Fire control method for sodium-ion battery system and related device

Abstract

The application provides a fire control method of a sodium ion battery system and related devices. First, cell data and sensing data of the sodium ion battery system are acquired. A risk score is determined according to the cell data and the sensing data, and the risk score is used to reflect the fire risk degree of the sodium ion battery system. A fire risk level is determined according to the relationship between the risk score and a real-time risk threshold. A fire control strategy corresponding to the fire risk level is determined. The fire control strategy is executed. The fire risk of the sodium ion battery system can be determined through multidimensional data, and fire control can be performed in a timely manner. The accuracy of fire control is improved while the computing power consumption is low, and changes such as aging of the battery system can be adapted.

Description

Technical Field

[0001] This application relates to the field of battery fire protection technology, and in particular to a fire control method and related device for a sodium-ion battery system. Background Technology

[0002] With the widespread application of energy storage battery systems, their safety issues are becoming increasingly prominent. Thermal runaway, a serious safety hazard in battery systems, can lead to severe consequences such as battery fires and explosions, posing a significant threat to people and property. Currently, most fire suppression systems for battery systems rely on a single temperature threshold, which directly triggers fire suppression upon exceeding the threshold. Furthermore, the tiered strategies are fixed and cannot adapt to the dynamic changes within the battery system. Summary of the Invention

[0003] In view of this, this application provides a fire control method and related device for a sodium-ion battery system, which can determine the fire risk of the sodium-ion battery system through multi-dimensional data and carry out fire control in a timely manner, improving the accuracy of fire control while having low computing power overhead, and can adapt to changes such as battery system aging.

[0004] In a first aspect, embodiments of this application provide a fire control method for a sodium-ion battery system, the method comprising: Acquire the cell data and sensor data of the sodium-ion battery system; A risk score is determined based on the cell data and the sensor data, and the risk score is used to reflect the fire risk level of the sodium-ion battery system. The fire risk level is determined based on the relationship between the risk score and the real-time risk threshold. Determine the fire control strategy corresponding to the fire risk level; Implement the aforementioned fire control strategy.

[0005] In one possible embodiment, acquiring the cell data and sensor data of the sodium-ion battery system includes: The voltage and internal resistance data of each cell in the sodium-ion battery system are obtained to obtain the cell data; Temperature data, gas data, and optical data are received from the sensor module to obtain the sensing data.

[0006] In one possible embodiment, determining the risk score based on the cell data and the sensor data includes: The temperature and the rate of temperature rise are determined based on the temperature data, wherein the temperature corresponds to a first weight and the rate of temperature rise corresponds to a second weight. The voltage drop rate is determined based on the voltage data, and the voltage drop rate corresponds to a third weight. The rate of change of internal resistance is determined based on the internal resistance data, and the rate of change of internal resistance corresponds to the fourth weight. The gas concentration is determined based on the gas data, and the gas concentration corresponds to the fifth weight. The optical data determines the optical band and optical frequency, with the optical band corresponding to the sixth weight and the optical frequency corresponding to the seventh weight; The risk score is determined based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight.

[0007] In one possible embodiment, determining the risk score based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight includes: The temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, and the optical frequency are filtered and normalized. The risk score is obtained by summing the products of the temperature with the first weight, the temperature rise rate with the second weight, the voltage drop rate with the third weight, the internal resistance change rate with the fourth weight, the gas concentration with the fifth weight, the optical band with the sixth weight, and the optical frequency with the seventh weight.

[0008] In one possible embodiment, the real-time risk threshold includes a first real-time threshold, a second real-time threshold, and a third real-time threshold; determining the fire risk level based on the relationship between the risk score and the real-time risk threshold includes: If the risk score is greater than or equal to the first real-time threshold and less than the second real-time threshold, the first risk level is determined as the fire risk level. If the risk score is greater than or equal to the second real-time threshold and less than the third real-time threshold, the second risk level is determined as the fire risk level. If the risk score is greater than or equal to the third real-time threshold, the third risk level is determined as the fire risk level.

[0009] In one possible embodiment, the method further includes: Obtain the baseline risk threshold, the current risk threshold, and the smoothing coefficient; The real-time risk threshold is updated by summing the product of the baseline risk threshold and the first coefficient, and the product of the current risk threshold and the smoothing coefficient. The first coefficient is the absolute value of the difference between the smoothing coefficient and 1.

[0010] In one possible embodiment, determining the fire control strategy corresponding to the fire risk level includes: If the fire risk level is the first risk level, a first fire-fighting strategy is determined. The first fire-fighting strategy includes activating the cooling system and reducing the charging power and discharging power of the sodium-ion battery system. If the fire risk level is the second risk level, a second fire-fighting strategy is determined. The second fire-fighting strategy includes activating the aerosol fire-fighting system and cutting off the charging circuit of the sodium-ion battery system. If the fire risk level is the third risk level, a third fire-fighting strategy is determined, which includes activating the fire sprinkler system, cutting off the main circuit of the sodium-ion battery system, and sending early warning information to the fire department terminal.

[0011] Secondly, embodiments of this application provide a fire control device for a sodium-ion battery system, the device comprising: The acquisition unit is used to acquire cell data and sensor data of the sodium-ion battery system; A scoring unit is used to determine a risk score based on the cell data and the sensor data, the risk score being used to reflect the fire risk level of the sodium-ion battery system. A grading unit is used to determine the fire risk level based on the relationship between the risk score and the real-time risk threshold. A determining unit is used to determine the fire control strategy corresponding to the fire risk level; An execution unit is used to execute the fire control strategy.

[0012] Thirdly, embodiments of this application provide an electronic device, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for performing steps in any method of the first aspect of this application.

[0013] Fourthly, embodiments of this application provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in any method of the first aspect of embodiments of this application.

[0014] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in any method of the first aspect of this application. The computer program product may be a software installation package.

[0015] As can be seen, the fire control method and related devices for the sodium-ion battery system described above first acquire the cell data and sensor data of the sodium-ion battery system; then, a risk score is determined based on the cell data and sensor data, and the risk score reflects the degree of fire risk of the sodium-ion battery system; the fire risk level is determined based on the relationship between the risk score and a real-time risk threshold; the fire control strategy corresponding to the fire risk level is determined; and the fire control strategy is executed. This method can determine the fire risk of the sodium-ion battery system through multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead, and can adapt to changes such as battery system aging. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This application provides an illustration of an application scenario for a fire control method for a sodium-ion battery system. Figure 2 A schematic flowchart illustrating a fire control method for a sodium-ion battery system provided in this application embodiment; Figure 3 A schematic flowchart illustrating another fire control method for a sodium-ion battery system provided in this application embodiment; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 5 A functional unit block diagram of a fire control device for a sodium-ion battery system provided in this application embodiment; Figure 6 A functional unit block diagram of a fire control device for a sodium-ion battery system provided in an embodiment of this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0019] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0020] It should be understood that the term "and / or" in this document 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, or B existing alone. Additionally, the character " / " in this document indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, "multiple" refers to two or more.

[0021] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0022] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] Please see Figure 1 , Figure 1 This is an application scenario diagram of a fire control method for a sodium-ion battery system provided in an embodiment of this application. In application scenario 100, it includes a control device 101, an exhaust ventilation device 102, a fire extinguishing device 103, and a recirculation device 104.

[0025] Sodium-ion battery systems can contain multiple cells, and in the event of thermal runaway, they can release flammable gases (such as hydrogen and carbon monoxide) and potentially cause a fire.

[0026] The control device 101 is the central control unit of the fire extinguishing system, which can be a programmable logic controller (PLC), an embedded industrial computer, a fire alarm control system, or a dedicated microprocessor that integrates a BMS communication interface and a fire extinguishing system control algorithm. While these systems have low computing power and are difficult to deploy complex neural network models, the method described in this application can ensure the accuracy of fire control while minimizing computing overhead.

[0027] The control device 101 can issue control commands to the exhaust ventilation device 102, the fire extinguishing device 103, and the recirculation device 104.

[0028] The exhaust ventilation device 102 is typically installed on the compartment of the sodium-ion battery system and includes an explosion-proof exhaust fan and an electric air valve to exhaust the air (including combustible gases) inside the compartment to the external environment in daily or emergency situations.

[0029] The fire extinguishing device 103 is a total flooding gas fire extinguishing system, such as an aerosol fire extinguishing device, a heptafluoropropane or perfluorohexanone fire extinguishing device, which can be installed inside the cabinet of the sodium ion battery system and releases the extinguishing agent after receiving the activation signal.

[0030] The reflux circulation device 104 is used to filter out the target gas in the confined space and return the remaining extinguishing agent gas after filtration to the confined space to form a closed loop reflux.

[0031] Sensors, such as gas sensors, spectral sensors, and temperature sensors, can also be installed in the sodium-ion battery system, which will not be elaborated here.

[0032] All of the above devices are controlled by control equipment 101 and work together to ensure the safe operation of the sodium-ion battery system.

[0033] Please see Figure 2 , Figure 2 A flowchart illustrating a fire control method for a sodium-ion battery system provided in this application embodiment specifically includes the following steps: Step 201: Obtain cell data and sensor data of the sodium-ion battery system.

[0034] Specifically, the voltage and internal resistance data of each cell in the sodium-ion battery system can be acquired to obtain the cell data; temperature data, gas data, and optical data from the sensor module can be received to obtain the sensing data.

[0035] Specifically, the voltage and internal resistance of each cell can be obtained through the battery management system interface, temperature data through the temperature sensor interface, and gas data through the gas sensor interface. The gas sensor can identify gases produced by the combustion of sodium-ion batteries, such as carbon monoxide and hydrogen. Optical data can be obtained through the spectral sensor. During thermal runaway, light of a specific wavelength is generated, and spectral analysis can confirm whether a fire has occurred.

[0036] It is evident that by acquiring the cell data and sensor data of the sodium-ion battery system, data support can be provided for subsequent accurate fire control.

[0037] Step 202: Determine the risk score based on the cell data and the sensor data.

[0038] The risk score is used to reflect the fire risk level of the sodium-ion battery system.

[0039] Specifically, the risk score can be determined based on the temperature data, where temperature corresponds to a first weight and temperature rise rate corresponds to a second weight; the voltage drop rate can be determined based on the voltage data, where voltage drop rate corresponds to a third weight; the internal resistance change rate can be determined based on the internal resistance data, where internal resistance change rate corresponds to a fourth weight; the gas concentration can be determined based on the gas data, where gas concentration corresponds to a fifth weight; the optical band and optical frequency can be determined based on the optical data, where optical band corresponds to a sixth weight and optical frequency corresponds to a seventh weight; and the risk score can be determined based on the temperature, temperature rise rate, voltage drop rate, internal resistance change rate, gas concentration, optical band, optical frequency, first weight, second weight, third weight, fourth weight, fifth weight, sixth weight, and seventh weight.

[0040] Specifically, the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, and the optical frequency can be filtered and normalized. The risk score is obtained by summing the products of the temperature with the first weight, the rate of temperature rise with the second weight, the rate of voltage drop with the third weight, the rate of change of internal resistance with the fourth weight, the gas concentration with the fifth weight, the optical band with the sixth weight, and the optical frequency with the seventh weight.

[0041] When calculating the risk score, the seven parameters—temperature, rate of temperature rise, rate of voltage drop, rate of change of internal resistance, gas concentration, optical band, and optical frequency—are first filtered and normalized to map each parameter to the same numerical range, such as 0 to 1. After normalization, the normalized value of each parameter is multiplied by its corresponding weight to obtain seven product results; these seven product results are then added together, and the sum is the risk score.

[0042] For example, suppose that at a certain moment, after data collection and normalization, the current temperature value is 0.85, the temperature rise rate is 0.60, the voltage drop rate is 0.40, the internal resistance change rate is 0.30, the gas concentration is 0.20, the optical band is 0.10, and the optical frequency is 0.05. Meanwhile, the preset weights from the first to the seventh are 0.30, 0.25, 0.15, 0.10, 0.10, 0.05, and 0.05, respectively. The products are calculated as follows: temperature contribution (0.85 x 0.30 = 0.255), temperature rise rate contribution (0.60 x 0.25 = 0.150), voltage drop rate contribution (0.40 x 0.15 = 0.060), internal resistance change rate contribution (0.30 x 0.10 = 0.030), gas concentration contribution (0.20 x 0.10 = 0.020), optical band contribution (0.10 x 0.05 = 0.005), and optical frequency contribution (0.05 x 0.05 = 0.0025). The sum of these seven contribution values ​​is 0.5225, which is the current risk score.

[0043] It is evident that determining the risk score based on the cell data and the sensor data can provide reliable data support for subsequently determining the accurate risk level.

[0044] Step 203: Determine the fire risk level based on the relationship between the risk score and the real-time risk threshold.

[0045] The real-time risk thresholds include a first real-time threshold, a second real-time threshold, and a third real-time threshold. If the risk score is greater than or equal to the first real-time threshold and less than the second real-time threshold, a first risk level is determined as the fire risk level; if the risk score is greater than or equal to the second real-time threshold and less than the third real-time threshold, a second risk level is determined as the fire risk level; if the risk score is greater than or equal to the third real-time threshold, a third risk level is determined as the fire risk level.

[0046] For example, the first real-time threshold is 0.35, the second real-time threshold is 0.65, and the third real-time threshold is 0.85. If the calculated risk score at a certain moment is 0.45, since 0.45 is greater than 0.35 and less than 0.65, the current fire risk level is determined to be the first risk level. If the risk score rises to 0.70, since 0.70 is greater than 0.65 and less than 0.85, it is determined to be upgraded to the second risk level. If the risk score further rises to 0.9, since 0.9 is greater than 0.85, it is determined to be the third risk level. Conversely, if the risk score is only 0.20, since 0.20 is less than 0.35, the system determines that the current state is safe, does not perform any fire-fighting actions, and only maintains routine monitoring.

[0047] It is evident that determining the fire risk level based on the relationship between the risk score and the real-time risk threshold can accurately determine the fire risk level and can adapt to changes such as battery system aging, thereby improving the accuracy of fire control.

[0048] Step 204: Determine the fire control strategy corresponding to the fire risk level.

[0049] Wherein, if the fire risk level is the first risk level, a first fire-fighting strategy is determined, which includes activating the cooling system and reducing the charging and discharging power of the sodium-ion battery system; if the fire risk level is the second risk level, a second fire-fighting strategy is determined, which includes activating the aerosol fire-fighting system and cutting off the charging circuit of the sodium-ion battery system; if the fire risk level is the third risk level, a third fire-fighting strategy is determined, which includes activating the fire sprinkler system, cutting off the main circuit of the sodium-ion battery system, and sending early warning information to the fire department terminal.

[0050] Specifically, if the fire risk level is the first risk level, a first fire-fighting strategy is determined to be implemented. The first fire-fighting strategy includes activating the cooling system to enhance the heat dissipation capacity of the sodium-ion battery module, while reducing the charging and discharging power of the sodium-ion battery system. By limiting energy input and output, the battery temperature rise trend is slowed down, preventing further deterioration of thermal runaway.

[0051] If the fire risk level is the second risk level, a second fire-fighting strategy is determined to be implemented. The second fire-fighting strategy includes activating the aerosol fire suppression system to suppress the spread of fire by releasing aerosol extinguishing agent into the battery module, while simultaneously cutting off the charging circuit of the sodium-ion battery system to prevent damage to the sodium-ion battery system.

[0052] If the fire risk level is the third risk level, the third fire-fighting strategy is determined to be implemented. The third fire-fighting strategy includes activating the fire sprinkler system, spraying perfluorohexanone extinguishing agent into the battery module to carry out immersion fire extinguishing to achieve rapid cooling and fire extinguishing, simultaneously cutting off the main circuit of the sodium-ion battery system to completely isolate the battery pack from external electrical connections, and sending early warning information to the fire department terminal to notify professional personnel to handle the situation.

[0053] For example, suppose at a certain moment, the risk score is 0.45, and after comparison with the real-time risk threshold, the fire risk level is determined to be the first risk level. At this time, the processor controls the cooling system to start operating, enhancing the convective heat dissipation of the battery module. Simultaneously, the battery management system limits the charging power to 30% of the rated power and the discharging power to 40% of the rated power, thereby slowing down the rate of battery temperature rise. If, during the execution of the first fire-fighting strategy, the risk score continues to rise to 0.68, reaching the determination condition for the second risk level, the processor upgrades the fire-fighting strategy to the second fire-fighting strategy. At this time, the aerosol fire-fighting system is activated, releasing aerosol extinguishing agent into the sodium-ion battery system. Simultaneously, the charging circuit is cut off through the battery management system, prohibiting any external power source from continuing to charge the sodium-ion battery system. If, during the execution of the second fire-fighting strategy, the risk score further rises to 0.85, reaching the determination condition for the third risk level, the fire-fighting strategy is upgraded to the third fire-fighting strategy. At this time, the fire sprinkler system is activated to spray perfluorohexanone extinguishing agent into the sodium-ion battery system. At the same time, the main circuit is cut off to completely isolate the battery pack from the external electrical system. The system also sends a warning message containing the location information of the sodium-ion battery system and the alarm time to the fire department terminal via the wireless communication module, requesting the intervention of external rescue forces.

[0054] Through the aforementioned three-tiered firefighting strategy, this invention can take appropriate prevention and control measures at different stages of the thermal runaway development of sodium-ion batteries. At the first risk level, it actively intervenes with mild means to prevent the situation from escalating. At the second risk level, it uses aerosols to suppress the spread of fire. At the third risk level, it uses perfluorohexanone spraying to extinguish the fire and requests external assistance. In this way, while ensuring safety, it avoids using high-cost firefighting methods when there are only minor abnormalities, thus taking into account both economy and safety.

[0055] Step 205: Execute the fire control strategy.

[0056] As can be seen, the fire control method for the sodium-ion battery system described above involves: first, acquiring the cell data and sensor data of the sodium-ion battery system; determining a risk score based on the cell data and sensor data, whereby the risk score reflects the degree of fire risk of the sodium-ion battery system; determining the fire risk level based on the relationship between the risk score and a real-time risk threshold; determining the fire control strategy corresponding to the fire risk level; and executing the fire control strategy. This method can determine the fire risk of the sodium-ion battery system using multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead and adapting to changes such as battery system aging.

[0057] The following is combined with Figure 3 Another fire control method for a sodium-ion battery system provided in this application embodiment will be described. Figure 3 Another fire control method for a sodium-ion battery system provided in this application embodiment specifically includes the following steps: Step 301: Obtain the baseline risk threshold, the current risk threshold, and the smoothing coefficient.

[0058] Step 302: Summing the product of the baseline risk threshold and the first coefficient, and the product of the current risk threshold and the smoothing coefficient, to update the real-time risk threshold.

[0059] Wherein, the first coefficient is the absolute value of the difference between the smoothing coefficient and 1. That is, the real-time risk threshold equals the current risk threshold × smoothing coefficient + baseline risk threshold × (1 / 2) * 1 / 2 ... Smoothing coefficient).

[0060] The baseline risk threshold is a basic risk level determined by calibration testing at the time the sodium-ion battery system leaves the factory. It is stored in the non-volatile storage unit of the sodium-ion battery system and remains fixed throughout the battery's entire lifespan. The current risk threshold is the real-time risk threshold obtained from the previous control cycle. The smoothing coefficient is a preset constant between zero and one, used to control the speed at which the real-time risk threshold follows the baseline risk threshold.

[0061] For example, suppose the baseline risk threshold is set to 0.30 and the smoothing coefficient is set to 0.95. The current risk threshold obtained from the previous control cycle update is 0.50. In this control cycle, the product of the smoothing coefficient 0.95 and the current risk threshold 0.50 is calculated to obtain a first product of 0.475. Simultaneously, the absolute value of the difference between the smoothing coefficient 0.95 and the first value, i.e., 0.05, is calculated and used as a first coefficient. Then, the baseline risk threshold 0.30 is multiplied by the first coefficient 0.05 to obtain a second product of 0.015. Finally, the first product 0.475 and the second product 0.015 are added to obtain the updated real-time risk threshold of 0.490. Therefore, it can be seen that if the sodium-ion battery does not continuously exhibit abnormalities, the real-time risk threshold will gradually regress from 0.50 to the baseline risk threshold of 0.30. Since the smoothing coefficient is 0.95, each update only moves the threshold by 5 percent towards the baseline, so the threshold changes very smoothly and will not cause a drastic jump in the threshold due to a single abnormal event.

[0062] For example, suppose the sodium-ion battery system gradually ages with increasing cycle count, and the current risk threshold remains stable around 0.35, while the baseline risk threshold remains unchanged at the factory value of 0.30, and the smoothing coefficient remains at 0.95. In each control cycle, due to the smoothing coefficient of 0.95, 95% of the updated real-time risk threshold comes from the current risk threshold, while only 5% comes from the baseline risk threshold. This means that the real-time risk threshold can slowly drift with the actual operating state of the sodium-ion battery, but the drift speed is effectively suppressed by the smoothing coefficient, preventing significant changes due to short-term data fluctuations. When the sodium-ion battery system experiences an increase in internal resistance and a systematic rise in the baseline risk level due to aging, the real-time risk threshold will gradually increase at a very gentle rate, automatically adapting to the new normal after the sodium-ion battery ages, and avoiding frequent false triggering of fire-fighting actions by aging batteries caused by a fixed threshold.

[0063] Step 303: Obtain cell data and sensor data of the sodium-ion battery system.

[0064] Step 304: Determine the risk score based on the cell data and the sensor data.

[0065] Step 305: Determine the fire risk level based on the relationship between the risk score and the real-time risk threshold.

[0066] Step 306: Determine the fire control strategy corresponding to the fire risk level.

[0067] Step 307: Execute the fire control strategy.

[0068] As can be seen, the fire control method for the sodium-ion battery system described above involves: first, acquiring the cell data and sensor data of the sodium-ion battery system; determining a risk score based on the cell data and sensor data, whereby the risk score reflects the degree of fire risk of the sodium-ion battery system; determining the fire risk level based on the relationship between the risk score and a real-time risk threshold; determining the fire control strategy corresponding to the fire risk level; and executing the fire control strategy. This method can determine the fire risk of the sodium-ion battery system using multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead and adapting to changes such as battery system aging.

[0069] For steps not detailed above, please refer to Figure 2 The steps and methods described herein will not be repeated here.

[0070] The following is combined with Figure 4 An electronic device according to an embodiment of this application will be described. Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. The electronic device 400 includes a processor 401, a memory 402, and a communication bus 403 for connecting the processor 401 and the memory 402.

[0071] In some possible implementations, memory 402 includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact discread-only memory (CD-ROM), which is used to store program code executed by electronic device 400 and data transmitted.

[0072] In some possible implementations, the electronic device 400 also includes a communication interface for receiving and sending data.

[0073] In some possible implementations, processor 401 may be one or more central processing units (CPUs). If processor 401 is a central processing unit (CPU), the central processing unit (CPU) may be a single-core central processing unit (CPU) or a multi-core central processing unit (CPU).

[0074] In some possible implementations, processor 401 may be a baseband chip, a chip, a central processing unit (CPU), a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof.

[0075] In specific implementation, the processor 401 in the electronic device 400 executes the program instructions 421 stored in the memory 402, which are applied to the control module of the energy storage system. The energy storage system also includes a multi-level detection module, a multi-level fire suppression module, and a multi-level energy storage module. The control module is communicatively connected to the multi-level detection module, the multi-level fire suppression module, and the multi-level energy storage module through a first communication link or a second communication link, and performs the following operations: Acquire the cell data and sensor data of the sodium-ion battery system; A risk score is determined based on the cell data and the sensor data, and the risk score is used to reflect the fire risk level of the sodium-ion battery system. The fire risk level is determined based on the relationship between the risk score and the real-time risk threshold. Determine the fire control strategy corresponding to the fire risk level; Implement the aforementioned fire control strategy.

[0076] In one possible embodiment, acquiring the cell data and sensor data of the sodium-ion battery system includes: The voltage and internal resistance data of each cell in the sodium-ion battery system are obtained to obtain the cell data; Temperature data, gas data, and optical data are received from the sensor module to obtain the sensing data.

[0077] In one possible embodiment, determining the risk score based on the cell data and the sensor data includes: The temperature and the rate of temperature rise are determined based on the temperature data, wherein the temperature corresponds to a first weight and the rate of temperature rise corresponds to a second weight. The voltage drop rate is determined based on the voltage data, and the voltage drop rate corresponds to a third weight. The rate of change of internal resistance is determined based on the internal resistance data, and the rate of change of internal resistance corresponds to the fourth weight. The gas concentration is determined based on the gas data, and the gas concentration corresponds to the fifth weight. The optical data determines the optical band and optical frequency, with the optical band corresponding to the sixth weight and the optical frequency corresponding to the seventh weight; The risk score is determined based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight.

[0078] In one possible embodiment, determining the risk score based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight includes: The temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, and the optical frequency are filtered and normalized. The risk score is obtained by summing the products of the temperature with the first weight, the temperature rise rate with the second weight, the voltage drop rate with the third weight, the internal resistance change rate with the fourth weight, the gas concentration with the fifth weight, the optical band with the sixth weight, and the optical frequency with the seventh weight.

[0079] In one possible embodiment, the real-time risk threshold includes a first real-time threshold, a second real-time threshold, and a third real-time threshold; determining the fire risk level based on the relationship between the risk score and the real-time risk threshold includes: If the risk score is greater than or equal to the first real-time threshold and less than the second real-time threshold, the first risk level is determined as the fire risk level. If the risk score is greater than or equal to the second real-time threshold and less than the third real-time threshold, the second risk level is determined as the fire risk level. If the risk score is greater than or equal to the third real-time threshold, the third risk level is determined as the fire risk level.

[0080] In one possible embodiment, the method further includes: Obtain the baseline risk threshold, the current risk threshold, and the smoothing coefficient; The real-time risk threshold is updated by summing the product of the baseline risk threshold and the first coefficient, and the product of the current risk threshold and the smoothing coefficient. The first coefficient is the absolute value of the difference between the smoothing coefficient and 1.

[0081] In one possible embodiment, determining the fire control strategy corresponding to the fire risk level includes: If the fire risk level is the first risk level, a first fire-fighting strategy is determined. The first fire-fighting strategy includes activating the cooling system and reducing the charging power and discharging power of the sodium-ion battery system. If the fire risk level is the second risk level, a second fire-fighting strategy is determined. The second fire-fighting strategy includes activating the aerosol fire-fighting system and cutting off the charging circuit of the sodium-ion battery system. If the fire risk level is the third risk level, a third fire-fighting strategy is determined, which includes activating the fire sprinkler system, cutting off the main circuit of the sodium-ion battery system, and sending early warning information to the fire department terminal.

[0082] As can be seen, the fire control method and related devices for the sodium-ion battery system described above first acquire the cell data and sensor data of the sodium-ion battery system; then, a risk score is determined based on the cell data and sensor data, and the risk score reflects the degree of fire risk of the sodium-ion battery system; the fire risk level is determined based on the relationship between the risk score and a real-time risk threshold; the fire control strategy corresponding to the fire risk level is determined; and the fire control strategy is executed. This method can determine the fire risk of the sodium-ion battery system through multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead, and can adapt to changes such as battery system aging.

[0083] It should be noted that the specific implementation of each operation can be described in the corresponding description of the method embodiments shown above. The electronic device 400 can be used to execute the method embodiments of this application, and will not be described again here.

[0084] The above primarily describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the electronic device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0086] When dividing each function into modules according to its corresponding function. Figure 5 This application provides a functional unit block diagram of a fire control device 500 for a sodium-ion battery system, the device comprising: Acquisition unit 510 is used to acquire cell data and sensor data of the sodium-ion battery system; The scoring unit 520 is used to determine a risk score based on the cell data and the sensor data, and the risk score is used to reflect the fire risk level of the sodium-ion battery system. The grading unit 530 is used to determine the fire risk level based on the relationship between the risk score and the real-time risk threshold. The determining unit 540 is used to determine the fire control strategy corresponding to the fire risk level; The execution unit 550 is used to execute the fire control strategy.

[0087] As can be seen, the fire control method and related devices for the sodium-ion battery system described above first acquire the cell data and sensor data of the sodium-ion battery system; then, a risk score is determined based on the cell data and sensor data, and the risk score reflects the degree of fire risk of the sodium-ion battery system; the fire risk level is determined based on the relationship between the risk score and a real-time risk threshold; the fire control strategy corresponding to the fire risk level is determined; and the fire control strategy is executed. This method can determine the fire risk of the sodium-ion battery system through multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead, and can adapt to changes such as battery system aging.

[0088] It should be noted that the specific implementation of each operation can be described in the corresponding description of the method embodiments shown above. The fire control device 500 of the sodium-ion battery system can be used to execute the method embodiments of this application, and will not be described again here.

[0089] When using integrated units, the following is combined with Figure 6 A detailed description is provided of another sodium-ion battery system fire control device 600 in the embodiments of this application, wherein the processing unit 601 is used to perform any step as described in the above method embodiments, and when performing data transmission such as sending, the communication unit 602 may be selectively invoked to complete the corresponding operation.

[0090] The fire control device 600 of the sodium-ion battery system may further include a storage unit 603 for storing program code and data. The processing unit 601 may be a processor, the communication unit 602 may be a wireless communication module, and the storage unit 603 may be a memory; the processing unit 601 is specifically used for: Acquire the cell data and sensor data of the sodium-ion battery system; A risk score is determined based on the cell data and the sensor data, and the risk score is used to reflect the fire risk level of the sodium-ion battery system. The fire risk level is determined based on the relationship between the risk score and the real-time risk threshold. Determine the fire control strategy corresponding to the fire risk level; Implement the aforementioned fire control strategy.

[0091] As can be seen, the fire control method and related devices for the sodium-ion battery system described above first acquire the cell data and sensor data of the sodium-ion battery system; then, a risk score is determined based on the cell data and sensor data, and the risk score reflects the degree of fire risk of the sodium-ion battery system; the fire risk level is determined based on the relationship between the risk score and a real-time risk threshold; the fire control strategy corresponding to the fire risk level is determined; and the fire control strategy is executed. This method can determine the fire risk of the sodium-ion battery system through multi-dimensional data and implement timely fire control, improving the accuracy of fire control while maintaining low computational overhead, and can adapt to changes such as battery system aging.

[0092] It should be noted that the specific implementation of each operation can be described in the corresponding description of the method embodiments shown above. The fire control device 600 of the sodium-ion battery system can be used to execute the method embodiments of this application, and will not be described again here.

[0093] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0094] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

[0095] It should be noted that, for the sake of simplicity, the above embodiments are all described as a series of actions. Those skilled in the art should understand that this application is not limited to the described order of actions, as some steps in the embodiments of this application can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions, steps, modules, or units involved are not necessarily essential to the embodiments of this application.

[0096] In the above embodiments, the descriptions of each embodiment in this application have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] The steps of the methods or algorithms described in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disk, portable hard disk, read-only optical disk (CD-ROM), or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Furthermore, the ASIC can reside in a terminal device or management device. Alternatively, the processor and storage medium can exist as discrete components in the terminal device or management device.

[0098] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in the embodiments of this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0099] The modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both. For example, for devices and products applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits. For devices and products applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The implementation is achieved through a software program that runs on the processor integrated within the chip module. The remaining modules / units (if any) can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into terminal equipment, each of their modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the terminal equipment. Alternatively, at least some modules / units can be implemented through a software program that runs on the processor integrated within the terminal equipment, while the remaining modules / units (if any) can be implemented using hardware methods such as circuits.

[0100] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the embodiments of this application. It should be understood that the above descriptions are merely specific embodiments of the embodiments of this application and are not intended to limit the protection scope of the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solutions of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. A fire control method for a sodium-ion battery system, characterized in that, The method includes: Acquire the cell data and sensor data of the sodium-ion battery system; A risk score is determined based on the cell data and the sensor data, and the risk score is used to reflect the fire risk level of the sodium-ion battery system. The fire risk level is determined based on the relationship between the risk score and the real-time risk threshold. Determine the fire control strategy corresponding to the fire risk level; Implement the aforementioned fire control strategy.

2. The method according to claim 1, characterized in that, The acquisition of cell data and sensor data of the sodium-ion battery system includes: The voltage and internal resistance data of each cell in the sodium-ion battery system are obtained to obtain the cell data; Temperature data, gas data, and optical data are received from the sensor module to obtain the sensing data.

3. The method according to claim 2, characterized in that, The step of determining the risk score based on the cell data and the sensor data includes: The temperature and the rate of temperature rise are determined based on the temperature data, wherein the temperature corresponds to a first weight and the rate of temperature rise corresponds to a second weight. The voltage drop rate is determined based on the voltage data, and the voltage drop rate corresponds to a third weight. The rate of change of internal resistance is determined based on the internal resistance data, and the rate of change of internal resistance corresponds to the fourth weight. The gas concentration is determined based on the gas data, and the gas concentration corresponds to the fifth weight. The optical data determines the optical band and optical frequency, with the optical band corresponding to the sixth weight and the optical frequency corresponding to the seventh weight; The risk score is determined based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight.

4. The method according to claim 3, characterized in that, The method of determining the risk score based on the temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, the optical frequency, the first weight, the second weight, the third weight, the fourth weight, the fifth weight, the sixth weight, and the seventh weight includes: The temperature, the rate of temperature rise, the rate of voltage drop, the rate of change of internal resistance, the gas concentration, the optical band, and the optical frequency are filtered and normalized. The risk score is obtained by summing the products of the temperature with the first weight, the temperature rise rate with the second weight, the voltage drop rate with the third weight, the internal resistance change rate with the fourth weight, the gas concentration with the fifth weight, the optical band with the sixth weight, and the optical frequency with the seventh weight.

5. The method according to claim 1, characterized in that, The real-time risk thresholds include a first real-time threshold, a second real-time threshold, and a third real-time threshold; determining the fire risk level based on the relationship between the risk score and the real-time risk thresholds includes: If the risk score is greater than or equal to the first real-time threshold and less than the second real-time threshold, the first risk level is determined as the fire risk level. If the risk score is greater than or equal to the second real-time threshold and less than the third real-time threshold, the second risk level is determined as the fire risk level. If the risk score is greater than or equal to the third real-time threshold, the third risk level is determined as the fire risk level.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the baseline risk threshold, the current risk threshold, and the smoothing coefficient; The real-time risk threshold is updated by summing the product of the baseline risk threshold and the first coefficient, and the product of the current risk threshold and the smoothing coefficient. The first coefficient is the absolute value of the difference between the smoothing coefficient and 1.

7. The method according to claim 5, characterized in that, The fire control strategy corresponding to the fire risk level includes: If the fire risk level is the first risk level, a first fire-fighting strategy is determined. The first fire-fighting strategy includes activating the cooling system and reducing the charging power and discharging power of the sodium-ion battery system. If the fire risk level is the second risk level, a second fire-fighting strategy is determined. The second fire-fighting strategy includes activating the aerosol fire-fighting system and cutting off the charging circuit of the sodium-ion battery system. If the fire risk level is the third risk level, a third fire-fighting strategy is determined, which includes activating the fire sprinkler system, cutting off the main circuit of the sodium-ion battery system, and sending early warning information to the fire department terminal.

8. A fire control device for a sodium-ion battery system, characterized in that, The device includes: The acquisition unit is used to acquire cell data and sensor data of the sodium-ion battery system; A scoring unit is used to determine a risk score based on the cell data and the sensor data, the risk score being used to reflect the fire risk level of the sodium-ion battery system. A grading unit is used to determine the fire risk level based on the relationship between the risk score and the real-time risk threshold. A determining unit is used to determine the fire control strategy corresponding to the fire risk level; An execution unit is used to execute the fire control strategy.

9. An electronic device, characterized in that, include: A processor, a memory, and one or more programs; the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-7.

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