A method for identifying dynamic gas production rate of soft-pack lithium battery and related equipment

Abstract

The present invention provides a method for identifying the dynamic gas production rate of a soft-pack lithium battery and related equipment, and relates to the technical field of lithium battery state analysis. The method includes: establishing a dynamic gas production rate identification device for a lithium battery; implementing a thermal abuse experiment of the lithium battery; establishing a gas production analytical model for the lithium battery; constructing a dynamic gas production rate identification model for the lithium battery; and solving the dynamic gas production rate identification model for the lithium battery. The present invention establishes a gas production rate identification device, obtains the volume change of the lithium battery through a thermal abuse experiment, and uses this as a fitting target to inversely calculate the dynamic gas production rate; the identification device is simple and low-cost, the identification process steps are clear and do not involve complex finite element or algorithm programming, which is easy for general engineers to master and has good engineering applicability. A gas production analytical model of coupled reaction, thermal circuit, and thermodynamic sub-model is constructed, and this is used as the core of the gas production rate identification model, which supports the effectiveness of the gas production rate identification results.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery status analysis, and in particular to a method for identifying the dynamic gas production rate of a soft-pack lithium battery and related equipment. Background Art

[0002] Lithium batteries are currently the most common electrochemical energy storage monomers in electric vehicles, energy storage, and portable electronic devices. High energy density, good cycle capacity, high operating voltage, and low self-discharge rate are the key advantages of lithium batteries for these applications. To meet the application requirements of charge capacity and operating voltage, lithium battery monomers are packaged into battery packs through series and parallel connections. Improving the energy density of lithium battery packs and ensuring their safety are the core tasks of designers. The heat generation and gas production behavior of lithium batteries caused by irreversible electrochemical reactions under thermal abuse conditions are of particular concern. Gas production is accompanied by heat generation, and these gases contain combustible components such as hydrogen, ethylene, and methane. Lithium batteries with exhaust valves may cause the battery pack to catch fire or explode by spraying flammable gases to the outside. For lithium batteries without exhaust valves, gas accumulation causes increased internal stress and deformation. Overpressure and large deformation have a negative impact on the insulating film, electrical and thermal contact, resulting in reduced Coulomb effect and short circuit fire. The safety of the battery pack during service is guaranteed by the battery management system, which predicts the heat generation and gas production behavior of the battery pack and prevents it from evolving into severe performance degradation and thermal runaway. This requires revealing the heat and gas production mechanism of lithium-ion batteries, and building an accurate reaction gas production identification model based on this.

[0003] The analysis of lithium battery gas production mainly relies on experimental analysis of the state and composition of the reaction gas. CN202311199037.7 discloses a lithium battery thermal runaway gas explosion limit device, system and use method to ensure the safety of lithium battery thermal abuse experiments. CN202322299103.X discloses a lithium battery internal gas detection device suitable for multi-channel gas detection, which can analyze the composition of the reaction gas. CN202310033519.9 discloses a lithium battery fire characteristic gas detection method and system based on an array sensor, which can analyze the type and concentration of the reaction gas. CN202221909104.0 discloses a lithium battery energy storage safety gas detection and warning device for lithium battery energy storage station safety warning. CN202322369344.7 discloses a lithium battery gas production measurement device, which uses a pressure sensor to obtain the gas production. CN202222241957.8 discloses a device for online detection of internal gas production in lithium batteries, which can measure gas pressure and composition. CN202011252603.2 discloses a method and device for analyzing the gas production rate of a lithium battery under thermal runaway, which measures the reaction gas pressure and temperature data by implanting sensors.

[0004] The above studies show that the analysis of lithium battery gas production behavior has received widespread attention, and a series of important experimental methods have emerged. However, identifying the dynamic gas production rate of each type of electrochemical reaction is still challenging. First, there are more than a dozen electrochemical reactions that are coupled with the evolution of lithium battery gas production and related to materials and operating conditions. It is difficult to establish a full-stage electrochemical / mechanical / thermal model, and identifying the gas production rate of each reaction based on the model faces theoretical difficulties. Secondly, existing experimental research focuses on lithium batteries with vents, and constructing a non-invasive gas production rate identification device for closed lithium batteries encounters engineering challenges.

[0005] To this end, a gas production analysis model for soft-pack lithium batteries was constructed, and a dynamic gas production rate identification model and solution algorithm were further established to obtain the dynamic gas production rate of each electrochemical reaction under thermal abuse conditions. This has important engineering significance for improving the accuracy of lithium battery status monitoring and the service safety of lithium battery packs. Summary of the invention

[0006] The present invention overcomes the shortcomings of the prior art and provides a method for identifying the dynamic gas production rate of soft-pack lithium batteries and related equipment. The method constructs a gas production rate identification device to obtain the temperature and volume state evolution of lithium batteries under thermal abuse conditions, constructs a heat generation, gas production, and heat transfer model to obtain the state evolution prediction result, establishes a dynamic gas production rate identification model and solution method, and reversely obtains the gas production rate evolution of each reaction based on experiments and numerical fitting.

[0007] To achieve the above object, an embodiment of the present invention provides a method for identifying the dynamic gas generation rate of a soft-pack lithium battery, the method comprising the following processing steps:

[0008] Step S1: Establishing a dynamic gas generation rate identification device for a lithium battery;

[0009] Step S2: performing a thermal abuse test on the lithium battery;

[0010] Step S3: establishing a gas generation analysis model of the lithium battery;

[0011] Step S4: constructing a dynamic gas generation rate identification model of the lithium battery;

[0012] Step S5: solving the dynamic gas generation rate identification model of the lithium battery.

[0013] Further, in step S1, the dynamic gas production rate identification device includes an upper plate, a lower plate, a counterweight, a thermocouple, a mechanical displacement sensor, and a guide column. The dynamic gas production rate identification device is used to identify the dynamic gas production rate of the lithium battery. The lithium battery in a fully charged state is clamped between the upper plate and the lower plate, the thermocouple is placed at the center position between the lithium battery and the lower plate, the counterweight is placed at the center position of the upper surface of the upper plate, the mechanical displacement sensor is fixed to the upper plate, and the two mechanical displacement sensors are symmetrically positioned along the center line of the upper plate, the probe of the mechanical displacement sensor faces the lower plate, the upper plate is fitted with the gap between the guide column and the lower plate, and a temperature test chamber is used to provide thermal abuse conditions for the lithium battery.

[0014] Furthermore, in step S2, the thermal abuse experiment is a thermal abuse experiment implemented according to the thermal abuse conditions based on the dynamic gas production rate identification device, the thermocouple outputs the temperature measurement results of the lithium battery at all times, the mechanical displacement sensor outputs the height measurement results of the lithium battery at all times, and a gas chromatograph is used to analyze the composition of the reaction gas inside the lithium battery after the thermal abuse experiment to obtain the reaction gas constant.

[0015] Furthermore, the thermal abuse condition includes: the temperature of the environment is heated from 25° C. to 230° C. at a rate of 5° C. / min and then kept at this temperature for 20 minutes.

[0016] Furthermore, the lithium battery comprises a battery cell, a soft pack and an electrolyte;

[0017] In the step S3, the modeling process of the gas production analytical model is as follows;

[0018] Step S3.1: Establish the heat generation equation, written as formula (1), that is, Q(t) = Q d (t)+Q r (t)+Q e (t),t∈[0,t (n) ]; t represents the current time, t (n) represents the end time of the thermal abuse experiment, Q(t) represents the heat generation rate of the lithium battery, Q d (t) represents the heat generation rate of SEI decomposition reaction, Q r (t) represents the heat generation rate of SEI regeneration reaction, Q e (t) represents the heat generation rate of the electrolyte decomposition reaction;

[0019] The heat generation rate of the SEI decomposition reaction is expressed as formula (2): Q d (t) = m a ·h d ·v d (t);

[0020] The heat generation rate of the SEI regeneration reaction is expressed as formula (3): Q r (t) = m a ·h r ·v r (t);

[0021] 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 SEI decomposition reaction rate, which can be expressed as formula (4):

[0022] v d (t) = -dx l / dt=f d ·x l (t)·exp(-E d / R u / T c (t));

[0023] f d represents the SEI decomposition reaction frequency, E d represents the SEI decomposition activation energy, T c (t) represents the temperature of the lithium battery, x l (t) represents the SEI lithium ion component, dx l / dt represents x l (t) rate of change; R u represents the universal gas constant, which is 8.324 J / (mol·K);

[0024] v r (t) represents the SEI regeneration reaction rate, which can be expressed as formula (5):

[0025] v r (t) = f r ·x r (t)·exp(-x s (t) / x0-E r / R u / T c (t));

[0026] f r represents the SEI regeneration reaction frequency, E r represents SEI regeneration activation energy, x r (t) represents the lithium ion insertion component of the anode, x s (t) represents the SEI thickness component; x r (t) grows synchronously with x s(t) decreases, and is written as formula (6): dx s / dt=-dx r / dt,dx s / dt represents x s The rate of change of (t), dx r / dt represents x r (t) rate of change;

[0027] The heat generation rate of the electrolyte decomposition reaction is expressed as formula (7): Q e (t) = m e ·h e ·v e (t);

[0028] m e Indicates the mass of electrolyte, h e represents the enthalpy change of the electrolyte decomposition reaction, v e (t) represents the electrolyte decomposition reaction rate, which can be expressed as formula (8):

[0029] v e (t) = -dx e / dt=f e ·x e (t)·(1-x e (t))·exp(-E e / R u / T c (t));

[0030] f e represents the decomposition reaction frequency of the electrolyte, E e represents the activation energy of electrolyte decomposition, x e (t) represents the electrolyte content;

[0031] Step S3.2: Establish the gas production equation, written as formula (9): dm / dt=r d (t)·v d (t)+r r (t)·v r (t)+r e (t)·v e (t);

[0032] dm / dt represents the mass change rate of the reaction gas inside the lithium battery, r d (t) represents the gas production rate of SEI decomposition, r r (t) represents the SEI regeneration rate, r e (t) represents the gas generation rate of electrolyte decomposition;

[0033] Step 3.3: Establish the thermal path model, the process is as follows;

[0034] The heat balance equation between the temperature of the battery cell and the temperature of the environment where the battery cell is located is derived as formula (10):

[0035] 0.5·Q(t)=(T c (t)-T(t)) / R g (t)=(T(t)-T f (t)) / R f =(T f (t)-T a (t)) / R a ;

[0036] T(t) represents the temperature of the reaction gas, T f (t) represents the surface temperature of the lithium battery, T a (t) represents the temperature of the environment; R a represents the convection thermal resistance between the upper plate and the environment, expressed as formula (11): R a =1 / (h a ·A f );A f represents the heat exchange area between the upper plate and the environment, h a Represents the convection coefficient; R f represents the thermal resistance of the upper plate, written as R f =H f / (K f ·A f );H f represents the thickness of the upper plate, K f represents the thermal conductivity of the upper plate; R g (t) represents the thermal resistance of the reaction gas, which is expressed as formula (11): R g (t) = D (t) / (K g A);A represents the heat exchange area between the lithium battery and the upper plate, K g represents the thermal conductivity of the reaction gas, and D(t) represents the gap thickness from the battery cell to the soft pack;

[0037] Step 3.4: Establish the thermodynamic sub-model. The process is as follows;

[0038] The state equation of the reaction gas is derived as formula (12): P = 0.5·m(t)·R·T(t) / (D(t)·A); R represents the reaction gas constant; P represents the pressure of the reaction gas, which is equal to the atmospheric pressure of the environment; the height of the lithium battery is written as formula (13): H(t) = H0+2·D(t); H(t) represents the height of the lithium battery, and H0 represents the initial value of the height.

[0039] Furthermore, in step S4, the dynamic gas production rate identification model is expressed as formula (14):

[0040] min(r d (k) ,r r (k) ,r e (k) )E R =abs(H(t (k) )-H E (t (k) )),k=1,2,...,n;

[0041] str d (k) >0,r r (k) >0,r e (k) >0;

[0042] H E (t (k) ) represents the height measurement result of the lithium battery, which is written as formula (15): H E (t (k) )=H0+(k-1)·dH;t (k) represents the kth discrete moment, k represents the discrete step number, n represents the discrete number; dH represents the equal height difference, which can be written as formula (16): dH = (H E (t (n) )-H0)) / n;H E (t (n) ) represents the height measurement result at the end time; H(t (k) ) represents the height prediction result at the k-th discrete moment, obtained by solving the gas production analytical model; abs represents the absolute value operator, min represents the minimization operator, and st represents the constraint operator; E R represents the fitting error; r d (k) represents the SEI decomposition gas production rate at the kth discrete moment, r r (k) represents the SEI regeneration rate at the kth discrete moment, r e (k) represents the gas production rate of electrolyte decomposition at the kth discrete moment; the value of n is established as formula (17): n<(H E (t (n) )-H0) / H S ;H S Indicates the resolution of a mechanical displacement sensor.

[0043] Further, in the step S5, the process of solving the dynamic gas generation rate identification model of the lithium battery is as follows;

[0044] Step S5.1: Determine the parameters of the dynamic gas production rate identification model, including operating parameters, geometric characteristics, electrochemical properties, and thermodynamic properties, which are summarized from the gas production analytical model; the operating parameters include P, T a (t), h a ; The geometric features include A, H0, A f , H f , the thermodynamic properties include K f , K g , R, the electrochemical properties include h d 、h r 、h e 、f d 、f r 、f e 、E d 、E r 、E e 、m a 、m e 、m 0 、x l 0 、x r 0 、x s 0 、x e 0 ;m 0 represents the initial mass value of the reaction gas inside the lithium battery, x l 0 represents the initial value of SEI lithium ion component, x r 0 represents the initial value of the lithium ion component inserted into the anode, x s 0 represents the initial value of the SEI thickness component, x e 0 Indicates the initial value of the electrolyte component;

[0045] Step S5.2: Determine a discrete number, the process is to determine the discrete number according to formula (17);

[0046] Step S5.3: extracting discrete data of equal height difference, the process is to extract the height measurement result of the discrete moment from the height measurement result according to formula (15);

[0047] Step S5.4: Calculate the dynamic gas production rate, the process is to solve equation (14) to obtain the SEI decomposition gas production rate, the SEI regeneration gas production rate, the electrolyte decomposition gas production rate, and the predicted results of the surface temperature of the lithium battery at the discrete moment;

[0048] Step S5.5: Verify the gas production rate identification result. The process is to compare the temperature measurement result with the predicted result of the surface temperature. If the maximum error is less than 2°C, the verification is passed.

[0049] The embodiment of the present invention further provides a system for identifying the dynamic gas generation rate of a soft-pack lithium battery, the system comprising:

[0050] The first establishment module is used to establish a dynamic gas generation rate identification device for a lithium battery;

[0051] An implementation module, used to implement a thermal abuse experiment of the lithium battery;

[0052] The second establishment module is used to establish a gas production analysis model of the lithium battery;

[0053] A construction module, used to construct a dynamic gas generation rate identification model of the lithium battery;

[0054] The solution module is used to solve the dynamic gas generation rate identification model of the lithium battery.

[0055] 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, the above-mentioned method for identifying the dynamic gas production rate of a soft-pack lithium battery is implemented.

[0056] An embodiment of the present invention further provides a computer program product, including computer instructions, which, when executed by a processor, implement the above-mentioned method for identifying the dynamic gas generation rate of a soft-pack lithium battery.

[0057] Compared with the prior art, the method for identifying the dynamic gas production rate of a soft-pack lithium battery of the present invention has the advantages that the method of the present invention can identify the gas production rate and temperature evolution curve under thermal abuse conditions. A gas production rate identification device is established, and the volume change of the lithium battery is obtained through thermal abuse experiments, and the dynamic gas production rate is inversely calculated based on this as the fitting target; the identification device is simple and low-cost, the identification process steps are clear and do not involve complex finite element or algorithm programming, which is easy for general engineers to master and has good engineering applicability. A gas production analytical model of coupled reaction, thermal circuit, and thermodynamic sub-model is constructed, and this is used as the core of the gas production rate identification model, which supports the effectiveness of the gas production rate identification results. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A schematic flow chart of a method for identifying the dynamic gas production rate of a soft-pack lithium battery according to a specific application example of the present invention is shown.

[0059] Figure 2 The schematic diagram of the structure of the dynamic gas production rate identification device of the soft-pack lithium battery of the specific application example of the present invention is shown.

[0060] Figure 3The thermal circuit model of a specific application example of the present invention is shown.

[0061] Figure 4 The sample height measurement results of a specific application example of the present invention are shown.

[0062] Figure 5 The calculation results of the SEI decomposition gas production rate of a specific application example of the present invention are shown.

[0063] Figure 6 The calculation results of the SEI regeneration gas rate of a specific application example of the present invention are shown.

[0064] Figure 7 The calculation results of the gas production rate of electrolyte decomposition of a specific application example of the present invention are shown.

[0065] Figure 8 The temperature prediction and measurement comparison of sample 1 of a specific application example of the present invention is shown.

[0066] Fig. 9 The temperature prediction and measurement comparison of sample 2 of a specific application example of the present invention is shown.

[0067] Fig.10 The temperature prediction and measurement comparison of sample 3 of a specific application example of the present invention is shown.

[0068] Fig.11 The schematic diagram of the structure of the dynamic gas production rate identification system of the soft-pack lithium battery of the specific application example of the present invention is shown.

[0069] Figure numerals: 20, lithium battery; 21, upper plate; 22, lower plate; 23, counterweight; 24, thermocouple; 25, mechanical displacement sensor; 26, guide column; 30, lithium battery model; 31, upper plate model; 32, battery cell; 33, reaction gas; 34, soft pack. DETAILED DESCRIPTION

[0070] 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.

[0071] The present invention provides a method for identifying the dynamic gas production rate of a soft-pack lithium battery. Figure 1 As shown, the method comprises the following steps: Step S1: establishing a dynamic gas generation rate identification device for a lithium battery;

[0072] Step S2: performing a thermal abuse test on the lithium battery;

[0073] Step S3: establishing a gas generation analysis model of the lithium battery;

[0074] Step S4: constructing a dynamic gas generation rate identification model of the lithium battery;

[0075] Step S5: solving the dynamic gas generation rate identification model of the lithium battery.

[0076] In the embodiment of the present invention, the method can be applied to three lithium batteries to illustrate the processing steps and method performance. The lithium batteries are all rectangular and have a battery cell, a soft pack and an electrolyte. The soft pack is made of a 0.088mm thick aluminum-plastic film, the battery cell type is a graphite anode and a lithium cobalt oxide cathode, and the electrolyte composition is 25% lithium hexafluorophosphate, 75% propionate carbonate solvent, and 20% additives.

[0077] Step S1: Establish a lithium battery dynamic gas production rate identification device. Figure 2 As shown, the identification device includes an upper plate 21, a lower plate 22, a counterweight 23, a thermocouple 24, two mechanical displacement sensors 25, and four guide columns 26, which are used to identify the dynamic gas production rate of the lithium battery 20. The lithium battery 20 in a fully charged state is clamped between the upper plate 21 and the lower plate 22, and the contact surface is evenly coated with thermal grease. The thermocouple 24 is placed at the center between the lithium battery 20 and the lower plate 22, and the counterweight 23 is placed at the center of the upper surface of the upper plate 21. The mechanical displacement sensor 25 is fixed at a symmetrical position of the center line of the upper plate 21, and the probe of the mechanical displacement sensor 25 faces the lower plate 22. The guide column 26 is fixed at the four corners of the lower plate 22, and forms an axial clearance with the circular through holes at the four corners of the upper plate 21. A temperature test chamber is used to provide thermal abuse conditions for lithium batteries, that is, the ambient temperature is heated from 25°C to 230°C at a rate of 5°C / minute and then kept warm for 20 minutes.

[0078] The identification device has the following advantages. ① The counterweight provides a fixed normal pressure to ensure that the gap from the soft pack to the battery cell is uniform when the lithium battery expands. The isobaric and uniform high conditions can simplify the state equation of the reaction gas. ② The thermal grease provides a uniform low thermal resistance heat conduction condition, which can simplify the thermal circuit model. ③ The mechanical displacement sensor has higher environmental adaptability than the digital sensor, which solves the problem of online displacement measurement in high temperature environment (230°C). ④ The self-lubricating Teflon column provides a normal resistance-free displacement condition, eliminating the error of displacement measurement. ⑤ The thermal abuse condition induces irreversible electrochemical reactions inside the stationary lithium battery, providing a clear reaction mechanism for identifying the gas production coefficient. In short, the experimental design avoids expensive test instruments (such as neutron imagers) and complex electrochemical reactions. The experimental tooling is simple and easy to use and minimizes the difficulty of identifying the gas production rate.

[0079] In this embodiment, the upper plate 21 and the lower plate 22 are made of aluminum alloy AL6061, the weight of the counterweight 23 is 1 kg, the thermocouple 24 is of type K-type / range -50°C-500°C, the mechanical displacement sensor 25 is of type KPZ / range 0.01 mm-20 mm, the guide column is made of polytetrafluoroethylene, the temperature test chamber is of type BTL-D2-408CT / LABCOMPANION, and the thermal grease is of type PTM7950SP / thermal resistance 0.04 cm2·K / W. The thermal abuse conditions refer to "Lithium-ion Batteries and Battery Packs for Portable Electronic Products - Safety Requirements" (GB / T 32241), which can induce irreversible electrochemical reactions inside the stationary lithium battery, including SEI decomposition, SEI regeneration, electrolyte decomposition, and release of heat and gas.

[0080] Step S2: Implementing a thermal abuse experiment of a lithium battery, that is, implementing the thermal abuse experiment based on the identification device according to the thermal abuse conditions, the thermocouple 24 outputs the temperature measurement results of the lithium battery 20 at all times, and the mechanical displacement sensor 25 outputs the height measurement results of the lithium battery 20 at all times; using a gas chromatograph to analyze the gas composition inside the lithium battery 20 after the thermal abuse experiment to obtain a reaction gas constant. In this embodiment, the gas chromatograph model is 7890B / AGILENT.

[0081] Step S3: Establishing a lithium battery gas generation analysis model.

[0082] The analysis model is established based on the identification device and the thermal abuse experiment. First, a reaction sub-model is established, including a heat generation equation and a gas production equation, incorporating SEI decomposition reaction, SEI regeneration reaction and electrolyte decomposition. Secondly, a thermal circuit model is established to describe the temperature evolution of the lithium battery under thermal abuse conditions. A thermodynamic sub-model is constructed again to simulate the volume evolution under fixed pressure and time-varying temperature. The reaction sub-model outputs the heat generation rate and gas production, which serve as the heat source of the thermal circuit model and the gas source of the thermal sub-model respectively, and the reaction rate is determined by the temperature output by the thermal circuit model. The temperature output by the thermal circuit model determines the change in the gas state in the thermal sub-model, and the gas gap obtained by the thermal sub-model determines the thermal resistance from the battery cell to the environment. The three sub-models are bidirectionally coupled through state quantities such as heat generation, gas production, temperature, and thermal resistance.

[0083] The process of establishing the gas production analysis model is as follows.

[0084] Step S3.1: Establish the heat generation equation, written as formula (1), that is, Q(t) = Q d (t)+Q r (t)+Q e (t),t∈[0,t (n) ]; t represents the current time, t (n)represents the end time of the thermal abuse experiment, Q(t) represents the heat generation rate of the lithium battery 20, and Q d (t) represents the heat generation rate of the SEI decomposition reaction, Q r (t) represents the heat generation rate of the SEI regeneration reaction, Q e (t) represents the heat generation rate of the electrolyte decomposition reaction.

[0085] The heat generation rate equation of SEI decomposition and regeneration reaction was proposed by Hatchard et al. based on the law of conservation of energy and is widely used in the analysis of heat generation of lithium batteries. The heat generation rate of SEI decomposition reaction is expressed as formula (2): Q d (t) = m a ·h d ·v d (t); The heat generation rate of the SEI regeneration reaction is expressed as formula (3): Q r (t) = m a ·h r ·v r (t); 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. d (t) represents the SEI decomposition reaction rate, which can be expressed as formula (4):

[0086] v d (t) = -dx l / dt=f d ·x l (t)·exp(-E d / R u / T c (t));

[0087] f d represents the SEI decomposition reaction frequency, E d represents the SEI decomposition activation energy, T c (t) represents the temperature of the lithium battery, x l (t) represents the SEI lithium ion component, dx l / dt represents x l (t) Rate of change. R u represents the universal gas constant, which is 8.324 J / (mol·K). r (t) represents the SEI regeneration reaction rate, which can be expressed as formula (5):

[0088] v r (t) = f r ·x r (t)·exp(-x s (t) / x0-E r / Ru / T c (t));

[0089] f r represents the SEI regeneration reaction frequency, E r represents SEI regeneration activation energy, x r (t) represents the lithium ion insertion component of the anode, x s (t) represents the SEI thickness component. r (t) grows synchronously with x s (t) decreases, and is written as formula (6): dx s / dt=-dx r / dt,dx s / dt represents x s The rate of change of (t), dx r / dt represents x r The rate of change of (t).

[0090] The heat generation rate of the electrolyte decomposition reaction is referred to MacNeil's research and is expressed as formula (7): Q e (t) = m e ·h e ·v e (t); m e Indicates the mass of electrolyte, h e represents the enthalpy change of the electrolyte decomposition reaction, v e (t) represents the decomposition reaction rate of the electrolyte, which is expressed as formula (8):

[0091] v e (t) = -dx e / dt=f e ·x e (t)·(1-x e (t))·exp(-E e / R u / T c (t));

[0092] f e represents the decomposition reaction frequency of the electrolyte, E e represents the activation energy of electrolyte decomposition, x e (t) represents the amount of electrolyte.

[0093] Step S3.2: Establishing the gas production equation.

[0094] Existing studies have verified that the gas production rate is roughly synchronized with the reaction rate. Conventional practice assumes that the gas production rate is a fixed value. The method of the present invention aims to reveal the nonlinear evolution of the gas production rate without introducing the fixed value assumption. The gas production rate of each reaction is synchronized with the reaction rate, and the change rate of gas production of lithium batteries is the sum of the change rates of gas production of all reactions.

[0095] The gas production equation is written as formula (9): dm / dt=r d (t)·v d (t)+r r (t)·v r (t)+r e (t)·v e (t); dm / dt represents the mass change rate of the reaction gas, r d (t) represents the gas production rate of SEI decomposition, r r (t) represents the SEI regeneration rate, r e (t) represents the gas generation rate of electrolyte decomposition.

[0096] The heat generation equation in step 3.1 and the gas generation equation in step 3.2 constitute the reaction sub-model.

[0097] Step 3.3: Establish a thermal path model. The modeling ideas are as follows: ① Use DC source, potential, resistance, and capacitance to describe heat source, temperature, thermal resistance, and heat capacity respectively; ② Lithium batteries have uniform electrochemical and thermodynamic properties because the temperature difference in the thickness direction of lithium batteries is small; ③ Consider the symmetry of boundary conditions and use the half-side structure of the identification device as the modeling object. ④ Ignore the heat capacity effect because the heat capacity of the reaction gas and the upper and lower plates is small; ⑤ The identification device and The heat exchange between the test chamber and the test chamber is uniform because the temperature test chamber provides good air circulation. Figure 3 As shown, the lithium battery model 30 corresponds to Figure 2 The lithium battery 20 in the upper plate model 31 corresponds to Figure 2 The upper plate 21 in the lithium battery model includes a battery cell 32, a reaction gas 33, and a soft pack 34.

[0098] The process of establishing the thermal circuit model is as follows.

[0099] According to Kirchhoff's law, the heat balance equation from the lithium battery cell 32 to the environment is derived as equation (10):

[0100] 0.5·Q(t)=(T c (t)-T(t)) / R g (t)=(T(t)-T f (t)) / R f =(T f (t)-T a (t)) / R a T(t) represents the reaction gas temperature, T f (t) represents the surface temperature of the lithium battery, T a (t) represents the ambient temperature. arepresents the convection thermal resistance between the upper plate and the environment, which is determined by the convection coefficient and the heat transfer area and is expressed as formula (11): R a =1 / (h a ·A f );A f represents the heat exchange area between the upper plate and the environment, h a Represents the convection coefficient; R f It represents the thermal resistance of the upper plate, which is determined by the thermal conductivity, heat transfer area and heat transfer distance, and is written as R f =H f / (K f ·A f );H f represents the thickness of the upper plate, K f R represents the thermal conductivity of the upper plate. g (t) represents the thermal resistance of the reaction gas, which can be expressed as formula (11): R g (t) = D (t) / (K g A);A represents the heat exchange area between the lithium battery and the upper plate, K g represents the thermal conductivity of the reaction gas, and D(t) represents the gap thickness from the battery cell to the soft pack.

[0101] The gap is filled with reactive gas. As the reactive gas increases, the thickness of the gap increases, resulting in a dynamic change in the thermal resistance of the reactive gas. The reactive sub-model and the thermal circuit sub-model form a bidirectional coupling through the cell temperature and the reactive gas thermal resistance.

[0102] Step 3.4: Establish the thermodynamic sub-model. The process is as follows.

[0103] The pressure of the reaction gas is much less than 2Mpa, and the temperature is higher than 0°C. Therefore, it can be equivalent to an ideal gas. The gas state equation is derived as formula (12): P = 0.5·m(t)·R·T(t) / (D(t)·A); R represents the reaction gas constant, which is obtained according to the gas composition analysis results in the identification experiment. P represents the pressure of the reaction gas. In the identification device, isobaric conditions are established, and P is fixed and equal to the ambient pressure. The height of the lithium battery changes dynamically, as written in formula (13): H(t) = H0+2·D(t); H(t) represents the height of the lithium battery, and H0 represents the initial value of the lithium battery height. The thermodynamic sub-model is coupled through the reaction gas temperature, mass and reaction sub-model, and is coupled with the thermal circuit sub-model through the gap thickness and gas temperature.

[0104] In summary, the gas production analytical model is a set of equations formed by equations (1) to (13).

[0105] Step S4: construct a lithium battery dynamic gas production rate identification model, written as formula (14):

[0106] min(r d (k) ,r r (k) ,r e (k) )E R =abs(H(t (k) )-H E (t (k) )),k=1,2,...,n

[0107] str d (k) >0,r r (k) >0,r e (k) >0

[0108] H E (t (k) ) represents the height measurement result obtained by discretizing the height difference in the thermal abuse experiment, which is written as formula (15): H E (t (k) )=H0+(k-1)·dH;t (k) represents the kth discrete moment, k represents the discrete step number, n represents the discrete number; dH represents the equal height difference, which is written as formula (16): dH = (H E (t (n) )-H0)) / n;H E (t (n) ) represents the height measurement result at the end time. (k) ) indicates t (k) The height prediction result at the time is obtained by solving the gas production analytical model. abs represents the absolute value operator, min represents the minimization operator, and st represents the constraint operator. R represents the fitting error. d (k) represents the SEI decomposition gas production rate at the kth discrete moment, r r (k) represents the SEI gas reproduction rate at the kth discrete moment, r e (k) represents the gas production rate of electrolyte decomposition at the kth discrete moment.

[0109] In this embodiment, the solver for solving the gas production analytical model is MATLAB / ODE45.

[0110] The larger the discrete number is, the more it can capture the nonlinear evolution of the gas production rate, but it is limited by the resolution of the displacement sensor. The principle of n is established as formula (17): n<(H E (t (n))-H0) / H S ;H S Indicates the resolution of the mechanical displacement sensor.

[0111] The thermal abuse experiment provides a uniform height condition. The height change of the lithium battery is equivalent to the volume change. The identification model searches for the gas production rate at each discrete moment by fitting the lithium battery volume measurement and prediction results.

[0112] Step S5: Solve the dynamic gas generation rate identification model of the lithium battery, the process is as follows.

[0113] Step S5.1: Determine the identification model parameters, including operating parameters, geometric characteristics, electrochemical properties, and thermodynamic properties, which are summarized from the gas production analysis model. The operating parameters include P, T a (t), h a . Geometric features include A, H0, A f , H f , thermodynamic properties include K f , K g , R, electrochemical properties include h d 、h r 、h e 、f d 、f r 、f e 、E d 、E r 、E e 、m a 、m e 、m 0 、x l 0 、x r 0 、x s 0 、x e 0 . m 0 represents the initial value of the gas production, x l 0 represents the initial value of the SEI lithium ion component, x r 0 represents the initial value of the lithium ion component inserted into the anode, x s 0 represents the initial value of the SEI thickness component, x e 0 Indicates the initial value of the electrolyte content.

[0114] The operating parameters are determined by the thermal abuse experimental conditions. The geometric characteristics can be directly measured, the thermodynamic properties are extracted from the literature, and the electrochemical properties are extracted from the product specifications provided by the lithium battery manufacturer. In this embodiment, the same identification model parameters of the three lithium battery samples are listed in Table 1, and the different identification model parameters are listed in Table 2.

[0115] Table 1

[0116]

[0117] Table 2

[0118] parameter unit Sample 1 Sample 2 Sample 3 <![CDATA[H0]]> mm 4.8 5.8 5.0 A 4408 5642 6018 <![CDATA[m a 、m e ]]> g 15.2,7.3 23.3,10.8 21.1,10.1 R J / (g·K) 0.208 0.206 0.211

[0119] Step S5.2: Determine a discrete number. The process is to determine the discrete number according to formula (17).

[0120] In this embodiment, the resolution of the mechanical displacement sensor is 0.001 mm, and the discrete numbers of the three lithium battery samples are determined to be the same value: 150.

[0121] Step S5.3: extracting discrete data with equal height difference, the process is to extract the height measurement result at the discrete moment from the height measurement result according to formula (15).

[0122] In this embodiment, the height measurement results at all times are as follows: Figure 4 , the height difference discrete data are listed in Table 3.

[0123] Table 3

[0124]

[0125] Step S5.4: Calculate the dynamic gas production rate. The process is to solve equation (14) to obtain the SEI decomposition gas production rate, the SEI regeneration gas production rate, the electrolyte decomposition gas production rate, and the lithium battery surface temperature prediction result at the discrete moment.

[0126] In this embodiment, the solver for solving equation (14) is MATLAB / fsolve, each solving process takes less than 10 seconds, and the computing platform is CORE 3.10GHz / RAM 16GB. The calculation results of the gas production rate of samples 1, 2, and 3 are listed in Table 4, Table 5, and Table 6, respectively. The gas production rate evolution curve is shown in Figure 5 , Figure 6 , Figure 7 .

[0127] Table 4

[0128]

[0129] Table 5

[0130]

[0131]

[0132] Table 6

[0133]

[0134] Step S5.5: Verify the gas production rate identification result. The process is to compare the temperature measurement result with the lithium battery surface temperature prediction result. If the maximum error is less than 2°C, the verification is passed.

[0135] The gas production analysis model is the core of the gas production rate identification model. Temperature is the key state quantity that links the reaction, heat circuit, and thermodynamic sub-model. The temperature prediction accuracy can verify the effectiveness of the gas production analysis model, thereby verifying the dynamic gas production rate identification results. In this embodiment, the maximum errors of the temperature prediction of the three samples are 0.60℃, 0.58℃, and 0.59℃, respectively. The comparison between the measured results and the predicted results is shown in Figure 2. Figure 8 , Fig. 9 , Fig.10 .

[0136] This embodiment shows that the method for identifying the dynamic gas production rate of a soft-pack lithium battery provided by the method of the present invention has the following advantages. In terms of applicability, the method establishes a gas production rate identification device, obtains the volume change of the lithium battery through a thermal abuse experiment, and uses this as the fitting target to inversely calculate the dynamic gas production rate; the identification device is simple and low-cost, the identification process steps are clear and do not involve complex finite element or algorithm programming, which is easy for general engineers to master and has good engineering applicability. In terms of accuracy, a gas production analytical model of coupled reactions, thermal circuits, and thermodynamic sub-models is constructed, and this is used as the core of the gas production rate identification model. The temperature prediction results are very close to the measurement results, which supports the effectiveness of the gas production rate identification results. In addition, the method of the present invention identifies the gas production rate and temperature evolution curves under thermal abuse conditions, and the identification and solution process has a time consumption of seconds and robust convergence.

[0137] The embodiment of the present invention also provides a dynamic gas generation rate identification system for soft-pack lithium batteries, such as Fig.11 As shown, the dynamic gas generation rate identification system 1100 of a soft-pack lithium battery includes:

[0138] The first establishing module 1101 is used to establish a dynamic gas generation rate identification device for a lithium battery;

[0139] An implementation module 1102 is used to implement a thermal abuse experiment of the lithium battery;

[0140] The second establishing module 1103 is used to establish a gas generation analysis model of the lithium battery;

[0141] A construction module 1104 is used to construct a dynamic gas generation rate identification model of the lithium battery;

[0142] A solution module 1105, used for solving a dynamic gas generation rate identification model of the lithium battery;

[0143] Among them, the dynamic gas production rate identification device includes an upper plate, a lower plate, a counterweight, a thermocouple, a mechanical displacement sensor, and a guide column. The dynamic gas production rate identification device is used to identify the dynamic gas production rate of the lithium battery. The lithium battery in a fully charged state is clamped between the upper plate and the lower plate, the thermocouple is placed at the center position between the lithium battery and the lower plate, the counterweight is placed at the center position of the upper surface of the upper plate, the mechanical displacement sensor is fixed to the upper plate, and the two mechanical displacement sensors are symmetrically positioned along the center line of the upper plate, the probe of the mechanical displacement sensor faces the lower plate, the upper plate is matched with the lower plate through the gap between the guide column, and a temperature test chamber is used to provide thermal abuse conditions for the lithium battery.

[0144] Wherein, the lithium battery comprises a battery cell, a soft pack and an electrolyte;

[0145] The modeling process of the gas production analytical model is as follows;

[0146] Establish the heat generation equation and write it as formula (1), that is, Q(t) = Q d (t)+Q r (t)+Q e (t),t∈[0,t (n) ]; t represents the current time, t (n) represents the end time of the thermal abuse experiment, Q(t) represents the heat generation rate of the lithium battery, Q d (t) represents the heat generation rate of SEI decomposition reaction, Q r (t) represents the heat generation rate of SEI regeneration reaction, Q e (t) represents the heat generation rate of the electrolyte decomposition reaction;

[0147] The heat generation rate of the SEI decomposition reaction is expressed as formula (2): Q d (t) = m a ·h d ·v d (t);

[0148] The heat generation rate of the SEI regeneration reaction is expressed as formula (3): Q r (t) = m a ·h r ·v r (t);

[0149] m a Indicates the amount of active substance, h drepresents the enthalpy change of SEI decomposition reaction, h r represents the enthalpy change of SEI regeneration reaction; v d (t) represents the SEI decomposition reaction rate, which can be expressed as formula (4):

[0150] v d (t) = -dx l / dt=f d ·x l (t)·exp(-E d / R u / T c (t));

[0151] f d represents the SEI decomposition reaction frequency, E d represents the SEI decomposition activation energy, T c (t) represents the temperature of the lithium battery, x l (t) represents the SEI lithium ion component, dx l / dt represents x l (t) rate of change; R u represents the universal gas constant, which is 8.324 J / (mol·K);

[0152] v r (t) represents the SEI regeneration reaction rate, which can be expressed as formula (5):

[0153] v r (t) = f r ·x r (t)·exp(-x s (t) / x0-E r / R u / T c (t));

[0154] f r represents the SEI regeneration reaction frequency, E r represents SEI regeneration activation energy, x r (t) represents the lithium ion insertion component of the anode, x s (t) represents the SEI thickness component; x r (t) grows synchronously with x s (t) decreases, and is written as formula (6): dx s / dt=-dx r / dt,dx s / dt represents x s The rate of change of (t), dx r / dt represents x r (t) rate of change;

[0155] The heat generation rate of the electrolyte decomposition reaction is expressed as formula (7): Qe (t) = m e ·h e ·v e (t);

[0156] m e Indicates the mass of electrolyte, h e represents the enthalpy change of the electrolyte decomposition reaction, v e (t) represents the electrolyte decomposition reaction rate, which can be expressed as formula (8):

[0157] v e (t) = -dx e / dt=f e ·x e (t)·(1-x e (t))·exp(-E e / R u / T c (t));

[0158] f e represents the decomposition reaction frequency of the electrolyte, E e represents the activation energy of electrolyte decomposition, x e (t) represents the electrolyte content;

[0159] The gas production equation is established and written as formula (9): dm / dt=r d (t)·v d (t)+r r (t)·v r (t)+r e (t)·v e (t);

[0160] dm / dt represents the mass change rate of the reaction gas inside the lithium battery, r d (t) represents the gas production rate of SEI decomposition, r r (t) represents the SEI regeneration rate, r e (t) represents the gas generation rate of electrolyte decomposition;

[0161] To establish a thermal path model, the process is as follows;

[0162] The heat balance equation between the temperature of the battery cell and the temperature of the environment where the battery cell is located is derived as formula (10):

[0163] 0.5·Q(t)=(T c (t)-T(t)) / R g (t)=(T(t)-T f (t)) / R f =(T f (t)-T a (t)) / Ra ;

[0164] T(t) represents the temperature of the reaction gas, T f (t) represents the surface temperature of the lithium battery, T a (t) represents the temperature of the environment; R a represents the convection thermal resistance between the upper plate and the environment, expressed as formula (11): R a =1 / (h a ·A f );A f represents the heat exchange area between the upper plate and the environment, h a Represents the convection coefficient; R f represents the thermal resistance of the upper plate, written as R f =H f / (K f ·A f );H f represents the thickness of the upper plate, K f represents the thermal conductivity of the upper plate; R g (t) represents the thermal resistance of the reaction gas, which is expressed as formula (11): R g (t) = D (t) / (K g A);A represents the heat exchange area between the lithium battery and the upper plate, K g represents the thermal conductivity of the reaction gas, and D(t) represents the gap thickness from the battery cell to the soft pack;

[0165] To establish the thermodynamic sub-model, the process is as follows;

[0166] The state equation of the reaction gas is derived as formula (12): P = 0.5 m(t) R T(t) / (D(t) A); R represents the reaction gas constant; P represents the pressure of the reaction gas, which is equal to the atmospheric pressure of the environment; the height of the lithium battery is written as formula (13): H(t) = H0 + 2 D(t); H(t) represents the height of the lithium battery, and H0 represents the initial value of the height;

[0167] The dynamic gas production rate identification model is expressed as formula (14):

[0168] min(r d (k) ,r r (k) ,r e (k) )E R =abs(H(t (k) )-H E (t (k) )),k=1,2,...,n;

[0169] str d (k) >0,r r (k) >0,r e (k) >0;

[0170] H E (t (k) ) represents the height measurement result of the lithium battery, which is written as formula (15): H E (t (k) )=H0+(k-1)·dH;t (k) represents the kth discrete moment, k represents the discrete step number, n represents the discrete number; dH represents the equal height difference, which can be written as formula (16): dH = (H E (t (n) )-H0)) / n;H E (t (n) ) represents the height measurement result at the end time; H(t (k) ) represents the height prediction result at the k-th discrete moment, obtained by solving the gas production analytical model; abs represents the absolute value operator, min represents the minimization operator, and st represents the constraint operator; E R represents the fitting error; r d (k) represents the SEI decomposition gas production rate at the kth discrete moment, r r (k) represents the SEI regeneration rate at the kth discrete moment, r e (k) represents the gas production rate of electrolyte decomposition at the kth discrete moment; the value of n is established as formula (17): n<(H E (t (n) )-H0) / H S ;H S Indicates the resolution of a mechanical displacement sensor.

[0171] The soft-pack lithium battery dynamic gas generation rate identification system 1100 provided in the embodiment of the present invention can achieve 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.

[0172] 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 above-mentioned soft-pack lithium battery dynamic gas production rate identification method embodiment 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, ROM, RAM, a magnetic disk or an optical disk.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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 identifying the dynamic gas production rate of a soft-pack lithium battery, characterized in that: The method comprises the following processing steps: Step S1: Establishing a dynamic gas generation rate identification device for a lithium battery; Step S2: performing a thermal abuse test on the lithium battery; Step S3: establishing a gas generation analysis model of the lithium battery; Step S4: constructing a dynamic gas generation rate identification model of the lithium battery; Step S5: solving the dynamic gas generation rate identification model of the lithium battery; Wherein, in the step S1, the dynamic gas production rate identification device includes an upper plate, a lower plate, a counterweight, a thermocouple, a mechanical displacement sensor, and a guide column. The dynamic gas production rate identification device is used to identify the dynamic gas production rate of the lithium battery. The lithium battery in a fully charged state is clamped between the upper plate and the lower plate, the thermocouple is placed at the center position between the lithium battery and the lower plate, the counterweight is placed at the center position of the upper surface of the upper plate, the mechanical displacement sensor is fixed to the upper plate, and the two mechanical displacement sensors are symmetrically positioned along the center line of the upper plate, the probe of the mechanical displacement sensor faces the lower plate, the upper plate is matched with the lower plate through the gap between the guide column, and a temperature test chamber is used to provide thermal abuse conditions for the lithium battery; Wherein, the lithium battery comprises a battery cell, a soft pack and an electrolyte; In the step S3, the modeling process of the gas production analytical model is as follows; Step S3.1: Establish the heat generation equation, written as formula (1), that is, Q(t) = Q d (t)+Q r (t)+Q e (t),t∈[0,t (n) ]; t represents the current time, t (n) represents the end time of the thermal abuse experiment, Q(t) represents the heat generation rate of the lithium battery, Q d (t) represents the heat generation rate of SEI decomposition reaction, Q r (t) represents the heat generation rate of SEI regeneration reaction, Q e (t) represents the heat generation rate of the electrolyte decomposition reaction; The heat generation rate of the SEI decomposition reaction is expressed as formula (2): Q d (t) = m a ·h d ·v d (t); The heat generation rate of the SEI regeneration reaction is expressed as formula (3): Q r (t) = m a ·h r ·v r (t); 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 SEI decomposition reaction rate, which can be expressed as formula (4): v d (t)=-dx l / dt=f d ·x l (t)·exp(-E d / R u / T c (t)); f d represents the SEI decomposition reaction frequency, E d represents the SEI decomposition activation energy, T c (t) represents the temperature of the lithium battery, x l (t) represents the SEI lithium ion component, dx l / dt represents x l (t) rate of change; R u represents the universal gas constant, which is 8.324 J / (mol·K); v r (t) represents the SEI regeneration reaction rate, which can be expressed as formula (5): v r (t)=f r ·x r (t)·exp(-x s (t) / x0-E r / R u / T c (t)); f r represents the SEI regeneration reaction frequency, E r represents SEI regeneration activation energy, x r (t) represents the lithium ion insertion component of the anode, x s (t) represents the SEI thickness component; x r (t) grows synchronously with x s (t) decreases, and is written as formula (6): dx s / dt=-dx r / dt,dx s / dt represents x s The rate of change of (t), dx r / dt represents x r (t) rate of change; The heat generation rate of the electrolyte decomposition reaction is expressed as formula (7): Q e (t) = m e ·h e ·v e (t); m e Indicates the mass of electrolyte, h e represents the enthalpy change of the electrolyte decomposition reaction, v e (t) represents the electrolyte decomposition reaction rate, which can be expressed as formula (8): v e (t)=-dx e / dt=f e ·x e (t)·(1-x e (t))·exp(-E e / R u / T c (t)); f e represents the decomposition reaction frequency of the electrolyte, E e represents the activation energy of electrolyte decomposition, x e (t) represents the electrolyte content; Step S3.2: Establish the gas production equation, written as formula (9): dm / dt=r d (t)·v d (t)+r r (t)·v r (t)+r e (t)·v e (t); dm / dt represents the mass change rate of the reaction gas inside the lithium battery, r d (t) represents the gas production rate of SEI decomposition, r r (t) represents the SEI regeneration rate, r e (t) represents the gas generation rate of electrolyte decomposition; Step 3.3: Establish the thermal path model, the process is as follows; The heat balance equation between the temperature of the battery cell and the temperature of the environment where the battery cell is located is derived as formula (10): 0.5·Q(t)=(T c (t)-T(t)) / R g (t)=(T(t)-T f (t)) / R f =(T f (t)-T a (t)) / R a ; T(t) represents the temperature of the reaction gas, T f (t) represents the surface temperature of the lithium battery, T a (t) represents the temperature of the environment; R a represents the convection thermal resistance between the upper plate and the environment, expressed as formula (11): R a =1 / (h a ·A f );A f represents the heat exchange area between the upper plate and the environment, h a Represents the convection coefficient; R f represents the thermal resistance of the upper plate, written as R f =H f / (K f ·A f );H f represents the thickness of the upper plate, K f represents the thermal conductivity of the upper plate; R g (t) represents the thermal resistance of the reaction gas, which is expressed as formula (11): R g (t) = D (t) / (K g A);A represents the heat exchange area between the lithium battery and the upper plate, K g represents the thermal conductivity of the reaction gas, and D(t) represents the gap thickness from the battery cell to the soft pack; Step 3.4: Establish the thermodynamic sub-model. The process is as follows; The state equation of the reaction gas is derived as formula (12): P = 0.5 m(t) R T(t) / (D(t) A); R represents the reaction gas constant; P represents the pressure of the reaction gas, which is equal to the atmospheric pressure of the environment; the height of the lithium battery is written as formula (13): H(t) = H0 + 2 D(t); H(t) represents the height of the lithium battery, and H0 represents the initial value of the height; Wherein, in the step S4, the dynamic gas production rate identification model is expressed as formula (14): min(r d (k) ,r r (k) ,r e (k) )E R =abs(H(t (k) )-H E (t (k) )),k=1,2,...,n; s.t.r d (k) >0,r r (k) >0,r e (k) >0; H E (t (k) ) represents the height measurement result of the lithium battery, which is written as formula (15): H E (t (k) )=H0+(k-1)·dH;t (k) represents the kth discrete moment, k represents the discrete step number, n represents the discrete number; dH represents the equal height difference, which can be written as formula (16): dH=(H E (t (n) )-H0)) / n;H E (t (n) ) represents the height measurement result at the end time; H(t (k) ) represents the height prediction result at the k-th discrete moment, obtained by solving the gas production analytical model; abs represents the absolute value operator, min represents the minimization operator, and st represents the constraint operator; E R represents the fitting error; r d (k) represents the SEI decomposition gas production rate at the kth discrete moment, r r (k) represents the SEI regeneration rate at the kth discrete moment, r e (k) represents the gas production rate of electrolyte decomposition at the kth discrete moment; the value of n is established as formula (17): n<(H E (t (n) )-H0) / H S ;H S Indicates the resolution of a mechanical displacement sensor.

2. The method according to claim 1, characterized in that In step S2, the thermal abuse experiment is a thermal abuse experiment carried out according to the thermal abuse conditions based on the dynamic gas production rate identification device, the thermocouple outputs the temperature measurement results of the lithium battery at all times, the mechanical displacement sensor outputs the height measurement results of the lithium battery at all times, and a gas chromatograph is used to analyze the composition of the reaction gas inside the lithium battery after the thermal abuse experiment to obtain the reaction gas constant.

3. The method according to claim 1, characterized in that The thermal abuse conditions include: the ambient temperature is heated from 25° C. to 230° C. at a rate of 5° C. / min and then kept at that temperature for 20 minutes.

4. The method according to claim 1, characterized in that In the step S5, the process of solving the dynamic gas generation rate identification model of the lithium battery is as follows; Step S5.1: Determine the parameters of the dynamic gas production rate identification model, including operating parameters, geometric characteristics, electrochemical properties, and thermodynamic properties, which are summarized from the gas production analytical model; the operating parameters include P, T a (t), h a ; The geometric features include A, H0, A f , H f , the thermodynamic properties include K f , K g , R, the electrochemical properties include h d 、h r 、h e 、f d 、f r 、f e 、E d 、E r 、E e 、m a 、m e 、m 0 、x l 0 、x r 0 、x s 0 、x e 0 ;m 0 represents the initial mass value of the reaction gas inside the lithium battery, x l 0 represents the initial value of SEI lithium ion component, x r 0 represents the initial value of the lithium ion component inserted into the anode, x s 0 represents the initial value of the SEI thickness component, x e 0 Indicates the initial value of the electrolyte component; Step S5.2: Determine a discrete number, the process is to determine the discrete number according to formula (17); Step S5.3: extracting discrete data of equal height difference, the process is to extract the height measurement result of the discrete moment from the height measurement result according to formula (15); Step S5.4: Calculate the dynamic gas production rate, the process is to solve equation (14) to obtain the SEI decomposition gas production rate, the SEI regeneration gas production rate, the electrolyte decomposition gas production rate, and the predicted results of the surface temperature of the lithium battery at the discrete moment; Step S5.5: Verify the gas production rate identification result. The process is to compare the temperature measurement result with the predicted result of the surface temperature. If the maximum error is less than 2°C, the verification is passed.

5. A dynamic gas production rate identification system for soft-pack lithium batteries, characterized in that: The system comprises: The first establishment module is used to establish a dynamic gas generation rate identification device for a lithium battery; An implementation module, used to implement a thermal abuse experiment of the lithium battery; The second establishment module is used to establish a gas production analysis model of the lithium battery; A construction module, used to construct a dynamic gas generation rate identification model of the lithium battery; A solution module, used for solving a dynamic gas generation rate identification model of the lithium battery; Wherein, the dynamic gas production rate identification device comprises an upper plate, a lower plate, a counterweight, a thermocouple, a mechanical displacement sensor, and a guide column. The dynamic gas production rate identification device is used to identify the dynamic gas production rate of the lithium battery. The lithium battery in a fully charged state is clamped between the upper plate and the lower plate, the thermocouple is placed at the center position between the lithium battery and the lower plate, the counterweight is placed at the center position of the upper surface of the upper plate, the mechanical displacement sensor is fixed to the upper plate, and the two mechanical displacement sensors are symmetrically positioned along the center line of the upper plate, the probe of the mechanical displacement sensor faces the lower plate, the upper plate is matched with the lower plate through the gap between the guide column, and a temperature test chamber is used to provide thermal abuse conditions for the lithium battery; Wherein, the lithium battery comprises a battery cell, a soft pack and an electrolyte; The modeling process of the gas production analytical model is as follows; Establish the heat generation equation and write it as formula (1), that is, Q(t) = Q d (t)+Q r (t)+Q e (t),t∈[0,t (n) ]; t represents the current time, t (n) represents the end time of the thermal abuse experiment, Q(t) represents the heat generation rate of the lithium battery, Q d (t) represents the heat generation rate of SEI decomposition reaction, Q r (t) represents the heat generation rate of SEI regeneration reaction, Q e (t) represents the heat generation rate of the electrolyte decomposition reaction; The heat generation rate of the SEI decomposition reaction is expressed as formula (2): Q d (t) = m a ·h d ·v d (t); The heat generation rate of the SEI regeneration reaction is expressed as formula (3): Q r (t) = m a ·h r ·v r (t); 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 SEI decomposition reaction rate, which can be expressed as formula (4): v d (t)=-dx l / dt=f d ·x l (t)·exp(-E d / R u / T c (t)); f d represents the SEI decomposition reaction frequency, E d represents the SEI decomposition activation energy, T c (t) represents the temperature of the lithium battery, x l (t) represents the SEI lithium ion component, dx l / dt represents x l (t) rate of change; R u represents the universal gas constant, which is 8.324 J / (mol·K); v r (t) represents the SEI regeneration reaction rate, which can be expressed as formula (5): v r (t)=f r ·x r (t)·exp(-x s (t) / x0-E r / R u / T c (t)); f r represents the SEI regeneration reaction frequency, E r represents SEI regeneration activation energy, x r (t) represents the lithium ion insertion component of the anode, x s (t) represents the SEI thickness component; x r (t) grows synchronously with x s (t) decreases, and is written as formula (6): dx s / dt=-dx r / dt,dx s / dt represents x s The rate of change of (t), dx r / dt represents x r (t) rate of change; The heat generation rate of the electrolyte decomposition reaction is expressed as formula (7): Q e (t) = m e ·h e ·v e (t); m e Indicates the mass of electrolyte, h e represents the enthalpy change of the electrolyte decomposition reaction, v e (t) represents the electrolyte decomposition reaction rate, which can be expressed as formula (8): v e (t)=-dx e / dt=f e ·x e (t)·(1-x e (t))·exp(-E e / R u / T c (t)); f e represents the decomposition reaction frequency of the electrolyte, E e represents the activation energy of electrolyte decomposition, x e (t) represents the electrolyte content; The gas production equation is established and written as formula (9): dm / dt=r d (t)·v d (t)+r r (t)·v r (t)+r e (t)·v e (t); dm / dt represents the mass change rate of the reaction gas inside the lithium battery, r d (t) represents the gas production rate of SEI decomposition, r r (t) represents the SEI regeneration rate, r e (t) represents the gas generation rate of electrolyte decomposition; To establish a thermal path model, the process is as follows; The heat balance equation between the temperature of the battery cell and the temperature of the environment where the battery cell is located is derived as formula (10): 0.5·Q(t)=(T c (t)-T(t)) / R g (t)=(T(t)-T f (t)) / R f =(T f (t)-T a (t)) / R a ; T(t) represents the temperature of the reaction gas, T f (t) represents the surface temperature of the lithium battery, T a (t) represents the temperature of the environment; R a represents the convection thermal resistance between the upper plate and the environment, expressed as formula (11): R a =1 / (h a ·A f );A f represents the heat exchange area between the upper plate and the environment, h a Represents the convection coefficient; R f represents the thermal resistance of the upper plate, written as R f =H f / (K f ·A f );H f represents the thickness of the upper plate, K f represents the thermal conductivity of the upper plate; R g (t) represents the thermal resistance of the reaction gas, which is expressed as formula (11): R g (t) = D (t) / (K g A);A represents the heat exchange area between the lithium battery and the upper plate, K g represents the thermal conductivity of the reaction gas, and D(t) represents the gap thickness from the battery cell to the soft pack; To establish the thermodynamic sub-model, the process is as follows; The state equation of the reaction gas is derived as formula (12): P = 0.5 m(t) R T(t) / (D(t) A); R represents the reaction gas constant; P represents the pressure of the reaction gas, which is equal to the atmospheric pressure of the environment; the height of the lithium battery is written as formula (13): H(t) = H0 + 2 D(t); H(t) represents the height of the lithium battery, and H0 represents the initial value of the height; The dynamic gas production rate identification model is expressed as formula (14): min(r d (k) ,r r (k) ,r e (k) )E R =abs(H(t (k) )-H E (t (k) )),k=1,2,...,n; s.t.r d (k) >0,r r (k) >0,r e (k) >0; H E (t (k) ) represents the height measurement result of the lithium battery, which is written as formula (15): H E (t (k) )=H0+(k-1)·dH;t (k) represents the kth discrete moment, k represents the discrete step number, n represents the discrete number; dH represents the equal height difference, which can be written as formula (16): dH=(H E (t (n) )-H0)) / n;H E (t (n) ) represents the height measurement result at the end time; H(t (k) ) represents the height prediction result at the k-th discrete moment, obtained by solving the gas production analytical model; abs represents the absolute value operator, min represents the minimization operator, and st represents the constraint operator; E R represents the fitting error; r d (k) represents the SEI decomposition gas production rate at the kth discrete moment, r r (k) represents the SEI regeneration rate at the kth discrete moment, r e (k) represents the gas production rate of electrolyte decomposition at the kth discrete moment; the value of n is established as formula (17): n<(H E (t (n) )-H0) / H S ;H S Indicates the resolution of a mechanical displacement sensor.

6. 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.

7. 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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