Battery thermal runaway early warning related parameter identification method and device, equipment and medium

Abstract

The embodiment of the present application relates to the technical field of battery, and discloses a battery thermal runaway early warning related parameter identification method, device, equipment and medium.The method comprises the following steps: at least analyzing temperature-dependent characteristics and SOC-dependent characteristics of battery EIS impedance characteristic parameters; at least on the basis of the temperature-dependent characteristics and the SOC-dependent characteristics, performing first EIS testing on the battery in at least one preset frequency range to determine at least a target impedance characteristic frequency point of the battery; at least performing second EIS testing on the battery at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point to verify the effectiveness of the target impedance characteristic frequency point; and in response to the effectiveness of the target impedance characteristic frequency point being verified, at least carrying out a local heating experiment to identify battery thermal runaway early warning related parameters under the target impedance characteristic frequency point.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method, apparatus, equipment and medium for identifying parameters related to battery thermal runaway early warning. Background Technology

[0002] Lithium-ion batteries (LIBs) have become a core component of modern energy storage solutions due to their high energy density, long cycle life, and low maintenance requirements. They are widely used in various scenarios such as portable electronic devices, electric vehicles, and large-scale energy storage systems.

[0003] One of the main safety risks of lithium-ion batteries is thermal runaway. Once thermal runaway occurs, excessive heat can cause fires or even explosions, leading to a decline in potential consumers' trust in the technology. Choosing appropriate thermal runaway early warning methods is crucial for preventing catastrophic battery failures and improving battery safety.

[0004] Researchers have proposed various methods for early detection of thermal runaway, such as using fiber optic sensors to measure internal battery pressure, measuring the expansion force caused by gases generated during internal side reactions in thermal runaway, and using pressure / gas sensors for gas detection. Although studies have confirmed the effectiveness of these methods in thermal runaway detection, only a few meet the practical application standards of industry. Electrochemical impedance spectroscopy (EIS) is a viable alternative. With the latest developments in chip-level impedance measurement technology, this technology can now be integrated into battery management systems (BMS). Integrating a single chip into the BMS allows for multi-channel impedance measurements of each cell within the battery module, which is undoubtedly a cost-effective and minimally destructive solution. Traditional full-spectrum EIS measurements take several minutes to complete, limiting their effectiveness in thermal runaway detection. Therefore, several studies have proposed single-frequency impedance assessment as a more efficient alternative, and research on applying single-frequency EIS to battery thermal runaway early warning is increasing.

[0005] However, current research on impedance-based thermal runaway early warning primarily targets energy storage batteries, and the experimental conditions for identifying impedance characteristic parameters in thermal runaway early warning are very limited. Furthermore, the selection of a fixed frequency point for obtaining these impedance characteristic parameters is not clearly defined. Therefore, for power batteries, which are the research subject of thermal runaway early warning, the question of how to select the optimal analysis frequency point (also known as the characteristic frequency point) remains unclear, and the experimental scenarios for identifying impedance characteristic parameters in thermal runaway early warning urgently need improvement. Summary of the Invention

[0006] The purpose of this invention is to provide a method, device, equipment, and medium for identifying battery thermal runaway early warning related parameters. It can at least realize the determination of the characteristic frequency points of lithium-ion power battery impedance and the identification of thermal runaway early warning impedance characteristic parameters based on the principle of battery electrochemical impedance and battery EIS test data under multiple temperature points and multiple SOC points. It can at least clarify the selection of the characteristic frequency points of power battery impedance and improve the test scenario for identifying thermal runaway early warning impedance characteristic parameters.

[0007] To address the aforementioned technical problems, in a first aspect, the present invention provides a method for identifying battery thermal runaway early warning related parameters, comprising at least:

[0008] At least analyze the temperature dependence and SOC dependence of the battery's EIS impedance characteristic parameters;

[0009] Based at least on the temperature-dependent characteristics and the SOC-dependent characteristics, perform at least one first EIS test within a preset frequency range on the battery to at least determine the target impedance characteristic frequency point of the battery;

[0010] At least perform a second EIS test on the battery at multiple temperature points and multiple SOC points at the target impedance characteristic frequency point to at least verify the effectiveness of the target impedance characteristic frequency point;

[0011] In response to the verification of the effectiveness of the target impedance characteristic frequency point, at least a local heating experiment is conducted to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

[0012] Optionally, the preset frequency range is at least 0.1192 Hz to 2014.1654 Hz.

[0013] Optionally, the multiple temperature points are obtained by selecting in increments of 5°C at least between -10°C and 50°C.

[0014] Optionally, the multiple SOC points include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

[0015] Based on the same concept, in a second aspect, the present invention also provides a battery thermal runaway early warning related parameter identification device for performing the battery thermal runaway early warning related parameter identification method described in any one of the first aspects;

[0016] The battery thermal runaway warning-related parameter identification device shall include at least the following:

[0017] The characteristic analysis module is used to analyze at least the temperature dependence and SOC dependence of the battery's EIS impedance characteristic parameters;

[0018] The first test module is used to perform at least one first EIS test on the battery within a preset frequency range, based at least on the temperature dependence characteristics and the SOC dependence characteristics, so as to at least determine the target impedance characteristic frequency point of the battery.

[0019] The second test module is used to perform a second EIS test on the battery at least at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point, so as to at least verify the effectiveness of the target impedance characteristic frequency point.

[0020] The heating experiment module is used to verify the effectiveness of the response to the target impedance characteristic frequency point by conducting at least a local heating experiment to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

[0021] Optionally, the preset frequency range is at least 0.1192 Hz to 2014.1654 Hz.

[0022] Optionally, the multiple temperature points are obtained by selecting in increments of 5°C at least between -10°C and 50°C.

[0023] Optionally, the multiple SOC points include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

[0024] Based on the same concept, in a third aspect, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor executes the program to implement the steps in the battery thermal runaway early warning related parameter identification method according to any one of the first aspects.

[0025] Based on the same concept, in a fourth aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps in the battery thermal runaway early warning related parameter identification method described in any one of the first aspects.

[0026] The technical solution provided by this invention firstly analyzes the temperature dependence and SOC dependence characteristics of the battery's EIS impedance characteristic parameters. Further, based on these characteristics, it performs at least one first EIS test within a preset frequency range to determine the battery's target impedance characteristic frequency point. Further, it performs at least one second EIS test at multiple temperature points and multiple SOC points at the target impedance characteristic frequency point to verify the effectiveness of the target impedance characteristic frequency point. Finally, in response to the verification of the effectiveness of the target impedance characteristic frequency point, it conducts at least a local heating experiment to identify battery thermal runaway warning-related parameters at the target impedance characteristic frequency point. Therefore, this invention can at least achieve the determination of the impedance characteristic frequency point of a lithium-ion power battery and the identification of thermal runaway warning impedance characteristic parameters based on the battery's electrochemical impedance principle and battery EIS test data at multiple temperature points and multiple SOC points, thus clarifying the selection of the power battery impedance characteristic frequency point and improving the experimental scenario for identifying thermal runaway warning impedance characteristic parameters. Attached Figure Description

[0027] Figure 1 This is a flowchart of a method for identifying battery thermal runaway early warning parameters provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the structure of a battery thermal runaway early warning related parameter identification device provided in an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention;

[0030] Figure 4 This is an EIS spectrum of three battery groups within a wide frequency range (20 frequency points) provided in an embodiment of the present invention;

[0031] Figure 5 This is a Bode plot of three battery groups within a wide frequency range (20 frequency points) provided in an embodiment of the present invention;

[0032] Figure 6 This is a graph showing the variation of the real part of the battery impedance parameter with SOC at temperatures ranging from -10℃ to 50℃ (a total of 13 temperature points), provided by an embodiment of the present invention.

[0033] Figure 7 This is a graph showing the variation of the imaginary part of battery impedance parameters with SOC at temperatures ranging from -10℃ to 50℃ (a total of 13 temperature points), provided by an embodiment of the present invention.

[0034] Figure 8 This is a schematic diagram of the device interaction for a local heating experiment provided in an embodiment of the present invention;

[0035] Figure 9 This is an embodiment of the present invention, which provides impedance characteristic parameters and temperature variation diagram at a static heating rate of 5℃ / min and a 190.7349 Hz Hz. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0038] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0039] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0040] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0041] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0042] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0043] Figure 1 This is a flowchart of a battery thermal runaway early warning related parameter identification method provided by an embodiment of the present invention. This embodiment is applicable to at least any thermal runaway analysis scenario for lithium-ion power batteries. The battery thermal runaway early warning related parameter identification method can be, but is not limited to, executed by the battery thermal runaway early warning related parameter identification device in this embodiment of the present invention. This execution entity can be implemented in software and / or hardware. Figure 1 As shown, the method for identifying parameters related to battery thermal runaway early warning includes at least the following steps:

[0044] S1. At least analyze the temperature dependence and SOC dependence of the battery's EIS impedance characteristic parameters.

[0045] Among the key precursors to thermal runaway is an abnormal rise in battery temperature. Understanding the temperature-dependent changes in impedance characteristic parameters before thermal runaway can provide an effective early warning system. To improve the accuracy of thermal runaway warnings and reduce false alarm rates, it is necessary to identify characteristic frequency points that are sensitive to temperature but not to state of charge (SOC) and perform impedance characteristic parameter identification at these frequencies. To achieve this, it is essential to first analyze the temperature and SOC dependence of impedance characteristic parameters across the entire EIS (electrochemical impedance spectroscopy) spectrum.

[0046] In the pre-defined low-frequency region of the EIS spectrum, battery impedance is primarily determined by the charge transfer process. This charge transfer reaction involves electron transfer at the electrode surface, a process closely related to the battery's state of charge (SOC). In other words, the charge transfer process itself is significantly affected by the battery's SOC. At lower SOCs, the reduction / oxidation reactions at the battery's electrode surface are more active, resulting in a faster charge transfer process and lower impedance. Conversely, at higher SOCs, electron transport within the battery is restricted, leading to a slower charge transfer process and higher impedance. Furthermore, temperature directly affects the kinetics of charge transfer; therefore, the charge transfer process is also temperature-dependent. Higher temperatures help increase the charge transfer rate, making the charge transfer process easier and thus reducing the battery's internal resistance. Consequently, in the pre-defined low-frequency region of the EIS spectrum, battery impedance is significantly influenced by the charge transfer process, making it highly sensitive to SOC, while temperature also affects its value.

[0047] Within the preset mid-frequency region of the EIS spectrum, the battery impedance is primarily determined by the film layer on the electrode surface (such as the Solid Electrolyte Interphase, SEI). The main function of this film layer is to isolate the electrolyte and electrode, preventing direct contact between them. It does not participate in the energy storage or release process, and therefore its impedance is largely unaffected by the state of charge (SOC). Within the preset mid-frequency range, the temperature dependence of the impedance characteristic parameters stems from the ionic conductivity of the SEI film between the graphite anode and the electrolyte; higher temperatures enhance ion conductivity within the SEI film. In summary, a stable SEI film impedance exhibits only a certain temperature dependence, while the influence of SOC is negligible.

[0048] The time constants of SOC-related processes such as charge transfer and lithium-ion diffusion are relatively large, while the period of high-frequency signals is much smaller than these time constants. Under high-frequency signals, the slow SOC-related processes (lithium-ion diffusion, charge transfer, etc.) have not yet responded; therefore, the influence of SOC cannot be reflected. The core impedance component corresponding to the preset high-frequency region of the EIS spectrum is the solution resistance (Rs). Rs is mainly determined by electrolyte concentration, temperature, and battery structure, with temperature having a significant impact on Rs. Since Rs is not directly related to SOC, the influence of SOC changes can be ignored.

[0049] Therefore, it is evident that battery impedance can be affected by state of charge (SOC) and temperature, and the frequency dependence of impedance leads to changes in the impedance spectrum. The temperature dependence of impedance is primarily determined by the battery material properties; this dependence exists across the entire frequency range of EIS, but is most significant in the preset high-frequency region. The SOC dependence of impedance is closely related to frequency: in the preset low-frequency region, impedance differences at different SOCs are significant; while at the preset mid- and high-frequency regions, the effect of SOC on impedance is negligible. However, excessively high frequency points (regions where the imaginary part of impedance in the EIS spectrum is negative) primarily reflect externally introduced inductive and impedance information rather than internal battery information. Therefore, the selected frequency points should not be too high; the optimal choice is a high-frequency region where the imaginary part of impedance is close to 0.

[0050] It is understood that the actual frequency range corresponding to the aforementioned preset low, medium and high frequency regions can be adjusted according to the actual adaptability of the battery, and the present invention does not limit this.

[0051] S2. Based on at least the temperature-dependent characteristics and SOC-dependent characteristics, perform at least one first EIS test within a preset frequency range on the battery to at least determine the target impedance characteristic frequency point of the battery.

[0052] In step S2, the impedance acquisition method used in the experiment can be to acquire the battery impedance signal by a 1LINX_FPC_V3.3_1168 board (such as one equipped with an NXP DNB1168 chip) soldered on the battery, transmit it to the PC_V4.1 board via daisy-chain communication, and then connect it to the computer host software via a USB cable.

[0053] In one specific implementation, optionally, the preset frequency range is at least 0.1192Hz~2014.1654Hz.

[0054] More specifically, the implementation process for the first EIS test can be as follows:

[0055] First, three batteries at 50% SOC were selected as parallel samples from the same batch of batteries. Twenty frequency points were then evenly selected within a wide frequency range of 0.1192 Hz to 2014.1654 Hz (e.g., 0.1192 Hz, 0.2384 Hz, 0.4768 Hz, 0.9537 Hz, 1.9074 Hz, 3.8147 Hz, 5.7221 Hz, 7.6294 Hz, 9.5368 Hz, 11.4441 Hz, 45.7765 Hz, 95.3677 Hz, 146.8662 Hz, 190.7349 Hz, 278.4736 Hz, 381.4707 Hz, 434.8766 Hz, 724.7944 Hz, 1007.0827 Hz). EIS tests were performed on the three batteries at 25°C using frequencies of 2014.1654 Hz and 2014.1654 Hz. The results yielded four impedance characteristic parameters: real part, imaginary part, impedance amplitude, and phase angle, at different frequency points. The obtained impedance characteristic parameter values ​​were then analyzed, and EIS and Bode plots of the three battery groups were plotted over a wide frequency range (20 frequency points), as shown below. Figure 4 and Figure 5 As shown, Figure 4 This invention provides an EIS spectrum of three battery groups within a wide frequency range (20 frequency points). Figure 5 This invention provides a Bode plot of three battery groups within a wide frequency range (20 frequency points). Finally, the frequency point whose imaginary part of the impedance is closest to 0 is initially selected as the characteristic frequency point that best reflects the battery temperature information (i.e., the aforementioned target impedance characteristic frequency point), corresponding to... Figure 4 and Figure 5 The frequency value closest to the intersection of the vertical axis is 190.7349 Hz.

[0056] S3. Perform a second EIS test on the battery at least at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point to at least verify the effectiveness of the target impedance characteristic frequency point.

[0057] There are several options for choosing the temperature point and the SOC point.

[0058] In another specific implementation, optionally, multiple temperature points are obtained by selecting in 5°C increments at least between -10°C and 50°C.

[0059] In another specific implementation, optionally, the multiple SOC points include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

[0060] Furthermore, the aforementioned step S3 can be specifically described as follows:

[0061] First, after consistency screening, EIS tests were performed on the batteries at multiple temperature points (5℃ increments from -10℃ to 50℃) and multiple SOC points (100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC) at the determined characteristic frequency points. Next, the effectiveness of the determined impedance characteristic frequency points was verified and summarized. The obtained impedance characteristic parameter values ​​were analyzed, and graphs of the real and imaginary parts of the battery impedance as a function of SOC were plotted from -10℃ to 50℃ (13 temperature points in total), as shown below. Figure 6 and Figure 7 As shown, Figure 6 This is a graph showing the variation of the real part of the battery impedance parameter with SOC at temperatures ranging from -10℃ to 50℃ (13 temperature points in total), provided by an embodiment of the present invention. Figure 7 This invention provides a graph showing the variation of the imaginary part of battery impedance with State of Charge (SOC) at 13 temperature points (-10℃ to 50℃). The graph reveals that at multiple identical temperature points, the real and imaginary parts of the battery impedance remain essentially unchanged across different SOC states, with differences only a few microohms. This indicates that the battery's impedance characteristic parameters are minimally affected by SOC at this frequency point. However, under the same SOC state, the real and imaginary parts of the battery impedance vary significantly at different temperature points. Specifically, at -10℃, the real and imaginary impedance values ​​are approximately 323 μΩ and 74 μΩ, respectively, while at 50℃, they become approximately 269 μΩ and -33 μΩ, respectively. This demonstrates that the battery's impedance characteristic parameters are significantly affected by temperature at this frequency point. These experimental results verify the effectiveness of the determined characteristic frequency points.

[0062] S4. The effectiveness of responding to the target impedance characteristic frequency point is verified by conducting at least a local heating experiment to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

[0063] in, Figure 8 This is a schematic diagram of the device interaction for a local heating experiment provided in an embodiment of the present invention, as shown below. Figure 8 As shown, temperature sensors are placed at key locations on the battery, and temperature change data is recorded by a test bench. The battery is then clamped securely in an explosion-proof enclosure using iron plate fixtures. Heating elements are connected to external heating equipment via wires. The heating equipment is controlled by the test bench, thereby controlling the heating rate of the heating elements. Simultaneously, impedance data is recorded by a laptop computer extending outside the explosion-proof enclosure. Furthermore, during dynamic testing simulating battery charging and discharging, the battery's positive and negative terminals are connected to a charge / discharge machine via cables extending outside the explosion-proof enclosure, and charging / discharging data is recorded by a host computer.

[0064] Furthermore, the key steps for conducting localized heating experiments can be:

[0065] First, the process of thermal runaway triggered by localized external heating when the battery is stationary was simulated. Considering the internal battery arrangement, the larger areas of the battery are more likely to be affected by localized heating. Therefore, a heating element was placed at the center of the larger battery area to simulate localized heating. It is known that the thermal runaway temperature of lithium iron phosphate batteries generally exceeds 500℃. Referring to the test specifications for thermal runaway in the national standard GB / T 36276-2023, a temperature rise rate of 5℃ / min was determined to be used to control the heating of the heating element. Heating was stopped and maintained at 500℃. Impedance characteristic parameters and temperature change data at characteristic frequency points were extracted throughout the entire test. Figure 9 This invention provides an embodiment of impedance characteristic parameters and temperature variation diagram at a static heating rate of 5℃ / min and a 190.7349 Hz Hz, as shown in the figure. Figure 9 As shown, it can be observed that during the process of local heating to the point where the explosion-proof valve bursts, the battery impedance amplitude first decreases, then increases in the opposite direction, and then increases sharply at the end, while the phase angle shows a trend of first increasing and then decreasing.

[0066] Static local heating tests simulated potential thermal runaway scenarios for batteries when stationary. Next, to simulate the complex environmental conditions that batteries might encounter within the vehicle's battery pack, several key influencing factors were added to the local heating process to simulate scenarios approaching real-world thermal runaway. These added factors included heating start-up time, charge / discharge rate, heating location, and battery aging state. The selected dynamic operating conditions at different charge / discharge rates—1C charge-DST discharge and 1C charge-FUDS discharge—are common operating conditions used in dynamic cycle testing to simulate real-world electric vehicle applications. These tests essentially covered the environmental impacts under real-world conditions. In addition, battery stationary and dynamic cycle tests without heating were conducted as a reference; the test list is summarized in Table 1. Similarly, impedance characteristic parameters and temperature change data at characteristic frequency points throughout the entire test process were extracted. By comprehensively analyzing the impedance signal change patterns, the relationship between impedance characteristic parameters and the thermal runaway process can be found.

[0067] Table 1

[0068]

[0069] The technical solution provided in this embodiment firstly analyzes the temperature dependence and SOC dependence characteristics of the battery's EIS impedance characteristic parameters. Further, based on these temperature and SOC dependence characteristics, it performs a first EIS test on the battery within at least one preset frequency range to determine the target impedance characteristic frequency point. Further, it performs a second EIS test on the battery at multiple temperature and SOC points under the target impedance characteristic frequency point to verify the effectiveness of the target impedance characteristic frequency point. Finally, in response to the verification of the effectiveness of the target impedance characteristic frequency point, it conducts a local heating experiment to identify battery thermal runaway warning-related parameters at the target impedance characteristic frequency point. Therefore, this embodiment can at least achieve the determination of the impedance characteristic frequency point of a lithium-ion power battery and the identification of thermal runaway warning impedance characteristic parameters based on the battery electrochemical impedance principle and battery EIS test data at multiple temperature and SOC points, thus clarifying the selection of the power battery impedance characteristic frequency point and improving the experimental scenario for identifying thermal runaway warning impedance characteristic parameters.

[0070] Figure 2 This is a schematic diagram of a battery thermal runaway early warning related parameter identification device provided in an embodiment of the present invention. This embodiment is applicable to at least any thermal runaway analysis scenario for lithium-ion power batteries. The battery thermal runaway early warning related parameter identification device can be implemented in software and / or hardware. Figure 2 As shown, the battery thermal runaway early warning related parameter identification device includes at least:

[0071] Characteristic analysis module 110 is used to analyze at least the temperature dependence and SOC dependence of the battery EIS impedance characteristic parameters;

[0072] The first test module 120 is used to perform at least one first EIS test on the battery within a preset frequency range, based on at least the temperature-dependent characteristics and SOC-dependent characteristics, so as to at least determine the target impedance characteristic frequency point of the battery.

[0073] The second test module 130 is used to perform a second EIS test on the battery at least at the target impedance characteristic frequency point at multiple temperature points and multiple SOC points, so as to at least verify the effectiveness of the target impedance characteristic frequency point.

[0074] The heating experiment module 140 is used to verify the effectiveness of the response to the target impedance characteristic frequency point by conducting at least a local heating experiment to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

[0075] Optionally, the preset frequency range is at least 0.1192 Hz to 2014.1654 Hz.

[0076] Optionally, multiple temperature points can be obtained by selecting in 5°C increments at least between -10°C and 50°C.

[0077] Optionally, the multiple SOC points may include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

[0078] The technical solution provided in this embodiment firstly analyzes the temperature dependence and SOC dependence characteristics of the battery's EIS impedance characteristic parameters using a characteristic analysis module. Further, based on the temperature dependence and SOC dependence characteristics, a first testing module performs at least one first EIS test within a preset frequency range on the battery to determine the target impedance characteristic frequency point. Further, a second testing module performs at least one second EIS test on the battery at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point to verify the effectiveness of the target impedance characteristic frequency point. Finally, in response to the verification of the effectiveness of the target impedance characteristic frequency point, a heating experiment module conducts at least a local heating experiment to identify battery thermal runaway warning-related parameters at the target impedance characteristic frequency point. Therefore, this embodiment can at least achieve the determination of the impedance characteristic frequency point of a lithium-ion power battery and the identification of thermal runaway warning impedance characteristic parameters based on the battery electrochemical impedance principle and battery EIS test data at multiple temperature points and multiple SOC points, thus clarifying the selection of the power battery impedance characteristic frequency point and improving the experimental scenario for identifying thermal runaway warning impedance characteristic parameters.

[0079] This embodiment provides an electronic device. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. See also: Figure 3The electronic device 1000 includes a processor 1001 and a memory 1002. The memory 1002 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 1001, the steps in any of the above-mentioned battery thermal runaway warning related parameter identification methods are performed. Through the above technical solution, the processor 1001 and the memory 1002 are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanism (not shown). The memory 1002 stores a computer program that can be executed by the processor. When the electronic device 1000 is running, the processor 1001 executes the computer program to execute the battery thermal runaway warning related parameter identification method in any optional implementation of the above embodiments, so as to at least achieve the following functions: at least analyze the temperature dependence characteristics and SOC dependence characteristics of the battery EIS impedance characteristic parameters; at least based on the temperature dependence characteristics and SOC dependence characteristics, perform at least one first EIS test within a preset frequency range on the battery to at least determine the target impedance characteristic frequency point of the battery; at least perform a second EIS test on the battery at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point to at least verify the effectiveness of the target impedance characteristic frequency point; in response to the effectiveness of the target impedance characteristic frequency point being verified, at least conduct a local heating experiment to identify battery thermal runaway warning related parameters under the target impedance characteristic frequency point.

[0080] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the battery thermal runaway warning-related parameter identification method provided in all embodiments of this application: at least analyzing the temperature dependence and SOC dependence characteristics of the battery's EIS impedance characteristic parameters; at least based on the temperature dependence and SOC dependence characteristics, performing a first EIS test on the battery within at least one preset frequency range to at least determine the target impedance characteristic frequency point of the battery; at least performing a second EIS test on the battery at multiple temperature points and multiple SOC points under the target impedance characteristic frequency point to at least verify the effectiveness of the target impedance characteristic frequency point; and in response to the verification of the effectiveness of the target impedance characteristic frequency point, conducting at least a local heating experiment to identify battery thermal runaway warning-related parameters under the target impedance characteristic frequency point.

[0081] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0082] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0083] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0084] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying parameters related to battery thermal runaway early warning, characterized in that, At least including: At least analyze the temperature dependence and SOC dependence of the battery's EIS impedance characteristic parameters; Based at least on the temperature-dependent characteristics and the SOC-dependent characteristics, perform at least one first EIS test within a preset frequency range on the battery to at least determine the target impedance characteristic frequency point of the battery; At least perform a second EIS test on the battery at multiple temperature points and multiple SOC points at the target impedance characteristic frequency point to at least verify the effectiveness of the target impedance characteristic frequency point; In response to the verification of the effectiveness of the target impedance characteristic frequency point, at least a local heating experiment is conducted to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

2. The method for identifying relevant parameters for battery thermal runaway early warning according to claim 1, characterized in that, The preset frequency range is at least 0.1192 Hz to 2014.1654 Hz.

3. The method for identifying relevant parameters for battery thermal runaway early warning according to claim 1, characterized in that, The multiple temperature points are obtained by selecting in increments of 5°C at least between -10°C and 50°C.

4. The method for identifying relevant parameters for battery thermal runaway early warning according to claim 1, characterized in that, The multiple SOC points include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

5. A battery thermal runaway early warning related parameter identification device, characterized in that, Used to perform the battery thermal runaway early warning related parameter identification method according to any one of claims 1-4; The battery thermal runaway early warning related parameter identification device includes at least: The characteristic analysis module is used to analyze at least the temperature dependence and SOC dependence of the battery's EIS impedance characteristic parameters; The first test module is used to perform at least one first EIS test on the battery within a preset frequency range, based at least on the temperature dependence characteristics and the SOC dependence characteristics, so as to at least determine the target impedance characteristic frequency point of the battery. The second test module is used to perform a second EIS test on the battery at least at the target impedance characteristic frequency point at multiple temperature points and multiple SOC points, so as to at least verify the effectiveness of the target impedance characteristic frequency point. The heating experiment module is used to verify the effectiveness of the response to the target impedance characteristic frequency point by conducting at least a local heating experiment to identify battery thermal runaway warning parameters at the target impedance characteristic frequency point.

6. The battery thermal runaway early warning related parameter identification device according to claim 5, characterized in that, The preset frequency range is at least 0.1192 Hz to 2014.1654 Hz.

7. The battery thermal runaway early warning related parameter identification device according to claim 5, characterized in that, The multiple temperature points are obtained by selecting in increments of 5°C at least between -10°C and 50°C.

8. The battery thermal runaway early warning related parameter identification device according to claim 5, characterized in that, The multiple SOC points include at least 100% SOC, 80% SOC, 60% SOC, 40% SOC, and 20% SOC.

9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the battery thermal runaway early warning related parameter identification method according to any one of claims 1-4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the battery thermal runaway early warning related parameter identification method according to any one of claims 1-4.

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