Parameter prediction method and system for fire temperature rise characteristics of lithium ion battery

Abstract

The invention discloses a parameter prediction method and system for a fire temperature rise characteristic of a lithium ion battery. The method comprises the following steps: constructing a three-stage test system comprising a full-size calorimeter combustion chamber, a standard test cabin with a movable ventilation opening and a full-size / equal-proportion reduction energy storage battery test body; selecting a battery sample with at least one parameter combination, and designing an entity experiment or simulation matched with the fire scale; an ignition system is built, each group of battery samples comprises at least one battery cell, and at least one independently controlled heating plate is arranged on each of two sides of each battery cell to directly heat to realize synchronous combustion of multiple battery cells and prevent gas explosion in a limited space. Different working conditions are simulated by dynamically regulating and controlling the opening size of the ventilation opening. Thermocouples are arranged based on limited space heat transfer and gas phase temperature simulation, and a fire temperature rise curve fitting the characteristics of the lithium ion battery is obtained through a contrast test and numerical simulation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of lithium battery fire experiment, more specifically, relates to a parameter prediction method and system for lithium ion battery fire temperature rise characteristics. BACKGROUND

[0002] In the study of lithium ion battery fire characteristics, the existing technology has significant limitations. Traditional fire temperature rise curves are mostly based on statistics of conventional combustibles such as wood, and there are essential differences between the temperature variation law and lithium battery jet fire. Lithium battery fire has the characteristics of higher temperature peak, faster temperature rise rate and high probability of rekindling. Directly applying traditional curves will lead to serious distortion of the evaluation results of battery cabin structure fire resistance, and cannot provide scientific basis for fire prevention design.

[0003] On the level of experiment, the existing scheme has obvious defects. The test chamber is mostly single fixed size, which is difficult to simulate different scene burning conditions from closed space to semi-open environment, and lacks standardized multi-scale chamber system, which cannot restore the spread chain from single battery thermal runaway to module, battery pack and even whole cabin fire, resulting in the research of stage characteristics of fire development. The sample selection has obvious limitations, focusing on a few chemical systems and capacity specifications, not covering different shell forms, state of charge and battery types of different manufacturers, and the data is not representative enough to reflect the diversity of lithium battery fire characteristics. The ignition method is simple and extensive, mostly relying on single heating or ignition means, which cannot realize the synchronous thermal runaway and overall combustion of multiple battery cells, and is easy to cause deflagration due to the accumulation of combustible gases (such as hydrogen and methane), with poor test safety and process controllability.

[0004] On the research method, the traditional mode is limited to simple statistical data of experiments, without effectively integrating numerical simulation and theoretical derivation, which is not only limited by the high cost and limited scene coverage of experiments, but also lacks deep analysis of fire mechanism, making it difficult to generalize the research conclusions to different application scenarios. The temperature measurement point arrangement lacks systematization, mostly using planar and localized point arrangement, which cannot capture the spatio-temporal distribution characteristics of temperature field in three-dimensional space, and the temperature data of key areas are missing, directly affecting the accurate analysis of fire spread law. The boundary condition regulation is too extensive, without dynamically optimizing the opening setting of the chamber combined with the oxygen demand of complete battery combustion and ventilation conditions, which is difficult to achieve the ideal test state of complete battery combustion and minimum system heat dissipation, resulting in a significant reduction in the effectiveness and comparability of test data.

[0005] In addition, the existing method of obtaining battery fire temperature rise curve is single, without constructing a curve system through comparative tests of battery fire and conventional combustible fire, digital test furnace simulation, full-scale numerical simulation and other multi-dimensional means, which is difficult to form a standardized temperature rise curve that fits the characteristics of lithium batteries, directly restricting the improvement of fire prevention standards for battery-powered ships, energy storage power stations and other equipment, and the accuracy of quantitative evaluation of fire risk. SUMMARY

[0006] The present application aims to solve the existing limitations of lithium-ion battery fire characteristics research, by fusing test simulation, numerical simulation and theoretical derivation, constructing a multi-scale test system, innovating the ignition and boundary condition regulation method, scientifically laying out the temperature measuring points, and multi-dimensionally constructing the temperature rise curve, to provide scientific basis for battery cabin fire prevention design, standard improvement and risk assessment, and to improve the systematicness and practicality of lithium battery fire research.

[0007] In view of the above defects or improvement needs of the prior art, as a first aspect of the present application, the present application provides a parameter prediction method for lithium-ion battery fire temperature rise characteristics, comprising: S1. Constructing a three-level test system including a full-size calorimeter combustion chamber, a standard test cabin, and a full-size / equivalent scale energy storage battery test body; the standard test cabin is equipped with a movable ventilation opening; S2. Selecting not less than one parameter combination mode of battery samples and completing entity experiment or simulation design setting based on seven levels of fire scale from single core to whole cabin matched with the fire scale; S3. Based on the heating plate, clamp device and electric arc ignition device, the ignition system is constructed to realize multi-battery core synchronous combustion and prevent cabin gas explosion; wherein each group of battery samples contains not less than one battery core, at least one heating plate is configured on both sides of each battery core, and each heating plate is controlled separately to realize direct heating of the matched battery core; S4. Dynamically regulating the opening size of the movable ventilation opening by combining methods including oxygen amount calculation, ventilation limited type combustion calculation and numerical simulation to simulate the combustion process under different working conditions; S5. Based on the heat transfer path in the limited space and the indoor gas phase temperature simulation calculation, the thermocouple arrangement is completed; wherein the probe head of the thermocouple arrangement needs to face the fire source; and then through comparative test and numerical simulation, the fire temperature rise curve conforming to the characteristics of lithium-ion battery is obtained.

[0008] Further, the parameter combination mode in S2 is: parameters including chemical system, capacity, shell form, state of charge and production manufacturer; the parameters have different value settings.

[0009] Further, the different value settings of the parameters are: The chemical system includes lithium iron phosphate LFP and ternary lithium NCM; the capacity is set to not less than 50 Ah and not more than 700 Ah; the shell form includes soft package and hard shell; the state of charge is between 0%-100%, and every 25% is a value setting; the production manufacturer is set to not less than 3 different production manufacturers.

[0010] Further, the process of dynamically regulating the opening size of the movable vent in the S4 includes the methods of oxygen amount calculation, ventilation-limited combustion calculation, and numerical simulation: Based on the lithium-ion battery combustion reaction formula, the theoretical oxygen demand is derived by the conservation of mass: , Wherein, is the oxygen consumption coefficient of unit mass of charged battery, is the total mass of the battery, is the state of charge; Combined with the cabin volume and the real-time oxygen concentration , the actual oxygen content is calculated: , Wherein, is the air density, and the oxygen supply-demand difference is obtained: , When , it is determined as an oxygen demand state; According to the ventilation-limited combustion theory, the critical ventilation quantity is calculated by using the modified Kawagoe formula: , Wherein, is the fuel characteristic coefficient, which is adapted according to the lithium battery; is the height parameter related to the opening; combined with the heat release rate: , Wherein, is the heat conversion coefficient; is the input energy related parameter; the correlation between and the opening area is established: , By real-time monitoring of HRR, the theoretical opening area required for the current combustion is back calculated , and then the opening size is adjusted through numerical simulation.

[0011] Further, the process of adjusting the opening size through numerical simulation is: Based on fluid dynamics, a three-dimensional response surface model is constructed, wherein, is the average temperature in the cabin; input and , the output oxygen concentration recovery rate and temperature fluctuation coefficient under different opening degrees; The constraint condition is set to ensure timely oxygen supply and controllable thermal stability, and the optimal opening area is obtained through curved surface optimization ; Further, the dynamic adjustment is completed by the method , wherein, is the deviation amount, , , is the PID coefficient; is the change rate of the deviation at the time t; the change is converted into the opening degree adjustment amount of the vent by the electric actuator, and the parameters are updated regularly, so that the opening area can track the optimal value in real time, and the quantitative control of the combustion process is realized. Further, the method for arranging the thermocouple based on the heat transfer path in the limited space and the simulation calculation of the indoor gas temperature in S5 is:

[0012] The total heat flow in the limited space is , which is dominated by the heat release rate , and satisfies the energy conservation: , wherein, is the radiation heat transfer amount, ; is the surface emissivity, is the Stefan-Boltzmann constant, is the radiation heat transfer area, is the gas temperature, is the wall temperature; is the convective heat transfer amount, ; is the convective heat transfer coefficient; is the wall heat storage amount, ; wherein, is the wall material density, is the specific heat capacity, is the wall volume participating in heat storage; The gas temperature distribution function in the space is obtained by CFD simulation , wherein is the spatial coordinate, is the time; Based on the heat flow density matching, the heat flow density at the measuring point needs to cover the critical interval of thermal runaway, and satisfies: , wherein,​​​ respectively collected from the thermal runaway test of lithium battery calibrated upper and lower limits of characteristic heat flux density; is the convective heat transfer coefficient; is the simulated gas phase temperature; is the simulated wall surface temperature; Based on the spatial gradient constraint, the temperature gradient of adjacent thermocouple measurement points needs to be less than the simulated convergence threshold : , wherein, is used to determine the position of the thermocouple arrangement in the confined space, and different subscripts correspond to different spatial positions; and correspond to the coordinates of the adjacent other spatial position point and the same time , which is used to calculate the gas phase temperature difference at the adjacent arrangement position, so as to measure the degree of temperature change between adjacent measurement points in the space; is the temperature gradient convergence threshold; Combining experimental data , simulation calculation and theoretical derivation, the thermocouple arrangement position needs to meet the following conditions at the same time: , wherein, is the simulated gas phase temperature of the th thermocouple arrangement point in the space; is the simulated gas phase temperature of the th arrangement point adjacent to ; Through the above formula, the optimal arrangement coordinates of the thermocouple in the space can be quantitatively derived, and the temperature collection covers the thermal runaway characteristic interval.

[0013] Further, the specific constraint condition that the detection head in S5 needs to face the fire source is: In order to make the thermocouple detection head face the fire source accurately capture the temperature, define the fire source direction correction coefficient : , wherein, is the unit vector of the normal direction of the thermocouple detection head, is the unit vector of the center of the fire source pointing to the detection point; when , According to the threshold set by the test design, it is considered that the detection head faces the fire source effectively; to ensure that the detection head effectively faces the fire source.

[0014] Further, the specific method for obtaining the temperature rise curve that fits the characteristics of lithium batteries in S5 through comparison tests and numerical simulation is: Select a known combustible temperature rise curve with similar thermal runaway characteristics to lithium ion batteries , extract its core characteristic parameters, and complete the normalization of the curve shape: , , where, is the normalized reference temperature, is the normalized time; is the initial temperature; is the instantaneous temperature at time ; is the peak temperature; is the duration of combustion; and simultaneously determine the maximum temperature rise rate and the heat release rate correlation coefficient ; Based on the similarity assumption, a migration fitting formula for the temperature rise curve of lithium batteries is constructed: , where, is the target fitting temperature of the lithium battery at normalized time ; is the peak temperature during the thermal runaway process of the lithium battery; is the migration correction coefficient, corrects the curve shape, corrects the peak position; the correction function is: used to adapt the differences between lithium batteries and reference combustibles; Through small-scale thermal runaway tests of lithium batteries, limited temperature data , is the key time point, and the optimal is solved by minimizing the deviation between the fitted curve and the test data: , where, is the battery temperature predicted by the model at the characteristic time ; is the battery temperature measured by experiment at time ; Through least squares iteration, the migration curve is fitted to the characteristics of the lithium battery test; Substitute the optimized into the fitting model, and combine the measured key parameters of the lithium battery to obtain the final curve: , wherein, is the final fitting temperature of the lithium battery in the actual physical time , is the optimized correction coefficient; is the combustion duration of the thermal runaway process of the lithium battery.

[0015] As a second aspect of the present application, the present application provides a parameter prediction system for fire temperature rise characteristics of a lithium ion battery, comprising: a unit for constructing a test system, for constructing a three-level test system including a full-size calorimeter combustion chamber, a standard test cabin, and a full-size / proportionally reduced energy storage battery test body; the standard test cabin is equipped with a movable ventilation opening; a multi-level fire scale setting unit for selecting battery samples with not less than one parameter combination mode and completing entity experiments or simulation design settings matched with seven levels of fire scales from single core to whole cabin; a synchronous ignition system building unit for building an ignition system based on heating plates, clamp devices, and arc striking devices to achieve synchronous combustion of multiple battery cores and prevent cabin gas explosion; wherein each group of battery samples contains not less than one battery core, at least one heating plate is configured on both sides of each battery core, and each heating plate is controlled separately to directly heat the matched battery core; a ventilation opening dynamic regulation unit for dynamically regulating the opening size of the movable ventilation opening to simulate the combustion process under different working conditions by combining methods including oxygen amount calculation, ventilation limited combustion calculation, and numerical simulation; a thermocouple arrangement and curve fitting unit for arranging thermocouples based on heat transfer paths in a limited space and indoor gas phase temperature simulation calculation; wherein the probe head of the arranged thermocouples faces the fire source; and then through comparative tests and numerical simulation, a fire temperature rise curve conforming to the characteristics of lithium ion batteries is obtained.

[0016] As a third aspect of the present application, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to perform any step of the parameter prediction method for fire temperature rise characteristics of a lithium ion battery.

[0017] Overall, compared with the prior art, the above technical solutions conceived by the present application can achieve the following beneficial effects: 1.The parameter prediction method for lithium ion battery fire temperature rise characteristics of the present application, by constructing a three-level test system including a full-size calorimeter combustion chamber, a standard test chamber and a full-size / proportionally reduced energy storage battery test body, combined with a movable ventilation opening dynamic regulation technology, a controllable environment basis is provided for lithium battery fire tests of different scales. The fire-resistant structure design of the standard test chamber ensures the safety of the test, and the movable ventilation opening can accurately simulate different ventilation conditions, so that the test environment is highly consistent with the actual scene, and the temperature rise data obtained is more realistic and referential, laying a reliable data foundation for subsequent parameter prediction.

[0018] 2.The parameter prediction method for lithium ion battery fire temperature rise characteristics of the present application, by establishing a seven-stage fire scale test framework from single core to whole cabin, combined with the ignition system composed of heating plate, clamp and electric arc ignition device, the synchronous combustion of multiple battery cells is realized and the splashing and explosion are effectively avoided. This hierarchical test design covers different fire development stages, and the precise control of the ignition system ensures the stability and repeatability of the test, which can fully capture the temperature rise characteristics at each stage and provide rich sample data for multi-dimensional prediction of temperature rise parameters.

[0019] 3.The parameter prediction method for lithium ion battery fire temperature rise characteristics of the present application, by comparing tests, digital test furnace simulation and numerical simulation to form three types of curve sets, and correcting them by comparing characteristic temperatures, heating rates and other indicators, the temperature rise curve that fits the characteristics of lithium batteries is constructed. The mutual verification and correction of the three types of curves reduce the error of a single method, improve the accuracy of the temperature rise curve, and make the temperature rise characteristic parameter prediction results based on the curve more consistent with the actual fire situation, providing accurate parameter basis for lithium ion battery fire prevention and control. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 The parameter prediction method for lithium ion battery fire temperature rise characteristics of the present application is a flow chart; Figure 2 The three-level test system of the present application is a schematic diagram; wherein a is the overall schematic diagram; b is the enlarged schematic diagram of node b in a diagram; Figure 3 The overall ignition system of the present application is a schematic diagram of multiple battery cells; Figure 4 The numerical simulation calculation of the present application is a schematic diagram; Figure 5 The thermocouple arrangement scheme of the present application is a schematic diagram; Figure 6 The thermocouple node device arrangement of the present application is a schematic diagram; Figure 7 The system unit diagram of the present application is a schematic diagram. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other. Embodiments

[0022] Please refer to Figure 1 The embodiment 1 provides a parameter prediction method for lithium ion battery fire temperature rise characteristics, comprising: S1. A three-level test system is constructed, including a full-size calorimeter combustion chamber, a standard test cabin, and a full-size / proportionally reduced energy storage battery test body; the standard test cabin is equipped with a movable ventilation opening; S2. Select at least one parameter combination mode of battery samples and complete entity experiments or simulation design settings based on seven levels of fire scale from single core to whole cabin matched with the fire scale; S3. The construction of an ignition system is completed based on a heating plate, a clamp device, and an electric arc ignition device to realize synchronous burning of multiple battery cores and prevent cabin gas explosion; wherein each group of battery samples contains at least one battery core, at least one heating plate is configured on both sides of each battery core, and each heating plate is controlled separately to directly heat the matched battery core; S4. The opening size of the movable ventilation opening is dynamically adjusted to simulate the combustion process under different working conditions by combining methods including oxygen amount calculation, ventilation limited type combustion calculation, and numerical simulation; S5. Thermocouple arrangement is completed based on heat transfer path in limited space and indoor gas phase temperature simulation calculation; wherein when the thermocouple is arranged, the probe head needs to face the fire source; and then through comparative test and numerical simulation, the fire temperature rise curve conforming to the characteristics of lithium ion battery is obtained.

[0023] The embodiment 1 further expands the above steps.

[0024] (1) Test system construction Please refer to Figure 2, a full-size calorimeter combustion chamber (in a specific preferred embodiment, the size specification is 6m x 6m x 4.8m, including equipment room, observation room) is used as the basis to support the subsequent test, which provides basic combustion environment data. On this basis, a fire standard test cabin (in a specific preferred embodiment, the size specification is 3.6m x 2.4m x 2.4m, the cabin wall is reinforced concrete and lined with firebrick, equipped with movable air vents, fire doors (lined with ceramic cotton)) is used to further simulate specific fire scenarios. Finally, the equal proportion reduced battery cabin is used as the correction direction to build a full-size / equal proportion reduced energy storage battery test body, which is gradually promoted through a three-level test system to simulate battery combustion scenarios under different scales and working conditions, and to provide test conditions for related research.

[0025] The full-size calorimeter combustion chamber is used as a basic combustion environment research platform, which has the characteristics of large space and independent partition (the equipment room ensures the stable operation of the instrument, and the observation room is convenient for personnel safety observation), which can carry out unconstrained and large-scale combustion basic test. The basic data such as heat release and smoke diffusion during battery combustion can be obtained, which provides a "real burning rule anchor point" for subsequent reduced scale tests, such as calibrating the basic heat release rate and flame propagation characteristics of battery combustion, so that small-scale tests have a reliable "large scene reference benchmark".

[0026] The fire standard test cabin based on ISO9705 is used as a standardized scene simulation carrier, which has the size and structure (reinforced concrete cabin wall + firebrick, simulating the actual fire-resistant structure of buildings / ships; movable air vents, fire doors, precise control of ventilation conditions) based on ISO9705 international standard, which can reproduce the standard fire development environment. By adjusting the opening degree of the air vent and the state of the fire door, typical fire scenes such as "limited / adequate ventilation" and "closed / semi-closed" can be simulated, the combustion spread rule of the battery in the standardized building / ship cabin environment can be studied, and the test gap from "basic large space" to "actual application scene" can be filled, so that the data is more in line with the engineering practice.

[0027] The full-size / equal proportion reduced energy storage battery test body is used as an actual working condition correction and verification platform, which focuses on the specific application scene of "energy storage battery cabin" and adapts to the spatial layout and structural characteristics in the combustion environment through equal proportion reduction (or full-size restoration). The "general combustion data" obtained from the previous two levels of tests can be used for actual environment verification and correction, such as studying the combustion characteristics of the battery in the narrow cabin of the ship and the complex ventilation pipe network, solving the engineering landing problem that the data of the standard test cabin cannot be directly adapted to the specific actual combustion scene, and providing accurate basis for the fire prevention and control of energy storage batteries.

[0028] (2) Multi-level fire scale setting The method of "multi-sample selection + hierarchical fire scale matching" is adopted to accurately capture the development law of lithium battery fire under different conditions through rich variable coverage and hierarchical scene simulation. The specific process is as follows: first, select battery samples covering different chemical systems, capacities, shells, states of charge, and manufacturers to build a comprehensive test basis with multiple samples; then, design corresponding entity tests or simulations for seven levels of fire scale from single core to whole cabin to restore the fire spread path step by step.

[0029] Specifically, in specific embodiments, about 700 batteries are selected, with chemical systems including LFP and NCM, covering mainstream technology routes such as lithium phosphate iron and ternary lithium, to compare the differences in thermal runaway under different chemical reaction characteristics; the capacity is set from 50Ah to 628Ah in a gradient, adapting to the application scenarios of small power cells to large energy storage cells, to study the influence of capacity on heat release rate; the shell includes soft package and hard shell, which will cause different risks of heat diffusion and deflagration due to structural differences, to verify the effect of packaging form on fire development; the state of charge is set at intervals of 25%, from 0% to 100%, to clarify the correlation between power reserve and thermal runaway triggering and spread; at least 3 manufacturers are included, such as Zhongxing Paian, Yijiatong, and Yiwilithium, to exclude individual manufacturer differences and ensure the universality of the test.

[0030] In terms of fire scale design, single core (1), multiple cores (2 / 4), module (8), single package (16) are carried out by entity test, simulating the process of single cell thermal runaway and small-scale heat diffusion, obtaining basic thermal runaway parameters (such as trigger temperature, heat release rate), providing data anchor points for subsequent large-scale tests; multiple packages (32 / 48 / 64 / 96), clusters and cabins (according to the actual ship layout) combined test and simulation, when multiple package test simulates the failure of battery package internal fire extinguishing, it can study the failure of fire extinguishing agent and the cross-package spread mechanism of thermal runaway; cluster and cabin level is based on the actual ship space layout, simulation restores the chain reaction of fire spreading from local battery package to whole cabin after the whole cabin fire extinguishing fails, covering the complete propagation chain of "cell-module-cabin", providing accurate data support for fire prevention and control (such as fire extinguishing system design, escape passage planning) in actual scenarios such as ships and energy storage stations, realizing the effective connection from laboratory data to engineering application.

[0031] (3) Synchronous ignition system construction Please refer to Figure 3 To realize the synchronous combustion of multiple cells and prevent explosion risk, a heating plate, clamp, and electric arc ignition device are cooperatively operated to build an ignition system, which simulates real fire scenarios and suppresses dangerous evolution through precise heat control, physical protection, and orderly ignition: With the hot plate as the core heat source, at least one cell is used for each group of battery samples, and the "double-sided layout + independent temperature control" design is adopted - at least one heating plate is configured on each side of each cell, and the temperature and heating time of each heating plate can be independently controlled. This setting can evenly transfer heat to the surface of the cell, accurately reproduce the real working conditions of "multi-directional heat accumulation triggering thermal runaway", solve the problem of asynchronous combustion caused by uneven heating of single heat source, ensure that multiple cells enter the thermal runaway state synchronously, and provide a stable test basis for studying the "thermal runaway chain reaction".

[0032] The fixture device serves as a physical support, which stabilizes the position of the cell, avoids displacement or falling of the cell during the combustion process due to thermal expansion and spattering, prevents the disorderly diffusion of flames and high-temperature substances from interfering with the test process, ensures that the multi-cell combustion is always within a controllable space, and focuses the test data on "cell self-thermal runaway spread" rather than being affected by external physical interference.

[0033] The arc striking device assumes the functions of "auxiliary ignition + risk guidance": on the one hand, based on the thermal environment established by the heating plate, the arc can ignite the escaped flammable gas in time to avoid the accumulation of gas to form an explosive mixture; on the other hand, by actively guiding the starting point of combustion, the multi-cell combustion develops in a "synchronous triggering, orderly spreading" path, suppressing the explosion risk while accurately simulating the complex scenario of "thermal + electrical" combined triggering in actual fires, providing more realistic data support for subsequent research on fire extinguishing strategies and explosion prevention.

[0034] This system, through the cooperation of multiple components, not only restores the real fire chain of multi-cell linked combustion, but also controls the explosion risk with physical protection and orderly ignition mechanism, allowing the test to obtain multi-cell combustion data close to actual application while ensuring the safety and repeatability of the test process, laying a solid hardware foundation for lithium battery fire characteristic research.

[0035] (4) Dynamic regulation of ventilation opening To simulate the lithium battery combustion process under different working conditions, the opening size of the ventilation opening is dynamically regulated through oxygen quantity calculation, ventilation limited combustion analysis and numerical simulation: first, based on the lithium battery combustion reaction and state of charge, the theoretical oxygen demand is calculated, the actual oxygen content in the cabin is compared, and the oxygen demand is judged; then, combined with the ventilation limited combustion theory, the heat release rate and opening area are related by a correction formula to deduce the theoretical opening demand.

[0036] In a preferred embodiment, the process of dynamically regulating the opening size of the movable ventilation opening by methods including oxygen quantity calculation, ventilation limited combustion calculation and numerical simulation is as follows: Based on the lithium battery combustion reaction formula, the theoretical oxygen demand is derived by the conservation of mass: , wherein, The oxygen consumption coefficient per unit mass of a charged cell. The total mass of the battery. It is in a charged state; Combined with cabin volume With real-time oxygen concentration Calculate the actual oxygen content: , in, Given air density, the oxygen supply and demand difference is obtained: , when When this occurs, it is determined to be an aerobic state; Based on the theory of ventilation-limited combustion, the critical ventilation rate is calculated using the modified Kawagoe formula: , in, This is the fuel characteristic coefficient, and an appropriate value is selected based on the lithium battery. For the height parameter related to the opening; combined with the heat release rate: , in, The thermal conversion coefficient; Input energy-related parameters; establish With opening area The connection: , By monitoring HRR in real time, the theoretical opening area required for current combustion can be calculated. Then, the opening size is adjusted through numerical simulation.

[0037] Next, a fluid dynamics model was constructed, inputting the oxygen content difference and the theoretical opening to simulate oxygen concentration recovery and temperature fluctuations under different opening degrees. Constraints were set to find the optimal opening area. Finally, PID control was used to dynamically adjust the opening degree based on the deviation between the actual and optimal opening, allowing the ventilation opening to adapt to combustion needs in real time. This accurately simulates the combustion process under various operating conditions, providing a controllable environment for studying fire development.

[0038] Please refer to Figure 4 In a preferred embodiment, the process of adjusting the opening size through numerical simulation is as follows: Based on fluid dynamics A three-dimensional response surface model, in which, The average temperature inside the cabin; input and Output oxygen concentration recovery rate under different aperture degrees and temperature fluctuation coefficient ; The constraint condition is set to ensure timely oxygen supply and controllable thermal stability, and the optimal opening area is obtained through curved surface optimization ; Further, the dynamic adjustment is completed by the method: , Among them, is the deviation amount, , , PID coefficient; is the change rate of the deviation at time , is converted into the opening degree adjustment amount of the air vent by the electric actuator, and the parameters are updated regularly, so that the opening area can track the optimal value in real time, and the quantitative control of the combustion process is realized.

[0039] (5) Thermocouple arrangement and curve fitting Please refer to Figure 5 and Figure 6 , in order to obtain the temperature rise curve conforming to the characteristics of lithium batteries, the thermocouple arrangement is completed based on the heat transfer path in the limited space and the indoor gas phase temperature simulation calculation. The gas phase temperature distribution in the space is obtained by CFD simulation, and the optimal arrangement position of the thermocouple is determined by combining the heat flux matching and the space gradient constraint, so that the heat flux density at the measuring point covers the critical interval of thermal runaway, and the temperature gradient between adjacent measuring points is less than the simulation convergence threshold, ensuring that the temperature collection covers the characteristic interval of thermal runaway.

[0040] In a preferred embodiment, the method for arranging thermocouples based on heat transfer path in a limited space and indoor gas phase temperature simulation calculation is: Let the total heat flow in the limited space be , dominated by the heat release rate , satisfy the energy conservation: , Among them, is the radiation heat transfer amount, ; is the surface emissivity, is the Stefan-Boltzmann constant, is the radiation heat transfer area, is the gas phase temperature, is the wall temperature; is the convective heat transfer amount, ; is the convective heat transfer coefficient; is the wall heat storage amount, ​​;in, The density of the wall material, For specific heat capacity, The wall surface is the volume of heat storage. The gas phase temperature distribution function in space was obtained through CFD simulation. ,in For spatial coordinates, For time; Based on heat flux density matching, the heat flux density at the measuring point It needs to cover the critical region of thermal runaway and meet the following requirements: , in, These were collected through lithium battery thermal runaway tests. The calibrated upper and lower limits of characteristic heat flux density; The convective heat transfer coefficient; To simulate gas phase temperature; To simulate wall temperature; Based on spatial gradient constraints, the temperature gradient between adjacent thermocouple measuring points It must be less than the simulation convergence threshold. : , in, Different subscripts are used to determine the location of thermocouples within a confined space. Corresponding to different spatial locations; and Correspondence refers to the coordinates of another adjacent spatial location point and the same time. It is used to calculate the gas phase temperature difference between adjacent locations, thereby measuring the degree of temperature change between adjacent measuring points in space; This is the temperature gradient convergence threshold; Combined with experimental data Simulation calculation And theoretical derivation, thermocouple placement The following conditions must be met simultaneously: , in, It is the first in space Simulated gas phase temperature at each thermocouple placement point; To and The adjacent first Simulated gas phase temperature at each arrangement point; The above formula can be used to quantify and derive the optimal coordinates of the thermocouple in space, and the temperature acquisition covers the thermal runaway characteristic range.

[0041] At the same time in the arrangement, by defining the fire source direction correction coefficient, ensure that the angle between the normal direction of the detection head and the direction of the fire source center pointing to the detection point meets the threshold requirement, so that the detection head effectively faces the fire source and accurately captures the temperature.

[0042] In the preferred embodiment, the specific constraint condition for the detection head to face the fire source is: In order to make the thermocouple detection head accurately capture the temperature when facing the fire source, define the fire source direction correction coefficient : , Among them, is the unit vector of the normal direction of the thermocouple detection head, is the unit vector of the fire source center pointing to the detection point; when , According to the threshold set by the test design, it is considered that the detection head effectively faces the fire source; to ensure that the detection head effectively faces the fire source.

[0043] Further, select a known combustible temperature rise curve similar to the thermal runaway characteristics of lithium batteries, extract its core characteristic parameters and complete the curve shape normalization. Based on the similarity assumption, a migration fitting formula for the temperature rise curve of lithium batteries is constructed, and limited temperature data is collected through small-scale thermal runaway tests. The minimum deviation between the fitted curve and the test data is used as the target to iteratively solve the optimal migration correction coefficient. Substitute the optimized coefficient into the fitting model, combine the measured key parameters of lithium batteries, and obtain the final temperature rise curve to accurately describe the temperature change during the thermal runaway process of lithium batteries.

[0044] In the preferred embodiment, the specific method for obtaining a temperature rise curve that fits the characteristics of lithium batteries through comparison tests and numerical simulation is: Select a known combustible temperature rise curve similar to the thermal runaway characteristics of lithium batteries , extract its core characteristic parameters, and complete the curve shape normalization: , , Among them, is the normalized reference temperature, is the normalized time; is the initial temperature; is the instantaneous temperature at time ; is the peak temperature; is the duration of combustion; and simultaneously determine the maximum temperature rise rate and the heat release rate correlation coefficient ; Based on the similarity assumption, a migration fitting formula for the temperature rise curve of lithium batteries is constructed: , wherein, is the target fitting temperature of the lithium battery at the normalized time ; is the peak temperature during the thermal runaway process of the lithium battery; is a migration correction coefficient, corrects the shape of the curve, corrects the position of the peak; the correction function is: for adapting the differences of the lithium battery and the reference combustible; through small-scale thermal runaway tests of the lithium battery, limited temperature data , is the key time point, and the optimal : , wherein, is the battery temperature predicted by the model at the characteristic time ; is the battery temperature measured by experiment at the time ; through the least square method iteration, the migration curve is fitted to the characteristics of the lithium battery test; the optimized is substituted into the fitting model, and the final curve is obtained by combining the key parameters of the lithium battery actually measured: , wherein, is the final fitting temperature of the lithium battery at the actual physical time , is the optimized correction coefficient; is the combustion duration of the thermal runaway process of the lithium battery.

[0045] In a specific preferred embodiment, as shown in Table 1; the following specific tests are carried out: , 1. Test preparation (1 day before the test); Select one battery pack (containing 16 pieces of 300 Ah lithium iron phosphate battery monomers) as the test object, and carry out preliminary preparation: Battery pretreatment: fully charge the battery (SOC = 100%), simulate the "full charge high risk" scene in actual application, assemble with heating pieces according to "cell double-sided layout" (add heating pieces on both sides of each cell to ensure the consistency of thermal runaway triggering), and fix the whole on the test bench to ensure the stability of the structure during the combustion process.

[0046] Temperature measurement arrangement: paste thermocouples at key positions on the surface of the battery, such as the positive and negative tabs of the battery cell, the middle of the shell, and the vicinity of the safety valve, to cover the areas prone to thermal runaway, and to accurately capture the timing of temperature changes, providing data support for subsequent analysis of the "thermal runaway propagation path".

[0047] Environmental adaptation: move the assembled battery pack into the test cabin, check that the ventilation and fire extinguishing systems in the cabin are in standby state, ensure that the test is carried out in a controllable environment, and at the same time, adjust the temperature, smoke, pressure monitoring equipment, and calibrate the data acquisition accuracy.

[0048] 2. Thermal runaway trigger (10:40-11:05 on the test day, estimated 25-27 min); Equipment verification: check the heating sheet power supply system, temperature monitor, and test cabin tightness one by one before the test, confirm that there are no problems such as leakage, data drift, and gas leakage, and ensure that the test parameters are true and reliable.

[0049] Continuous heating: start the heating sheet and uniformly heat the battery at a constant power (simulate the continuous action of external heat source), and monitor the temperature change of the battery surface in real time. When the temperature reaches the critical value of lithium iron phosphate battery thermal runaway (about 200-250°C), continue to observe until the safety valve opens and flammable gas is ejected - this stage simulates the process of "battery cell being disturbed by external heat, gradually breaking through the thermal runaway threshold", records the inflection point data from "slow rise" to "rapid rise", and is used for analyzing the thermal runaway trigger mechanism.

[0050] 3. Ignition and ignition (11:05-11:10 on the test day, estimated 30s-1min); Risk controllable ignition: when the battery is monitored to eject flammable gas (such as hydrocarbons and CO generated by electrolyte decomposition), the test cabin igniter is remotely triggered from the monitoring room (the ignition source is kept at a safe distance from the battery to avoid premature detonation), and the accumulated flammable gas is precisely ignited. This step simulates the fire trigger condition of "leaked flammable gas meeting open flame" in the actual scene, controls the ignition time, studies the conversion process from "thermal runaway gas" to "open flame", and at the same time avoids the explosion caused by disordered accumulation of gas.

[0051] 4. Observation of combustion (11:10-12:00 on the test day, estimated 20-40min); Multi-dimensional monitoring: in the test cabin, simultaneously record the temperature field distribution (thermocouple data at different positions), smoke concentration (thermocouple data at different positions) , , flammable gas concentration, flame shape (height, spreading direction), and pressure change (cabin pressure fluctuation), to reproduce the fire development chain of "battery cell combustion → module spread → battery pack overall combustion".

[0052] Key phenomena capture: Focus on observing the thermal runaway transmission characteristics (whether the combustion of a single cell triggers a chain reaction of runaway to adjacent cells), changes in combustion intensity (the moment corresponding to the peak heat release rate), and the interaction of extinguishing agents (if the extinguishing system is activated, record its suppression effect on combustion), to provide empirical evidence for subsequent fire prevention and control strategies.

[0053] 5. Final cleanup (1 day after the test); Safety monitoring: The ventilation system of the test chamber is kept running continuously to monitor the temperature and gas concentration inside the chamber in real time until the temperature of the battery debris drops to within ±10°C of the ambient temperature and the concentration of combustible components and toxic gases in the flue gas is below the safety threshold.

[0054] Site restoration: After the environmental parameters meet the standards, clean up the battery debris and combustion residue in the test chamber, check and record the damage to equipment such as heating elements and thermocouples, so as to provide a reference for subsequent test equipment maintenance and parameter optimization, restore the test site to its initial state, and ensure that subsequent tests can be repeated.

[0055] Core logic: Through the process of "precise preparation → controllable triggering → phased observation → safe conclusion", the complete disaster process of lithium battery from "fully charged and stationary" to "thermal runaway combustion" is simulated. Multi-dimensional data is collected to analyze the thermal runaway mechanism, fire spread law and key points of prevention and control, and to provide real test samples for energy storage safety research.

[0056] Example 2 Please refer to Figure 7 This embodiment 2 provides a parameter prediction system for the temperature rise characteristics of lithium-ion battery fires, including: The test system construction unit is used to construct a three-level test system including a full-size calorimeter combustion chamber, a standard test chamber, and a full-size / scale-downsized energy storage battery test body; the standard test chamber is equipped with movable ventilation openings; A multi-level fire scale setting unit is used to select battery samples with no less than one parameter combination and complete the physical experiment or simulation design setting that matches the fire scale based on the seven levels of fire scale from single cell to whole compartment. The synchronous ignition system construction unit is used to construct the ignition system based on heating plates, clamping devices and electric arc ignition devices to achieve synchronous combustion of multiple battery cells and prevent chamber gas explosion; wherein, each group of battery samples contains no less than one battery cell, and at least one heating plate is configured on both sides of each battery cell, and each heating plate is controlled individually to directly heat the battery cell it is matched with. The ventilation opening dynamic control unit is used to dynamically control the opening size of movable ventilation openings by combining methods including oxygen quantity calculation, ventilation-restricted combustion calculation and numerical simulation to simulate the combustion process under different working conditions. The thermocouple arrangement and the curve fitting unit are used to complete the thermocouple arrangement based on the simulation calculation of the heat transfer path in the limited space and the indoor gas phase temperature; wherein when the thermocouple arrangement, the detection head needs to face the fire source; and then through the comparison test and numerical simulation, the fire temperature rise curve fitting the characteristics of the lithium ion battery is obtained.

[0057] Embodiment 3 The embodiment 3 also provides a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement any step of the parameter prediction method of the lithium ion battery fire temperature rise characteristics.

[0058] The computer readable storage medium can include a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage medium capable of storing program codes.

[0059] For the computer readable storage medium provided in the present application, refer to the above method embodiments, and the present application will not be repeated here.

[0060] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present application, and is not used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of predicting parameters of a lithium-ion battery fire temperature rise characteristic, characterized by, The method comprises the following steps of: S1. constructing a three-level test system comprising a full-size calorimeter combustion chamber, a standard test cabin, and a full-size / reduced-size energy storage battery test body; The standard test cabin is equipped with a movable ventilation opening; S2. selecting battery samples in not less than one parameter combination mode and completing entity experiments or simulation design settings matched with fire scales from single core to whole cabin based on the fire scales; S3. constructing an ignition system based on a heating plate, a clamp device, and an electric arc ignition device to realize synchronous combustion of multiple battery cores and prevent cabin gas explosion; wherein each group of battery samples contains not less than one battery core, at least one heating plate is arranged on each side of each battery core, and each heating plate is controlled separately to directly heat the matched battery core; S4. dynamically adjusting the opening size of the movable ventilation opening by combining methods including oxygen amount calculation, ventilation-restricted combustion calculation, and numerical simulation to simulate the combustion process under different working conditions; S5. arranging thermocouples based on the heat transfer path in the restricted space and simulation calculation of indoor gas phase temperature to obtain a temperature rise curve suitable for the characteristics of lithium ion batteries. The parameter combination mode in S2 is: parameters including chemical system, capacity, shell form, state of charge, and manufacturer; and the parameters have different value settings.

2. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 1, characterized in that, The different value settings of the parameters are as follows:

3. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 2, characterized in that, The chemical system includes lithium iron phosphate LFP and ternary lithium NCM; the capacity is set to not less than 50 Ah and not more than 700 Ah; the shell form includes soft package and hard shell; the state of charge is between 0% and 100%, and every 25% is a value setting; and the manufacturer is set to not less than 3 different manufacturers. The process of dynamically adjusting the opening size of the movable ventilation opening in S4 by combining methods including oxygen amount calculation, ventilation-restricted combustion calculation, and numerical simulation is as follows:

4. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 1, characterized in that, Based on the lithium ion battery combustion reaction formula, the theoretical oxygen demand is derived by the conservation of mass: According to the ventilation-restricted combustion theory, the critical ventilation amount is calculated by using the modified Kawagoe formula: ， wherein, is the oxygen consumption coefficient for a unit mass of the state of charge battery, is the total mass of the battery, is the state of charge; Combined cabin volume With real-time oxygen concentration Actual oxygen content is calculated: ， wherein, For air density, the oxygen supply-demand difference is obtained: ， When the aerobic state is determined; The process of adjusting the opening size by numerical simulation is as follows: ， wherein, is a fuel property coefficient, adapted from lithium batteries; is an opening-related height parameter; in combination with heat release rate: ， wherein is the thermal conversion factor; is the input energy related parameter; establishing a correlation with the open area Aop ， By monitoring the HRR in real time, the theoretical opening area required for the current combustion is back calculated Further, the opening size is adjusted by numerical simulation.

5. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 4, characterized in that, The method for arranging thermocouples in S5 based on the heat transfer path in the restricted space and simulation calculation of indoor gas phase temperature is as follows: Based on fluid dynamics construction Three-dimensional response surface model, wherein, The average temperature in the cabin is; input With , output oxygen concentration recovery rate under different opening degree And temperature fluctuation coefficient ; The setting constraint condition ensures that oxygen supply is timely and thermal stability is controllable, and the optimal opening area is obtained through curved surface optimization ; Further, the method is completed by dynamic adjustment: ， in, This is the deviation amount. , , These are the PID coefficients; For at any time deviation The rate of change; via electric actuator This is converted into the vent opening adjustment amount, and the parameters are updated regularly to ensure that the opening area tracks the optimal value in real time, thereby achieving quantitative control of the combustion process.

6. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 1, characterized in that, Through the above formula, the optimal arrangement coordinates of the thermocouples in the space can be quantitatively derived, and the temperature collection covers the characteristic interval of thermal runaway. Let the total heat flow in the confined space be The heat release rate predominates, satisfying the energy conservation: ， wherein, is the radiative heat transfer, ; is the surface emissivity, is the Stefan-Boltzmann constant, is the radiative heat transfer area, is the gas phase temperature, is the wall temperature; the convective heat transfer amount, ; the convective heat transfer coefficient; is the wall surface heat storage amount, ; wherein, is the wall surface material density, is the specific heat capacity, is the wall surface participating heat storage volume; The temperature distribution function of the gas phase in the space is obtained by CFD simulation wherein is the spatial coordinate, is the time; Based on heat flux matching, heat flux at the measurement point The critical interval of thermal runaway needs to be covered, and the following conditions are met: ， wherein, respectively are the upper and lower limits of the characteristic heat flux density calibrated from the data collected in the lithium battery thermal runaway test calibrated upper and lower limits of the characteristic heat flux density; is the convective heat transfer coefficient; is the simulated gas phase temperature; is the simulated wall temperature; Temperature gradient of adjacent thermocouple measurement points based on spatial gradient constraint Less than simulation convergence threshold : ， wherein, for determining the position of the thermocouple arrangement within the confined space, different subscripts corresponding to different spatial positions; with corresponding to the coordinates of the adjacent other spatial position point and the same time for calculating the temperature difference of the gas phase at the adjacent arrangement positions, in order to measure the steepness of the temperature change between the adjacent measuring points in the space; is a temperature gradient convergence threshold value; In combination with the test data , simulation calculations and theoretical derivations, the thermocouple placement must satisfy the following: ， wherein, is the simulated gas phase temperature at the th thermocouple placement point in space; is the simulated gas phase temperature at the adjacent placement point; and adjacent placement point. The specific constraint condition that the probe head arranged in S5 needs to face the fire source is as follows:

7. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 1, characterized in that, The specific method for obtaining a temperature rise curve suitable for the characteristics of lithium batteries in S5 by comparing experiments and numerical simulation is as follows: In order to make the thermocouple probe head face the fire source and accurately capture the temperature, a fire source direction correction coefficient is defined : ， wherein, is a unit vector in the normal direction of the thermocouple probe head, is a unit vector from the center of the fire source to the probe point; when , According to the threshold set by the test design, the probe head is considered to face the fire source effectively; to ensure that the probe head effectively faces the fire source.

8. The parameter prediction method for the temperature rise characteristics of a lithium-ion battery fire according to claim 1, characterized in that, Based on the similarity assumption, a migration fitting formula of the lithium battery temperature rise curve is constructed: Selecting the known combustible temperature rise curve with the similarity of the thermal runaway characteristics of lithium-ion batteries , extracting its core characteristic parameters, and completing the normalization of the curve shape: ， ， wherein, Tnorm is the normalized reference temperature, t is the normalized time; T0 is the initial temperature; t is the time Tinst is the instantaneous temperature at time t; Tpeak is the peak temperature; t is the duration of the burn; and simultaneously determining the maximum rate of temperature rise and the heat release rate correlation ; Through the least square method iteration, the migration curve is fitted to the characteristics of the lithium battery test; ， wherein, is the target fit temperature for the lithium battery at a normalized time under; is the peak temperature during the thermal runaway process of the lithium battery; is a migration correction factor, corrects the curve shape, corrects the peak position; the correction function is: used to adapt the differences of the lithium battery and the reference combustible; Through small-scale thermal runaway test of lithium battery, limited temperature data is collected , The key time point is solved by fitting the curve with the minimum deviation of the test data : ， wherein, is the battery temperature predicted by the model at a characteristic time is the battery temperature predicted by the model at a characteristic time is the battery temperature measured by experiment at a time is the battery temperature measured by experiment at a time The unit for constructing a test system is used for constructing a three-level test system comprising a full-size calorimeter combustion chamber, a standard test cabin, and a full-size / reduced-size energy storage battery test body; The optimized Substitute the fitting model into the measured key parameters of lithium batteries to obtain the final curve: ， wherein, is the final fitted temperature of the lithium battery in actual physical time under the thermal runaway process, is the optimized correction factor; is the duration of the combustion of the lithium battery thermal runaway process.

9. A system for predicting parameters of lithium-ion battery fire temperature rise characteristics, characterized by, ​ ​ The standard test cabin is equipped with movable ventilation openings; The multi-level fire scale setting unit is used for selecting battery samples in not less than one parameter combination mode and completing physical experiment or simulation design setting matched with the fire scale based on seven levels of fire scale from single core to whole cabin; The synchronous ignition system building unit is used for completing the construction of the ignition system based on heating plates, clamp devices and electric arc striking devices to realize the synchronous combustion of multiple battery cores and prevent the explosion of cabin gas; wherein each group of battery samples contains not less than one battery core, at least one heating plate is configured on each side of each battery core, and each heating plate is controlled separately to realize the direct heating of the matched battery core; The ventilation opening dynamic regulation unit is used for dynamically regulating the opening size of the movable ventilation opening by combining methods including oxygen amount calculation, ventilation limited combustion calculation and numerical simulation to simulate the combustion process under different working conditions; The thermocouple arrangement and curve fitting unit is used for completing the arrangement of thermocouples based on the heat transfer path in the limited space and the simulation calculation of the indoor gas phase temperature; wherein when the thermocouples are arranged, the detection head needs to face the fire source; and then the fire temperature rise curve conforming to the characteristics of the lithium ion battery is obtained through comparative test and numerical simulation.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to perform the parameter prediction method of the lithium ion battery fire temperature rise characteristics according to any one of claims 1-8.

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