Early warning system and method for thermal runaway of lithium ion battery based on multi-modal perception

Abstract

This application relates to the field of new energy vehicle technology, and in particular to an early warning system and method for thermal runaway of lithium-ion batteries based on multimodal sensing. The system includes: a multi-source sensing unit arranged around each individual battery cell, each multi-source sensing unit comprising at least a gas detection component for collecting environmental parameters around the battery cell, a temperature sensing component for collecting temperature parameters of the battery cell, and a pressure sensing component for collecting mechanical deformation parameters of the battery cell; a signal processing unit connected to the multi-source sensing unit for uniformly collecting and converting multi-source sensing signals from all battery cells; and a battery management unit connected to the signal processing unit for cross-validating and determining the thermal runaway risk level of the battery cell, and outputting corresponding warning commands and protective control signals based on the thermal runaway risk level. This solves the problem that related technologies only collect environmental data within the lithium battery pack and cannot provide timely warnings.

Description

Technical Field

[0001] This application relates to the field of new energy vehicle technology, and in particular to an early warning system and method for thermal runaway of lithium-ion batteries based on multimodal perception. Background Technology

[0002] With the rapid development of new energy vehicles and energy storage systems, the safety of lithium-ion batteries has become a critical challenge. Traditional battery management systems (BMS) rely on the detection of single parameters such as voltage and current to achieve battery safety management, but they suffer from problems such as response lag and high false alarm rates. Batteries generate gases during operation and thermal runaway. The early stages of thermal runaway are typically accompanied by characteristic gases produced by the decomposition of the electrolyte and solid electrolyte interface film, such as CO, H2, and C2H4; abnormal local temperature rises; and changes in mechanical stress caused by electrode / separator deformation. Therefore, there is an urgent need for an integrated and intelligent solution to achieve accurate early warning of battery thermal runaway.

[0003] A related technology proposes an early warning and automatic control method for lithium battery thermal runaway. This scheme establishes a mathematical model to determine the development process of lithium battery thermal runaway using environmental data. Then, it uses multiple sensors (gas, temperature, and smoke sensors) to collect environmental data inside the lithium battery box in real time. The changes in the collected environmental data are analyzed online according to the established mathematical model, and early warnings are issued based on the risk level of thermal runaway development. Once thermal runaway develops and causes a fire, a fire control device is automatically activated to control the spread of thermal runaway. However, although this scheme uses multiple sensors, it only collects environmental data inside the lithium battery box and does not collect data from the battery cells, thus failing to provide timely early warning. Summary of the Invention

[0004] This application provides a lithium-ion battery thermal runaway early warning system and method based on multimodal sensing to solve the problems in related technologies that use multiple sensors but only collect environmental data inside the lithium battery box without collecting cell data, thus failing to provide timely warnings.

[0005] The first aspect of this application provides a lithium-ion battery thermal runaway early warning system based on multimodal sensing, comprising: A multi-source sensing unit arranged around a single battery cell, the multi-source sensing unit including at least a gas detection component for collecting environmental parameters around the battery cell, a temperature sensing component for collecting battery cell temperature parameters, and a pressure sensing component for collecting battery cell mechanical deformation parameters. The signal processing unit connected to the multi-source sensing unit is used to uniformly collect and convert multi-source sensing signals from all battery cells. The battery management unit connected to the signal processing unit is used to perform cross-validation on the multi-source sensor signals to determine the risk level of thermal runaway of the battery cell, and output the corresponding level of warning command and protection control signal according to the risk level of thermal runaway of the battery cell.

[0006] Optionally, the gas detection component is arranged in the surrounding area of ​​the cell explosion-proof valve to collect the concentration of characteristic gas and surrounding gas pressure parameters when the cell is depressurized.

[0007] Optionally, the temperature sensing component and the pressure sensing component are integrated into a single sensing module, which is attached to the outer surface area of ​​the battery cell to synchronously collect the battery cell body temperature, temperature rise rate, and expansion force parameters during the charging and discharging process.

[0008] Optionally, the multi-source sensing unit uses any one or a combination of two of the signal acquisition methods of fiber optic sensing and electrical sensing to complete data transmission.

[0009] Optionally, the battery management unit has a built-in multi-feature cross-determination logic, which includes at least a three-level progressive early warning mechanism. Different early warning levels correspond to different multi-parameter coupling determination conditions. The corresponding level of early warning output is triggered only when the parameter threshold combination of the corresponding dimension is met.

[0010] Optionally, the three-level progressive early warning mechanism specifically includes: When a single sensing dimension parameter exceeds the first-level threshold, a first-level attention warning is triggered, and monitoring data is continuously retained and cyclical inspection is maintained. When a single sensor dimension parameter exceeds the secondary threshold and at least one other sensor dimension parameter exceeds the primary threshold, a secondary risk warning is triggered, and a protection strategy of power reduction and thermal management pre-adjustment is actively initiated. When a single sensor dimension parameter exceeds the level 3 threshold, and at least one other sensor dimension parameter exceeds the level 2 threshold, a level 3 thermal runaway confirmation warning is triggered, a vehicle-level alarm signal is output, and all-dimensional safety intervention actions are initiated.

[0011] Optionally, the battery management unit has a built-in multimodal feature training model to continuously optimize the cross-judgment rules through historical early warning data and dynamically adjust the threshold range of parameters in each dimension.

[0012] A second aspect of this application provides a method for early warning of thermal runaway in lithium-ion batteries based on multimodal sensing, comprising the following steps: Collect multi-dimensional raw sensing data of lithium-ion battery cells, wherein the multi-dimensional raw sensing data includes at least gas and pressure parameters around the cell, temperature and temperature rise rate parameters of the cell body, and expansion force parameters during the charging and discharging process of the cell. The multi-dimensional raw perception data is subjected to unified noise reduction and normalization preprocessing to convert it into a standardized feature dataset that can be directly used for judgment. The standardized feature dataset is input into a pre-constructed multi-feature cross-judgment logic to complete the thermal runaway risk classification identification through threshold coupling verification of different dimension parameters. Only when the corresponding number of dimension parameters trigger the corresponding threshold conditions, the corresponding level of warning instruction is output. Based on the identified thermal runaway risk level, a matching battery safety protection strategy is implemented to provide early warning and proactive intervention throughout the entire process of lithium-ion battery thermal runaway.

[0013] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the multimodal sensing-based early warning method for thermal runaway of lithium-ion batteries as described in the above embodiments.

[0014] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for early warning of thermal runaway in lithium-ion batteries based on multimodal sensing.

[0015] The lithium-ion battery thermal runaway early warning system and method based on multimodal sensing proposed in this application uses different sensors placed in different parts of the battery pack and cells to measure changes in air pressure, temperature, and expansion force inside the battery pack and cells. This can more comprehensively reflect the state of the battery pack, more accurately determine battery thermal runaway, provide early warning, and ensure the safety of new energy electric vehicles.

[0016] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0017] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a block diagram of an early warning system for thermal runaway of a lithium-ion battery based on multimodal sensing, according to an embodiment of this application. Figure 2 This is a diagram showing the arrangement of a sensor for early warning of thermal runaway in a power battery located in a single cell, according to an embodiment of this application. Figure 3 This is a layout diagram of a power battery thermal runaway early warning system according to an embodiment of this application; Figure 4 This is a flowchart of an early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing, according to an embodiment of this application. Figure 5 This is a schematic diagram illustrating the specific execution of an early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing, according to an embodiment of this application. Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0018] Explanation of reference numerals in the attached figures: 10-Early warning system for thermal runaway of lithium-ion battery based on multimodal sensing; 101-Multi-source sensing unit; 1011-Gas pressure sensor; 1012-Temperature sensor; 1013-Pressure sensor; 102-Signal processing unit; 103-Battery management unit; 104-Battery module; 105-Cell explosion-proof valve; 106-Cell; 107-Fiber optic cable; 601-Memory; 602-Processor; 603-Communication interface. Detailed Implementation

[0019] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0020] The following description, with reference to the accompanying drawings, describes an embodiment of a lithium-ion battery thermal runaway early warning system and method based on multimodal sensing.

[0021] Figure 1 This is a block diagram of an early warning system for thermal runaway of a lithium-ion battery based on multimodal sensing, according to an embodiment of this application.

[0022] like Figure 1 As shown, the lithium-ion battery thermal runaway early warning system 10 based on multimodal sensing includes: a multi-source sensing unit 101, a signal processing unit 102, and a battery management unit 103.

[0023] The system includes a multi-source sensing unit 101 arranged around each individual battery cell 106. Each multi-source sensing unit 101 includes at least a gas detection component for collecting environmental parameters around the battery cell 106, a temperature sensing component for collecting temperature parameters of the battery cell 106, and a pressure sensing component for collecting mechanical deformation parameters of the battery cell 106. A signal processing unit 102 connected to the multi-source sensing unit 101 is used to uniformly collect and convert multi-source sensing signals from all battery cells 106. A battery management unit 103 connected to the signal processing unit 102 is used to perform cross-validation on the multi-source sensing signals to determine the thermal runaway risk level of the battery cell 106, and output corresponding warning commands and protective control signals based on the thermal runaway risk level of the battery cell 106.

[0024] In some embodiments, a gas detection component is arranged in the surrounding area of ​​the cell explosion-proof valve 105 to collect the concentration of characteristic gas and surrounding gas pressure parameters when the cell 106 is depressurized.

[0025] In actual operation, the gas detection component can be a gas pressure sensor 1011. The gas pressure sensor 1011 is placed around the cell explosion-proof valve 105 or at the bottom of the mica plate near the cell explosion-proof valve 105 to monitor and collect the characteristic gas concentration and surrounding gas pressure parameters discharged when the cell 106 is depressurized.

[0026] In some embodiments, the temperature sensing component and the pressure sensing component are integrated into a single sensing module, which is attached to the outer surface area of ​​the battery cell 106 to simultaneously collect the battery cell body temperature, temperature rise rate, and expansion force parameters during the charging and discharging process.

[0027] In actual operation, the temperature sensing component can be a temperature sensor 1012 and the pressure sensing component can be a pressure sensor 1013. The temperature sensor 1012 and the pressure sensor 1013 can be placed on the large surface or side of the battery cell 106, or the temperature sensor 1012 and the pressure sensor 1013 can be integrated and arranged on the large surface of the battery cell 106 to collect and monitor the battery cell temperature, temperature rise rate and expansion force data.

[0028] In some embodiments, the multi-source sensing unit 101 uses any one or a combination of two of the signal acquisition methods of fiber optic sensing and electrical sensing to complete data transmission.

[0029] In actual operation, the gas detection component, temperature sensing component and pressure sensing component in the multi-source sensing unit 101 are connected to the signal processing unit 102 by any one or a combination of two of the following methods: fiber optic sensing 107 and electrical sensing, so as to complete the data transmission of the multi-source sensing signals to the signal processing unit 102.

[0030] In some embodiments, the battery management unit 103 has a built-in multi-feature cross-determination logic, which includes at least three levels of progressive warning mechanism. Different warning levels correspond to different multi-parameter coupling judgment conditions. The warning output of the corresponding level is triggered only when the parameter threshold combination of the corresponding dimension is met.

[0031] In some embodiments, the three-level progressive early warning mechanism is specifically as follows: When a single sensing dimension parameter exceeds the first-level threshold, a first-level attention warning is triggered, and monitoring data is continuously retained and cyclical inspection is maintained. When a single sensor dimension parameter exceeds the secondary threshold, and at least one other sensor dimension parameter exceeds the primary threshold, a secondary risk warning is triggered, and a protection strategy of power reduction and thermal management pre-adjustment is actively initiated. If a single sensor dimension parameter exceeds the Level 3 threshold, and at least one other sensor dimension parameter exceeds the Level 2 threshold, a Level 3 thermal runaway confirmation warning is triggered, outputting a vehicle-level alarm signal and initiating full-dimensional safety intervention actions.

[0032] In some embodiments, the battery management unit 103 incorporates a multimodal feature training model to continuously optimize cross-judgment rules and dynamically adjust the threshold range of parameters in each dimension using historical early warning data.

[0033] In actual operation, the battery management unit 103 incorporates multi-feature cross-judgment logic to cross-verify and judge multi-source sensor signals. If any signal does not exceed the threshold, it indicates that the battery cell 106 is currently in a safe state and working normally, and the data is recorded and continuously monitored. If any sensor data exceeds the first-level threshold, a first-level attention warning is triggered, monitoring data is continuously retained and continuous inspection is maintained. If the second-level threshold is not exceeded subsequently, the risk of thermal runaway is low. If any sensor value exceeds the second-level threshold and any other sensor data exceeds the first-level threshold, a second-level risk warning is triggered, and a "warning" is displayed, indicating a higher risk of thermal runaway. Preventive protection strategies are activated, such as power reduction or thermal management. If any sensor data exceeds the third-level threshold and any other sensor data exceeds the second-level threshold, a third-level thermal runaway confirmation warning is triggered, thermal runaway is confirmed, a thermal runaway alarm signal is issued, and thermal management strategies are activated simultaneously.

[0034] The following is a detailed description of the early warning system for thermal runaway of lithium-ion batteries based on multimodal sensing proposed in this application, through a specific embodiment.

[0035] The gas detection component uses a gas pressure sensor 1011, the temperature sensing component uses a temperature sensor 1012, and the pressure sensing component uses a pressure sensor 1013.

[0036] like Figure 2As shown, a gas pressure sensor 1011 is positioned near the cell explosion-proof valve 105105 to monitor the gas pressure and characteristic gas concentration around the cell 106. A temperature sensor 1012 and a pressure sensor 1013 are integrated and positioned on the large surface of the cell 106 to monitor the cell temperature, temperature rise rate, and expansion force. This arrangement method can monitor the gas pressure and characteristic gas concentration around each cell inside the battery pack, as well as the cell temperature, temperature rise rate, and expansion force. The system comprehensively judges the thermal runaway situation, avoiding false alarms from single-sensor arrangements and optimizing the internal safety monitoring system method of the battery pack.

[0037] Furthermore, such as Figure 3 As shown, a gas pressure sensor 1011, a temperature sensor 1012, and a pressure sensor 1013 are arranged on a battery cell 106, and multiple battery cells 106 are arranged to form a battery module 104. Figure 2 The orientation sensor is connected to the signal processing unit 102 via optical fiber 107. The signal processing unit 102 collects signals transmitted from the sensors arranged on each battery cell 106, processes the collected signals into signal data that can be received by the battery management unit 103, and transmits it to the battery management unit 103 for unified signal processing, monitoring, and comprehensive judgment. This method can monitor the status of each battery cell 106 in real time, and locate and judge the safety performance of each battery cell 106 based on sensor signals. In addition, based on the integrated multimodal sensing system, it can promptly detect and warn of thermal runaway states of battery cells 106 and take corresponding measures to deal with them.

[0038] Specifically, such as Figure 4As shown, starting from the application of high voltage to the entire vehicle, the multimodal sensing battery thermal runaway early warning system begins operation. The signal processing unit 102 begins to collect data from each cell 106 in real time, including but not limited to data from gas pressure sensors, temperature sensors, and pressure sensors. The signal processing unit 102 then processes the signals into data signals acceptable to the battery management unit 103 and transmits them to the battery management unit 103. The battery management unit 103 then processes the data in real time to determine and monitor thermal runaway. If all signals do not exceed the threshold, it indicates that the battery cell is currently in a safe and normal working state, and data is recorded and continuously monitored. If any sensor data exceeds the threshold, a Level 1 warning is issued with a "Pay Attention" prompt. If the data does not subsequently exceed the Level 2 warning, the risk of thermal runaway is low. If any sensor value exceeds the Level 2 warning and any other sensor data exceeds the Level 1 threshold, a Level 2 warning is issued with a "Warning" prompt, indicating a higher risk of thermal runaway. The battery management unit 103 activates preventative protection strategies, such as power reduction or thermal management. If any sensor data exceeds the Level 3 threshold and any other sensor data exceeds the Level 2 threshold, a Level 3 warning is issued, confirming thermal runaway, issuing a thermal runaway alarm signal, and simultaneously activating the thermal management strategy. This method effectively avoids false alarms caused by a single sensor, improves the accuracy of thermal runaway assessment, enhances vehicle safety, and increases the escape rate of passengers. Furthermore, this method is only one possible judgment logic. Other judgment logics can be used based on the cross-modal feature method to train a multimodal model and achieve high-precision judgment.

[0039] In summary, the lithium-ion battery thermal runaway early warning system based on multimodal sensing proposed in the embodiments of this application has the following beneficial effects: (1) It can detect both gas and pressure changes simultaneously, which is more accurate than detecting only gas or pressure. (2) Real-time monitoring of the temperature and expansion force changes of individual cells inside the battery pack can quickly locate the cell's position and status; (3) The current safety performance of the battery cell is judged from multiple dimensions and multiple modes, and early warning is given in advance so that measures can be taken to prevent potential safety accidents and meet the safety requirements of automobiles.

[0040] Next, referring to the accompanying drawings, a method for early warning of thermal runaway of lithium-ion batteries based on multimodal sensing, according to an embodiment of this application, is described.

[0041] Figure 5 This is a flowchart of an early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing, according to an embodiment of this application.

[0042] like Figure 5 As shown, this early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing includes the following steps: In step S501, multi-dimensional raw sensing data of a single lithium-ion battery cell is collected. The multi-dimensional raw sensing data includes at least parameters such as gas and pressure around the cell, temperature and temperature rise rate of the cell body, and expansion force parameters during the charging and discharging process of the cell.

[0043] In step S502, the multi-dimensional raw perception data is subjected to unified noise reduction and normalization preprocessing to convert it into a standardized feature dataset that can be directly used for judgment.

[0044] In step S503, the standardized feature dataset is input into the pre-constructed multi-feature cross-judgment logic to complete the thermal runaway risk classification identification through threshold coupling verification of different dimension parameters. Only when the corresponding number of dimension parameters trigger the corresponding threshold conditions, the corresponding level of warning instruction is output.

[0045] In step S504, a matching battery safety protection strategy is executed based on the identified thermal runaway risk level to provide early warning and proactive intervention for the entire process of lithium-ion battery thermal runaway.

[0046] It should be noted that the foregoing explanation of the embodiment of the lithium-ion battery thermal runaway early warning system based on multimodal perception also applies to the lithium-ion battery thermal runaway early warning method based on multimodal perception in this embodiment, and will not be repeated here.

[0047] The early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing proposed in the embodiments of this application has the following beneficial effects: (1) It can detect both gas and pressure changes simultaneously, which is more accurate than detecting only gas or pressure. (2) Real-time monitoring of the temperature and expansion force changes of individual cells inside the battery pack can quickly locate the cell's position and status; (3) The current safety performance of the battery cell is judged from multiple dimensions and multiple modes, and early warning is given in advance so that measures can be taken to prevent potential safety accidents and meet the safety requirements of automobiles.

[0048] Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0049] The electronic device may include: a memory 601, a processor 602, and a computer program stored on the memory 601 and capable of running on the processor 602.

[0050] When the processor 602 executes the program, it implements the early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing provided in the above embodiments.

[0051] Furthermore, electronic devices also include: Communication interface 603 is used for communication between memory 601 and processor 602.

[0052] The memory 601 is used to store computer programs that can run on the processor 602.

[0053] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0054] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0055] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0056] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0057] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for early warning of thermal runaway in lithium-ion batteries based on multimodal sensing.

[0058] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0059] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0060] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0061] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0062] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0063] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0064] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0065] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A lithium-ion battery thermal runaway early warning system based on multimodal sensing, characterized in that, include: A multi-source sensing unit arranged around a single battery cell, the multi-source sensing unit including at least a gas detection component for collecting environmental parameters around the battery cell, a temperature sensing component for collecting battery cell temperature parameters, and a pressure sensing component for collecting battery cell mechanical deformation parameters. The signal processing unit connected to the multi-source sensing unit is used to uniformly collect and convert multi-source sensing signals from all battery cells. The battery management unit connected to the signal processing unit is used to perform cross-validation on the multi-source sensor signals to determine the risk level of thermal runaway of the battery cell, and output the corresponding level of warning command and protection control signal according to the risk level of thermal runaway of the battery cell.

2. The lithium-ion battery thermal runaway early warning system based on multimodal sensing according to claim 1, characterized in that, The gas detection component is arranged in the surrounding area of ​​the cell explosion-proof valve to collect the concentration of characteristic gases and surrounding gas pressure parameters when the cell is depressurized.

3. The early warning system for thermal runaway of lithium-ion batteries based on multimodal sensing according to claim 1, characterized in that, The temperature sensing component and the pressure sensing component are integrated into a single sensing module, which is attached to the outer surface area of ​​the battery cell to synchronously collect the battery cell body temperature, temperature rise rate, and expansion force parameters during the charging and discharging process.

4. The early warning system for thermal runaway of lithium-ion batteries based on multimodal sensing according to claim 1, characterized in that, The multi-source sensing unit uses any one or a combination of two of the signal acquisition methods, namely fiber optic sensing and electrical sensing, to complete data transmission.

5. The early warning system for thermal runaway of lithium-ion batteries based on multimodal sensing according to claim 1, characterized in that, The battery management unit has a built-in multi-feature cross-determination logic, which includes at least three levels of progressive early warning mechanism. Different early warning levels correspond to different multi-parameter coupling judgment conditions. The corresponding level of early warning output is triggered only when the parameter threshold combination of the corresponding dimension is met.

6. The lithium-ion battery thermal runaway early warning system based on multimodal sensing according to claim 5, characterized in that, The three-level progressive early warning mechanism is as follows: When a single sensing dimension parameter exceeds the first-level threshold, a first-level attention warning is triggered, and monitoring data is continuously retained and cyclical inspection is maintained. When a single sensor dimension parameter exceeds the secondary threshold and at least one other sensor dimension parameter exceeds the primary threshold, a secondary risk warning is triggered, and a protection strategy of power reduction and thermal management pre-adjustment is actively initiated. When a single sensor dimension parameter exceeds the level 3 threshold, and at least one other sensor dimension parameter exceeds the level 2 threshold, a level 3 thermal runaway confirmation warning is triggered, a vehicle-level alarm signal is output, and all-dimensional safety intervention actions are initiated.

7. The early warning system for thermal runaway of lithium-ion batteries based on multimodal sensing according to claim 1, characterized in that, The battery management unit has a built-in multimodal feature training model to continuously optimize the cross-judgment rules and dynamically adjust the threshold range of parameters in each dimension through historical early warning data.

8. A method for early warning of thermal runaway in lithium-ion batteries based on multimodal sensing, characterized in that, The lithium-ion battery thermal runaway early warning system based on multimodal sensing, as described in any one of claims 1-7, comprises the following steps: Collect multi-dimensional raw sensing data of lithium-ion battery cells, wherein the multi-dimensional raw sensing data includes at least gas and pressure parameters around the cell, temperature and temperature rise rate parameters of the cell body, and expansion force parameters during the charging and discharging process of the cell. The multi-dimensional raw perception data is subjected to unified noise reduction and normalization preprocessing to convert it into a standardized feature dataset that can be directly used for judgment. The standardized feature dataset is input into a pre-constructed multi-feature cross-judgment logic to complete the thermal runaway risk classification identification through threshold coupling verification of different dimension parameters. Only when the corresponding number of dimension parameters trigger the corresponding threshold conditions, the corresponding level of warning instruction is output. Based on the identified thermal runaway risk level, a matching battery safety protection strategy is implemented to provide early warning and proactive intervention throughout the entire process of lithium-ion battery thermal runaway.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the multimodal sensing-based early warning method for thermal runaway of lithium-ion batteries as described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the early warning method for thermal runaway of lithium-ion batteries based on multimodal sensing as described in claim 8.

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