Solid-state battery thermal runaway early warning method and system based on electric-magnetic dual-mode fusion

Abstract

The invention relates to the technical field of battery management, in particular to a solid-state battery thermal runaway early warning method and system based on electric-magnetic dual-mode fusion. The method comprises the following steps: injecting a sinusoidal current disturbance signal with a preset frequency into a to-be-detected solid-state battery, and synchronously acquiring a voltage response signal of the battery; performing time-frequency transformation on the voltage response signal to obtain time-frequency domain representation; calculating an energy concentration index and a time continuity index based on the time-frequency domain representation; if it is judged that a first early warning condition is met based on the energy concentration index and the time continuity index, first-stage early warning is triggered; after the first-stage early warning is triggered, starting non-contact monitoring on an external magnetic field of the solid-state battery; and on the basis of the monitored magnetic field data, judging that a second early warning condition is met, and triggering second-stage early warning. According to the invention, early, rapid and non-destructive early warning of thermal runaway can be realized.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and in particular to a method and system for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion. Background Technology

[0002] With the rapid development of electric vehicles, higher demands are being placed on the energy density and safety of power batteries. Solid-state batteries are considered an important direction for the next generation of power batteries due to their high energy density and high safety, but their thermal runaway behavior is not yet fully understood. Existing thermal runaway early warning methods are mostly designed for traditional lithium-ion batteries, employing electrical methods such as contact electrochemical impedance spectroscopy (EIS), which suffer from problems such as information redundancy, computational complexity, and impedance instability at high temperatures.

[0003] Furthermore, existing methods are difficult to perform non-destructive testing when the battery is nearing failure, and lack adaptability to the non-uniformity of interfacial impedance in solid-state batteries at high temperatures.

[0004] Therefore, there is an urgent need for a method that can solve the problems of information redundancy, low computational efficiency, high-temperature failure and poor reliability faced by existing early warning methods in solid-state battery applications, and achieve early, rapid and non-destructive early warning of thermal runaway. Summary of the Invention

[0005] In view of the above problems, this disclosure provides a solid-state battery thermal runaway early warning method and system based on electro-magnetic dual-mode fusion to overcome or at least partially solve the above problems. The purpose is to solve the problems of information redundancy, low computational efficiency, high-temperature failure and poor reliability faced by existing early warning methods in solid-state battery applications, and to achieve early, rapid and non-destructive early warning of thermal runaway.

[0006] The objective of this invention can be achieved through the following technical solutions: A first aspect of the present invention provides a method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion, comprising: A sinusoidal current disturbance signal of a preset frequency is injected into the solid-state battery under test, and the voltage response signal of the battery is acquired simultaneously; the voltage response signal is transformed by time and frequency to obtain a time-frequency domain representation. Based on the time-frequency domain representation, the energy concentration index and the time continuity index are calculated; If the energy concentration index and time continuity index are used to determine whether the first warning condition is met, then the first stage warning is triggered. After triggering the first-stage warning, non-contact monitoring of the external magnetic field of the solid-state battery is initiated. If the monitored magnetic field data is determined to meet the second warning condition, then the second-stage warning will be triggered.

[0007] further, The first warning condition is that the energy concentration index is greater than a first threshold and the time continuity index is less than a second threshold.

[0008] further, The second warning condition is the occurrence of a preset abnormal magnetic field event; the preset abnormal magnetic field event is a reversal of magnetic field polarity.

[0009] further, The step of performing time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation includes: Based on the generalized S-transform, the time-domain voltage response is converted into a time-frequency domain signal. The discrete form of the generalized S-transform is as follows: ; Where n, k, and m are time, frequency, and time index, respectively; The signal is a discrete voltage response with a length of N and a sampling frequency of . ; A sliding Gaussian window; The width of the Gaussian window is related to the frequency. Inversely proportional, ; Discrete frequency (Hz); right Logarithmic scaling is performed to obtain the time-frequency domain. .

[0010] further, The calculation of the Energy Concentration Index (ECI) includes: Based on the time-frequency domain, the amplitude profile in the frequency dimension is calculated. , represented as: ; in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; The normalized fourth moment of the amplitude profile is calculated as the energy concentration index (ECI), expressed as: ; in, Number of frequency points; for The mean; It is the square of the variance.

[0011] further, Calculating the Time Continuity Index (TCI) includes: Based on the time-frequency domain, the amplitude profile in the time dimension is calculated. , Represented as: ; in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; Calculate the coefficient of variation of the amplitude profile. , represented as ; in, The mean; Standard deviation; TCI was obtained .

[0012] Furthermore, after triggering the first-stage warning, the non-contact monitoring of the external magnetic field of the solid-state battery is initiated, including: After triggering the first-stage warning, monitor the magnetization of the solid-state battery. , represented as: ,in, For volume, denoted as , where is the magnetic moment of a single metal atom.

[0013] further, The magnetization The change in the external magnetic field of the battery It can be represented as: ; in, These are geometric constants related to the sensor location and battery structure. The mass magnetic susceptibility of the metal deposit. This represents the cumulative mass of the transition metal reduction products.

[0014] A second aspect of the present invention provides a solid-state battery thermal runaway early warning system based on electro-magnetic dual-mode fusion, comprising: The signal excitation and acquisition module is used to inject a sinusoidal current disturbance signal of a preset frequency into the solid-state battery under test and simultaneously acquire the voltage response signal of the battery. The signal processing module is used to perform time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation; and to calculate the energy concentration index and the time continuity index based on the time-frequency domain representation. The magnetic field monitoring module is used to initiate non-contact monitoring of the external magnetic field of the solid-state battery after the first stage warning is triggered. The early warning module is used to determine whether the first early warning condition is met based on the energy concentration index and the time continuity index, and to trigger the first stage of early warning. Based on the monitored magnetic field data, it is used to determine whether the second warning condition is met and to trigger the second-stage warning.

[0015] A third aspect of the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the solid-state battery thermal runaway early warning method based on electro-magnetic dual-mode fusion as described in the first aspect.

[0016] The technical solution proposed in this application can bring the following beneficial effects: 1. This invention adopts a full-stage non-invasive early warning system, integrating electrical and magnetic monitoring to achieve full-process coverage from slow interface degradation to the precursor of violent explosion. In the final stage, non-contact monitoring is used to achieve non-invasive diagnosis.

[0017] 2. This invention satisfies the requirement of rapid online calculation. This invention directly analyzes the 1kHz single-frequency response signal, avoiding the full-band scanning and complex calculation of traditional EIS, and shortening the online time to 0.007 seconds.

[0018] 3. This invention establishes two new indices, Energy Concentration Index (ECI) and Time Continuity Index (TCI), to evaluate the performance of early warning response signals online, and quantifies the interface impedance non-uniformity and state fluctuation of solid-state batteries respectively, so as to realize quantitative early warning of thermal runaway.

[0019] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are described below. Attached Figure Description

[0020] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this disclosure. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart illustrating the steps of a solid-state battery thermal runaway early warning method based on electro-magnetic dual-mode fusion, as provided in the embodiments of this specification. Figure 2 This is a three-dimensional time-frequency diagram of a solid-state battery under normal conditions, provided in the embodiments of this specification. Figure 3 This is a frequency distribution diagram of a solid-state battery under normal conditions provided in the embodiments of this specification; Figure 4 This is a time evolution diagram of a solid-state battery under normal conditions provided in the embodiments of this specification; Figure 5 This is the active barcode of the solid-state battery under normal conditions provided in the embodiments of this specification; Figure 6 This is a three-dimensional time-frequency graph of the battery temperature when it is above 60 degrees Celsius, provided in the embodiments of this specification. Figure 7 This is the full spectrum diagram of the battery when the temperature is above 60 degrees Celsius, as provided in the embodiments of this specification. Figure 8 This is a frequency distribution diagram provided in the embodiments of this specification when the battery temperature is above 60 degrees Celsius; Figure 9 This is a time evolution diagram of the battery temperature above 60 degrees Celsius provided in the embodiments of this specification; Figure 10 This is the active barcode provided in the embodiments of this specification when the battery temperature is above 60 degrees Celsius; Figure 11 This is a threshold effect diagram of the first-stage warning under different SOCs provided in the embodiments of this specification; Figure 12 This is a graph showing the second-stage magnetic field mutation provided in the embodiments of this specification; Figure 13 This is a schematic diagram of the structure of a solid-state battery thermal runaway early warning system based on electro-magnetic dual-mode fusion, provided in the embodiments of this specification. Figure 14 This is a schematic diagram of the hardware for online disturbance-response signal measurement. Detailed Implementation

[0021] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. The technical solutions provided by various embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0022] This application provides a method and system for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion.

[0023] like Figure 1 The figure shows a flowchart of a solid-state battery thermal runaway early warning method based on electro-magnetic dual-mode fusion. The first aspect of the present invention provides a method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion, comprising the following steps: S101. Inject a sinusoidal current disturbance signal of a preset frequency into the solid-state battery under test, and simultaneously acquire the battery's voltage response signal. S102. Perform time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation; S103. Based on the time-frequency domain representation, calculate the energy concentration index and the time continuity index; S104. If the first warning condition is met based on the energy concentration index and the time continuity index, then the first stage warning is triggered. S105. After triggering the first stage warning, non-contact monitoring of the external magnetic field of the solid-state battery is initiated. S106. Based on the monitored magnetic field data, if the second warning condition is met, the second stage warning is triggered.

[0024] Based on step S101, firstly as follows: Figure 14 As shown, the solid-state battery is connected to a differential amplifier, which is used to measure the response signal. The solid-state battery is also connected to a differential amplifier and a precision resistor in parallel for measuring the actual disturbance signal. The signal is then sent to the host computer via a data acquisition unit for data acquisition and calculation. The disturbance signal is injected via a waveform generator.

[0025] To achieve real-time evaluation of the battery system response under a 1kHz disturbance, a disturbance-response measurement platform based on a four-wire Kelvin connection was built. First, a waveform generator produces a 5V sinusoidal disturbance signal with a frequency of 1kHz. Then, a voltage-controlled current source (VCCS) provides load driving capability and injects the sinusoidal disturbance into the battery under test. Simultaneously, a high-precision differential amplifier acquires the resulting voltage response. A 500 mΩ precision resistor connected in series with the battery is used to accurately measure the actual disturbance current. The disturbance and response signals measured by the platform meet the Kramers-Kronig causality and linearity requirements. Finally, the response signal acquired by the data acquisition card (DAQ) is sent to the host computer for further processing.

[0026] This invention employs a four-wire Kelvin configuration to eliminate the influence of wire resistance on measurement accuracy. Its core function is to inject a 1kHz sinusoidal disturbance signal in real time and acquire the battery voltage response. The specific hardware and parameters used are as follows: Disturbance signal generation unit: Waveform generator (model FY6300-20M) generates a 5V, 1kHz sinusoidal current disturbance signal with high frequency accuracy. 20ppm ensures the stability of the disturbance signal.

[0027] Signal injection unit: Voltage-controlled current source (VCCS, model KW-BPVCCS1000) injects disturbance signals into the solid-state battery, with an output current range of... 1A, meeting battery safety testing requirements.

[0028] Signal acquisition unit: A high-precision differential amplifier acquires the battery's voltage response signal. Suppress common-mode interference; 500 m series connection Precision resistor (model BWL-EE, 3W, temperature range 55~175℃) for real-time measurement of actual disturbance current. ; The data acquisition card (DAQ, model ART-USB3132A) acquires voltage and current signals at a sampling frequency of 5000Hz and a resolution of 16 bits to ensure signal fidelity.

[0029] Data processing unit: The host computer receives DAQ data, performs time-frequency analysis and index calculation, and the online processing time is ≤0.007 seconds.

[0030] The hardware module of this invention must meet the Kramers-Kronig causality and linearity requirements, that is, the phase difference and amplitude relationship between the disturbance signal and the response signal must conform to the characteristics of a linear system to ensure the effectiveness of subsequent signal analysis.

[0031] This invention designs a two-stage early warning system, with the first stage using electrical monitoring and the second stage using magnetic field monitoring. Through the technical solution of "electrical monitoring-magnetic field monitoring" dual-modal fusion, it identifies early anomalies of thermal runaway and explosion precursors, respectively. The first stage achieves early warning of thermal runaway through the process of "perturbation injection - response acquisition - time-frequency analysis - index extraction"; This invention designs an excitation-response subdues-disturbing (ERSD) method, whose core lies in bypassing traditional electrochemical impedance spectroscopy calculations and directly performing time-frequency analysis on the voltage response signal of a battery under a 1 kHz sinusoidal current disturbance.

[0032] A 1 kHz sinusoidal voltage signal is generated using a waveform generator, and then converted into a current disturbance by a voltage-controlled current source (VCCS). ( The disturbance current amplitude (calculated using a precision resistor voltage divider) is injected into the battery via a four-wire Kelvin connection, and the battery's voltage response signal is acquired simultaneously. .

[0033] Based on step S102, time-frequency analysis and generalized S-transform are performed, specifically including: The step of performing time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation includes: The time-domain voltage response is converted into a time-frequency domain signal based on the generalized S-transform. To preserve the features in the time and frequency dimensions, the transformation formula is as follows: ; in, To analyze the time center of the window, For frequency, It is a frequency-dependent Gaussian window function used to highlight fault-sensitive features and suppress redundant information in disturbance signals.

[0034] In practical calculations, discretization is used, so the discrete form of the generalized S-transform is: ; in, , These are time, frequency, and time sample indexes, respectively. The signal is a discrete voltage response with a length of N and a sampling frequency of . ; For sliding Gaussian windows, The width of the Gaussian window is related to the frequency. Inversely proportional; Discrete frequency (Hz); right Logarithmic scaling is performed to obtain the time-frequency domain. Highlighting fault-inducing characteristics.

[0035] Based on step S103, The calculated energy concentration index (ECI) is used to represent the sharpness of the energy distribution in the quantized frequency domain and reflects the uniformity of the interface impedance of the solid-state battery.

[0036] First, based on the time-frequency domain, the amplitude profile in the frequency dimension is calculated. , represented as: ; in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; Then, the normalized fourth moment of the amplitude profile is calculated as the energy concentration index (ECI), expressed as: ; in, Number of frequency points; for The mean; It is the square of the variance.

[0037] further, The Time Continuity Index (TCI) is calculated. The Time Continuity Index (TCI) represents the stability of the signal energy in the quantized time domain and reflects the degree of fluctuation in battery state.

[0038] First, based on the time-frequency domain, the amplitude profile in the time dimension is calculated. , Represented as: ; in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; Then, the coefficient of variation of the amplitude profile is calculated. , represented as ; in, The mean; Standard deviation; Finally, TCI definition For the normalized inverse of , we get TCI as The closer the TCI value is to 1, the more stable the time-domain signal is; a decrease in the TCI value indicates that the internal state fluctuations of the battery are aggravated, such as the change in interface impedance caused by electrolyte expansion.

[0039] Based on step S104, a first warning condition is set, wherein the first warning condition is that the energy concentration index is greater than a first threshold and the time continuity index is less than a second threshold. For example, setting an early warning threshold: Under normal conditions, the ECI is approximately 2.65. Under normal conditions, the TCI is approximately 0.94. When the following conditions are met... and When this occurs, the first-stage warning is triggered, and the waveform generator and VCCS disturbance signal injection are stopped to avoid putting extra burden on the battery.

[0040] Based on steps S105 and S106, Upon triggering the first-stage warning, non-contact monitoring of the external magnetic field of the solid-state battery is initiated to capture potential explosion precursor signals that may occur at the end of thermal runaway. When the first-stage warning is triggered, runaway triggers the reduction of the positive electrode transition metal, generating a ferromagnetic metal deposit with a permanent magnetic moment, whose collective magnetic square represents a macroscopic magnetization intensity. This alters the magnetic field distribution around the battery, including: After triggering the first-stage warning, monitor the magnetization of the solid-state battery. , represented as: ,in, For volume, denoted as , where is the magnetic moment of a single metal atom.

[0041] The magnetization The change in the external magnetic field of the battery It can be represented as: ; in, These are geometric constants related to the sensor location and battery structure. The mass magnetic susceptibility of the metal deposit. This represents the cumulative mass of the transition metal reduction products.

[0042] As thermal runaway intensifies, metal deposits accumulate, and the external magnetic field strength continuously increases. When the battery experiences thermal runaway and approaches explosion, a strong fault current is generated internally, triggering a sudden change in magnetic field polarity. When a reversal of magnetic field polarity is detected, a second-stage warning can be triggered.

[0043] The second warning condition is the occurrence of a preset abnormal magnetic field event; the preset abnormal magnetic field event is a reversal of magnetic field polarity.

[0044] This invention integrates contact-type electrical monitoring (early stage) and non-contact magnetic field monitoring (late stage), avoiding the safety risks of contact measurement under critical conditions, covering the entire stage of thermal runaway, and achieving non-invasive diagnosis.

[0045] In addition, this invention directly analyzes the 1kHz response signal, avoiding the complex impedance calculation and full-band scanning of traditional EIS. The online calculation time is only 0.007 seconds, which is about 700 times faster than the fastest existing fast EIS (5 seconds), meeting the needs of real-time vehicle monitoring.

[0046] The ECI and TCI indices proposed in this invention are respectively associated with uneven interfacial impedance distribution (caused by solid electrolyte expansion) and continuous fluctuations in battery state (intensified interfacial reaction), as well as the magnetic field abrupt change associated with transition metal deposition (a characteristic of the end stage of thermal runaway). Each index corresponds to a clear physicochemical mechanism and has strong interpretability.

[0047] This invention employs an online ERSD and magnetic field monitoring SSB test bench, and designs two types of experiments to verify the effectiveness of the two-stage early warning system: 1. The battery is pulse-heated using a heating plate to make its temperature exceed the normal operating range, and the effectiveness of the first-stage warning method is verified under different states of charge (SOC). 2. The battery was continuously heated until thermal runaway and fire / explosion occurred, in order to verify the overall effectiveness of the proposed two-stage early warning strategy.

[0048] All experiments were conducted in an explosion-proof enclosure to ensure safety, and were connected to an ERSD module, a magnetic field monitoring module, and temperature or voltage monitoring equipment. During the experiments, exhaust fans were turned on to promptly remove harmful gases. Once the first-stage warning was triggered, the waveform generator was immediately shut down to stop injecting disturbance signals and ensure no damage to the battery. The second stage was then initiated, with continuous magnetic field monitoring.

[0049] The magnetic field sensor is fixed above the fixture and has no physical contact with the battery, so it will not interfere with the battery even in the critical stage before the explosion. By comparing the trigger time of the first-stage warning with the time of the second-stage magnetic field change, the time stamps of the two-stage warnings can be obtained, and the warning lead time for each stage can be calculated based on the industry-standard thermal runaway judgment criteria.

[0050] like Figure 2 As shown, a 1 kHz perturbation is applied to a solid-state battery at normal temperature. Figure 2 In this model, the x-axis represents frequency, the y-axis represents time, and the z-axis represents amplitude; for example... Figure 3 As shown, Figure 3 The horizontal axis represents time, and the vertical axis represents the average amplitude. The results show that the ECI remains stable at around 2.65. Figure 4 As shown, Figure 4 The horizontal axis represents time, and the vertical axis represents the average amplitude. The results show that the TCI remains stable at around 0.94. Figure 5 As shown, Figure 5 The horizontal axis represents time, and the vertical axis represents activity level. Black bars indicate that the activity level is higher than the average. The results show that the activity barcode signal shows an active percentage of 51.8%, with no warnings triggered.

[0051] High temperatures cause solid electrolytes to expand, altering the contact pressure at the electrode / electrolyte interface and leading to uneven interfacial impedance distribution. This non-uniformity causes fluctuations in the 1 kHz perturbation response along the time dimension, therefore... Figure 6 , Figure 7 As shown: Figure 6 and Figure 7 The text intuitively illustrates the fluctuations and sparsity in the response, among which... Figure 6 In the diagram, the x-axis represents frequency, the y-axis represents time, and the z-axis represents amplitude. Figure 7 In the diagram, the horizontal axis represents time, and the vertical axis represents frequency. like Figure 8 , Figure 9 As shown, further verification of the index calculations revealed that the ECI was 3.33 during the abnormal period, higher than the normal value of 2.65; the TCI was 0.89 during the abnormal period, lower than the normal value of 0.94; among which, Figure 8 The horizontal axis represents time, and the vertical axis represents the average amplitude. Figure 9 The horizontal axis represents time, and the vertical axis represents the average amplitude.

[0052] like Figure 10 As shown, Figure 10 The horizontal axis represents time, and the vertical axis represents activity level. Figure 10 This provides an intuitive way to observe the temporal distribution of signal activity. Black bars represent periods where signal strength is above average, while white areas represent periods where it is below average. The bar spacing ratio results show that under abnormal high-temperature conditions, the battery signal is only 43%, lower than the normal value of 51.8%.

[0053] The first-stage warning threshold is set to "ECI>3 and TCI<0.9". According to industry standards, determining thermal runaway requires a temperature exceeding 60°C, a temperature rise rate exceeding 1°C / s, or a voltage drop reaching 25% of the initial value. In contrast, the first-stage warning relies on fluctuations in the 1kHz disturbance response index caused by the thermal expansion and contraction of the solid electrolyte, providing a 9-minute warning (traditional methods require heating to 130°C for a voltage drop to occur, while the method of this invention triggers a warning at 62°C).

[0054] Figure 11 The threshold effect diagrams for the first-stage early warning under different SOCs (State of Charge) are shown, demonstrating the effectiveness verification results of the first-stage early warning method under different SOCs. Figure 11 The horizontal axis represents the ECI value, and the vertical axis represents the TCI value.

[0055] To address the characteristic differences of batteries at different states of charge (SOC, 0%~100%), the threshold adaptability of ECI and TCI was experimentally calibrated. Heating experiments were conducted on solid-state batteries at different SOCs, and the ECI and TCI values ​​under normal and abnormal states were measured at each SOC. The results show that the warning threshold (ECI and TCI) at different SOCs... , It is applicable to all conditions. When the SOC is low (0%~20%), the TCI drops to a minimum of 0.86, but still meets the judgment condition of "abnormal state TCI<0.9". When the SOC is high (80%~100%), the ECI rises to a maximum of 3.5, the warning trigger is more sensitive, and there are no false alarms. Therefore, the warning coverage of the entire SOC range can be achieved without adjusting the threshold.

[0056] Once a Level 1 warning is issued, continue monitoring of the magnetic field until a reversal of magnetic field polarity occurs due to an abnormal current, triggering a Level 2 warning.

[0057] Figure 12 This is a graph showing the magnetic field mutation curve in the second stage. Figure 12The horizontal axis represents time, and the vertical axis represents magnetic field strength. Approximately 20 seconds before the thermal runaway explosion, the fluxgate sensor detected a rapid polarity reversal and a violent abrupt change in the external magnetic field, immediately triggering the second-stage warning. The experiment revealed that within the following 20 seconds, the temperature rose sharply, the voltage dropped rapidly, and ignition and explosion occurred.

[0058] The abrupt reversal of magnetic field polarity indicates a shift in the primary physical mechanism from static magnetization to dynamic electromagnetic induction. This mechanism, characterized by a rapidly generated, intense localized internal current prior to battery rupture, represents a direct measurement of the fault current itself, marking a transition from a chemical degradation process to an explosive electrical and mechanical failure event.

[0059] A second aspect of the present invention provides a solid-state battery thermal runaway early warning system 1300 based on electro-magnetic dual-mode fusion, comprising: The signal excitation and acquisition module 1301 is used to inject a sinusoidal current disturbance signal of a preset frequency into the solid-state battery under test, and simultaneously acquire the voltage response signal of the battery. Signal processing module 1302 is used to perform time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation; and to calculate the energy concentration index and the time continuity index based on the time-frequency domain representation. The magnetic field monitoring module 1303 is used to initiate non-contact monitoring of the external magnetic field of the solid-state battery after the first stage warning is triggered. The early warning module 1304 is used to determine whether the first early warning condition is met based on the energy concentration index and the time continuity index, and to trigger the first stage of early warning. Based on the monitored magnetic field data, it is used to determine whether the second warning condition is met and to trigger the second-stage warning.

[0060] A third aspect of the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the solid-state battery thermal runaway early warning method based on electro-magnetic dual-mode fusion as described in the first aspect.

[0061] This embodiment can divide the method into functional modules based on the above method example. For example, each function can be assigned to a separate module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0062] When each functional module is divided according to its corresponding function, it may include: a signal excitation and acquisition module, a signal processing module, a magnetic field monitoring module, and an early warning module. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional descriptions of the corresponding functional modules, and will not be repeated here.

[0063] This embodiment also provides a computer-readable storage medium (including but not limited to disk storage, CD-ROM, optical storage, etc.) storing computer program code. When the computer program code is run on a computer, the computer executes the above-mentioned related method steps to realize the solid-state battery thermal runaway early warning method and system based on electro-magnetic dual-mode fusion provided in the above embodiment.

[0064] This embodiment also provides a computer program product. When the computer program product is run on a computer, it causes the computer to perform the aforementioned steps to realize the solid-state battery thermal runaway early warning method and system based on electro-magnetic dual-mode fusion provided in the above embodiment. The beneficial effects of the above embodiments can be found in the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0065] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0066] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. In the description of this disclosure, it should be understood that if terms such as "upper," "lower," "front," "rear," "left," and "right" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, they are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the indicated position or element must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0067] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0068] The above are merely embodiments of this disclosure and are not intended to limit the scope of this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of the claims of this disclosure.

Claims

1. A method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion, characterized in that, include: A sinusoidal current disturbance signal of a preset frequency is injected into the solid-state battery under test, and the voltage response signal of the battery is acquired simultaneously. The voltage response signal is subjected to time-frequency transformation to obtain a time-frequency domain representation; Based on the time-frequency domain representation, the energy concentration index and the time continuity index are calculated; If the energy concentration index and time continuity index are used to determine whether the first warning condition is met, then the first stage warning is triggered. After triggering the first-stage warning, non-contact monitoring of the external magnetic field of the solid-state battery is initiated. If the monitored magnetic field data is determined to meet the second warning condition, then the second-stage warning will be triggered.

2. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, The first warning condition is that the energy concentration index is greater than a first threshold and the time continuity index is less than a second threshold.

3. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, The second warning condition is the occurrence of a preset abnormal magnetic field event; the preset abnormal magnetic field event is a reversal of magnetic field polarity.

4. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, The step of performing time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation includes: Based on the generalized S-transform, the time-domain voltage response is converted into a time-frequency domain signal. The discrete form of the generalized S-transform is as follows: ； Where n, k, and m are time, frequency, and time index, respectively; The signal is a discrete voltage response with a length of N and a sampling frequency of . ; A sliding Gaussian window; The width of the Gaussian window is related to the frequency. Inversely proportional, ; Discrete frequency; right Logarithmic scaling is performed to obtain the time-frequency domain. .

5. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, The calculation of the Energy Concentration Index (ECI) includes: Based on the time-frequency domain, the amplitude profile in the frequency dimension is calculated. , represented as: ； in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; The normalized fourth moment of the amplitude profile is calculated as the energy concentration index (ECI), expressed as: ； in, Number of frequency points; for The mean; It is the square of the variance.

6. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, Calculating the Time Continuity Index (TCI) includes: Based on the time-frequency domain, the amplitude profile in the time dimension is calculated. , Represented as: ; in, This refers to the discrete frequency index within the target frequency band. For time indexing, For time points; Calculate the coefficient of variation of the amplitude profile. , represented as ; in, The mean; Standard deviation; TCI was obtained .

7. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 1, characterized in that, After triggering the first-stage warning, the non-contact monitoring of the external magnetic field of the solid-state battery is initiated, including: After triggering the first-stage warning, monitor the magnetization of the solid-state battery. , represented as: ,in, For volume, denoted as , where is the magnetic moment of a single metal atom.

8. The method for early warning of thermal runaway in solid-state batteries based on electro-magnetic dual-mode fusion according to claim 7, characterized in that, The magnetization The change in the external magnetic field of the battery It can be represented as: ； in, These are geometric constants related to the sensor location and battery structure. The mass magnetic susceptibility of the metal deposit. This represents the cumulative mass of the transition metal reduction products.

9. A solid-state battery thermal runaway early warning system based on electro-magnetic dual-mode fusion, characterized in that, include: The signal excitation and acquisition module is used to inject a sinusoidal current disturbance signal of a preset frequency into the solid-state battery under test and simultaneously acquire the voltage response signal of the battery. The signal processing module is used to perform time-frequency transformation on the voltage response signal to obtain a time-frequency domain representation; Based on the time-frequency domain representation, the energy concentration index and the time continuity index are calculated; The magnetic field monitoring module is used to initiate non-contact monitoring of the external magnetic field of the solid-state battery after the first-stage warning is triggered. The early warning module is used to determine whether the first early warning condition is met based on the energy concentration index and the time continuity index, and to trigger the first stage of early warning. Based on the monitored magnetic field data, it is used to determine whether the second warning condition is met and to trigger the second-stage warning.

10. A computer-readable storage medium, characterized in that, It stores instructions that, when executed by one or more processors, cause the processors to perform the solid-state battery thermal runaway early warning method based on electro-magnetic dual-mode fusion as described in any one of claims 1-8.

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