A method for evaluating thermal runaway risk of a battery cell based on multi-parameter quantification
By employing a multi-parameter quantitative evaluation method, and utilizing adiabatic self-heating experiments and the shoelace theorem to calculate the battery thermal safety assessment coefficient, the problems of large errors and lack of parameter weight adjustment mechanisms in traditional evaluation methods are solved, thus achieving a more accurate assessment of battery thermal runaway risk and system safety guidance.
Patent Information
- Application Number
- CN202610775325.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-01
- Publication Date
- 2026-08-25
AI Technical Summary
Traditional battery thermal runaway risk assessment methods rely on a single temperature threshold, ignoring material-specific differences and test condition deviations, resulting in large prediction errors. Furthermore, the lack of a dynamic adjustment mechanism for parameter weights in multi-parameter studies hinders the engineering application of battery safety technologies.
A multi-parameter quantitative evaluation method was adopted. Experimental parameters were obtained through adiabatic self-generated heat thermal runaway experiments. A model coordinate system was established, and the boundaries and actual points were marked. The battery thermal safety assessment coefficient was calculated using the shoelace theorem to conduct a risk assessment.
It improves the accuracy and consistency of battery thermal runaway risk assessment and provides guidance on thermal safety protection for vehicles and energy storage systems.
Smart Images
Figure CN122632077A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of batteries, and more specifically, to a method for quantitatively assessing the risk of thermal runaway in battery cells based on multiple parameters. Background Technology
[0002] With the widespread application of high-energy-density lithium-ion battery systems in electric vehicles, energy storage power stations, and other applications, thermal runaway risk assessment technology has become a core issue in ensuring battery safety. Traditional assessment methods mainly rely on a single temperature threshold, but this has significant limitations: the temperature threshold method ignores material-specific differences and test condition deviations, which leads to higher prediction errors. At the same time, the measured gas-producing components do not match the traditional ideal gas assumptions, and the TNT equivalent estimation deviation reaches ±50%.
[0003] Although multi-parameter research has begun to focus on this issue in recent years While it has a synergistic effect with Q-value (total energy release), it still faces the challenge of lacking a dynamic adjustment mechanism for parameter weights, which severely restricts the engineering application of battery safety technology.
[0004] Therefore, it is necessary to develop a method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative methods.
[0005] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention
[0006] This invention proposes a method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative evaluation. It can assess the degree of thermal runaway hazards between the same system or different systems, and provides certain guidance for the thermal safety protection of vehicles and energy storage systems.
[0007] In a first aspect, embodiments of this disclosure provide a method for quantitatively assessing the risk of thermal runaway in battery cells based on multiple parameters, including: A thermal runaway experiment was conducted on the battery to obtain experimental parameters; The experimental parameters are used as model parameters to establish the model coordinate system; Mark the boundary values of the model parameters in the model coordinate system to obtain the corresponding model boundary points; The actual values of the model parameters are plotted on the model coordinate system to obtain the corresponding actual points of the model; Based on the model boundary points and the actual points in the model, the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment is calculated and a risk assessment is conducted based on the shoelace theorem.
[0008] Preferably, obtaining experimental parameters includes: The data from the thermal runaway test are processed, and the experimental parameters are obtained by combining the time-temperature curve and the temperature-temperature rise rate curve after the test, according to the judgment criteria of enterprise standards, industry standards, national standards or experimental requirements.
[0009] Preferably, the experimental parameters include the self-generated heat initiation temperature, the thermal runaway initiation temperature, and the thermal runaway initiation temperature.
[0010] Preferably, the model parameters also include the total energy Q released during thermal runaway, , , .
[0011] Preferably, Q1 is:
[0012] in, .
[0013] Preferably, for: .
[0014] Preferably, based on the model boundary points and the actual points in the model, the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment is calculated using the shoelace theorem, and a risk assessment is conducted, including: Calculate the baseline area based on the shoelace theorem, using the model boundary points. Calculate the actual area based on the actual points in the model and the shoelace theorem. The battery thermal safety assessment coefficient is calculated based on the reference area and the actual area, and a risk assessment is conducted.
[0015] Preferably, the reference area is:
[0016] Where S is the reference area. Let be the model boundary point corresponding to the i-th model parameter, and n be the total number of model parameters.
[0017] Preferably, the actual area is:
[0018] Among them, S m Let m be the actual area of the thermal runaway experiment. Let be the actual point of the model corresponding to the i-th model parameter.
[0019] Preferably, the battery thermal safety assessment coefficient is:
[0020] in, is the battery thermal safety assessment coefficient for the m-th thermal runaway experiment.
[0021] The method of the present invention has other features and advantages that will be apparent from or will be set forth in detail in the accompanying drawings and following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description
[0022] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts.
[0023] Figure 1 A flowchart illustrating the steps of a method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantification according to an embodiment of the present invention is shown. Detailed Implementation
[0024] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.
[0025] Figure 1 A flowchart illustrating the steps of a method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantification according to an embodiment of the present invention is shown.
[0026] like Figure 1 As shown, the method for quantitatively assessing the risk of thermal runaway in battery cells based on multiple parameters includes: Step 101: Conduct an adiabatic self-generated heat thermal runaway experiment on the battery and obtain experimental parameters; Step 102: Use the experimental parameters as model parameters to establish the model coordinate system; Step 103: Mark the boundary values of the model parameters in the model coordinate system to obtain the corresponding model boundary points; Step 104: Mark the actual values of the model parameters in the model coordinate system to obtain the corresponding actual points of the model; Step 105: Based on the model boundary points and the actual points of the model, calculate the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment based on the shoelace theorem and conduct a risk assessment.
[0027] In one example, obtaining experimental parameters includes: The data from the thermal runaway test are processed, and the experimental parameters are obtained by combining the time-temperature curve and the temperature-temperature rise rate curve after the test, according to the judgment criteria of enterprise standards, industry standards, national standards or experimental requirements.
[0028] In one example, the experimental parameters include the self-generating heat initiation temperature, the thermal runaway initiation temperature, and the thermal runaway initiation temperature.
[0029] In one example, the model parameters also include the total energy Q released during thermal runaway. , , .
[0030] In one example, Q1 is:
[0031] in, .
[0032] In one example for: .
[0033] In one example, based on the model boundary points and the actual model points, the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment is calculated using the shoelace theorem, and a risk assessment is performed, including: Calculate the baseline area based on the shoelace theorem, using the model boundary points. Calculate the actual area based on the actual points in the model and the shoelace theorem. The battery thermal safety assessment coefficient is calculated based on the reference area and the actual area, and a risk assessment is conducted.
[0034] In one example, the reference area is:
[0035] Where S is the reference area. Let be the model boundary point corresponding to the i-th model parameter, and n be the total number of model parameters.
[0036] In one example, the actual area is:
[0037] Among them, S m Let m be the actual area of the thermal runaway experiment. Let be the actual point of the model corresponding to the i-th model parameter.
[0038] In one example, the battery thermal safety assessment coefficient is:
[0039] in, is the battery thermal safety assessment coefficient for the m-th thermal runaway experiment.
[0040] Specifically, according to the experimental requirements, the battery undergoes an adiabatic self-generated thermal runaway test. The battery used in the test is not limited to lithium batteries, sodium-ion batteries, solid-state batteries, etc. The adiabatic self-generated thermal runaway test can be conducted using adiabatic self-generated heat equipment, such as an accelerated adiabatic thermal instrument (ARC). The data after the thermal runaway test is processed, mainly by combining the time-temperature curve and temperature-temperature rise rate curve after the test, and obtaining experimental parameters, such as the self-generated heat initiation temperature, according to the judgment criteria of enterprise standards, industry standards, national standards, or experimental requirements. Thermal runaway initiation temperature Thermal runaway initiation temperature ; In addition to the experimental parameters obtained above, other parameters can be added as model parameters, such as the total energy released in thermal runaway, Q, or... , , .
[0041] Establish a two-dimensional plane coordinate system, confirm the number of model parameters n and the model boundary, mark the boundary values of the model parameters in the model coordinate system, obtain the corresponding model boundary points, and calculate the reference area based on the shoelace theorem based on the model boundary points:
[0042] Where S is the reference area. Let be the model boundary point corresponding to the i-th model parameter, and n be the total number of model parameters.
[0043] Plot the actual values of the model parameters on the model coordinate system to obtain the corresponding actual points on the model. Calculate the actual area based on these actual points and the shoelace theorem.
[0044] Among them, S m Let m be the actual area of the thermal runaway experiment. Let be the actual point of the model corresponding to the i-th model parameter.
[0045] Calculate the battery thermal safety assessment coefficient based on the reference area and the actual area:
[0046] in, Let be the battery thermal safety assessment coefficient for the m-th thermal runaway experiment. It is dimensionless and lies between 0 and 1, where the adjustment mechanism establishes a parameter sensitivity matrix w through an algorithm, making... = ,in These are the weighting coefficients for each parameter.
[0047] In the system The batteries in this experiment were ranked according to their thermal safety coefficients, such as... > In other words, if the thermal safety factor of the battery is greater in the first test than in the second test, it means that the battery experiment in the first test was more hazardous, and so on. The higher the value, the greater the risk of battery thermal runaway.
[0048] To facilitate understanding of the solutions and effects of the embodiments of the present invention, a specific application example is given below. Those skilled in the art should understand that this example is merely for the purpose of understanding the present invention, and any specific details therein are not intended to limit the present invention in any way.
[0049] Example 1
[0050] Taking the currently commercially available 109Ah square lithium iron phosphate battery and 109Ah square sodium-ion battery as examples, this invention is described in a comprehensive and detailed manner. The method is not limited to these types of batteries, but is applicable to all commercially available and self-made secondary batteries.
[0051] (1) Charge the target battery to the specified state of charge; (2) Place the target battery in an adiabatic accelerated calorimeter to obtain the thermal runaway temperature curve of the battery and obtain the characteristic temperature parameters. , , As shown in Table 1; Table 1
[0052] (3) Establish the boundary of the digital model and the reference area S
[0053] The number of parameters is n=3, and the boundary is established using a polar coordinate system: The maximum values for each parameter boundary are set (based on industry experience):
[0054] As polar diameter Convert polar coordinates to rectangular coordinates. Vertex 1: (150, 0); Vertex 2: (-100, 173.2); Vertex 3: (-150, -259.8); Calculate the baseline area S = 58455 using the shoelace theorem. (4) Calculate the area of each battery using the shoelace theorem. =21475; =28706.25; =41830.25; (5) Calculate the thermal safety factor ; Ranking of thermal safety factors: That is, the thermal runaway hazard of battery C is the highest, and that of battery A is the lowest.
[0055] Those skilled in the art should understand that the above description of the embodiments of the present invention is only intended to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any of the examples given.
[0056] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.
Claims
1. A method for quantitatively assessing the risk of thermal runaway in battery cells based on multiple parameters, characterized in that, include: A thermal runaway experiment was conducted on the battery to obtain experimental parameters; The experimental parameters are used as model parameters to establish the model coordinate system; Mark the boundary values of the model parameters in the model coordinate system to obtain the corresponding model boundary points; The actual values of the model parameters are plotted on the model coordinate system to obtain the corresponding actual points of the model; Based on the model boundary points and the actual points in the model, the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment is calculated and a risk assessment is conducted based on the shoelace theorem.
2. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 1, wherein, The experimental parameters to be obtained include: The data from the thermal runaway test are processed, and the experimental parameters are obtained by combining the time-temperature curve and the temperature-temperature rise rate curve after the test, according to the judgment criteria of enterprise standards, industry standards, national standards or experimental requirements.
3. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 2, wherein, The experimental parameters include the self-generated heat initiation temperature, the thermal runaway initiation temperature, and the thermal runaway initiation temperature.
4. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 1, wherein, The model parameters also include the total energy released during thermal runaway, Q, , , .
5. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 4, wherein, Q1 is: in, .
6. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 4, wherein, for: 。 7. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 1, wherein, Based on the model boundary points and actual model points, the battery thermal safety assessment coefficient corresponding to this thermal runaway experiment is calculated and a risk assessment is conducted using the shoelace theorem, including: Calculate the baseline area based on the shoelace theorem, using the model boundary points. Calculate the actual area based on the actual points in the model and the shoelace theorem. The battery thermal safety assessment coefficient is calculated based on the reference area and the actual area, and a risk assessment is conducted.
8. The method for assessing the risk of thermal runaway in battery cells based on multi-parameter quantitative analysis according to claim 1, wherein, The base area is: Where S is the reference area. Let be the model boundary point corresponding to the i-th model parameter, and n be the total number of model parameters.
9. The method for assessing the risk of thermal runaway in a battery cell based on multi-parameter quantitative analysis according to claim 8, wherein, The actual area is: Among them, S m Let m be the actual area of the thermal runaway experiment. Let be the actual point of the model corresponding to the i-th model parameter.
10. The method for assessing the risk of thermal runaway in a battery cell based on multi-parameter quantitative analysis according to claim 9, wherein, The battery thermal safety assessment coefficient is: in, is the battery thermal safety assessment coefficient for the m-th thermal runaway experiment.