A system and method for measuring parameters of thermal runaway eruption kinetics of a lithium battery

Abstract

The present application relates to the technical field of lithium battery eruption parameter measurement, and is a lithium battery thermal runaway eruption kinetics parameter measurement system and method, which specifically comprises the following steps: controlling the use state of a high-speed camera array; constructing a dynamic field model and a thermal distribution model under lithium battery thermal runaway eruption; calculating a first sampling validity, adjusting an initial sampling frequency, and obtaining a first adjusted frequency; calculating a lithium battery ejection coefficient and drawing a change trend curve; evaluating a second sampling validity and dynamically controlling the sampling frequency of the high-speed camera array to obtain a second adjusted frequency; and keeping the second adjusted frequency to measure the lithium battery runaway eruption process. The present application solves the problem in the prior art that, due to the fast speed of lithium battery thermal runaway eruption, the sampling frequency of the camera is difficult to dynamically adjust in real time according to the lithium battery eruption parameters, resulting in incomplete data collection for the lithium battery thermal runaway eruption process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lithium battery eruption parameter measurement, and is a lithium battery thermal runaway eruption dynamics parameter measurement system and method. BACKGROUND

[0002] Lithium batteries are widely used in electronic products, electric vehicles and other high-power demand fields as a high-energy-density energy storage device. However, lithium batteries may experience thermal runaway under abnormal conditions, leading to a rapid increase in internal temperature and eventually causing a violent eruption and explosion. This thermal runaway eruption not only poses a serious safety threat to equipment and users, but also poses potential risks to the environment and public safety; a significant feature of lithium battery thermal runaway eruption is the extremely fast ejection speed. During the eruption process, high-temperature gas and electrolyte inside the battery are rapidly released, forming a high-speed jet stream, and the speed of this jet phenomenon usually reaches several meters per second or even higher, making it extremely challenging to accurately measure the eruption process. In the study of lithium battery thermal runaway eruption, accurate measurement of dynamics parameters is crucial. By measuring parameters such as eruption speed, jet angle, and distribution of eruption material, we can gain a deeper understanding of the dynamics characteristics during the thermal runaway process, thereby providing suggestions for battery design improvement and providing a basis for optimization of protection systems. However, due to the following problems, many difficulties are encountered in the actual measurement process: First, the eruption point of lithium battery thermal runaway is usually not accurately determined in advance, and this uncertainty makes it difficult to set the shooting angle of the camera in advance. The randomness of the eruption point may cause the camera to fail to capture the eruption process at the best angle, thereby affecting the accuracy of the measurement results; second, the eruption speed of lithium batteries during thermal runaway is extremely fast, which may exceed the sampling capacity of traditional camera systems. The rapid change in eruption speed requires the camera system to have a high enough sampling frequency to capture the rapid changes during the eruption process. If the sampling frequency is insufficient, important dynamic characteristics during the eruption process may be missed, resulting in the inability to accurately record the inflection point data of the eruption trend curve, and a too high sampling frequency will increase the real-time data processing capacity of the computer; finally, due to the large variation in eruption speed, a static sampling frequency may not be able to adapt to the eruption characteristics at different stages, therefore, it is necessary to dynamically adjust the sampling frequency of the camera to ensure that key data of speed changes can be accurately recorded during the entire eruption process.

[0003] In the prior art, a lithium battery thermal runaway simulation test system and test method are disclosed in Chinese Patent No. CN118376931A. The test system includes a battery thermal runaway trigger device, a spray material post-processing device, a spray material storage device, a flammability online test device, and a control system connected in sequence. The spray material collection device in the battery thermal runaway trigger device can comprehensively collect the spray material of the battery thermal runaway, and through the spray material post-processing device, the spray material storage device, and the flammability online test device, the spray material can be collected and ignited in real time according to the unit time step, and the spray material generated after the battery thermal runaway can be analyzed and tested for flammability in real time, providing theoretical and practical guidance for battery thermal runaway prevention and control and post-thermal runaway ignition behavior prediction.

[0004] The test system described in the above patent mainly focuses on the collection and processing of spray materials, and does not involve real-time monitoring of dynamic characteristics during the spraying process, such as spraying speed and spraying angle. The lack of dynamic monitoring of the spraying process can lead to the inability to accurately capture rapid changes and key data during the spraying process, thereby affecting the comprehensive understanding of the thermal runaway dynamics. SUMMARY

[0005] The technical problem to be solved by the present application is that in the prior art, considering the fast speed of lithium battery thermal runaway, the sampling frequency of the camera is difficult to dynamically adjust in real time according to the lithium battery spraying parameters, resulting in incomplete data collection during the lithium battery thermal runaway spraying process. A lithium battery thermal runaway spraying dynamics parameter measurement system and method are proposed.

[0006] To achieve the above purpose, the technical scheme of the lithium battery thermal runaway spraying dynamics parameter measurement method of the present application includes the following steps:

[0007] S1: using an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controlling the use state of the high-speed camera array according to the temperature distribution of the surface of the lithium battery;

[0008] S2: extracting battery state data of the lithium battery thermal runaway spraying state shot by the high-speed camera array, and constructing a dynamic field model and a thermal distribution model under the lithium battery thermal runaway spraying according to the battery state data;

[0009] S3: extracting dynamics characteristic data in the dynamic field model, and calculating a first sampling effectiveness according to the dynamics characteristic data, adjusting the initial sampling frequency of the high-speed camera array according to the first sampling effectiveness, and obtaining a first adjustment frequency;

[0010] S4: extracting thermodynamic characteristic data in the thermal distribution model, calculating the lithium battery ejection coefficient in the lithium battery thermal runaway eruption process in real time, and drawing a trend curve of the lithium battery ejection coefficient in the lithium battery thermal runaway eruption process with respect to the eruption time according to the thermodynamic characteristic data;

[0011] S5: in the trend curve of the lithium battery ejection coefficient with respect to the eruption time, marking the data sampling points of the high-speed camera array, monitoring the trend curve in real time, evaluating the second sampling validity of the high-speed camera array, and dynamically controlling the sampling frequency of the high-speed camera array according to the second sampling validity to obtain a second adjustment frequency;

[0012] S6: maintaining the second adjustment frequency to measure the lithium battery thermal runaway eruption process.

[0013] Specifically, in S1, the real-time monitoring of the temperature distribution of the lithium battery surface using the infrared camera specifically includes: acquiring temperature distribution image data of the lithium battery surface, and performing grayscale processing on the temperature distribution image data; presetting a maximum grayscale threshold and a minimum grayscale threshold corresponding to the thermal runaway eruption temperature; screening the pixel points in the temperature distribution image within the maximum grayscale threshold and the minimum grayscale threshold; and marking the pixel region obtained by screening as a lithium battery thermal runaway key monitoring area.

[0014] Specifically, in S1, dynamically controlling the use state of the high-speed camera array according to the temperature distribution of the lithium battery surface specifically includes: extracting the lithium battery thermal runaway key monitoring area, and controlling the 4 high-speed cameras to keep the on state through the electric pan-tilt head, wherein the first high-speed camera is directly aimed at the front of the lithium battery for capturing the front main area of the lithium battery thermal runaway; the second high-speed camera is arranged on the left side of the lithium battery for capturing the left side main area of the lithium battery thermal runaway; the third high-speed camera is arranged on the right side of the lithium battery for capturing the right side main area of the lithium battery thermal runaway; and the fourth high-speed camera is arranged directly above the lithium battery for capturing the overhead secondary area of the lithium battery thermal runaway.

[0015] Specifically, the power field model in S2 includes: real-time eruption speed data, eruption area length data, eruption angle data, and eruption morphology data; and the thermal distribution model in S2 includes: lithium battery surface temperature data, heat flux density data, thermal diffusivity, and convective heat transfer coefficient.

[0016] Specifically, in S3, the calculation strategy of the first sampling validity e1 is specifically:

[0017]

[0018] Wherein, in the positive main area of the battery out-of-control eruption, the distance is divided into X sampling effective unit analysis distances with one meter as a sampling effective unit, x is the subscript, indicating the xth sampling effective unit analysis distance;

[0019] v x ,v x-1 ,v x+1 Respectively, the real-time eruption speed of the lithium battery in the xth, x-1th and x+1th sampling effective unit analysis distance;

[0020] The average value of the real-time eruption speed of the lithium battery in the X sampling effective unit analysis distance.

[0021] Specifically, in S3, the calculation strategy of the first adjustment frequency pl1 is specifically:

[0022] pl1=e1×pl0;

[0023] Wherein, pl0 is the initial sampling frequency of the high-speed camera array.

[0024] Specifically, S4 includes the following specific steps:

[0025] S41: Extracting the thermodynamic feature data in the heat distribution model;

[0026] S42: Real-time calculation of the lithium battery ejection coefficient ps in the battery thermal runaway eruption process, and the calculation strategy of the lithium battery ejection coefficient is specifically as follows:

[0027] ps=∫∫∫(ε1×Q1+ε2×Q2)dW;

[0028] Wherein, W is the unit volume of the monitoring closed space of the lithium battery thermal runaway eruption;

[0029] ε1,ε2 are the combustion heat proportion coefficient and the convection heat proportion coefficient respectively;

[0030] Q1 is the combustion heat released by the lithium battery thermal runaway eruption to the monitoring closed space;

[0031] Q1=ln[R′(t)+2.32], R′(t) is the heat function of the lithium battery thermal runaway eruption;

[0032] Q2 is the heat generated by the heat convection between the air in the monitoring closed space and the lithium battery during the lithium battery thermal runaway eruption process; S ldc is the surface area of the lithium battery; Te max ,Te min is the maximum and minimum temperature of the lithium battery surface during the lithium battery thermal runaway eruption process; respectively, are the average value of the surface temperature of the lithium battery and the average value of the air temperature in the monitoring closed space during the thermal runaway eruption process of the lithium battery; hc is the convective heat transfer coefficient;

[0033] S43: draw a trend curve of the lithium battery eruption coefficient of the lithium battery thermal runaway eruption process versus the eruption time.

[0034] Specifically, S5 includes the following specific steps:

[0035] S51: in the trend curve of the lithium battery eruption coefficient versus the eruption time, mark the data sampling points of the high-speed camera array to obtain a data sampling point set {A1, A2...A j ...A J}, wherein j is an index, representing the jth data sampling point of the high-speed camera array, and J is the total number of data sampling points; A j represents the sampling time point corresponding to the jth data sampling point.

[0036] S52: monitor the trend curve in real time, and evaluate the second sampling effectiveness e2 of the high-speed camera array, and the calculation strategy of the second sampling effectiveness is specifically:

[0037]

[0038] wherein g′ j ,g′ j-1 ,g′ j+1 respectively represent the derivative values of the trend curve at the jth, j-1th and j+1th data sampling points; represents the forward midpoint of the sampling time point corresponding to the jth data sampling point and the sampling time point corresponding to the j+1th data sampling point of the trend curve; represents the reverse midpoint of the sampling time point corresponding to the j-1th data sampling point and the sampling time point corresponding to the jth data sampling point of the trend curve; represents the derivative value at the forward midpoint; represents the derivative value at the reverse midpoint.

[0039] Specifically, S5 further includes the following specific steps:

[0040] S53: dynamically control the sampling frequency of the high-speed camera array according to the second sampling effectiveness to obtain a second adjustment frequency pl2, wherein the acquisition strategy of the second adjustment frequency is:

[0041] pl2 = e2 × pl1.

[0042] In addition, the lithium battery thermal runaway eruption dynamics parameter measurement system of the present application comprises the following modules:

[0043] The camera usage control module, the model construction module, the first adjustment frequency acquisition module, the change trend curve drawing module, the second adjustment frequency acquisition module, and the kinetic parameter measurement module are used.

[0044] The camera usage control module uses an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controls the usage state of the high-speed camera array according to the temperature distribution of the surface of the lithium battery.

[0045] The model construction module is used to extract battery state data of the lithium battery in a thermal runaway eruption state photographed by the high-speed camera array, and construct a dynamic field model and a thermal distribution model of the lithium battery in the thermal runaway eruption according to the battery state data.

[0046] The first adjustment frequency acquisition module is used to extract kinetic characteristic data in the dynamic field model, calculate a first sampling validity according to the kinetic characteristic data, adjust an initial sampling frequency of the high-speed camera array according to the first sampling validity, and obtain a first adjustment frequency.

[0047] The change trend curve drawing module is used to extract thermodynamic characteristic data in the thermal distribution model, calculate a lithium battery ejection coefficient in a lithium battery thermal runaway eruption process in real time, and draw a change trend curve of the lithium battery ejection coefficient with the eruption time in the lithium battery thermal runaway eruption process according to the thermodynamic characteristic data.

[0048] The second adjustment frequency acquisition module is used to mark a data sampling point of the high-speed camera array in the change trend curve of the lithium battery ejection coefficient with the eruption time, monitor the change trend curve in real time, evaluate a second sampling validity of the high-speed camera array, dynamically control a sampling frequency of the high-speed camera array according to the second sampling validity, and obtain a second adjustment frequency.

[0049] The kinetic parameter measurement module is used to keep measuring the lithium battery thermal runaway eruption process at the second adjustment frequency.

[0050] Compared with the prior art, the technical effects of the present application are as follows:

[0051] 1、The present application uses an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controls the usage state of the high-speed camera array, which enables the camera to adjust the shooting angle and position in real time, thereby improving the capture accuracy of the eruption point.

[0052] 2、The power field model and the thermal force distribution model constructed according to the battery state data, the kinetic characteristic data are extracted, and the sampling frequency is dynamically adjusted, so that the change trend of the jetting speed in the high-speed jetting process can be accurately captured in real time, and the problem of inaccurate data caused by insufficient or excessive sampling frequency in the traditional method is avoided.

[0053] 3、The data sampling points are marked in the change trend curve, the sampling validity is evaluated in real time, the sampling frequency of the high-speed camera array is dynamically controlled according to the sampling validity, the dynamic adjustment of the sampling frequency is optimized, so that the key data in each stage of the jetting process can be accurately recorded, the data at the peak inflection point of the change trend curve is comprehensively sampled, the comprehensiveness and accuracy of the data are ensured, and excessive data processing load is avoided. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0055] Among them:

[0056] Figure 1 It is a flowchart of a lithium battery thermal runaway jetting kinetics parameter measurement method of the present application.

[0057] Figure 2 It is a structural schematic diagram of a lithium battery thermal runaway jetting kinetics parameter measurement system of the present application.

[0058] Figure 3 It is an example diagram of four jetting stages in the lithium battery jetting process of the present application.

[0059] Figure 4 It is a temperature trend comparison curve of the surface temperature of the lithium battery with jetting time in the jetting process of two lithium batteries of the same type in the same jetting environment in the embodiment of the present application.

[0060] Figure 5 It is a drawing flowchart of the change trend curve of the lithium battery jetting coefficient with jetting time of the present application.

[0061] The drawings show that: 101 is the first jetting stage and the second jetting stage of the lithium battery; 102 is the second jetting stage and the third jetting stage of the lithium battery; 103 is the third jetting stage and the fourth jetting stage of the lithium battery. DETAILED DESCRIPTION

[0062] In order to make the above objectives, features and advantages of the present application more obvious and comprehensible, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0063] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the concept of the present application, so the present application is not limited to the specific embodiments disclosed below.

[0064] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an embodiment that is separate or alternative to other embodiments.

[0065] Embodiment one

[0066] As shown in Figure 1 , Figure 5 , a method for measuring thermal runaway eruption dynamics parameters of a lithium battery according to an embodiment of the present application, as shown in Figure 1 , includes the following specific steps:

[0067] S1: using an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controlling the use state of the high-speed camera array according to the temperature distribution of the surface of the lithium battery;

[0068] In S1, the use of the infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time specifically includes: obtaining temperature distribution image data of the surface of the lithium battery, and performing grayscale processing on the temperature distribution image data, presetting a maximum grayscale threshold and a minimum grayscale threshold corresponding to the runaway eruption temperature, screening the pixel points in the temperature distribution image within the maximum grayscale threshold and the minimum grayscale threshold, and marking the pixel region obtained by screening as a lithium battery runaway eruption key monitoring area.

[0069] In S1, the use state of the high-speed camera array is dynamically controlled according to the temperature distribution of the surface of the lithium battery, specifically including: extracting the lithium battery runaway eruption key monitoring area, and controlling the 4 high-speed cameras through the electric pan-tilt to keep them in the on state, wherein the first high-speed camera is directly aimed at the front of the lithium battery for capturing the front main area of the lithium battery runaway eruption; the second high-speed camera is arranged on the left side of the lithium battery for capturing the left side main area of the lithium battery runaway eruption; the third high-speed camera is arranged on the right side of the lithium battery for capturing the right side main area of the lithium battery runaway eruption; and the fourth high-speed camera is arranged directly above the lithium battery for capturing the overhead secondary area of the lithium battery runaway eruption.

[0070] S2: extracting battery state data of lithium battery thermal runaway eruption state shot by high-speed camera array, and constructing power field model and thermal distribution model of lithium battery thermal runaway eruption according to the battery state data;

[0071] The battery state data in S2 includes: real-time eruption speed data, eruption area length data, eruption angle data and eruption morphology data, lithium battery surface temperature data, heat flux density data, thermal diffusivity and convective heat transfer coefficient;

[0072] The power field model in S2 includes: real-time eruption speed data, eruption area length data, eruption angle data and eruption morphology data;

[0073] The thermal distribution model in S2 includes: lithium battery surface temperature data, heat flux density data, thermal diffusivity and convective heat transfer coefficient.

[0074] S3: extracting dynamic characteristic data in the power field model, and calculating first sampling effective degree according to the dynamic characteristic data, adjusting initial sampling frequency of high-speed camera array according to the first sampling effective degree, and obtaining first adjustment frequency;

[0075] In S3, the calculation strategy of the first sampling effective degree e1 is specifically:

[0076]

[0077] Wherein, in the front main area of battery runaway eruption, the distance is divided into X sampling effective degree unit analysis distances with one meter as a sampling effective degree unit, x is the subscript, which represents the xth sampling effective degree unit analysis distance;

[0078] v x ,v x-1 ,v x+1 The real-time eruption speed of lithium battery in the xth, x-1th and x+1th sampling effective degree unit analysis distance, respectively;

[0079] The average value of the real-time eruption speed of lithium battery in X sampling effective degree unit analysis distances.

[0080] In S3, the calculation strategy of the first adjustment frequency pl1 is specifically:

[0081] pl1=e1×pl0;

[0082] Wherein, pl0 is the initial sampling frequency of high-speed camera array.

[0083] S4: extracting the thermodynamic characteristic data in the thermal distribution model, calculating the lithium battery ejection coefficient in the lithium battery thermal runaway eruption process in real time, and drawing a trend curve of the lithium battery ejection coefficient in the lithium battery thermal runaway eruption process with respect to the eruption time according to the thermodynamic characteristic data;

[0084] As shown in Figure 5 , S4 includes the following specific steps:

[0085] S41: extracting the thermodynamic characteristic data in the thermal distribution model;

[0086] S42: calculating the lithium battery ejection coefficient ps in the lithium battery thermal runaway eruption process in real time, and the calculation strategy of the lithium battery ejection coefficient is as follows:

[0087] ps = ∫∫∫(ε1×Q1+ε2×Q2)dW;

[0088] Wherein, W is the unit volume of the monitoring closed space of the lithium battery thermal runaway eruption;

[0089] ε1, ε2 are combustion heat proportion coefficient and convection heat proportion coefficient, respectively;

[0090] Q1 is the combustion heat released by the lithium battery thermal runaway eruption to the monitoring closed space;

[0091] Q1 = ln[R'(t) + 2.32], R'(t) is a heat function of the lithium battery thermal runaway eruption;

[0092] Exemplarily, an expression of a heat function of the lithium battery thermal runaway eruption is given in this embodiment: R'(t) = n djy ×ΔH fj +n Li ×ΔH rs , n djy is the number of moles of the eruption electrolyte in the electrolyte; ΔH fj is the enthalpy change of the high-temperature decomposition of the electrolyte; n Li is the number of moles of lithium metal; ΔH rs is the enthalpy change of the lithium metal combustion reaction;

[0093] Q2 is the heat generated by the convection between the air in the monitoring closed space and the lithium battery in the lithium battery thermal runaway eruption process; S ldc is the surface area of the lithium battery; Te max , Te min is the maximum and minimum temperature of the surface of the lithium battery in the lithium battery thermal runaway eruption process; is the average temperature of the surface of the lithium battery and the average temperature of the air in the monitoring closed space, respectively; and hc is the convection heat transfer coefficient;

[0094] Exemplarily, in the present embodiment, a determination strategy of the convective heat transfer coefficient hc is provided, and the specific strategy comprises:

[0095]

[0096] wherein dr is the thermal conductivity of the electrolyte of the lithium battery;

[0097] lm is the dimensionless value of the maximum spewing distance of the lithium battery;

[0098] Re is the Reynolds number; ρ is the heat flux density of the electrolyte of the lithium battery, μ is the viscosity of the electrolyte, and L is the length data of the spewing area of the lithium battery;

[0099] Pr is the Prandtl number; γ is the thermal diffusivity; σ is the dynamic viscosity of the electrolyte of the lithium battery,

[0100] S43: draw a trend curve of the lithium battery spewing coefficient of the lithium battery thermal runaway spewing process versus the spewing time.

[0101] S5: mark the data sampling points of the high-speed camera array in the trend curve of the lithium battery spewing coefficient versus the spewing time, monitor the trend curve in real time, evaluate the second sampling effectiveness of the high-speed camera array, dynamically control the sampling frequency of the high-speed camera array according to the second sampling effectiveness, and obtain a second adjustment frequency;

[0102] S5 comprises the following specific steps:

[0103] S51: mark the data sampling points of the high-speed camera array in the trend curve of the lithium battery spewing coefficient versus the spewing time, and obtain a data sampling point set {A1, A2...A j ...A J}, wherein j is an index, representing the jth data sampling point of the high-speed camera array, and J is the total number of data sampling points; A j represents the sampling time point corresponding to the jth data sampling point.

[0104] S52: monitor the trend curve in real time, and evaluate the second sampling effectiveness e2 of the high-speed camera array, and the calculation strategy of the second sampling effectiveness is specifically:

[0105]

[0106] wherein g′ j , g′ j-1 , and g′ j+1 represent the derivative values of the trend curve at the jth, j-1th, and j+1th data sampling points, respectively. represents a forward midpoint of the change trend curve at a sampling time point corresponding to the jth data sampling point and a sampling time point corresponding to the j+1th data sampling point; represents a reverse midpoint of the change trend curve at a sampling time point corresponding to the j-1th data sampling point and a sampling time point corresponding to the jth data sampling point; represents a derivative value at the forward midpoint; represents a derivative value at the reverse midpoint.

[0107] S5 further comprises the following specific steps:

[0108] S53: dynamically control the sampling frequency of the high-speed camera array according to the second sampling validity to obtain a second adjustment frequency pl2, wherein the acquisition strategy of the second adjustment frequency is:

[0109] pl2=e2×pl1.

[0110] S6: maintain the second adjustment frequency to measure the lithium battery out-of-control eruption process.

[0111] Embodiment two

[0112] As shown in Figure 2 , a lithium battery thermal runaway eruption kinetics parameter measurement system of an embodiment of the present application, as shown in Figure 2 , comprises the following modules:

[0113] The camera usage control module, the model construction module, the first adjustment frequency acquisition module, the change trend curve drawing module, the second adjustment frequency acquisition module, and the kinetics parameter measurement module;

[0114] The camera usage control module uses an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controls the usage state of the high-speed camera array according to the temperature distribution of the surface of the lithium battery;

[0115] The model construction module is used to extract battery state data of the lithium battery in a thermal runaway eruption state photographed by the high-speed camera array, and dynamically constructs a dynamic field model and a thermal distribution model of the lithium battery in a thermal runaway eruption state according to the battery state data;

[0116] The first adjustment frequency acquisition module is used to extract dynamic characteristic data in the dynamic field model, and calculate a first sampling validity according to the dynamic characteristic data, adjust the initial sampling frequency of the high-speed camera array according to the first sampling validity, and obtain a first adjustment frequency;

[0117] The change trend curve drawing module is configured to extract thermodynamic characteristic data in the thermal distribution model, calculate a lithium battery ejection coefficient in a lithium battery thermal runaway explosion process in real time, and draw a change trend curve of the lithium battery ejection coefficient with respect to ejection time in the lithium battery thermal runaway explosion process according to the thermodynamic characteristic data.

[0118] The second adjustment frequency acquisition module is configured to mark a data sampling point of the high-speed camera array in the change trend curve of the lithium battery ejection coefficient with respect to ejection time, monitor the change trend curve in real time, evaluate a second sampling effectiveness of the high-speed camera array, and dynamically control a sampling frequency of the high-speed camera array according to the second sampling effectiveness to obtain a second adjustment frequency.

[0119] The dynamic parameter measurement module is configured to keep the second adjustment frequency to measure the lithium battery thermal runaway explosion process.

[0120] Embodiment three

[0121] Exemplarily, a specific implementation of a technical solution of the lithium battery thermal runaway explosion dynamic parameter measurement method is given in the embodiment, including:

[0122] In the embodiment, the surface temperature of the two lithium batteries in the same type in the same ejection environment is sampled by the technical solution of the lithium battery thermal runaway explosion dynamic parameter measurement method.

[0123] As shown in the embodiment, the ejection of the lithium battery mainly includes a first ejection phase, a second ejection phase, a third ejection phase, and a fourth ejection phase. Figure 3

[0124] In the first ejection phase, the internal electrolyte of the lithium battery is heated, and is in an ejection preparation phase. In the first ejection phase, the surface temperature of the lithium battery slowly rises.

[0125] In the second ejection phase, the internal electrolyte of the lithium battery is rapidly ejected. In the second ejection phase, the surface temperature of the lithium battery rapidly rises.

[0126] In the third ejection phase, the internal electrolyte of the lithium battery is gradually ejected out. In the third ejection phase, the surface temperature of the lithium battery appears a downward trend.

[0127] In the fourth ejection phase, the ejection of the lithium battery is completed. In the fourth ejection phase, the surface temperature of the lithium battery is in a gradually stable trend.

[0128] Further, as shown in the embodiment, a temperature trend comparison curve of the two lithium batteries is drawn according to the surface temperature of the lithium battery in the ejection process. Figure 4

[0129] ​​According to Figure 4 As shown in the above-mentioned technical solution of the lithium battery thermal runaway eruption dynamics parameter measurement method, the peak inflection point time of the two temperature trend curves in the eruption process of the two lithium batteries can be made to tend to be consistent by dynamically controlling the sampling frequency of the high-speed camera array through the sampling effectiveness during the eruption process of the two lithium batteries in the same type under the same eruption environment. It is illustrated that the above-mentioned technical solution of the lithium battery thermal runaway eruption dynamics parameter measurement method can adapt to the change of the eruption speed in real time, has small error, and ensures that the change trend of the eruption speed can be accurately captured during the high-speed eruption process, thereby avoiding the problem of inaccurate data caused by insufficient or too fast sampling frequency of the sampling key stage in the traditional method.

[0130] It should be understood that the size of the sequence number of the above-mentioned processes does not mean the order of execution in various embodiments of the present application, and the execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0131] It should be understood that determining B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0132] The above-mentioned embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. When realized by software, the above-mentioned embodiments can be realized in the form of a computer program product in whole or in part. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the flow or function according to the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center and the like containing one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD) or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0133] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software mode depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0134] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0135] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be realized by other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a kind of, and actual implementation can have another division mode, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0136] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiment according to actual needs.

[0137] In addition, the functional units in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0138] In the description of the specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in combination with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0139] In summary, compared with the prior art, the technical effects of the present application are as follows:

[0140] 1、The present application can improve the accuracy of capturing the spewing point by using infrared cameras to monitor the temperature distribution of the lithium battery surface in real time and dynamically controlling the use state of the high-speed camera array, which enables the camera to adjust the shooting angle and position in real time, even if the spewing point is uncertain, the camera system can still maintain in the key area through dynamic adjustment, ensuring that the key data of the spewing process is accurately recorded, and reducing the data loss caused by the randomness of the spewing point.

[0141] 2、The power field model and thermal distribution model constructed according to the battery state data can extract dynamic characteristic data and dynamically adjust the sampling frequency, which can adapt to the change of the spewing speed in real time, ensuring that the change trend of the spewing speed can be accurately captured in the high-speed spewing process, avoiding the problem of inaccurate data caused by insufficient or excessive sampling frequency in the traditional method.

[0142] 3、The present application marks the data sampling points in the change trend curve and evaluates the sampling effectiveness in real time, dynamically controls the sampling frequency of the high-speed camera array according to the sampling effectiveness, optimizes the dynamic adjustment of the sampling frequency, so that the key data can be accurately recorded in each stage of the spewing process, which is beneficial to the comprehensive sampling of the data at the peak inflection point of the change trend curve, ensuring the comprehensiveness and accuracy of the data, while avoiding excessive data processing load.

[0143] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, the above embodiments and descriptions in the specification are only to illustrate the principles of the present application, and various changes and improvements can be made without departing from the spirit and scope of the present application, which fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for measuring parameters of thermal runaway propagation kinetics of a lithium battery, characterized in that: The method comprises the following specific steps: S1: using an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time, and dynamically controlling the use state of the high-speed camera array according to the temperature distribution of the surface of the lithium battery; S2: extracting the battery state data of the lithium battery under thermal runaway eruption of the lithium battery shot by the high-speed camera array, and constructing a dynamic field model and a thermal distribution model of the lithium battery under thermal runaway eruption of the lithium battery according to the battery state data; S3: extracting the dynamic characteristic data in the dynamic field model, and calculating the first sampling validity according to the dynamic characteristic data, adjusting the initial sampling frequency of the high-speed camera array according to the first sampling validity, and obtaining the first adjustment frequency; S4: extracting the thermodynamic characteristic data in the thermal distribution model, real-time calculating the lithium battery ejection coefficient in the lithium battery ejection process, and drawing the trend curve of the lithium battery ejection coefficient with the ejection time according to the thermodynamic characteristic data; S5: marking the data sampling point of the high-speed camera array in the trend curve of the lithium battery ejection coefficient with the ejection time, real-time monitoring the trend curve, evaluating the second sampling validity of the high-speed camera array, and dynamically controlling the sampling frequency of the high-speed camera array according to the second sampling validity, and obtaining the second adjustment frequency; S6: maintaining the second adjustment frequency to measure the lithium battery runaway eruption process.

2. The method of claim 1, wherein the method is characterized by, In S1, the use of an infrared camera to monitor the temperature distribution of the surface of the lithium battery in real time specifically includes: obtaining temperature distribution image data of the surface of the lithium battery, and performing gray scale processing on the temperature distribution image data, presetting a maximum gray threshold and a minimum gray threshold corresponding to the runaway eruption temperature, screening the pixel points in the temperature distribution image within the maximum gray threshold and the minimum gray threshold, and marking the pixel region obtained by screening as a lithium battery runaway eruption key monitoring area.

3. The method of claim 2, wherein the method is performed on a lithium battery. In S1, the use state of the high-speed camera array is dynamically controlled according to the temperature distribution of the surface of the lithium battery, which specifically includes: extracting the lithium battery runaway eruption key monitoring area, and controlling 4 high-speed cameras through an electric pan-tilt to keep them in a powered-on state, wherein a first high-speed camera is directly aimed at the front of the lithium battery for capturing the front main area of the lithium battery runaway eruption; a second high-speed camera is arranged on the left side of the lithium battery for capturing the left side main area of the lithium battery runaway eruption; a third high-speed camera is arranged on the right side of the lithium battery for capturing the right side main area of the lithium battery runaway eruption; and a fourth high-speed camera is arranged directly above the lithium battery for capturing the overhead auxiliary area of the lithium battery runaway eruption.

4. The method of claim 3, wherein the method is performed on a lithium battery. The dynamic field model in S2 includes: real-time ejection speed data, ejection area length data, ejection angle data and ejection morphology data; and the thermal distribution model in S2 includes: lithium battery surface temperature data, heat flux density data, thermal diffusivity and convective heat transfer coefficient.

5. The method of claim 4, wherein the method further comprises: In S3, the calculation strategy of the first sampling validity e1 is specifically: Wherein, in the positive main area of the battery out-of-control eruption, the eruption area length is divided by analyzing the distance with one meter as a sampling effective unit, and a total of X sampling effective unit analysis distances are obtained, x is the subscript, indicating the xth sampling effective unit analysis distance; v x ,v x-1 ,v x+1 respectively the real-time discharge rate of the lithium battery in the xth, x-1th and x+1th sampling validity unit analysis distance The mean of the real-time spewing speed of lithium batteries in distance is analyzed for X sampling effectiveness units.

6. The method of claim 5, wherein the method further comprises: In S3, the calculation strategy of the first adjustment frequency pl1 is specifically: pl1=e1×pl0; Wherein, pl0 is the initial sampling frequency of the high-speed camera array.

7. The method of claim 6, wherein the method further comprises: S4 includes the following specific steps: S41: extract the thermodynamic feature data in the thermal distribution model; S42: real-time calculation of the lithium battery ejection coefficient ps in the process of battery thermal runaway eruption, the calculation strategy of the lithium battery ejection coefficient is as follows: ps=∫∫∫(ε1×Q1+ε2×Q2)dW; Wherein, W is the unit volume of the monitoring closed space of lithium battery thermal runaway eruption; ε1,ε2 are combustion heat proportion coefficient and convection heat proportion coefficient respectively; Q1 is the combustion heat released by lithium battery thermal runaway eruption to the monitoring closed space; Q1=ln[R′(t)+2.32], R′(t) is the heat function of lithium battery thermal runaway eruption; Q2 is the heat generated by the thermal convection between the air in the enclosed space and the lithium battery during the thermal runaway spewing process of the lithium battery; S ldc is the surface area of the lithium battery; Te max , Te min is the maximum temperature and the minimum temperature on the surface of the lithium battery during the thermal runaway spewing process of the lithium battery; is the average temperature of the lithium battery surface and the average temperature of the air in the enclosed space, respectively; and hc is the convective heat transfer coefficient. S43: draw the trend curve of the lithium battery ejection coefficient with the eruption time in the process of lithium battery thermal runaway eruption.

8. The method of claim 7, wherein the method further comprises: S5 includes the following specific steps: S51: In the trend curve of the change of the lithium battery injection coefficient with the injection time, mark the data sampling points of the high-speed camera array to obtain a data sampling point set {A1, A2...A j ...A J}, wherein j is an index, representing the jth data sampling point of the high-speed camera array, and J is the total number of data sampling points; A j represents the sampling time point corresponding to the jth data sampling point. S52: real-time monitoring of the trend curve, evaluating the second sampling effectiveness e2 of the high-speed camera array, and the calculation strategy of the second sampling effectiveness is specifically: wherein g′ j g′ j-1 g′ j+1 respectively represent derivative values of the change trend curve at the jth, (j-1)th and (j+1)th data sampling points; represents a forward midpoint of the change trend curve at a sampling time point corresponding to the jth data sampling point and a sampling time point corresponding to the (j+1)th data sampling point; represents a reverse midpoint of the change trend curve at a sampling time point corresponding to the (j-1)th data sampling point and a sampling time point corresponding to the jth data sampling point; represents a derivative value at the forward midpoint; represents a derivative value at the reverse midpoint.

9. The method of claim 8, wherein the method further comprises: S5 also includes the following specific steps: S53: dynamically control the sampling frequency of the high-speed camera array according to the second sampling effectiveness, and obtain the second adjustment frequency pl2, wherein the acquisition strategy of the second adjustment frequency is: pl2=e2×pl1.

10. A system for measuring thermal runaway jetting kinetics parameters of a lithium battery, for implementing a method for measuring thermal runaway jetting kinetics parameters of a lithium battery according to any one of claims 1 to 9, characterized in that, The system includes the following modules: Camera use control module, model construction module, first adjustment frequency acquisition module, trend curve drawing module, second adjustment frequency acquisition module, and dynamic parameter measurement module; The camera use control module uses an infrared camera to monitor the temperature distribution of the lithium battery surface in real time, and dynamically controls the use state of the high-speed camera array according to the temperature distribution of the lithium battery surface; The model construction module is used to extract the battery state data of the lithium battery thermal runaway eruption state photographed by the high-speed camera array, and construct the dynamic field model and thermal distribution model of the lithium battery thermal runaway eruption according to the battery state data dynamics; The first adjustment frequency acquisition module is used to extract the dynamic feature data in the dynamic field model, calculate the first sampling effectiveness according to the dynamic feature data, adjust the initial sampling frequency of the high-speed camera array according to the first sampling effectiveness, and obtain the first adjustment frequency; The trend curve drawing module is used to extract the thermodynamic feature data in the thermal distribution model, real-time calculation of the lithium battery ejection coefficient in the process of battery thermal runaway eruption, and draw the trend curve of the lithium battery ejection coefficient with the eruption time in the process of lithium battery thermal runaway eruption according to the thermodynamic feature data; The second adjustment frequency acquisition module is configured to mark a data sampling point of the high-speed camera array in a variation trend curve of the lithium battery ejection coefficient with respect to the ejection time, monitor the variation trend curve in real time, evaluate a second sampling validity of the high-speed camera array, dynamically control a sampling frequency of the high-speed camera array according to the second sampling validity, and obtain a second adjustment frequency. The dynamics parameter measurement module is configured to keep the second adjustment frequency to measure the lithium battery out-of-control ejection process.

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