problem. According to formula (6), the static problem of the current period is derived as follows:

[0057] 0.5*Q k =(T k -T A k ) / (R G +R A )+C*(T k -T k-1 ) / dt.

[0058] Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1):

[0059] Q k =m A *(h D *v D k +h R *v R k).

[0060] v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2):

[0061] v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))).

[0062] v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3):

[0063] v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k )).

[0064] Step 3.5: Solve the static problem. The static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 Output result T k 、v D k 、v R k .

[0065] Step 3.6: Calculate the state variable increment. Calculate dx according to formula (2): D k :

[0066] dx D k =-v D k *dt,

[0067] Calculate dx according to formula (3) R k :

[0068] dx R k =-v Rk *dt,

[0069] Calculate dy according to formula (4) k :

[0070] dy k =-y k *dt.

[0071] Step 3.7: Calculate the gas production. Calculate dm according to formula (5): G k :

[0072] dm G k =(γ D *v D k +γ R *v R k )*dt,

[0073] dm G k Indicates the gas production increment in the current period; calculate m G k :

[0074] m G k =m G k-1 +dm G k ,

[0075] m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period.

[0076] Step 3.8: Calculate the gas pressure. According to formula (11), calculate P k :

[0077] P k =m G k *R C *T k / (A*δ)

[0078] P k Indicates the gas pressure during the current period.

[0079] Step 3.9: Determine whether the critical condition is met. The critical condition is rewritten as P k ≥P * If the critical condition is not met, set k = k + 1 and return to step 3.3. If the critical condition is met, output the critical time tC .

[0080] Furthermore, in step 4, the process of solving the optimal structural design parameters is as follows.

[0081] Step 4.1: Select design variables. Select the assembly gap δ as the design variable of the lithium battery to be determined.

[0082] Step 4.2: Construct the optimization equation of design variables. C =t C (δ) represents the critical time t C is a function of δ. Let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, that is, the design variable optimization equation.

[0083] Step 4.3: Solve the design variable optimization equation. Given the optimization interval of δ, that is, the interval with upper and lower boundaries. Use MATLAB@fsolve solver to solve, given the solver's convergence limit of 0.001, given the solution algorithm Levenberg-marquardt, given the initial solution of δ. Output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

[0084] To achieve the above object, the present invention also proposes a hard-pack lithium battery structure design device, the device comprising:

[0085] A first establishment module is used to establish a thermal abuse condition of a lithium battery;

[0086] The second building module is used to build a lithium battery status assessment model;

[0087] The first solution module is used to solve the lithium battery state assessment model;

[0088] The second solution module is used to solve the optimal structural design parameters;

[0089] Among them, establishing thermal abuse conditions for lithium batteries refers to hanging a fully charged lithium battery in a hot box with circulating air convection under standard atmospheric pressure, heating the ambient temperature to 403±2K at a rate of 5K per minute, and then keeping it warm for 30 minutes; the thermal abuse condition lasts 3060 seconds, including 1260 seconds of heating time and 1800 seconds of insulation time; if the lithium battery does not experience a pressure relief event under the thermal abuse conditions, it is deemed to meet the thermal abuse safety standards.

[0090] Furthermore, the second establishing module is specifically used for:

[0091] Establishing electrochemical sub-model;

[0092] The heat generation equation of lithium batteries under thermal abuse conditions is written as formula (1):

[0093] Q(t)=m A *(h D *v D (t)+h R *v R (t));

[0094] t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance; h D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction; v D (t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment; the reaction rate of SEI decomposition is expressed as formula (2):

[0095] v D (t) = -dx D / dt=f D *x D (t)*exp(-E / (R U *T(t));

[0096] f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K); x D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D (t) is derived with respect to time; exp represents the exponential operator; the reaction rate of SEI regeneration is expressed as formula (3):

[0097] v R (t) = -dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t));

[0098] f R represents the frequency factor of SEI regeneration; x R(t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t); y(t) increases synchronously with x R (t) is reduced and written as formula (4):

[0099] dy / dt=-dx R / dt;

[0100] dy / dt represents the time derivative of y(t);

[0101] The gas production rate is synchronized with the reaction rate, which can be expressed as formula (5):

[0102] dm G / dt=γ D *v D (t)+γ R *v R (t);

[0103] dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment; γ D represents the gas generation coefficient of SEI decomposition, γ R represents the gas production coefficient of SEI regeneration;

[0104] A thermodynamic sub-model is established; the thermodynamic sub-model includes the heat transfer equation and the gas state equation; the heat transfer equation is derived as equation (6):

[0105] 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt;

[0106] T A (t) represents the current ambient temperature, dT / dt represents the time derivative of T(t); according to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7):

[0107] T A (t)=298+t / 12,0s≤t<1260s; T A (t) = 403, t ≥ 1260 s;

[0108] R G represents the conduction thermal resistance from the cell to the casing, which can be expressed as formula (8):

[0109] R G =δ / (K G *A);

[0110] δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity; R A represents the convection thermal resistance from the case to the environment, which is expressed as formula (9):

[0111] R A =1 / (h A *A);

[0112] h A represents the convective heat transfer coefficient; C represents the heat capacity of the battery cell, which can be expressed as formula (10):

[0113] C=c*m B ;

[0114] c represents the specific heat capacity of the battery cell, mB represents the mass of the battery cell; the gas state equation is derived as formula (11):

[0115] δ*A*P(t)=R C *m G (t)*T(t);

[0116] P(t) represents the gas pressure at the current moment, R C represents the gas constant; m G The initial value of (t) is written as formula (12):

[0117] m G 0 =δ*A*P 0 / (R C *T 0 );

[0118] P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0 =0.103MPa, T 0 =298K; integrating equations (1)-(12) to form a lithium battery state assessment model; the input parameters include static parameters and dynamic variable initial values; the static variables include active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (hA ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ); the initial values ​​of state variables include x D 0 、x R 0 ,y 0 ;x D 0 Represents x D The initial value of (t), x R 0 Represents x R The initial value of (t); the output result is t * , t * represents the critical moment when the critical condition is satisfied; the critical condition is P(t) ≥ P * , P * Indicates the pressure relief valve threshold.

[0119] Furthermore, the first solution module is specifically used for:

[0120] Assign input parameters; collect static parameters and initial values ​​of dynamic variables as input parameters for solving the lithium battery state assessment model;

[0121] Given solution parameters; given dt, dt represents the time step of the equal time period discretization method; given k = 1, k represents the time period sequence number; given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 represents the initial value of the dimensionless thickness increment of SEI;

[0122] Update state variables; including time, ambient temperature, SEI lithium ion fraction, SEI lithium ion embedded fraction, SEI dimensionless thickness; calculate t k :

[0123] t k =k*dt,

[0124] t k Indicates the time of the current period; t k Substitute into formula (7) and calculate T A k , T A kIndicates the ambient temperature of the current period; calculate x D k :

[0125] x D k =x D k-1 +dx D k-1 ,

[0126] x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1 Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the lithium ion fraction contained in SEI in the previous period; calculate x R k :

[0127] x R k =x R k-1 +dx R k-1 ,

[0128] x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 represents the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period; calculate y k :

[0129] y k =y k-1 +dy k-1 ,

[0130] y k represents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 represents the dimensionless thickness increment of SEI in the previous period;

[0131] Construct a static problem; According to formula (6), the static problem of the current period is derived as follows:

[0132] 0.5*Q k =(T k -T A k ) / (R G +RA )+C*(T k -T k-1 ) / dt;

[0133] Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1):

[0134] Q k =m A *(h D *v D k +h R *v R k );

[0135] v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2):

[0136] v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t));

[0137] v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3):

[0138] v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k ));

[0139] Solve a static problem; the static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 ; Output result T k 、v D k 、v R k ;

[0140] Calculate the state variable increment; calculate dx according to formula (2)D k :

[0141] dx D k =-v D k *dt,

[0142] Calculate dx according to formula (3) R k :

[0143] dx R k =-v R k *dt,

[0144] Calculate dy according to formula (4) k :

[0145] dy k =-y k *dt;

[0146] Calculate the gas production; Calculate dm according to formula (5) G k :

[0147] dm G k =(γ D *v D k +γ R *v R k )*dt,

[0148] dm G k Indicates the gas production increment in the current period; calculate m G k :

[0149] m G k =m G k-1 +dm G k ,

[0150] m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period;

[0151] Calculate the gas pressure; According to formula (11), calculate P k :

[0152] P k =mG k *R C *T k / (A*δ);

[0153] P k Indicates the gas pressure of the current period;

[0154] Determine whether the critical condition is met; the critical condition is rewritten as P k ≥P * ; If the critical condition is not met, set k = k + 1 and return the updated state variable; if the critical condition is met, output the critical time t C .

[0155] Furthermore, the second solution module is specifically used for:

[0156] Select design variables; select assembly gap δ as the design variable of the lithium battery to be determined;

[0157] Construct the optimization equation of design variables; C =t C (δ) represents the critical time t C is a function of δ; let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, i.e., the design variable optimization equation;

[0158] Solve the design variable optimization equation; give the optimization interval of δ, that is, the interval with upper and lower boundaries; use MATLAB@fsolve solver to solve, give the solver's convergence limit 0.001, give the solution algorithm Levenberg-marquardt, and give the initial solution of δ; output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

[0159] To achieve the above object, the present invention further proposes a readable storage medium on which a program is stored, and the program implements the above method when executed by a processor.

[0160] To achieve the above object, the present invention also proposes a computer program product, including computer instructions, which implement the above method when executed by a processor.

[0161] Compared with the prior art, the structural design method of a hard-pack lithium battery of the present invention has the following advantages: In terms of applicability, the method takes meeting the thermal abuse safety standard as the design goal, searches for the optimal assembly gap of the hard-pack lithium battery, and provides a practical tool for optimizing the structural design of the lithium battery. The modeling and solution process has clear steps and does not involve complex finite element or algorithm programming. It is easy for general engineers to master and has good engineering applicability. In terms of efficiency, the solution of the method of the present invention involves the nesting of univariate nonlinear equations, the outer layer solves the optimal assembly gap, and the inner layer solves the battery cell temperature. This process requires executing dozens of univariate nonlinear equation solutions, and theoretically has a computational efficiency of seconds and robust convergence. In terms of accuracy, the optimal assembly gap obtained by the method of the present invention enables the lithium battery to just meet the thermal abuse safety standard, laying a theoretical foundation for precise safety design. BRIEF DESCRIPTION OF THE DRAWINGS

[0162] Figure 1 The structural design method flow of a specific application example of the present invention is shown.

[0163] Figure 2 The temperature evolution curve of a specific application example of the present invention is shown.

[0164] Figure 3 The pressure evolution curve of a specific application example of the present invention is shown.

[0165] Figure 4 The gas production rate evolution curve of a specific application example of the present invention is shown.

[0166] Figure 5 The structural design device process of a specific application example of the present invention is shown. DETAILED DESCRIPTION

[0167] The present invention is further described below in conjunction with an embodiment, but does not constitute any limitation to the present invention. Any limited number of modifications made within the scope of the claims of the present invention are still within the scope of the claims of the present invention.

[0168] The present invention provides a hard-pack lithium battery structure design method, such as Figure 1 As shown, the method includes the following steps.

[0169] In this embodiment, the method of the present invention is applied to 1865132 square and 4680 cylindrical lithium batteries to illustrate the processing steps and method performance. The lithium battery has a battery cell, a shell, and an electrolyte. The anode material of the battery cell is graphite, and the cathode material of the battery cell is lithium cobalt oxide. The electrolyte composition is 15% lithium hexafluorophosphate, 75% propionate carbonate solvent, and 10% additives. The shell is made of 1.0 mm aluminum alloy and has a pressure relief valve.

[0170] Step 1: Establish thermal abuse conditions for lithium batteries. According to GB 31241-2022 "Lithium-ion batteries and battery packs for portable electronic products - Safety requirements", establish thermal abuse conditions for lithium batteries. Figure 2 As shown, a fully charged lithium battery is suspended in a hot box with circulating air convection under standard atmospheric pressure, and the ambient temperature is heated to 403±2K at a rate of 5K per minute, and then kept warm for 30 minutes. The thermal abuse condition lasts for 3060 seconds, including 1260 seconds of heating time and 1800 seconds of holding time. If the lithium battery does not experience a pressure release event under thermal abuse conditions, it is deemed to meet the thermal abuse safety standards specified in GB 31241-2022.

[0171] Step 2: Establish a lithium battery state assessment model. The model contains an electrochemical sub-model and a thermodynamic sub-model. The electrochemical sub-model describes the energy and material conversion in the decomposition and regeneration reaction of the solid electrolyte interface (SEI), and the thermodynamic sub-model characterizes the heat transfer process of the lithium battery and the evolution of the reaction gas state. The electrochemical and thermodynamic sub-models are coupled through state variables to form a lithium battery state assessment model based on a group of ordinary differential equations.

[0172] Step 2.1: Establish the electrochemical sub-model.

[0173] The heat generated by lithium batteries under thermal abuse conditions mainly comes from the decomposition and regeneration reaction of SEI on the graphite anode. The heat generation equation was proposed by Hatchard et al. and is written as formula (1):

[0174] Q(t)=m A *(h D *v D (t)+h R *v R (t)).

[0175] t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance. D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction. D (t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment.

[0176] The reaction rate equation is based on the classic Arrhenius formula. The reaction rate of SEI decomposition is expressed as equation (2):

[0177] v D (t) = -dx D / dt=f D *xD (t)*exp(-E / (R U *T(t))).

[0178] f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K). D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D (t) is derived with respect to time. exp represents the exponential operator. The reaction rate of SEI regeneration is expressed as formula (3):

[0179] v R (t) = -dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t))).

[0180] f R Represents the frequency factor of SEI regeneration. x R (t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t). y(t) increases synchronously with x R (t) is reduced and written as formula (4):

[0181] dy / dt=-dx R / dt.

[0182] dy / dt represents the time derivative of y(t).

[0183] During the electrochemical reaction, gas generation is accompanied by heat generation, and the gas generation rate is synchronized with the reaction rate, which can be expressed as formula (5):

[0184] dm G / dt=γ D *v D (t)+γ R *v R (t)

[0185] dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment.D represents the gas generation coefficient of SEI decomposition, γ R Represents the gas generation coefficient of SEI regeneration.

[0186] Step 2.2: Establish a thermodynamic sub-model. The thermodynamic sub-model includes the heat transfer equation and the gas state equation. The heat transfer equation describes the conduction and convection heat transfer process from the battery cell to the environment. In view of the symmetry of the lithium battery structure and the thermal abuse condition in the thickness direction, according to Kirchhoff's law, the heat transfer equation is derived as equation (6):

[0187] 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt.

[0188] T A (t) represents the current ambient temperature, and dT / dt represents the time derivative of T(t). According to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7):

[0189] T A (t)=298+t / 12,0s≤t<1260s; T A (t)=403,t≥1260s.

[0190] R G It represents the conduction thermal resistance from the cell to the shell, which is related to the gas thermal conductivity, heat exchange area and assembly gap distance, and is expressed as formula (8):

[0191] R G =δ / (K G *A).

[0192] δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity. R A It represents the convection thermal resistance from the shell to the environment, which is related to the heat transfer area and the heat transfer coefficient and is expressed as formula (9):

[0193] R A =1 / (h A *A).

[0194] h A represents the convective heat transfer coefficient. C represents the heat capacity of the battery cell, which is related to the specific heat capacity and the mass of the battery cell and is expressed as formula (10):

[0195] C=c*m B .

[0196] c represents the specific heat capacity of the battery cell, and mB represents the mass of the battery cell.

[0197] The gas state equation describes the equilibrium relationship between the temperature, pressure, and volume of the reaction gas. The hard-pack lithium battery is equipped with a pressure relief valve with a threshold value of less than 2.0 MPa. The temperature of the reaction gas under thermal abuse conditions is higher than 273 K. In accordance with the assumption of ideal gas, the gas state equation is derived as formula (11):

[0198] δ*A*P(t)=R C *m G (t)*T(t).

[0199] P(t) represents the gas pressure at the current moment, R c Represents the gas constant. m G The initial value of (t) is written as formula (12):

[0200] m G 0 =δ*A*P 0 / (R C *T 0 ).

[0201] P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0 =0.103MPa, T 0 =298K.

[0202] The integrated formula (1)-formula (12) forms a lithium battery state assessment model. The input parameters include static parameters and dynamic variable initial values. The static variables are active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (h A ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ). The initial values ​​of the state variables include x D 0 、x R 0 ,y 0 .x D 0 Represents x D The initial value of (t), x R 0 Represents x R The output is t* , t * represents the critical moment when the critical condition is satisfied. The critical condition is P(t)≥P * , P * represents the pressure relief valve threshold, in this embodiment, P * =1.0MPa.

[0203] Step 3: Solve the lithium battery state assessment model. The lithium battery state assessment model uses the equal-period discretization method to discretize the dynamic problem into a series of equal-length static problems. The state value calculated in the previous period is used as the input of the next period, and the lithium battery state of each period is solved sequentially.

[0204] Step 3.1: Input parameter assignment. Collect the initial values ​​of static parameters and dynamic variables as input parameters for solving the lithium battery state assessment model. The same input parameters for 1865132 square and 4680 cylindrical lithium batteries are listed in Table 1, and the unique input parameters are listed in Table 2.

[0205] Table 1

[0206] symbol unit Numeric <![CDATA[h D 、h R ]]> mm 257，1714 <![CDATA[f D 、f R ]]> J / g 1.67E15, 2.50E13 E J / mol 135000 <![CDATA[γ D 、c R ]]> g 0.156，0.142 δ mm 0.1 <![CDATA[K G ]]> W / (mm·K) 0.236 <![CDATA[h A ]]> <![CDATA[W·mm 2 / K]]> 300000 <![CDATA[c,R C ]]> J / (g·K) 0.95，0.21 <![CDATA[x D 0 、x R 0 ,and 0 ]]> - 0.15，0.75，0.97

[0207] Table 2

[0208] symbol unit Prismatic lithium battery Cylindrical lithium battery A <![CDATA[mm 2 ]]> 9257 10116 <![CDATA[m A ]]> g 47.1 72.6 <![CDATA[m B ]]> g 158.6 244.3

[0209] Step 3.2: Given solution parameters. Given dt = 12s, dt represents the time step of the equal time period discretization method. Given k = 1, k represents the time period sequence number. Given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 Represents the initial value of the dimensionless thickness increment of SEI.

[0210] Step 3.3: Update state variables, including time, ambient temperature, fraction of lithium ions contained in SEI, fraction of lithium ions embedded in SEI, and dimensionless thickness of SEI. Calculate t k :

[0211] t k =k*dt,

[0212] t k Indicates the time of the current period. k Substitute into formula (7) and calculate T Ak , T A k Indicates the ambient temperature of the current period. Calculate x D k :

[0213] x D k =x D k-1 +dx D k-1 ,

[0214] x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1 Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the fraction of lithium ions contained in SEI in the previous period. Calculate x R k :

[0215] x R k =x R k-1 +dx R k-1 ,

[0216] x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 represents the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period. Calculate y k :

[0217] y k =y k-1 +dy k-1 ,

[0218] y k represents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 Represents the dimensionless thickness increment of SEI in the previous period.

[0219] Step 3.4: Construct static problem. According to formula (6), the static problem of the current period is derived as follows:

[0220] 0.5*Q k =(T k -TA k ) / (R G +R A )+C*(T k -T k-1 ) / dt.

[0221] Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1):

[0222] Q k =m A *(h D *v D k +h R *v R k ).

[0223] v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2):

[0224] v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))).

[0225] v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3):

[0226] v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k )).

[0227] Step 3.5: Solve the static problem. The static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 Output result T k 、v D k 、v R k .

[0228] Step 3.6: Calculate the state variable increment. Calculate dx according to formula (2): D k :

[0229] dx D k =-v D k *dt,

[0230] Calculate dx according to formula (3) R k :

[0231] dx R k =-v R k *dt,

[0232] Calculate dy according to formula (4) k :

[0233] dy k =-y k *dt.

[0234] Step 3.7: Calculate the gas production. Calculate dm according to formula (5): G k :

[0235] dm G k =(γ D *v D k +γ R *v R k )*dt,

[0236] dm G k Indicates the gas production increment in the current period; calculate m G k :

[0237] m G k =m G k-1 +dm G k ,

[0238] m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period.

[0239] Step 3.8: Calculate the gas pressure. According to formula (11), calculate P k :

[0240] P k =m G k *R C *T k / (A*δ)

[0241] P k Indicates the gas pressure during the current period.

[0242] Step 3.9: Determine whether the critical condition is met. The critical condition is rewritten as P k ≥P * If the critical condition is not met, set k = k + 1 and return to step 3.3. If the critical condition is met, output the critical time t C .

[0243] Step 4: Solve for the optimal structural design parameters.

[0244] Step 4.1: Select design variables. Select the assembly gap as the design variable of the lithium battery to be determined. If the assembly gap is too small, it will not meet the thermal abuse safety standard specified in GB 31241-2022, that is, the temporary moment is earlier than 3060 seconds. If the assembly gap is too large, the lithium battery cell may slide and rub in the shell, inducing short circuit and spontaneous combustion.

[0245] Step 4.2: Construct the optimization equation for design variables. Consider the assembly gap δ as the design variable, t C =t C (δ) represents the critical time t C is a function of δ. Let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, that is, the design variable optimization equation.

[0246] Step 4.3: Solve the optimization equation for the design variables. Given the optimization interval of δ, that is, the interval with upper and lower boundaries. In this embodiment, the optimization interval is [0mm, 5mm]. Solve using MATLAB@fsolve solver, given the convergence limit of the solver is 0.001, given the solution algorithm Levenberg-marquardt, and given the initial solution is 0.1mm. Output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

[0247] In this embodiment, the solution of the structural design parameters of the square lithium battery converged stably after 4 iterations, which took 9 seconds, and the optimal assembly gap was 0.135mm. The solution of the cylindrical lithium battery took 8 iterations and 14 seconds, and the optimal assembly gap was 0.234mm. The computing platform is CORE@3.10GHz / RAM@16GB. The critical pressure release moment of the two lithium batteries is 3060, which just meets the prescribed thermal abuse safety standard. However, according to the initial solution of the assembly gap of 0.1mm given by engineering experience, the temporary moments of the square and cylindrical lithium batteries are 2892 seconds and 2240 seconds, respectively, which cannot meet the thermal abuse safety standard, indicating the engineering significance of the method of the present invention. The solutions of the iterative process of optimizing the structural design parameters of the two batteries are listed in Table 3. In addition, the above solution outputs the evolution curves of the temperature, pressure, and gas production rate of the lithium battery with the optimal assembly gap under thermal abuse conditions, as shown respectively. Figure 2 , Figure 3 , Figure 4 shown.

[0248] Table 3

[0249]

[0250]

[0251] This embodiment shows that a hard-pack lithium battery structure design method provided by the present invention has the following advantages. In terms of applicability, the method takes meeting the thermal abuse safety standard as the design goal, searches for the optimal assembly gap of the hard-pack lithium battery, and provides a practical tool for optimizing the structural design of the lithium battery. The modeling and solution process has clear steps and does not involve complex finite element or algorithm programming. It is easy for general engineers to master and has good engineering applicability. In terms of efficiency, the solution of the method of the present invention takes no more than 15 seconds and has a computational efficiency of seconds. In terms of convergence, the method of the present invention can converge after several iterations and has robust convergence. In terms of accuracy, the optimal assembly gap obtained by the method of the present invention enables the lithium battery to just meet the thermal abuse safety standard, laying a theoretical foundation for precise safety design.

[0252] The present invention also provides a hard-pack lithium battery structure design device, such as Figure 5 As shown, the hard-pack lithium battery structure design device 500 includes:

[0253] A first establishing module 501 is used to establish a thermal abuse condition of a lithium battery;

[0254] The second establishing module 502 is used to establish a lithium battery status assessment model;

[0255] A first solution module 503, used to solve a lithium battery state assessment model;

[0256] The second solution module 504 is used to solve the optimal structural design parameters;

[0257] Among them, establishing thermal abuse conditions for lithium batteries refers to hanging a fully charged lithium battery in a hot box with circulating air convection under standard atmospheric pressure, heating the ambient temperature to 403±2K at a rate of 5K per minute, and then keeping it warm for 30 minutes; the thermal abuse condition lasts 3060 seconds, including 1260 seconds of heating time and 1800 seconds of insulation time; if the lithium battery does not experience a pressure relief event under the thermal abuse conditions, it is deemed to meet the thermal abuse safety standards.

[0258] Further, the second establishing module 502 is specifically used for:

[0259] Establishing electrochemical sub-model;

[0260] The heat generation equation of lithium batteries under thermal abuse conditions is written as formula (1):

[0261] Q(t)=m A *(h D *v D (t)+h R *v R (t));

[0262] t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance; h D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction; v D (t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment; the reaction rate of SEI decomposition is expressed as formula (2):

[0263] v D (t) = -dx D / dt=f D *x D (t)*exp(-E / (R U *T(t));

[0264] f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K); x D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D(t) is derived with respect to time; exp represents the exponential operator; the reaction rate of SEI regeneration is expressed as formula (3):

[0265] v R (t) = -dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t));

[0266] f R represents the frequency factor of SEI regeneration; x R (t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t); y(t) increases synchronously with x R (t) is reduced and written as formula (4):

[0267] dy / dt=-dx R / dt;

[0268] dy / dt represents the time derivative of y(t);

[0269] The gas production rate is synchronized with the reaction rate, which can be expressed as formula (5):

[0270] dm G / dt=γ D *v D (t)+γ R *v R (t);

[0271] dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment; γ D represents the gas generation coefficient of SEI decomposition, γ R represents the gas production coefficient of SEI regeneration;

[0272] A thermodynamic sub-model is established; the thermodynamic sub-model includes the heat transfer equation and the gas state equation; the heat transfer equation is derived as equation (6):

[0273] 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt;

[0274] TA (t) represents the current ambient temperature, dT / dt represents the time derivative of T(t); according to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7):

[0275] T A (t)=298+t / 12,0s≤t<1260s; T A (t) = 403, t ≥ 1260 s;

[0276] R G represents the conduction thermal resistance from the cell to the casing, which can be expressed as formula (8):

[0277] R G =δ / (K G *A);

[0278] δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity; R A represents the convection thermal resistance from the case to the environment, which is expressed as formula (9):

[0279] R A =1 / (h A *A);

[0280] h A represents the convective heat transfer coefficient; C represents the heat capacity of the battery cell, which can be expressed as formula (10):

[0281] C=c*m B ;

[0282] c represents the specific heat capacity of the battery cell, mB represents the mass of the battery cell; the gas state equation is derived as formula (11):

[0283] δ*A*P(t)=R C *m G (t)*T(t);

[0284] P(t) represents the gas pressure at the current moment, R C represents the gas constant; m G The initial value of (t) is written as formula (12):

[0285] m G 0 =δ*A*P 0 / (R C *T 0 );

[0286] P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0=0.103MPa, T 0 =298K; integrating equations (1)-(12) to form a lithium battery state assessment model; the input parameters include static parameters and dynamic variable initial values; the static variables include active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (h A ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ); the initial values ​​of state variables include x D 0 、x R 0 ,y 0 ;x D 0 Represents x D The initial value of (t), x R 0 Represents x R The initial value of (t); the output result is t * , t * represents the critical moment when the critical condition is satisfied; the critical condition is P(t) ≥ P * , P * Indicates the pressure relief valve threshold.

[0287] Furthermore, the first solution module 503 is specifically used for:

[0288] Assign input parameters; collect static parameters and initial values ​​of dynamic variables as input parameters for solving the lithium battery state assessment model;

[0289] Given solution parameters; given dt, dt represents the time step of the equal time period discretization method; given k = 1, k represents the time period sequence number; given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 represents the initial value of the dimensionless thickness increment of SEI;

[0290] Update state variables; including time, ambient temperature, SEI lithium ion fraction, SEI lithium ion embedded fraction, SEI dimensionless thickness; calculate t k :

[0291] t k =k*dt,

[0292] t k Indicates the time of the current period; t k Substitute into formula (7) and calculate T A k , T A k Indicates the ambient temperature of the current period; calculate x D k :

[0293] x D k =x D k-1 +dx D k-1 ,

[0294] x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1 Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the lithium ion fraction contained in SEI in the previous period; calculate x R k :

[0295] x R k =x R k-1 +dx R k-1 ,

[0296] x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 represents the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period; calculate y k :

[0297] y k =y k-1 +dy k-1 ,

[0298] y krepresents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 represents the dimensionless thickness increment of SEI in the previous period;

[0299] Construct a static problem; According to formula (6), the static problem of the current period is derived as follows:

[0300] 0.5*Q k =(T k -T A k ) / (R G +R A )+C*(T k -T k-1 ) / dt;

[0301] Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1):

[0302] Q k =m A *(h D *v D k +h R *v R k );

[0303] v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2):

[0304] v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t));

[0305] v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3):

[0306] v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k ));

[0307] Solve a static problem; the static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 ; Output result T k 、v D k 、v R k ;

[0308] Calculate the state variable increment; calculate dx according to formula (2) D k :

[0309] dx D k =-v D k *dt,

[0310] Calculate dx according to formula (3) R k :

[0311] dx R k =-v R k *dt,

[0312] Calculate dy according to formula (4) k :

[0313] dy k =-y k *dt;

[0314] Calculate the gas production; Calculate dm according to formula (5) G k :

[0315] dm G k =(γ D *v D k +γ R *v R k )*dt,

[0316] dm G k Indicates the gas production increment in the current period; calculate m G k :

[0317] m G k =m Gk-1 +dm G k ,

[0318] m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period;

[0319] Calculate the gas pressure; According to formula (11), calculate P k :

[0320] P k =m G k *R C *T k / (A*δ);

[0321] P k Indicates the gas pressure of the current period;

[0322] Determine whether the critical condition is met; the critical condition is rewritten as P k ≥P * ; If the critical condition is not met, set k = k + 1 and return the updated state variable; if the critical condition is met, output the critical time t C .

[0323] Furthermore, the second solution module 504 is specifically used for:

[0324] Select design variables; select assembly gap δ as the design variable of the lithium battery to be determined;

[0325] Construct the optimization equation of design variables; C =t C (δ) represents the critical time t C is a function of δ; let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, i.e., the design variable optimization equation;

[0326] Solve the design variable optimization equation; give the optimization interval of δ, that is, the interval with upper and lower boundaries; use MATLAB@fsolve solver to solve, give the solver's convergence limit 0.001, give the solution algorithm Levenberg-marquardt, and give the initial solution of δ; output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

[0327] The hard-pack lithium battery structure design device 500 provided by the present invention can realize Figure 1 The various processes implemented by the method embodiment shown can achieve the same beneficial effects, and will not be described again here to avoid repetition.

[0328] The embodiment of the present invention further provides a readable storage medium on which a program is stored. When the program is executed by a processor, each process of the embodiment of the hard-pack lithium battery structure design method is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The readable storage medium is, for example, a ROM, RAM, a magnetic disk or an optical disk.

[0329] The embodiment of the present invention also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of the method embodiment shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0330] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0331] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0332] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for designing a hard-pack lithium battery structure, characterized in that: The method includes the following processing steps: Step 1: Establish thermal abuse conditions for lithium batteries; Step 2: Establish a lithium battery status assessment model; Step 3: Solve the lithium battery state assessment model; Step 4: Solve for the optimal structural design parameters; In the step 1, the establishment of thermal abuse conditions for lithium batteries refers to hanging the fully charged lithium battery in a hot box with circulating air convection under standard atmospheric pressure, heating the ambient temperature to 403±2K at a rate of 5K per minute, and then keeping the temperature for 30 minutes; The thermal abuse condition lasts 3060 seconds, including 1260 seconds of heating time and 1800 seconds of insulation time; if the lithium battery does not experience a pressure relief event under the thermal abuse condition, it is deemed to meet the thermal abuse safety standards.

2. The method according to claim 1, characterized in that: In step 2, the process of establishing the lithium battery status assessment model is: Step 2.1: Establish the electrochemical sub-model; The heat generation equation of lithium batteries under thermal abuse conditions is written as formula (1): Q(t)=m A *(h D *v D (t)+h R *v R (t)); t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance; h D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction; v D (t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment; the reaction rate of SEI decomposition is expressed as formula (2): v D (t)=-dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))); f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K); x D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D (t) is derived with respect to time; exp represents the exponential operator; the reaction rate of SEI regeneration is expressed as formula (3): v R (t)=-dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t))); f R represents the frequency factor of SEI regeneration; x R (t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t); y(t) increases synchronously with x R (t) is reduced and written as formula (4): dy / dt=-dx R / dt; dy / dt represents the time derivative of y(t); The gas production rate is synchronized with the reaction rate, which can be expressed as formula (5): dm G / dt=γ D *v D (t)+γ R *v R (t); dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment; γ D represents the gas generation coefficient of SEI decomposition, γ R represents the gas production coefficient of SEI regeneration; Step 2.2: Establish a thermodynamic sub-model; the thermodynamic sub-model includes the heat transfer equation and the gas state equation; the heat transfer equation is derived as equation (6): 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt; T A (t) represents the current ambient temperature, dT / dt represents the time derivative of T(t); according to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7): T A (t)=298+t / 12,0s≤t<1260s;T A (t)=403,t≥1260s; R G represents the conduction thermal resistance from the cell to the casing, which can be expressed as formula (8): R G =δ / (K G *A); δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity; R A represents the convection thermal resistance from the case to the environment, which is expressed as formula (9): R A =1 / (h A *A); h A represents the convective heat transfer coefficient; C represents the heat capacity of the battery cell, which can be expressed as formula (10): C=c*m B ; c represents the specific heat capacity of the battery cell, mB represents the mass of the battery cell; the gas state equation is derived as formula (11): δ*A*P(t)=R C *m G (t)*T(t); P(t) represents the gas pressure at the current moment, R C represents the gas constant; m G The initial value of (t) is written as formula (12): m G 0 =δ*A*P 0 / (R C *T 0 ); P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0 =0.103MPa, T 0 =298K; integrating equations (1)-(12) to form a lithium battery state assessment model; the input parameters include static parameters and dynamic variable initial values; the static variables include active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (h A ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ); the initial values ​​of state variables include x D 0 、x R 0 ,y 0 ;x D 0 Represents x D The initial value of (t), x R 0 Represents x R The initial value of (t); the output result is t * , t * represents the critical moment when the critical condition is satisfied; the critical condition is P(t) ≥ P * , P * Indicates the pressure relief valve threshold.

3. The method according to claim 1, characterized in that: In step 3, the process of solving the lithium battery state assessment model is: Step 3.1: Input parameter assignment; collect static parameters and dynamic variable initial values ​​as input parameters for solving the lithium battery state assessment model; Step 3.2: Given solution parameters; given dt, dt represents the time step of the equal time period discretization method; given k = 1, k represents the time period sequence number; given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 represents the initial value of the dimensionless thickness increment of SEI; Step 3.3: Update state variables, including time, ambient temperature, fraction of lithium ions contained in SEI, fraction of lithium ions embedded in SEI, dimensionless thickness of SEI; calculate t k : t k =k*dt, t k Indicates the time of the current period; t k Substitute into formula (7) and calculate T A k , T A k Indicates the ambient temperature of the current period; calculate x D k : x D k =x D k-1 +dx D k-1 , x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1 Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the lithium ion fraction contained in SEI in the previous period; calculate x R k : x R k =x R k-1 +dx R k-1 , x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 Indicates the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period; calculate y k : the k =y k-1 +to k-1 , y k represents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 represents the dimensionless thickness increment of SEI in the previous period; Step 3.4: Construct static problem; According to formula (6), the static problem of the current period is derived as follows: 0.5*Q k =(T k -T A k ) / (R G +R A )+C*(T k -T k-1 ) / dt; Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1): Q k =m A *(h D *v D k +h R *v R k ); v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2): v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))); v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3): v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k )); Step 3.5: Solve the static problem; the static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 ; Output result T k ,kk v D 、v R ; Step 3.6: Calculate the state variable increment; calculate dx according to formula (2) D k : dx D k =-v D k *dt, Calculate dx according to formula (3) R k : dx R k =-v R k *dt, Calculate dy according to formula (4) k : of k -y k *your; Step 3.7: Calculate gas production; Calculate dm according to formula (5) G k : dm G k =(γ D *v D k +γ R *v R k )*dt, dm G k Indicates the gas production increment in the current period; calculate m G k : m G k =m G k-1 +dm G k , m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period; Step 3.8: Calculate the gas pressure; According to formula (11), calculate P k : P k =m G k *R C *T k / (A*δ); P k Indicates the gas pressure of the current period; Step 3.9: Determine whether the critical condition is met; the critical condition is rewritten as P k ≥P * ; If the critical condition does not hold, set k = k + 1 and return to step 3.3; If the critical condition holds, output the critical time t C .

4. The method according to claim 1, characterized in that In step 4, the process of solving the optimal structural design parameters is: Step 4.1: Select design variables; Select the assembly gap δ as the design variable of the lithium battery to be determined; Step 4.2: Construct the optimization equation of design variables; C =t C (δ) represents the critical time t C is a function of δ; let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, i.e., the design variable optimization equation; Step 4.3: Solve the optimization equation for the design variables; give the optimization interval of δ, i.e., the interval with upper and lower boundaries; Use MATLAB @fsolve solver to solve, give the solver convergence limit 0.001, give the solution algorithm Levenberg-marquardt, give the initial solution of δ; output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

5. A hard-pack lithium battery structure design device, characterized in that: The device comprises: A first establishment module is used to establish a thermal abuse condition of a lithium battery; The second building module is used to build a lithium battery status assessment model; The first solution module is used to solve the lithium battery state assessment model; The second solution module is used to solve the optimal structural design parameters; Among them, establishing thermal abuse conditions for lithium batteries refers to hanging a fully charged lithium battery in a hot box with circulating air convection under standard atmospheric pressure, heating the ambient temperature to 403±2K at a rate of 5K per minute, and then keeping it warm for 30 minutes; the thermal abuse condition lasts 3060 seconds, including 1260 seconds of heating time and 1800 seconds of insulation time; if the lithium battery does not experience a pressure relief event under the thermal abuse conditions, it is deemed to meet the thermal abuse safety standards.

6. The device according to claim 5, characterized in that The second establishing module is specifically used for: Establishing electrochemical sub-model; The heat generation equation of lithium batteries under thermal abuse conditions is written as formula (1): Q(t)=m A *(h D *v D (t)+h R *v R (t)); t represents the current time, Q(t) represents the heat generation rate at the current time, t represents the current time, m A Indicates the amount of active substance; h D represents the enthalpy change of SEI decomposition reaction, h R represents the enthalpy change of SEI regeneration reaction; v D (t) represents the reaction rate of SEI decomposition at the current moment, v R (t) represents the reaction rate of SEI regeneration at the current moment; the reaction rate of SEI decomposition is expressed as formula (2): v D (t)=-dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))); f D represents the frequency factor of SEI decomposition, E represents the activation energy of SEI, and R U represents the universal gas constant, which is 8.314 J / (mol·K); x D (t) represents the lithium ion fraction contained in SEI at the current moment, T(t) represents the cell temperature at the current moment, and dx D / dt represents x D (t) is derived with respect to time; exp represents the exponential operator; the reaction rate of SEI regeneration is expressed as formula (3): v R (t)=-dx R / dt=f D *x R (t)*exp(-y(t) / y 0 )*exp(-E / (R U *T(t))); f R represents the frequency factor of SEI regeneration; x R (t) represents the fraction of lithium ions embedded in SEI at the current moment, dx R / dt represents x R (t) is derived with respect to time, y(t) represents the dimensionless thickness of SEI, y 0 represents the initial value of y(t); y(t) increases synchronously with x R (t) is reduced and written as formula (4): dy / dt=-dx R / dt; dy / dt represents the time derivative of y(t); The gas production rate is synchronized with the reaction rate, which can be expressed as formula (5): dm G / dt=γ D *v D (t)+γ R *v R (t); dm G / dt means m G (t) derivative with respect to time, m G (t) represents the gas production at the current moment; γ D represents the gas generation coefficient of SEI decomposition, γ R represents the gas production coefficient of SEI regeneration; A thermodynamic sub-model is established; the thermodynamic sub-model includes the heat transfer equation and the gas state equation; the heat transfer equation is derived as equation (6): 0.5*Q(t)=(T(t)-T A (t)) / (R G +R A )+C*dT / dt; T A (t) represents the current ambient temperature, dT / dt represents the time derivative of T(t); according to the thermal abuse conditions of lithium batteries, T A (t) is analyzed as a piecewise function and written as formula (7): T A (t)=298+t / 12,0s≤t<1260s;T A (t)=403,t≥1260s; R G represents the conduction thermal resistance from the cell to the casing, which can be expressed as formula (8): R G =δ / (K G *A); δ represents the assembly clearance, A represents the heat exchange area, K G Represents thermal conductivity; R A represents the convection thermal resistance from the case to the environment, which is expressed as formula (9): R A =1 / (h A *A); h A represents the convective heat transfer coefficient; C represents the heat capacity of the battery cell, which can be expressed as formula (10): C=c*m B ; c represents the specific heat capacity of the battery cell, mB represents the mass of the battery cell; the gas state equation is derived as formula (11): δ*A*P(t)=R C *m G (t)*T(t); P(t) represents the gas pressure at the current moment, R C represents the gas constant; m G The initial value of (t) is written as formula (12): m G 0 =δ*A*P 0 / (R C *T 0 ); P 0 Indicates the initial value of gas pressure, T 0 Indicates the initial value of ambient temperature. According to the thermal abuse conditions, P 0 =0.103MPa, T 0 =298K; integrating equations (1)-(12) to form a lithium battery state assessment model; the input parameters include static parameters and dynamic variable initial values; the static variables include active substance mass (m A ), reaction enthalpy change (h D 、h R ), frequency factor (f D 、f R ), activation energy (E), gas production coefficient (γ D , γ R ), heat transfer area (A), assembly clearance (δ), thermal conductivity (K G ), heat transfer coefficient (h A ), specific heat capacity (c), battery cell mass (m B ), gas constant (R C ); the initial values ​​of state variables include x D 0 、x R 0 ,y 0 ;x D 0 Represents x D The initial value of (t), x R 0 Represents x R The initial value of (t); the output result is t * , t * represents the critical moment when the critical condition is satisfied; the critical condition is P(t) ≥ P * , P * Indicates the pressure relief valve threshold.

7. The device according to claim 5, characterized in that The first solution module is specifically used for: Assign input parameters; collect static parameters and initial values ​​of dynamic variables as input parameters for solving the lithium battery state assessment model; Given solution parameters; given dt, dt represents the time step of the equal time period discretization method; given k = 1, k represents the time period sequence number; given dx D 0 =0,dx R 0 =0,dy 0 =0,dx D 0 Indicates the initial value of the increment of the fraction of lithium ions contained in SEI, dx R 0 represents the initial value of the increment of the SEI embedded lithium ion fraction, dy 0 represents the initial value of the dimensionless thickness increment of SEI; Update state variables; including time, ambient temperature, SEI lithium ion fraction, SEI lithium ion embedded fraction, SEI dimensionless thickness; calculate t k : t k =k*dt, t k Indicates the time of the current period; t k Substitute into formula (7) and calculate T A k , T A k Indicates the ambient temperature of the current period; calculate x D k : x D k =x D k-1 +dx D k-1 , x D k Indicates the fraction of lithium ions contained in SEI in the current period, x D k-1 Indicates the fraction of lithium ions contained in SEI in the previous period, dx D k-1 Indicates the increment of the lithium ion fraction contained in SEI in the previous period; calculate x R k : x R k =x R k-1 +dx R k-1 , x R k represents the SEI embedded lithium ion fraction in the current period, x R k-1 Indicates the fraction of lithium ions embedded in SEI in the previous period, dx R k-1 represents the increment of the SEI embedded lithium ion fraction in the previous period; calculate y k : the k =y k-1 +to k-1 , y k represents the dimensionless thickness of SEI in the current period, y k-1 represents the dimensionless thickness of SEI in the previous period, dy k-1 represents the dimensionless thickness increment of SEI in the previous period; Construct static problems; According to formula (6), the static problem of the current period is derived as follows: 0.5*Q k =(T k -T A k ) / (R G +R A )+C*(T k -T k-1 ) / dt; Q k represents the heat generation rate in the current period, which can be written as follows according to formula (1): Q k =m A *(h D *v D k +h R *v R k ); v D k represents the SEI decomposition reaction rate in the current period, which can be written as follows according to formula (2): v D k =dx D / dt=f D *x D (t)*exp(-E / (R U *T(t))); v R k represents the SEI regeneration reaction rate in the current period, which can be written as follows according to formula (3): v R k =f D *x R k *exp(-y k / y 0 )*exp(-E / (R U *T k )); Solve a static problem; the static problem contains an unknown number T k The nonlinear equation is solved using the MATLAB@fsolve solver, with a convergence limit of 0.001, a solution algorithm Levenberg-marquardt, and an initial solution of T k-1 ; Output result T k 、v D k 、v R k ; Calculate the state variable increment; calculate dx according to formula (2) D k : dx D k =-v D k *dt, Calculate dx according to formula (3) R k : dx R k =-v R k *dt, Calculate dy according to formula (4) k : of k -y k *your; Calculate the gas production; Calculate dm according to formula (5) G k : dm G k =(γ D *v D k +γ R *v R k )*dt, dm G k Indicates the gas production increment in the current period; calculate m G k : m G k =m G k-1 +dm G k , m G k Indicates the gas production in the current period, m G k-1 Indicates the gas production in the previous period; Calculate the gas pressure; According to formula (11), calculate P k : P k =m G k *R C *T k / (A*δ); P k Indicates the gas pressure of the current period; Determine whether the critical condition is met; the critical condition is rewritten as P k ≥P * ; If the critical condition is not met, set k = k + 1 and return the updated state variable; if the critical condition is met, output the critical time t C .

8. The device according to claim 5, characterized in that The second solution module is specifically used for: Select design variables; select assembly gap δ as the design variable of the lithium battery to be determined; Construct the optimization equation of design variables; C =t C (δ) represents the critical time t C is a function of δ; let t C (δ) = 3060s, forming a nonlinear equation with a unique unknown number δ, i.e., the design variable optimization equation; Solve the optimization equation for design variables; give the optimization interval of δ, that is, the interval with upper and lower boundaries; Use MATLAB @fsolve solver to solve, give the solver convergence limit 0.001, give the solution algorithm Levenberg-marquardt, give the initial solution of δ; output δ * ,t C * , δ * represents the optimal assembly clearance that meets the thermal abuse safety standard, t C * Indicates the critical moment of pressure release of lithium battery with optimal assembly gap.

9. A readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

10. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 4.

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