Method for estimating adsorption and health state of modified material in thermal runaway gas of lithium ion battery

Abstract

The invention relates to an adsorption and health state estimation method of a modified material in lithium ion battery thermal runaway gas, and belongs to the technical field of battery health management. The method comprises the following steps: S1, constructing a gas sensor material, namely an indium selenide (InSe) single layer, and constructing a CuO-InSe single layer through copper oxide (CuO) modification; s2, calculating adsorption energy, an energy band gap and transfer charges based on a density functional theory; s3, calculating the desorption time of the adsorption system at different temperatures according to the adsorption energy, wherein the desorption time is used for proving the potential of CuO-InSe as an adsorbent of CO, C2H2 and C2H4 and a sensor of CO2; a quantitative model for fitting the energy band gap and the adsorption energy with the CO partial pressure is established, the lithium ion battery health state estimation is realized based on the model, and a solid theoretical basis and a practical model are provided for predicting the failure stage of the lithium ion battery and designing an intelligent early warning system.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery health management and relates to a method for adsorbing a modified material in thermal runaway gas of a lithium-ion battery and estimating its health status. Background Art

[0002] Lithium-ion batteries have become an indispensable energy storage device in today's life due to their outstanding advantages such as high energy density, long cycle life and environmental friendliness. They are widely used in renewable energy storage power stations, electric vehicles and various portable electronic products, and occupy a dominant position in the secondary battery market.

[0003] However, despite the increasing maturity of lithium-ion battery technology, its safety issues remain one of the key bottlenecks limiting its further application. Among them, thermal runaway is the most serious safety accident of lithium-ion batteries. When a battery experiences thermal runaway, a violent chain exothermic reaction will occur inside, causing the battery temperature and pressure to rise sharply, and ultimately releasing a large amount of flammable and toxic gases and huge energy. This will not only permanently damage the battery performance, but also pose a serious threat to the safety of users' lives and property and the ecological environment. Therefore, accurate and timely thermal runaway warning for lithium-ion batteries is of vital importance to ensure their safe application.

[0004] At present, an effective thermal runaway warning method is to use gas sensors to monitor the characteristic gases released by the battery. Before or when thermal runaway occurs, the battery will release a variety of gases such as CO, H2, CH4, etc. By adsorbing these thermal runaway gases through specific sensor materials and detecting changes in the physical or chemical properties of the material (such as conductivity) caused by the adsorption effect, early warning of thermal runaway failures can be achieved. Among the many sensor materials, single-layer indium selenide (InSe) is considered to be a potential material for adsorbing thermal runaway gases due to its excellent carrier mobility and good chemical stability. Generally, the adsorption energy (E ads ), analyze the energy band gap (E g ) changes and evaluate first-principles parameters such as transferred charge (ΔQ) to analyze and evaluate the adsorption capacity of sensing materials for thermal runaway gases. Designing and achieving efficient and highly sensitive adsorption of thermal runaway characteristic gases in sensor materials is one of the core technical challenges in improving the accuracy of thermal runaway fault warnings in lithium-ion batteries.

[0005] In addition, most existing technologies are limited to qualitative detection of the presence or absence of gas, and lack the ability to quantitatively assess the health status of the battery. During the evolution of lithium-ion batteries from normal to thermal runaway failure, their internal state continues to deteriorate, and the concentration or partial pressure (PCO) of the characteristic gas released (such as CO gas) also increases continuously. This partial pressure value is closely related to the severity of thermal runaway. At the same time, the properties of the gas adsorption system, such as the adsorption energy (E ads ) and band gap (E g ) will also continue to change with changes in gas concentration. Therefore, how to build a quantitative relationship model between the characteristic parameters of the sensor (such as band gap and adsorption energy) and the partial pressure of the key gas (PCO) to accurately predict the failure stage of lithium-ion batteries and design an intelligent early warning system is a key challenge in achieving real-time estimation of the state of health (SoH) of lithium-ion batteries and graded early warning. Existing technologies still have gaps in this regard.

[0006] In summary, existing technologies for using gas sensors for lithium-ion battery thermal runaway warnings still face limitations, including a need to improve the sensor material's adsorption efficiency and an inability to quantitatively assess the battery's failure process and estimate its state of health. Therefore, the development of a novel modified sensing material and its corresponding state of health estimation method is urgently needed to address or at least alleviate these technical issues. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide a method for adsorption of modified materials in thermal runaway gases in lithium-ion batteries and health status estimation. A quantitative model is established to relate the band gap and adsorption energy to the CO partial pressure, providing a solid theoretical basis and practical model for predicting the failure stage of lithium-ion batteries and designing intelligent early warning systems.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] A method for adsorption of modified materials in thermal runaway gas of lithium-ion batteries and health state estimation specifically comprises the following steps:

[0010] S1: Constructing a gas sensor material, namely an indium selenide (InSe) monolayer, and then modifying it with copper oxide (CuO) to construct a CuO-InSe monolayer;

[0011] S2: Calculation of adsorption energy, band gap, and transfer charge based on density functional theory (DFT);

[0012] S3: Establish a quantitative model for fitting the band gap and adsorption energy with the CO partial pressure, and use this model to estimate the health status of lithium-ion batteries.

[0013] Furthermore, step S1 specifically includes: using Materials Studio software to construct a sensor material, namely an indium selenide (InSe) monolayer, improving the adsorption performance of the InSe monolayer by copper oxide (CuO) modification, and calculating the binding energy (E) of the CuO-InSe monolayer. b ):

[0014] E b =E CuO-InSe -E InSe -E CuO

[0015] Among them, E CuO-InSe represents the energy of CuO-InSe monolayer, E InSe represents the energy of the InSe monolayer, E CuO represents the energy of CuO.

[0016] Furthermore, in step S2, the structures of the adsorption material, the thermal runaway gas, and the system after the adsorption of the gas are optimized, and the adsorption energy E of the thermal runaway gas adsorbed on the InSe monolayer or CuO-InSe monolayer is calculated. ads :

[0017] E ads =E suf / gas -E suf -E gas

[0018] Among them, E suf / gas represents the energy of the gas adsorbed on the InSe monolayer or CuO-InSe monolayer system, E suf represents the energy of InSe monolayer or CuO-InSe monolayer, E gas Represents the energy of thermal runaway gas.

[0019] Furthermore, in step S2, the energy band gap E of the system is calculated by energy band analysis. g :

[0020] E g =|E CBM -E VBM |

[0021] Among them, E CBM represents the conduction band minimum, E VBM represents the valence band maximum.

[0022] Furthermore, in step S2, the Mulliken transfer charge ΔQ of the system after the thermal runaway gas adsorption is calculated by charge distribution analysis:

[0023] ΔQ=Q a -Q b

[0024] Among them, Q a represents the transferred charge of the system after adsorption of thermal runaway gas, Q b Represents the transferred charge of the system before adsorbing thermal runaway gas.

[0025] Furthermore, in step S2, by calculating the adsorption energy (E ads ), band gap (E g ), transfer charge (ΔQ) and molecular dynamics to reflect the adsorption performance of the adsorption material for lithium battery thermal runaway gases (main components: CO, CO2, C2H2 and C2H4).

[0026] Furthermore, step S3 specifically includes the following steps:

[0027] S31: Fitting of band gap, adsorption energy and CO partial pressure using MATLAB fitting toolbox:

[0028] E ads =F(P CO ),E g =F(P CO )

[0029] Among them, E ads =F(P CO ) represents the adsorption energy E ads and CO partial pressure P CO The fitting relationship, E g =F(P CO ) represents the band gap E ads and CO partial pressure P CO The fitting relationship of

[0030] S32: Evaluate the fitting results and determine the fitting effect:

[0031]

[0032] Among them, SSE is the sum of squared errors, R-square is the coefficient of determination, RMSE is the root mean square error, SST is the sum of squared differences between the true data and the true data mean, n is the total number of data samples, and y i represents the i-th real data, Represents the i-th fitting data.

[0033] Furthermore, step S3 further includes: according to the adsorption energy E ads The desorption time t of the adsorption system at different temperatures is calculated:

[0034]

[0035] Among them, f0 represents the test frequency, K B represents the Boltzmann constant, and T is the ambient temperature.

[0036] The beneficial effects of the present invention are:

[0037] (1) Significantly Improved Adsorption Performance: This invention modifies an indium selenide (InSe) monolayer material with copper oxide (CuO), significantly enhancing its adsorption of key gases (CO, CO2, C2H2, and C2H4) generated by thermal runaway in lithium-ion batteries. Compared to the original InSe material, the modified CuO-InSe exhibits improved adsorption of all three gases (CO, C2H2, and C2H4).

[0038] (2) Improving the electronic sensitivity of the material: The modification of copper oxide effectively reduces the band gap of the InSe monolayer, which indicates that the conductivity of the material is enhanced and it is more sensitive to the adsorption of gas molecules, which is conducive to its development into a highly sensitive sensor device.

[0039] (3) Providing a new method for estimating the state of health of batteries: The present invention innovatively establishes a quantitative model that considers the energy band gap (E g ) and adsorption energy (E ads ) and the partial pressure of the key gas CO in thermal runaway (P CO This provides an innovative computational approach for real-time assessment of battery health by monitoring the electrical properties of materials.

[0040] (4) The model is accurate and reliable, enabling precise early warning: The quantitative fitting model established by the present invention has very high accuracy and reliability, among which: the R-square value of the relationship between the band gap and the CO partial pressure is 0.9331. The R-square value of the relationship between the adsorption energy and the CO partial pressure is 0.9707. This makes it possible to infer the CO gas concentration by monitoring the changes in the material's electrical signal, and then accurately predict the "normal operation", "fault triggering" and "fault" stages of the battery, simplifying the analysis of the failure process and achieving precise fault early warning.

[0041] (5) Good application potential and practicality: Through the calculation and analysis of desorption time, the present invention proves that the modified material can not only serve as an efficient adsorbent for CO, C2H2 and C2H4, but also has the potential to become a CO2 sensor, showing its versatility and reusability in practical applications.

[0042] In summary, the present invention not only develops a new material with excellent adsorption performance for thermal runaway gases in lithium batteries, but more importantly, provides a set of accurate and reliable battery health status estimation and fault warning methods based on this material, providing a solid theoretical foundation and practical technical model for the design of a new generation of intelligent battery safety management and warning systems.

[0043] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0045] Figure 1 A flow chart of a method for adsorption of a modified material in a lithium-ion battery thermal runaway gas and health status estimation provided by an embodiment of the present invention;

[0046] Figure 2 Optimized structures of key gases for thermal runaway, InSe monolayer, and CuO-InSe monolayer;

[0047] Figure 3 Molecular dynamics simulations for InSe monolayer and CuO-InSe monolayer;

[0048] Figure 4 The adsorption energy and band gap changes of the adsorption system after the adsorption of thermal runaway key gases on InSe monolayer and CuO-InSe monolayer;

[0049] Figure 5 The desorption time of CO / CuO-InSe adsorption system in different thermal runaway stages;

[0050] Figure 6 Data fitting of energy band gap and adsorption energy under different CO partial pressure conditions. DETAILED DESCRIPTION

[0051] The following describes the embodiments of the present invention by means of specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0052] See also Figure 1 The embodiment of the present invention provides a method for adsorption of a modified material in thermal runaway gas of a lithium-ion battery and estimation of its health status, which specifically includes the following steps:

[0053] Step S1: Use Materials Studio software to construct the sensor material - indium selenide (InSe) monolayer, improve the adsorption performance of the InSe monolayer by copper oxide (CuO) modification, and calculate the binding energy (E) of the CuO-SnSe monolayer. b ):

[0054] E b =E CuO-InSe -E InSe -E CuO

[0055] Among them, E CuO-InSe represents the energy of CuO-InSe monolayer, E InSe represents the energy of the InSe monolayer, E CuO represents the energy of CuO.

[0056] Figure 2 The molecular structures of the four gases generated by the battery thermal runaway failure and the stable optimized structure of the InSe monolayer before and after doping with CuO are shown. The CO triple bond length of CO is The bond lengths of the CC triple bond and CH bond of C2H2 are and The bond lengths of the CC double bond and CH bond of C2H4 are and The bond angle of HCH is 116.632°, and the CO double bond length of CO2 is All four gases have stable structures after structural optimization.

[0057] Step S2: Calculate the adsorption energy (E ads ), band gap (E g ), transfer charge (ΔQ) and molecular dynamics to reflect the adsorption performance of the adsorption material for lithium battery thermal runaway gases (mainly composed of CO, CO2, C2H2 and C2H4), specifically including:

[0058] (1) The structures of the adsorption material, the thermal runaway gas, and the system after gas adsorption were optimized respectively, and the adsorption energy of the thermal runaway gas adsorbed on the InSe monolayer or CuO-InSe monolayer was calculated:

[0059] E ads =E suf / gas -E suf -E gas

[0060] Among them, E suf / gas represents the energy of the gas adsorbed on the InSe monolayer or CuO-InSe monolayer system, E sufrepresents the energy of InSe monolayer or CuO-InSe monolayer, E gas represents the energy of thermal runaway gas;

[0061] (2) Calculate the band gap of the system through energy band analysis:

[0062] E g =|E CBM -E VBM |

[0063] Among them, E CBM represents the conduction band minimum, E VBM represents the valence band maximum;

[0064] (3) Through charge distribution analysis, the Mulliken transfer charge of the system after thermal runaway gas adsorption is calculated:

[0065] ΔQ=Q a -Q b

[0066] Among them, Q a represents the transferred charge of the system after adsorption of thermal runaway gas, Q b Represents the transferred charge of the system before adsorbing thermal runaway gas.

[0067] (4) Molecular dynamics simulations of InSe monolayer and CuO-InSe monolayer were performed. The results are as follows Figure 3 shown.

[0068] Step S3: Compare the adsorption performance of InSe monolayer and CuO-InSe monolayer for lithium battery thermal runaway gases (mainly CO, CO2, C2H2 and C2H4), specifically: according to E in step S2 ads 、E g , ΔQ calculation method, and compare the adsorption properties of InSe monolayer and CuO-InSe monolayer after adsorption of thermal runaway gas, such as Figure 4 As shown in the figure, after copper oxide modification, the band gap of the InSe monolayer decreases from 1.707eV to 0.875eV, indicating enhanced electronic sensitivity. From the data, compared with the original InSe, the adsorption effect of CuO-InSe on CO, C2H2 and C2H4 is significantly improved by 130.1%, 76.9% and 75.7%, respectively.

[0069] Step S4: Calculate the desorption time of the adsorption system at different temperatures, specifically including: ads , calculate the desorption time t of thermal runaway gas adsorbed by lithium ions in CuO-InSe monolayer at 298K, 398K and 498K respectively:

[0070]

[0071] Where f0 represents the test frequency (10 12 s -1 ), K B represents the Boltzmann constant (8.62×10-5eV / K), and T is the ambient temperature.

[0072] like Figure 5 As shown, the desorption time demonstrates its potential as an adsorbent for CO, C2H2, and C2H4, as well as a sensor for CO2.

[0073] Step S5: Establish a quantitative model for fitting the band gap and adsorption energy with the CO partial pressure, and estimate the health status of the lithium-ion battery based on the model, such as Figure 6 shown.

[0074] S51: Fitting of band gap and adsorption energy with CO partial pressure using MATLAB fitting toolbox:

[0075] Input:E ads ,E g ,P CO →MATLAB Tool

[0076] →Output:E ads =F(P CO ),E g =F(P CO )

[0077] Among them, E ads =F(P CO ) represents the fitting relationship between adsorption energy and CO partial pressure, E g =F(P CO ) represents the fitting relationship between the band gap and CO partial pressure;

[0078] S52: Evaluate the fitting results and determine the fitting effect:

[0079]

[0080] Among them, SSE is the sum of squared errors, R-square is the coefficient of determination, RMSE is the root mean square error, SST is the sum of squared differences between the true data and the true data mean, n is the total number of data samples, and y i represents the i-th real data, Represents the i-th fitting data.

[0081] According to existing research analysis, Figure 6T1, T2 and T3 are the normal working stage (300K~350K), fault triggering stage (350K~475K) and fault stage (475K~575K) of lithium-ion batteries respectively. g and P CO The mathematical relationship satisfies the curve f(x)=0.9537+0.1353exp(-exp(26.7403*(x-0.6672))), the R-square value is 0.9331, the SEE value is 0.0021, and the RMSE is 0.0266, indicating that the mathematical model has high accuracy and reliability. Figure 6 As can be seen from the figure, with the increase of CO gas partial pressure, E g The overall trend is downward, and the decline is most obvious in the T2 period. This may be because the chemical reaction occurring in this stage helps to improve the conductivity of the electrode-electrolyte interface. The conductivity calculation formula can be used to know the change of conductivity (σ). By real-time monitoring the change of the material electrical signal, P CO Information can be used to predict the battery health status. ads As the CO gas partial pressure increases, it continues to decrease, satisfying f(x)=-0.8079x2-1.0614x-1.2741, the R-square value is 0.9707, the SEE value is 0.0687, and the RMSE is 0.1311. The fitting effect is good, which simplifies the failure process of the lithium-ion battery. Based on this, accurate fault warning can be achieved.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for adsorption of modified materials in thermal runaway gases of lithium-ion batteries and health status estimation, characterized in that: The method specifically comprises the following steps: S1: Constructing a gas sensor material, namely an indium selenide (InSe) monolayer, and then modifying it with copper oxide (CuO) to construct a CuO-InSe monolayer. S2: Calculation of adsorption energy, band gap and transfer charge based on density functional theory; S3: Establish a quantitative model for fitting the band gap and adsorption energy with the CO partial pressure, and use this model to estimate the health status of lithium-ion batteries.

2. The adsorption and health status estimation method according to claim 1, characterized in that: Step S1 specifically includes: using software to construct the sensor material, that is, the indium selenide InSe monolayer, improving the adsorption performance of the InSe monolayer by copper oxide CuO modification, and calculating the binding energy E of the CuO-InSe monolayer b : AND b =And CuO-InSe -AND InSe -AND CuO Among them, E CuO-InSe represents the energy of CuO-InSe monolayer, E InSe represents the energy of the InSe monolayer, E CuO represents the energy of CuO.

3. The adsorption and health status estimation method according to claim 1, characterized in that: In step S2, the structures of the adsorption material, the thermal runaway gas, and the system after the adsorption of the gas are optimized, and the adsorption energy E of the thermal runaway gas adsorbed on the InSe monolayer or CuO-InSe monolayer is calculated. ads : AND ads =And suf / gas -AND suf -AND gas Among them, E suf / gas represents the energy of the gas adsorbed on the InSe monolayer or CuO-InSe monolayer system, E suf represents the energy of InSe monolayer or CuO-InSe monolayer, E gas Represents the energy of thermal runaway gas.

4. The adsorption and health status estimation method according to claim 1, characterized in that: In step S2, the energy band gap E of the system is calculated by energy band analysis. g : AND g =|E CBM -AND VBM | Among them, E CBM represents the conduction band minimum, E VBM represents the valence band maximum.

5. The adsorption and health status estimation method according to claim 1, characterized in that: In step S2, the Mulliken transfer charge ΔQ of the system after the thermal runaway gas adsorption is calculated by charge distribution analysis: ΔQ=Q a -Q b Among them, Q a represents the transferred charge of the system after adsorption of thermal runaway gas, Q b Represents the transferred charge of the system before adsorbing thermal runaway gas.

6. The adsorption and health status estimation method according to claim 1, 3, 4 or 5, characterized in that: In step S2, the adsorption energy E is calculated ads , band gap E g , transfer charge ΔQ and molecular dynamics to reflect the adsorption performance of the adsorption material for thermal runaway gases in lithium batteries.

7. The adsorption and health status estimation method according to claim 1, characterized in that: Step S3 specifically includes the following steps: S31: Fitting of band gap and adsorption energy with CO partial pressure using the fitting toolbox: E ads =F(P CO ),E g =F(P CO ) Among them, E ads =F(P CO ) represents the adsorption energy E ads and CO partial pressure P CO The fitting relationship, E g =F(P CO ) represents the band gap E ads and CO partial pressure P CO The fitting relationship of S32: Evaluate the fitting results and determine the fitting effect: Among them, SSE is the sum of squared errors, R-square is the coefficient of determination, RMSE is the root mean square error, SST is the sum of squared differences between the true data and the true data mean, n is the total number of data samples, and y i represents the i-th real data, Represents the i-th fitting data.

8. The adsorption and health status estimation method according to claim 1 or 3, characterized in that: Step S3 also includes: according to the adsorption energy E ads The desorption time t of the adsorption system at different temperatures is calculated: Among them, f0 represents the test frequency, K B represents the Boltzmann constant, and T is the ambient temperature.

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