阅读说明：本技术 基于拉曼光谱的锂离子电池热失控动态预警系统及方法 (Raman spectrum-based dynamic early warning system and method for thermal runaway of lithium ion battery ) 是由 陈达 张伟 郝朝龙 张青松 于 2021-07-16 设计创作，主要内容包括：本发明公开了一种基于拉曼光谱的锂离子电池热失控动态预警系统及方法,系统包括：激光器、拉曼探头、空芯光纤波导、单色仪、分光光路、光电检测器件和嵌入式计算机；空芯光纤波导采集锂离子电池周围的气体；拉曼探头具有输入光纤和接收光纤；激光器发出的激发光通过输入光纤传输至空芯光纤波导中,生成拉曼光谱散射光；拉曼光谱散射光经接收光纤收集后,依次经单色仪和分光光路后传输至光电检测器件,生成光谱数据；嵌入式计算机对光谱数据进行数据分析,在气体浓度和气体浓度的变化率超出阈值时,发出锂离子电池热失控警报。本发明综合特征气体种类及其浓度变化速率信息,开发分阶段的锂离子电池热失控预警模型,实现热失控早期的动态预警。(The invention discloses a thermal runaway dynamic early warning system and method for a lithium ion battery based on Raman spectrum, wherein the system comprises the following steps: the device comprises a laser, a Raman probe, a hollow fiber waveguide, a monochromator, a light splitting optical path, a photoelectric detection device and an embedded computer; collecting gas around the lithium ion battery by the hollow fiber waveguide; the Raman probe is provided with an input optical fiber and a receiving optical fiber; exciting light emitted by the laser is transmitted into the hollow-core optical fiber waveguide through the input optical fiber to generate Raman spectrum scattering light; after being collected by a receiving optical fiber, the Raman spectrum scattered light is transmitted to a photoelectric detection device through a monochromator and a light splitting optical path in sequence to generate spectrum data; and the embedded computer performs data analysis on the spectral data and sends out a thermal runaway alarm of the lithium ion battery when the gas concentration and the change rate of the gas concentration exceed a threshold value. The invention integrates the characteristic gas types and the concentration change rate information thereof, develops a staged lithium ion battery thermal runaway early warning model and realizes the early dynamic early warning of the thermal runaway.)

1. The utility model provides a lithium ion battery thermal runaway dynamic early warning system based on raman spectrum which characterized in that includes: the Raman spectrometer comprises a laser (1), a Raman probe (2), a hollow-core optical fiber waveguide (3), a monochromator (4), a light splitting optical path (5), a photoelectric detection device (6) and an embedded computer (7) which are connected in sequence;

the hollow optical fiber waveguide (3) is used as a gas battery and collects gas in the surrounding environment of the lithium ion battery in real time;

the Raman probe (2) is coupled with the hollow-core optical fiber waveguide (3); the Raman probe (2) is provided with an input optical fiber (8) and a receiving optical fiber (9); exciting light emitted by the laser (1) is transmitted into the hollow-core optical fiber waveguide (3) through the input optical fiber (8) to generate Raman spectrum scattering light; after being collected by the receiving optical fiber (9), the Raman spectrum scattered light is transmitted to the photoelectric detection device (6) after sequentially passing through the monochromator (4) and the light splitting optical path (5), so as to generate spectrum data, and the spectrum data is transmitted to the embedded computer (7);

and the embedded computer (7) performs data analysis on the spectrum data, dynamically calculates the concentration change and the concentration change rate of the monitored gas species, and sends out a thermal runaway alarm of the lithium ion battery when the gas concentration and the gas concentration change rate exceed threshold values.

2. The thermal runaway dynamic early warning system for the lithium ion battery based on the Raman spectrum as claimed in claim 1, wherein both ends of the hollow optical fiber waveguide (3) are respectively connected with an air inlet (10) and an air outlet (11); the gas in the surrounding environment of the lithium ion battery enters the hollow-core optical fiber waveguide (3) through the air inlet channel (10), and then is discharged from the air outlet (11) to the hollow-core optical fiber waveguide (3).

3. The thermal runaway dynamic early warning system for the lithium ion battery based on the Raman spectrum as claimed in claim 2, wherein a dehumidification filtering unit (12), a pressure regulation and control unit (13) and a temperature regulation and control unit (14) are sequentially installed on the air inlet channel (10) from a sampling port to the direction of the hollow glass fiber waveguide (3); the dehumidifying and filtering unit (12) is used for removing moisture and impurities in the gas; the pressure regulating unit (13) is used for keeping the gas in the gas inlet channel in a constant pressure state; the temperature regulation and control unit (14) is used for keeping the gas in the air inlet channel in a constant temperature state.

4. The lithium ion battery thermal runaway dynamic warning system based on the Raman spectrum as claimed in claim 1, wherein the outer periphery of the hollow-core optical fiber waveguide (3) is coated with an Ag/AgI composite coating.

5. The lithium ion battery thermal runaway dynamic early warning system based on Raman spectrum as claimed in claim 1, wherein the embedded computer (7) further stores the spectrum data in real time and generates Raman spectrum to display; the Raman spectrum is used for representing the type and concentration change of the monitored gas in the surrounding environment of the lithium ion battery.

6. A thermal runaway dynamic early warning method of a lithium ion battery based on a Raman spectrum is suitable for the thermal runaway dynamic early warning system of the lithium ion battery based on the Raman spectrum, which is characterized by comprising the following steps:

taking the gas species component and concentration change flowing through the hollow optical fiber waveguide as the judgment basis of the thermal runaway condition of the lithium ion battery;

constructing a battery state model and a thermal runaway early warning model of a lithium ion battery thermal runaway development process based on gas components and concentration changes;

monitoring the gas type and concentration change in the surrounding environment of the lithium ion battery in real time based on a battery state model in the thermal runaway development process of the lithium ion battery, dynamically calculating the gas concentration change rate, and estimating the thermal runaway state of the lithium ion battery according to the gas concentration change and the gas concentration change rate;

and calculating whether the gas concentration and the concentration change rate of various monitored gases reach a threshold value in real time based on the thermal runaway early warning model, and sending out a thermal runaway alarm when the gas concentration and the concentration change rate exceed the threshold value.

7. The lithium ion battery thermal runaway dynamic early warning method based on the Raman spectrum of claim 6, wherein the construction process of the battery state model of the lithium ion battery thermal runaway development process is as follows:

at a certain time t, describing the state of the lithium ion battery by gas concentration data of the ith gas, and the expression is as follows:

P_i＝(C_i,S_i) (ii) a Wherein S is_i＝ΔC_i/Δt；

C_iDenotes the gas concentration, Δ C, of the ith gas_iRepresenting the gas concentration C in the time interval deltat_iAmount of change, S_iRepresenting a rate of change of the gas concentration of the gas in the ith;

describing the lithium ion battery state at the current moment t by using gas concentration data of various gases, and constructing a battery state model of the lithium ion battery thermal runaway development process, wherein the expression of the battery state model is as follows:

Q_t＝(P₁,P₂,P₃,...,P_m)；

wherein m represents that m types of monitored gases are contained in the environment around the lithium ion battery.

8. The lithium ion battery thermal runaway dynamic early warning method based on the Raman spectrum of claim 7, wherein the construction process of the thermal runaway early warning model is as follows:

constructing a mathematical model P for early warning of ith gas concentration in nth stage of thermal runaway of lithium ion battery_i，nThe expression is as follows:

P_i,n＝(C_i,n,S_i,n,C_n,Si)；

wherein, C_i,nThreshold, S, indicating that gas concentration of the ith gas triggers an nth stage warning_i,nThreshold value, C, representing the gas concentration rate of change of the ith gas triggering the warning of the nth stage_n,SiThe setting value of the concentration parameter of the ith gas for maintaining the normal work of the lithium ion battery at present is represented;

independently judging the early warning state W of the nth stage of the thermal runaway of the lithium ion battery according to the gas concentration threshold of the ith gas_i,nThe expression is as follows:

W_i,n＝(C_i≥C_i,n)∨(S_i≥S_i,n)∧(C_i≥C_n,si)；

judging the state Q of the lithium ion battery at the time t by utilizing the mutual independence of the gas concentrations of m monitored gases_tWhether the nth stage early warning is triggered or not is determined, and the expression is as follows:

W_n＝W_1,n∨W_2,n∨...W_m,n。

9. the lithium ion battery thermal runaway dynamic early warning method based on the Raman spectrum of claim 7, wherein the construction process of the thermal runaway early warning model is as follows:

comprehensively judging the state Q of the lithium ion battery at the time t by selecting the gas concentration parameters of m monitored gases and limiting the gas concentrations of various gases in any combination_tWhether an nth stage early warning signal is triggered or not is determined, and the expression is as follows:

10. the dynamic warning method for thermal runaway of the lithium ion battery based on Raman spectrum according to claim 8 or 9,represents the ambient gas concentration C in the normal state of the lithium ion battery obtained in a plurality of measurements_iAverage value of (1), C_i,nRepresents that the concentration C of the overflow gas of the lithium ion battery under the thermal runaway state in the nth stage is measured in a plurality of measurements_iAverage value of (1), S_i,nThe value of (A) is determined according to the gas concentration C in the ambient environment of the lithium ion battery in the nth stage thermal runaway state measured in a plurality of thermal runaway tests of the battery_iIs the rate of change S_iAverage value of (a).

Technical Field

The invention relates to the technical field of lithium ion batteries, in particular to a thermal runaway dynamic early warning system and method of a lithium ion battery based on Raman spectrum.

Background

At present, the mainstream lithium ion battery thermal runaway detection is based on a battery energy management system (BMS) and is mostly used in the field of electric automobiles, and a thermal runaway alarm is carried out by detecting the terminal voltage and surface temperature abnormity of each battery in real time by taking a built-in voltage sensor and a built-in temperature sensor as measuring means. The thermal runaway monitoring scheme based on the BMS can only be applied to the use stage of the lithium ion battery, and can only detect the surface information of the battery pack, so that the occurrence and development states of thermal runaway inside the battery cell are difficult to judge in time. In addition, the BMS system needs a large number of sensors, so that the hardware cost is high, and meanwhile, the calculation load is caused by a large number of monitoring data, so that the overall performance and the early warning speed of the BMS are influenced.

A large number of researches show that the thermal runaway of the lithium ion battery is a gradual change process of occurrence and development, and in the early stage of the thermal runaway, characteristic gases such as carbon monoxide, carbon dioxide, hydrogen, methane, ethylene and the like overflow outwards, and the thermal runaway process can be monitored by detecting the gases in the surrounding environment of the lithium ion battery. Because the gas has good diffusivity, the gas quickly fills the internal space of the battery pack, and the occurrence and development stage of the thermal runaway of the lithium ion battery can be accurately evaluated at any position of the battery pack. Therefore, the characteristic gas detection technology can be used for monitoring the dynamic early warning of the full-ring thermal runaway of the lithium ion battery in production, transportation, application, recovery and the like. Common gas detection and analysis methods, such as gas chromatography, mass spectrometry, electrochemical gas sensors, semiconductor gas sensors, infrared absorption spectrometry, and the like, respectively have respective defects in the aspects of accuracy, stability, real-time performance, instrument and equipment size, gas type, gas concentration resolution capability, and the like, and are difficult to meet the dynamic early warning requirement of lithium ion thermal runaway. The gas raman spectrum detection technology, as a non-contact detection means, has the remarkable advantages of simplicity, rapidness, high sensitivity, high flux and the like, and can perform online real-time detection on various gas components (including nonpolar diatomic gases such as N2, O2 and H2), so how to provide a raman spectrum-based dynamic early warning system and method for thermal runaway of a lithium ion battery is a problem that needs to be solved by technical personnel in the field.

Disclosure of Invention

In view of the above, the invention provides a dynamic warning system and method for thermal runaway of a lithium ion battery based on raman spectroscopy, which integrate the characteristic gas type and the concentration change rate information thereof, develop a staged thermal runaway warning model of the lithium ion battery, and realize early dynamic warning of thermal runaway.

In order to achieve the purpose, the invention adopts the following technical scheme:

a dynamic early warning system for thermal runaway of a lithium ion battery based on Raman spectrum comprises: the device comprises a laser, a Raman probe, a hollow fiber waveguide, a monochromator, a light splitting path, a photoelectric detection device and an embedded computer which are connected in sequence;

the hollow optical fiber waveguide is used as a gas battery and collects gas in the surrounding environment of the lithium ion battery in real time;

the Raman probe is coupled with the hollow-core optical fiber waveguide; the Raman probe is provided with an input optical fiber and a receiving optical fiber; exciting light emitted by the laser is transmitted into the hollow-core optical fiber waveguide through the input optical fiber to generate Raman spectrum scattering light; after being collected by the receiving optical fiber, the Raman spectrum scattered light is transmitted to the photoelectric detection device after sequentially passing through the monochromator and the light splitting optical path, so as to generate spectrum data, and the spectrum data is transmitted to the embedded computer;

and the embedded computer performs data analysis on the spectrum data, dynamically calculates the concentration change and the concentration change rate of the monitored gas species, and sends out a thermal runaway alarm of the lithium ion battery when the change rates of the gas concentration and the gas concentration exceed threshold values.

Preferably, in the above dynamic warning system for thermal runaway of a lithium ion battery based on raman spectroscopy, both ends of the hollow optical fiber waveguide are connected with an air inlet and an air outlet respectively; and gas in the surrounding environment of the lithium ion battery enters the hollow-core fiber waveguide through the air inlet channel and is discharged from the air outlet.

Preferably, in the above dynamic early warning system for thermal runaway of a lithium ion battery based on raman spectroscopy, a dehumidification filtering unit, a pressure regulation and control unit and a temperature regulation and control unit are sequentially installed on the air inlet channel from the sampling port thereof to the direction of the hollow glass fiber waveguide; the dehumidification filtering unit is used for removing moisture and impurities in the gas; the pressure regulating and controlling unit is used for keeping the gas in the gas inlet channel in a constant pressure state; the temperature regulation and control unit is used for keeping the gas in the air inlet channel in a constant temperature state.

Preferably, in the above raman spectrum-based dynamic early warning system for thermal runaway of the lithium ion battery, an Ag/AgI composite coating is coated on the outer peripheral side of the hollow-core optical fiber waveguide.

Preferably, in the above raman spectrum-based dynamic warning system for thermal runaway of the lithium ion battery, the embedded computer further stores the spectrum data in real time, generates a raman spectrum, and displays the raman spectrum; the Raman spectrum is used for representing the type and concentration change of the monitored gas in the surrounding environment of the lithium ion battery.

Preferably, in the above dynamic early warning system for thermal runaway of a lithium ion battery based on raman spectroscopy, the excitation light emitted by the laser is a high-power narrow-linewidth light beam with a wavelength of 532 nm.

The invention also provides a dynamic early warning method for the thermal runaway of the lithium ion battery based on the Raman spectrum, which is suitable for the dynamic early warning system for the thermal runaway of the lithium ion battery based on the Raman spectrum and comprises the following steps:

taking the gas species component and concentration change flowing through the hollow optical fiber waveguide as the judgment basis of the thermal runaway condition of the lithium ion battery;

constructing a battery state model and a thermal runaway early warning model of a lithium ion battery thermal runaway development process based on gas components and concentration changes;

monitoring the gas type and concentration change in the surrounding environment of the lithium ion battery in real time based on a battery state model in the thermal runaway development process of the lithium ion battery, dynamically calculating the gas concentration change rate, and estimating the thermal runaway state of the lithium ion battery according to the gas concentration change and the gas concentration change rate;

and calculating whether the gas concentration and the concentration change rate of various monitored gases reach a threshold value in real time based on the thermal runaway early warning model, and sending out a thermal runaway alarm when the gas concentration and the concentration change rate exceed the threshold value.

Preferably, in the above dynamic early warning method for lithium ion battery thermal runaway based on raman spectroscopy, the construction process of the battery state model in the development process of lithium ion battery thermal runaway is as follows:

at a certain time t, describing the state of the lithium ion battery by gas concentration data of the ith gas, and the expression is as follows:

P_i＝(C_i,S_i) (ii) a Wherein S is_i＝ΔC_i/Δt；

C_iDenotes the gas concentration, Δ C, of the ith gas_iRepresenting the gas concentration C in the time interval deltat_iAmount of change, S_iRepresenting a rate of change of the gas concentration of the gas in the ith;

describing the lithium ion battery state at the current moment t by using gas concentration data of various gases, and constructing a battery state model of the lithium ion battery thermal runaway development process, wherein the expression of the battery state model is as follows:

Q_t＝(P₁,P₂,P₃,...,P_m)；

wherein m represents that m types of monitored gases are contained in the environment around the lithium ion battery.

Wherein m represents that m types of monitored gases are contained in the environment around the lithium ion battery. The monitored gas species are 10, and comprise 8 thermal runaway characteristic mark gases: CO 2₂，H₂，C₂H₄，CO，C₂H₅F，CH₃OCH₃，CH₃OCHO，CH₄And O present in two kinds of air₂、N₂。

Preferably, in the above dynamic warning method for thermal runaway of a lithium ion battery based on raman spectroscopy, the construction process of the thermal runaway warning model is as follows:

constructing a mathematical model P for early warning of ith gas concentration in nth stage of thermal runaway of lithium ion battery_i，nThe expression is as follows:

P_i,n＝(C_i,n,S_i,n,C_n,Si)；

wherein, C_i,nThreshold, S, indicating that gas concentration of the ith gas triggers an nth stage warning_i,nThreshold value, C, representing the gas concentration rate of change of the ith gas triggering the warning of the nth stage_n,SiThe setting value of the concentration parameter of the ith gas for maintaining the normal work of the lithium ion battery at present is represented;

independently judging the early warning state W of the nth stage of the thermal runaway of the lithium ion battery according to the gas concentration threshold of the ith gas_i,nThe expression is as follows:

W_i,n＝(C_i≥C_i,n)∨(S_i≥S_i,n)∧(C_i≥C_n,si)；

judging the state Q of the lithium ion battery at the time t by utilizing the mutual independence of the gas concentrations of m monitored gases_tWhether the nth stage early warning is triggered or not is determined, and the expression is as follows:

W_n＝W_1,n∨W_2,n∨...W_m,n。

preferably, in the above dynamic warning method for thermal runaway of a lithium ion battery based on raman spectroscopy, the construction process of the thermal runaway warning model is as follows:

comprehensively judging the state Q of the lithium ion battery at the time t by selecting the gas concentration parameters of m monitored gases and limiting the gas concentrations of various gases in any combination_tWhether an nth stage early warning signal is triggered or not is determined, and the expression is as follows:

preferably, in the above dynamic early warning method for thermal runaway of lithium ion battery based on raman spectrum,represents the ambient gas concentration C in the normal state of the lithium ion battery obtained in a plurality of measurements_iAverage value of (1), C_i,nRepresents that the concentration C of the overflow gas of the lithium ion battery under the thermal runaway state in the nth stage is measured in a plurality of measurements_iAverage value of (1), S_i,nThe value of (A) is determined according to the gas concentration C in the ambient environment of the lithium ion battery in the nth stage thermal runaway state measured in a plurality of thermal runaway tests of the battery_iIs the rate of change S_iAverage value of (a).

According to the technical scheme, compared with the prior art, the invention discloses and provides the thermal runaway dynamic early warning system and method for the lithium ion battery based on the Raman spectrum, the high-power narrow-linewidth laser with the wavelength of 532nm is used as a light source, the detection sensitivity of the gas Raman spectrum can be greatly enhanced by combining the Ag/AgI composite coating hollow-core optical fiber waveguide, the related technology has the remarkable advantages of high resolution, high flux, simplicity, rapidness and the like, and the rapid online analysis and detection of the gas can be efficiently realized. In the actual early warning process, the gas Raman spectrum can accurately judge the occurrence and development stages of thermal runaway of different types of lithium ion batteries by measuring the peak intensity of the characteristic spectrum of 10 gases, and a corresponding response threshold is constructed to realize 1-10-level dynamic response, so that the early warning success rate of the thermal runaway of the lithium ion batteries is remarkably improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a schematic structural diagram of a thermal runaway dynamic early warning system of a lithium ion battery based on raman spectroscopy, provided by the invention;

FIG. 2 is an enlarged view of the structure of portion A of FIG. 1 according to the present invention;

fig. 3 is a raman spectrum comparison graph of ambient gas in normal and thermal runaway states of the lithium ion battery provided by the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1-2, an embodiment of the present invention discloses a dynamic warning system for thermal runaway of a lithium ion battery based on raman spectroscopy, which includes: the Raman spectrometer comprises a laser 1, a Raman probe 2, a hollow-core optical fiber waveguide 3, a monochromator 4, a light splitting optical path 5, a photoelectric detection device 6 and an embedded computer 7 which are connected in sequence; wherein, the laser 1 is a 532nm high-power narrow linewidth laser.

The hollow optical fiber waveguide 3 is used as a gas battery, and collects gas in the surrounding environment of the lithium ion battery in real time to detect the sampled gas.

The Raman probe 2 is coupled with the hollow-core optical fiber waveguide 3; the raman probe 2 has an input optical fiber 8 and a receiving optical fiber 9; exciting light emitted by the laser 1 is transmitted into the hollow-core optical fiber waveguide 3 through the input optical fiber 8 to generate Raman spectrum scattering light; after being collected by a receiving optical fiber 9, the Raman spectrum scattered light is transmitted to a photoelectric detection device 6 after sequentially passing through a monochromator 4 and a light splitting optical path 5, so as to generate spectrum data, and the spectrum data is transmitted to an embedded computer 7;

the embedded computer 7 carries out data analysis on the spectral data, dynamically calculates the concentration change and the concentration change rate of the monitored gas species, and sends out a thermal runaway alarm of the lithium ion battery when the gas concentration and the change rate of the gas concentration exceed threshold values. The embedded computer 7 also stores the spectral data in real time, generates a Raman spectrum and displays the Raman spectrum; the raman spectrum is used to characterize the species and concentration changes of the monitored gas in the environment surrounding the lithium ion battery.

In one embodiment, the air inlet 10 and the air outlet 11 are respectively connected to two ends of the hollow-core fiber waveguide 3; the gas in the surrounding environment of the lithium ion battery enters the hollow-core fiber waveguide 3 through the gas inlet 10 and then is discharged out of the hollow-core fiber waveguide 3 through the gas outlet 11.

More advantageously, the air inlet 10 is sequentially provided with a dehumidifying and filtering unit 12, a pressure regulating and controlling unit 13 and a temperature regulating and controlling unit 14 from the sampling port to the direction of the hollow glass fiber waveguide 3; the dehumidifying filter unit 12 is used for removing moisture and impurities in the gas; the pressure regulating unit 13 is used for keeping the gas in the gas inlet channel in a constant pressure state; the temperature control unit 14 is used for keeping the gas in the inlet channel in a constant temperature state. The dehumidification filtering unit 12, the pressure regulation and control unit 13 and the temperature regulation and control unit 14 are arranged, so that the stability of the measurement condition can be ensured, and the gas detection and the spectral data analysis and comparison of the laser Raman spectrum can be conveniently realized.

The periphery of the hollow-core optical fiber waveguide 3 is coated with an Ag/AgI composite coating, so that the detection sensitivity of the gas Raman spectrum can be greatly enhanced.

The embodiment of the invention also provides a lithium ion battery thermal runaway dynamic early warning method based on the Raman spectrum, which is suitable for the lithium ion battery thermal runaway dynamic early warning system based on the Raman spectrum, and comprises the following steps:

the gas species component and concentration change flowing through the hollow optical fiber waveguide are used as the judgment basis of the thermal runaway condition of the lithium ion battery;

constructing a battery state model and a thermal runaway early warning model of a lithium ion battery thermal runaway development process based on gas components and concentration changes;

monitoring the gas type and concentration change in the surrounding environment of the lithium ion battery in real time based on a battery state model of the lithium ion battery in the thermal runaway development process, dynamically calculating the gas concentration change rate, and predicting the thermal runaway state of the lithium ion battery according to the gas concentration change and the gas concentration change rate;

and calculating whether the gas concentration and the concentration change rate of various monitored gases reach a threshold value in real time based on a thermal runaway early warning model, and sending out a thermal runaway alarm when the gas concentration and the concentration change rate exceed the threshold value.

The embodiment of the invention adopts a gas Raman spectrum detection system to detect the peripheral gas of the lithium ion battery in real time in a pumping mode, takes the change rate of the gas type and concentration as a judgment condition for judging the thermal runaway of the lithium ion battery, carries out comprehensive online analysis on the data of various gases, judges the generation and development stages of the thermal runaway of the battery, and carries out dynamic grading alarm according to the danger degree and the stages of the thermal runaway.

Setting the target gas to include CO₂，H₂，C₂H₄，CO，C₂H₅F，CH₃OCH₃，CH₃OCHO，CH₄Eight thermal runaway features mark the presence of O in gas and air₂、N₂There are 10 gases in total. Let C_iRepresents the i-th gas concentration data, Δ C_iData C representing the gas concentration over a time period Δ t (i.e., the integration time of the Raman spectroscopy measurement)_iThe amount of change of (c), the rate of change S of the gas concentration_iExpressed as: s_i＝ΔC_i/Δt。

Cell state P described by the i-th gas concentration data at a certain moment_iExpressed as:

P_i＝(C_i,S_i)

battery state model Q of current time t described by ten gas concentration data_tExpressed as:

Q_t＝(P₁,P₂,P₃,…,P₁₀)。

mathematical model P for early warning of ith gas concentration in nth stage of thermal runaway of lithium ion battery_i,nExpressed as:

wherein, C_i，_nTriggering threshold of nth stage early warning for ith gas concentration, S_i,nTriggering a threshold for the nth phase warning for the ith gas concentration change rate,the set value of the concentration parameter of the ith gas for maintaining the normal work of the lithium ion battery at present.

Independently judging the nth stage early warning W of the thermal runaway of the lithium ion battery according to the concentration threshold of the ith gas_i，nThe decision formula of (1) is as follows:

judging the battery state Q at the time t by mutually independent 10 kinds of monitored gas concentrations_tWhether to trigger nth stage early warning W_nThe formula of (1) is:

W_n＝W_1，n∨W_2，n∨…VW_10，n

the thermal runaway state of the battery is comprehensively judged through a plurality of items in the 10 measured gas concentration parameters, and the mathematical model expression of the thermal runaway of the 10 gas concentrations triggering the nth stage early warning is as follows:

…

comprehensively judging the battery state Q at the time t by selecting 10 gas concentration parameters and limiting the concentration of various gases in any combination_tWhether to trigger the nth stage early warning signal.

The normal state of the lithium ion battery is realized by the following modes: in a measurement gas circuit, high-purity nitrogen or inert gas is firstly injected for 2 minutes, and then dry and pure air in the environment is used for blowing, the air is measured by utilizing the thermal runaway dynamic early warning system of the lithium ion battery based on the Raman spectrum, and the measurement process comprises the following steps:

firstly, the dehumidification filtering unit 12, the pressure regulation and control unit 13 and the temperature regulation and control unit 14 are adopted to maintain the constant temperature and the constant pressure of the monitored gas in the gas tank, so that the uniformity of Raman spectrum measurement conditions is ensured, and the establishment of a subsequent mathematical model and the thermal runaway early warning are facilitated.

And secondly, correcting and calibrating the system, sampling and measuring the air in the normal environment, and obtaining the background spectrum data of the thermal runaway Raman spectrum gas detection of the lithium ion battery. Multiple thermal runaway tests of battery are carried out, and early warning method is implementedC_i，nAnd S_i，nAnd the numerical values are set.

Finally, by adopting the battery state model and the thermal runaway early warning model of the embodiment of the invention, the change of the gas type and the concentration is used as a judgment condition for judging the occurrence of the thermal runaway of the lithium ion battery, the occurrence and development stages of the thermal runaway of the battery are judged, and the alarm is graded according to the danger degree and the stages of the thermal runaway occurrence.

As shown in FIG. 3, which is a comparison graph of Raman spectra of ambient gas under normal and thermal runaway conditions of a lithium ion battery, the abscissa is wave number, and the ordinate is dimensionless intensity value, it can be seen by comparison that H absent in air occurs in the thermal runaway release process of the lithium ion battery₂And various hydrocarbon gases, as well as the original O in the air₂And N₂The content is obviously reduced, which shows that the Raman spectrum-based lithium ion battery thermal runaway dynamic early warning technology can perform high-dynamic and large-flux real-time online monitoring analysis and has the capability of generating and developing complete gas component and concentration data information of the whole period for the lithium ion battery thermal runaway.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.