Lithium battery thermal runaway early warning method based on soc, temperature and deformation

Abstract

The application provides a lithium battery thermal runaway early warning method based on SOC, temperature and deformation, which comprises the following steps: collecting deformation, temperature and state of charge (SOC) output by a sensor during an initial cycle stage and a subsequent cycle process of a target lithium battery, and establishing a thermal output reference, a deformation-SOC reference and a creep reference during the initial cycle stage respectively; obtaining a deformation caused by battery expansion according to the thermal output reference and a thermal output component caused by real-time temperature; obtaining a fatigue aging drift of the sensor according to the creep reference, a creep drift component of the sensor during a static period and a total drift during the static period; obtaining a real deformation of the sensor according to a sensitivity factor of the sensor, a deformation caused by battery expansion at each SOC and a total drift; and comparing the real deformation with the deformation-SOC reference to determine whether the target lithium battery has a thermal runaway risk. The method realizes early identification and graded early warning of the thermal runaway risk, and effectively improves the early warning reliability.

Description

Technical Field

[0001] This invention relates to the field of lithium battery safety monitoring and battery management system technology, specifically to a lithium battery thermal runaway early warning method, device and storage medium based on SOC, temperature and deformation. Background Technology

[0002] Lithium-ion batteries, with their advantages of high energy density, long cycle life, and low self-discharge rate, are widely used in new energy vehicles, energy storage power stations, and portable electronic devices. However, during charge-discharge cycles and aging, lithium-ion batteries are prone to internal micro-short circuits, electrolyte decomposition, electrode expansion, and abnormal thickening of the SEI film, which can ultimately lead to safety accidents such as thermal runaway, fire, and explosion. Therefore, accurate detection and early warning throughout the entire life cycle are crucial for ensuring the safe operation of lithium-ion batteries. Currently, the industry's lithium-ion battery status detection and thermal runaway early warning technologies are mainly divided into two mainstream solutions: 1. Voltage and temperature-based early warning solutions: This solution suffers from a severe lag in the parameters it collects. When a sudden drop in voltage or a sudden rise in temperature is detected, serious internal side reactions have already occurred, leaving very little time for intervention and making early prediction and proactive protection impossible. 2. Battery expansion force-based monitoring solutions: To address the lag in voltage and temperature detection, existing technologies typically place pressure sensors in the middle of individual battery cells. Once the battery module is packaged, these sensors cannot be removed or replaced. If the sensor fails, the entire monitoring system fails, resulting in extremely high maintenance costs.

[0003] In summary, existing technologies suffer from problems such as inaccurate battery health status assessment, delayed early warning, poor sensor adaptability to operating conditions, and inconvenient operation and maintenance. Therefore, there is an urgent need for a high-precision, proactive, and stable early warning method for battery thermal runaway risks. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a lithium battery thermal runaway early warning method, device and storage medium based on SOC, temperature and deformation that can realize early identification and graded early warning of thermal runaway risk and effectively improve the reliability of early warning.

[0005] In a first aspect, the present invention provides a method for early warning of thermal runaway in lithium batteries based on SOC, temperature, and deformation, wherein a flexible deformation sensor is attached to the side of the lithium battery cell, and the method includes the following steps:

[0006] S1. During the initial cycling phase of the target lithium battery, the deformation, temperature, and state of charge (SOC) output by the sensor are collected, and thermal output reference, deformation-SOC reference, and creep reference are established respectively. Among them, the thermal output reference represents the relationship between the thermal deformation of the sensor and the temperature; the deformation-SOC reference represents the relationship between the deformation of the target lithium battery caused by battery expansion under normal conditions and the SOC; the creep reference represents the relationship between the plastic deformation of the sensor under static conditions and constant temperature and the time.

[0007] S2. During the subsequent cycling process of the target lithium battery, deformation, temperature and state of charge (SOC) are collected synchronously in real time.

[0008] S3. Based on the heat output reference and the heat output component caused by the real-time temperature, obtain the deformation caused by battery expansion;

[0009] S4. Based on the creep reference, the creep drift component of the sensor during the resting period, and the total drift during the resting period, the fatigue aging drift of the sensor is obtained.

[0010] S5. The true deformation of the sensor is obtained based on the sensor's sensitivity factor, the deformation caused by battery expansion at each SOC, and the total drift. The sensitivity factor is obtained based on the sensor's impulse response change, and the true deformation is used to represent the actual degree of change of the target lithium battery compared to its initial state.

[0011] S6. Compare the actual deformation with the deformation-SOC benchmark, and determine whether the target lithium battery has a risk of thermal runaway based on the comparison results.

[0012] In a second aspect, the present invention also provides an apparatus comprising one or more processors and a memory, wherein the memory contains instructions executable by the one or more processors to cause the one or more processors to perform a lithium battery thermal runaway early warning method based on SOC, temperature and deformation according to various embodiments of the present invention.

[0013] Thirdly, the present invention also provides a storage medium storing a computer program that enables a computer to execute a lithium battery thermal runaway early warning method based on SOC, temperature, and deformation according to various embodiments of the present invention.

[0014] The lithium battery thermal runaway early warning method based on SOC, temperature, and deformation provided by various embodiments of the present invention collects the deformation, temperature, and SOC output by sensors during the initial cycling stage of the target lithium battery, and establishes thermal output benchmark, deformation-SOC benchmark, and creep benchmark respectively. During the subsequent cycling process of the target lithium battery, deformation, temperature, and SOC are collected synchronously in real time. Based on the thermal output benchmark and the thermal output component caused by real-time temperature, the deformation caused by battery expansion is obtained. Based on the creep benchmark, the creep drift component of the sensor during the resting period, and the total drift during the resting period, the fatigue aging drift of the sensor is obtained. Based on the sensor's sensitivity factor, the deformation caused by battery expansion at each SOC, and the total drift, the true deformation of the sensor is obtained. The sensitivity factor is obtained based on the change in the sensor's impulse response, and the true deformation is used to represent the actual degree of change of the target lithium battery compared to its initial state. The true deformation is compared with the deformation-SOC benchmark, and the method of judging whether the target lithium battery has a risk of thermal runaway is determined based on the comparison results. This method realizes early identification and graded early warning of thermal runaway risk, effectively improving the reliability of early warning. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the installation of a flexible deformation sensor according to an embodiment of the present invention.

[0016] Figure 2 The flowchart illustrates a lithium battery thermal runaway early warning method based on SOC, temperature, and deformation, as provided in an embodiment of the present invention.

[0017] Figure 3 This is a schematic diagram of the structure of a device provided in an embodiment of the present invention. Detailed Implementation

[0018] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0019] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] like Figure 2 As shown, this invention provides a method for early warning of thermal runaway in lithium batteries based on SOC, temperature, and deformation, using a flexible deformation sensor such as... Figure 1 As shown, it is pasted onto the side of the lithium battery cell. The above method includes the following steps:

[0021] S1: During the initial cycling phase of the target lithium battery, the deformation, temperature, and state of charge (SOC) output by the sensor are collected, and thermal output reference, deformation-SOC reference, and creep reference are established respectively. Among them, the thermal output reference represents the relationship between the thermal deformation of the sensor and the temperature; the deformation-SOC reference represents the relationship between the deformation of the target lithium battery caused by battery expansion under normal conditions and the SOC; the creep reference represents the relationship between the plastic deformation of the sensor under static conditions and constant temperature and the time.

[0022] S2: During the subsequent cycling process of the target lithium battery, deformation, temperature and state of charge (SOC) are collected synchronously in real time.

[0023] S3: Based on the thermal output reference and the thermal output component caused by real-time temperature, obtain the deformation caused by battery expansion;

[0024] S4: Based on the creep reference, the creep drift component of the sensor during the resting period, and the total drift during the resting period, the fatigue aging drift of the sensor is obtained.

[0025] S5: The true deformation of the sensor is obtained based on the sensor's sensitivity factor, the deformation caused by battery expansion at each SOC, and the total drift. The sensitivity factor is obtained based on the sensor's impulse response change, and the true deformation is used to represent the actual degree of change of the target lithium battery compared to its initial state.

[0026] S6: Compare the actual deformation with the deformation-SOC benchmark, and determine whether the target lithium battery has a risk of thermal runaway based on the comparison results.

[0027] Specifically, in step S1:

[0028] 1) Parameter Acquisition: During the initial cycling phase of the target lithium battery (the first cycle (or battery certification test cycle)), the time series of the following parameters are simultaneously acquired:

[0029] Deformation The initial rest period before the start of the first cycle, during which the battery is neither charging nor discharging, is defined as the sensor output at this point as zero. ; All subsequent deformation values ​​refer to the amount of change relative to this zero point: The flexible deformation sensor is attached to the geometric center of the side of the lithium battery cell; In more embodiments, the flexible deformation sensor can be attached to other positions on the side of the lithium battery cell according to actual needs, without specific limitations, and similar technical effects can be obtained.

[0030] Temperature T(t): The temperature sensor is attached 1 cm away from the flexible deformation sensor;

[0031] Voltage V(t) and current I(t) are obtained by voltage sampling circuit and current sampling circuit, respectively, with a sampling frequency of not less than 1Hz.

[0032] The state of charge (SOC) is calculated from the voltage V(t) and current I(t) using conventional algorithms in the prior art.

[0033] Normal loop start state: SOC=5%, end state: SOC=95%;

[0034] 2) Establish a thermal output reference for the deformation sensor: Change the ambient temperature and record the deformation output of the deformation sensor relative to time t0. Since the initial time has been zeroed out, the heat output model is as follows:

[0035]

[0036] Where T is the real-time temperature, and the coefficients a, b, and c are obtained through fitting.

[0037] 3) Establish the deformation-SOC benchmark (ε-SOC benchmark): After subtracting the thermal output from the original deformation of the deformation sensor, the deformation change caused by battery expansion is obtained:

[0038]

[0039] Will Resample at equal intervals according to SOC (step size can be 0.5% or 1%) to obtain the expansion deformation ε-SOC benchmark:

[0040]

[0041] in, For the base loop The corresponding deformation change, this benchmark reflects the variation of the deformation of the target lithium battery under normal conditions (reference temperature) with SOC. Simultaneously, it records... (Rate of deformation);

[0042] 4) Establish creep baseline: During the resting phase (already zeroed) before the start of the initial cycle, record the plastic deformation output of the flexible deformation sensor over time. Since the initial value is zero, the creep model is: The coefficients were obtained by fitting. , ;

[0043] 5) Establish an active impulse response benchmark

[0044] After the initial cycle was completed, at room temperature (25°C), during the battery resting phase (SOC=50%), a short-time current pulse was injected (pulse current: 2mA, pulse width: 3ms), and the dynamic response of deformation change was recorded: peak value change. ;

[0045] In step S2:

[0046] In subsequent cycles of the target lithium battery (the kth cycle (k≥1)), real-time data collection is performed. and SOC;

[0047] In step S3:

[0048] Thermal output subtraction: In the same reference stage, after subtracting the thermal output component caused by real-time temperature based on the thermal output reference, the deformation caused only by battery expansion is obtained. :

[0049]

[0050] SOC domain resampling: Resampling at equal intervals according to SOC (step size can be 0.5% or 1%) yields the following sequence:

[0051]

[0052] In step S4:

[0053] Predict the current settling time based on creep baseline ( Creep drift component within) , This is the total duration of the rest phase before the start of each cycle.

[0054] Based on the total drift during the resting period (During the resting period before the start of the kth cycle) (Total drift of internal deformation sensor) and creep drift component Heat output at current temperature Calculate the fatigue aging drift of the flexible deformation sensor :

[0055]

[0056] In step S5:

[0057] At fixed cycle intervals (e.g., every 50 cycles), at room temperature (25°C) and with the battery at rest (SOC=50%), inject a current pulse (pulse current: 2mA, pulse width: 3ms); record the pulse response curve of the deformation sensor and extract the current peak deformation. ;in, The peak deformation of the battery under quiescent conditions (SOC=50%) after the initial cycle is completed, at room temperature of 25°C, with the battery at rest. A short-time current pulse (pulse current: 2mA, pulse width: 3ms) is injected.

[0058] Sensor sensitivity factor:

[0059]

[0060] Each Compensated deformation After deducting fatigue aging drift (assuming uniform distribution with SOC) and compensating for sensitivity decay, the true deformation of the target lithium battery is obtained. :

[0061]

[0062] This value represents the actual expansion change of the battery itself relative to its initial state, eliminating the effects of sensor creep, fatigue, and decreased sensitivity.

[0063] In step S6:

[0064] Real-time monitoring of temperature T(t) and its rate of change Real deformation and its rate of change The SOC is converted into a decimal between 0 and 1 (0% to 100%) for processing. The unit is ;

[0065] Level 1 warning: When and When the system is running at full load (water cooling / air cooling), the charging and discharging power is limited (charging current is reduced to 50% of the rated value, and discharging current is limited to 80% of the rated value).

[0066] Level II warning: When T > 40℃ and When the damage continues to increase, the main charging and discharging relay will be immediately disconnected, the energy storage power station will be linked to the grid and disconnected from the grid connection switch, the BMS will locate and report the fault, issue an audible and visual alarm, and record the data for the 10 minutes before the warning to provide support for fault tracing.

[0067] Level 3 warning: When T > 60℃ and and If this indicates that the safety valve has been opened, immediately activate the fire extinguishing device inside the battery pack.

[0068] The above embodiments can achieve early identification and graded warning of thermal runaway risk, effectively improving the reliability of warning.

[0069] Furthermore, after step S6, step S7 is also included:

[0070] The health status of the flexible deformation sensor is assessed based on the number of battery cycles and the corresponding sensitivity factor during active pulses.

[0071] The first method of judgment is:

[0072] Record the number of battery cycles during active pulses. (Record once every 50 cycles) and the corresponding sensitivity factor A linear degradation model is adopted. Fit the most recent n data points, where Estimated by least squares method:

[0073]

[0074] Set sensitivity failure threshold ;

[0075] Remaining lifespan ,in, Let i be the current sensitivity factor, and i be the i-th value within the most recent n data points.

[0076] When RUL < 20, stop data acquisition and use of the flexible deformation sensor and prompt to replace the flexible deformation sensor.

[0077] The second method of judgment is:

[0078] Establishing a health index based on the self-attenuation characteristics of flexible deformation sensors :

[0079]

[0080] Set sensitivity failure threshold Fatigue drift failure threshold = ;

[0081] when If this occurs, stop data acquisition and use of the flexible deformation sensor and prompt the user to replace the flexible deformation sensor.

[0082] in, For fatigue aging drift, weight .

[0083] Specifically, the following is an example with data:

[0084] The flexible deformation sensor and temperature sensor were attached to the geometric center of the battery side. After standing for 2 hours at 25°C and SOC=5%, the sensor output was adjusted to 0 (i.e., the amount of deformation change). Record the initial temperature T0 = 25℃;

[0085] Initial cycle data acquisition: A complete charge-discharge cycle is performed at a 0.5C rate: first, constant current charging to 3.65V, then constant current discharging to 2.7V, with a sampling frequency of 1Hz. The following signals are acquired simultaneously: deformation. Temperature T (°C), Voltage U (V), Current I (A), State of Charge (%);

[0086] By changing the ambient temperature and then compensating for temperature variations, the deformation of the deformation sensor output relative to time t0 is recorded. ;by For example, as shown below:

[0087]

[0088] Fit coefficients ;

[0089] The following benchmark points were obtained:

[0090] Creep benchmark:

[0091] After being left to stand for 24 hours, the output of the flexible deformation sensor drifted from 0 to... Collect samples every half hour. To obtain the creep reference by fitting. ;by For example, as shown below:

[0092]

[0093] Fit coefficients ;

[0094] 300th cycle:

[0095] With the battery having undergone 300 cycles (ambient temperature 25-30℃), and after resting for 1 hour at 26.5℃ before the start of the 300th cycle, the sensor output change... For example;

[0096] Settling period:

[0097] Creep prediction:

[0098] Heat output:

[0099] Fatigue aging drift:

[0100] This indicates that slippage or plastic deformation has occurred between the sensor and the adhesive layer. Irreversible drift;

[0101] Sensitivity attenuation factor:

[0102] After 300 cycles, during the resting phase, an active pulse was applied again (at room temperature of 25°C, with the battery at rest (SOC=50%), pulse current: 2mA, pulse width: 3ms) to measure the peak deformation change. , The benchmark value is For example, sensor sensitivity attenuation factor This means a 12.5% ​​decrease in sensitivity;

[0103] Actual deformation change of the battery:

[0104] The deformation of a battery after compensation is calculated when the SOC is 50% after 300 cycles. The fatigue aging drift is 210. Taking 28.575 as an example, its actual deformation change is:

[0105] ;

[0106] The benchmark value is , Increase This indicates that the battery is irreversibly expanding.

[0107] Thermal runaway warning:

[0108] For example, the following anomaly was detected when the SOC was 95% during the 300th charge cycle:

[0109] , The system outputs a Level 1 warning, activates the cooling system, and limits the charging power.

[0110] If the temperature continues to rise to 62℃, and , The system outputs a Level 3 warning, immediately disconnects the main circuit relay, and activates the fire protection system;

[0111] Sensor lifespan prediction:

[0112] Record the sensitivity decay factor after 150, 200, 250, and 300 cycles:

[0113]

[0114] First method of judgment:

[0115] Adopting a degradation model Fitting by least squares method

[0116]

[0117]

[0118] Remaining lifespan:

[0119]

[0120] Remaining lifespan: 670 cycles; no replacement prompt will be triggered.

[0121] The second method of judgment:

[0122] Establishing a health index based on the self-attenuation characteristics of flexible deformation sensors :

[0123]

[0124] Set sensitivity failure threshold Fatigue drift failure threshold = , ;

[0125]

[0126] No replacement prompt will be triggered.

[0127] Figure 3 This is a schematic diagram of the structure of a device provided in an embodiment of the present invention.

[0128] like Figure 3 As shown, in another aspect, this application also provides a device including one or more central processing units (CPUs) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage portion 308 into a random access memory (RAM) 303. Various programs and data required for device operation are also stored in the RAM 303. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0129] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0130] In particular, according to embodiments of this disclosure, the methods described in any of the above embodiments can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for performing any of the above methods. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311.

[0131] In another aspect, this application also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus of the above embodiments; or it may be a standalone computer-readable storage medium not assembled into the device. The computer-readable storage medium stores one or more programs that are used by one or more processors to perform the methods described in this application.

[0132] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or operation, or by a combination of dedicated hardware and computer instructions.

[0133] The units or modules described in the embodiments of this application can be implemented in software or hardware. The described units or modules can also be located in a processor; for example, each unit can be a software program located in a computer or mobile smart device, or a separately configured hardware device. The names of these units or modules do not, in some cases, constitute a limitation on the unit or module itself.

[0134] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the concept of this application. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for early warning of thermal runaway in lithium batteries based on SOC, temperature, and deformation, characterized in that, A flexible deformation sensor is attached to the side of a lithium battery cell. The method includes the following steps: S1. During the initial cycling phase of the target lithium battery, the deformation, temperature, and state of charge (SOC) output by the sensor are collected, and a thermal output reference, a deformation-SOC reference, and a creep reference are established respectively. The thermal output reference represents the relationship between the thermal deformation of the sensor and temperature; the deformation-SOC reference represents the relationship between the deformation of the target lithium battery caused by battery expansion under normal conditions and SOC; and the creep reference represents the relationship between the plastic deformation of the sensor under static conditions and constant temperature and time. S2. During subsequent cycles of the target lithium battery, the deformation, temperature, and state of charge (SOC) are collected synchronously in real time. S3. Based on the heat output reference and the heat output component caused by the real-time temperature, obtain the deformation caused by battery expansion; S4. Based on the creep reference, the creep drift component of the sensor during the resting period, and the total drift during the resting period, the fatigue aging drift of the sensor is obtained; S5. The true deformation of the sensor is obtained based on the sensor's sensitivity factor, the deformation caused by battery expansion at each SOC, and the total drift; wherein the sensitivity factor is obtained based on the sensor's impulse response change, and the true deformation is used to represent the actual degree of change of the target lithium battery compared to its initial state; S6. Compare the actual deformation with the deformation-SOC benchmark, and determine whether the target lithium battery has a risk of thermal runaway based on the comparison results.

2. The method according to claim 1, characterized in that, The heat output reference is a polynomial of temperature, and the polynomial is: Where T is the real-time temperature, and the coefficients a, b, and c are obtained through fitting. This serves as the thermal output reference.

3. The method according to claim 1, characterized in that, The creep reference is a logarithmic time function, which is: Among them, coefficient , Obtained through fitting, This serves as the creep reference.

4. The method according to claim 1, characterized in that, In the initial cycling phase of the target lithium battery, an active pulse response benchmark was also established; wherein, the pulse response benchmark represents the peak deformation of the initial pulse response after the sensor is injected with a short-time current pulse in a static state and at a constant temperature after the first cycle is completed. The sensitivity factor is the ratio of the current peak deformation of the impulse response to the initial peak deformation of the impulse response, and the sensitivity factor is updated every fixed number of cycles.

5. The method according to claim 1, characterized in that, The actual deformation is compared with the deformation-SOC benchmark, and the determination of whether the target lithium battery has a risk of thermal runaway based on the comparison results includes: Real-time monitoring of temperature and temperature change rate, the actual deformation and the actual deformation change rate; wherein, the actual deformation change rate is calculated based on the actual deformation and the state of charge (SOC); When the temperature change rate is greater than the first temperature change rate threshold and the actual deformation change rate is greater than the first actual deformation change rate threshold, the heat dissipation system is started to operate at full load and the charging and discharging power is limited. When the temperature exceeds the first temperature threshold and the rate of change of the actual deformation continues to increase, the main charging and discharging relay is immediately disconnected, the energy storage power station is linked to the grid to disconnect the grid connection switch, the BMS locates and reports, issues an audible and visual alarm, and records the data for the 10 minutes before the warning, providing support for fault tracing. When the temperature is greater than the second temperature threshold, the rate of temperature change is greater than the second rate of temperature change threshold, and the rate of change of actual deformation is greater than the second rate of change of actual deformation threshold, the fire extinguishing device inside the battery pack shall be activated immediately. Wherein, the first temperature threshold is less than the second temperature threshold, the first true deformation rate threshold is less than the second true deformation rate threshold, and the first temperature rate threshold is less than the second temperature rate threshold.

6. The method according to claim 1, characterized in that, After determining whether the target lithium battery has a risk of thermal runaway, the process further includes step S7: The health status of the sensor is assessed based on the number of battery cycles and the corresponding sensitivity factor during active pulses.

7. The method according to claim 6, characterized in that, The assessment of the sensor's health status based on the battery's cycle count and corresponding sensitivity factor during active pulses includes: Record the number of battery cycles during active pulses. and the corresponding sensitivity factor A linear degradation model is adopted. Fit the data to the most recent n data points; where, Estimated by least squares method: Set sensitivity failure threshold ; Remaining lifespan ,in This is the sensitivity factor for the current pulse; when During the next cycle, data acquisition and use of the sensor are stopped, and a prompt is displayed to replace the sensor.

8. The method according to claim 6, characterized in that, The assessment of the sensor's health status based on the battery's cycle count and corresponding sensitivity factor during active pulses includes: A health index is established based on the sensor's own attenuation characteristics. : Set sensitivity failure threshold Fatigue drift failure threshold = ; when If this occurs, stop data acquisition and use of the sensor, and prompt the user to replace the sensor. in, The fatigue aging drift amount, weight .

9. A device for early warning of thermal runaway, characterized in that, The device includes: One or more processors; Memory, used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in any one of claims 1-8.

10. A storage medium storing a computer program, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-8.

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