A method and device for evaluating thermal runaway risk of lithium-ion battery cells

Abstract

The present application proposes a method and device for assessing the thermal runaway risk of a lithium-ion battery cell, which relates to the technical field of application of liquid lithium-ion batteries for energy storage, and includes the following steps: obtaining battery operating data within a preset time period, the battery operating data including measured voltage and load current, obtaining reference solid electrolyte interface SEI film resistance and output voltage according to the load current and based on the electrochemical aging model; performing parameter identification on the electrochemical performance model according to the output voltage and the measured voltage to obtain the true SEI film resistance; calculating the thermal runaway risk coefficient of the battery according to the reference SEI film resistance and the true SEI film resistance; and evaluating the battery safety risk level according to the thermal runaway risk coefficient. The present invention is based on electrochemical principles, calculates the reference SEI film resistance when the battery has no thermal runaway risk, and then obtains the true SEI film resistance based on the working data by using parameter identification, and calculates the battery thermal runaway risk coefficient to evaluate the battery safety state, thereby improving the accuracy and reliability of thermal runaway risk assessment.

Description

Technical Field

[0001] The present application relates to the technical field of application of liquid lithium-ion batteries for energy storage, and in particular to a method and device for assessing the risk of thermal runaway of a lithium-ion battery cell. Background Art

[0002] With the foreseeable depletion of global energy resources and the severe economic situation, the world is paying more and more attention to clean energy. At the same time, my country has also proposed a dual-carbon policy to meet the needs of technology layout and industrialization. Among them, energy storage technology is a bridge connecting the supply side and demand side of clean energy, and perfect energy storage technology is a key factor in the industrialization of clean energy.

[0003] Lithium-ion battery energy storage is the mainstream solution in the energy storage industry, occupying the vast majority of the market share. However, due to certain force majeure factors (such as undetectable manufacturing defects), lithium-ion batteries will experience thermal runaway with a certain probability. In order to avoid the loss of life and property caused by thermal runaway, the battery management system needs to have the ability to predict thermal runaway in advance to warn and avoid the occurrence of thermal runaway.

[0004] At present, there is no perfect solution in academia or industry to achieve early warning of thermal runaway. Statistical theory methods or big data-based methods are generally used to evaluate the thermal runaway risk of batteries. However, batteries will show predictable changes in the early stages of thermal runaway. However, these methods and technologies are limited to battery output signals and lack the support of electrochemical mechanisms. They fail to deeply explore the internal state changes of batteries in the early stages of thermal runaway and are insufficient to accurately predict the risk of thermal runaway. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for assessing the thermal runaway risk of a lithium-ion battery cell in the field of application technology of liquid lithium-ion batteries for energy storage.

[0006] The first aspect of the present application provides a method for assessing the thermal runaway risk of a lithium-ion battery cell, which is characterized by comprising:

[0007] Acquire battery operating condition data within a preset time period, wherein the battery operating condition data includes measured voltage and load current, and acquire reference solid electrolyte interface SEI film resistance and output voltage according to the load current and based on an electrochemical aging model;

[0008] Perform parameter identification on the electrochemical performance model according to the output voltage and the measured voltage to obtain the real SEI film resistance;

[0009] Calculating a thermal runaway risk coefficient of a battery according to the reference SEI film resistance and the actual SEI film resistance;

[0010] The battery safety risk level is evaluated according to the thermal runaway risk coefficient.

[0011] Optionally, obtaining a reference SEI film resistance includes:

[0012] Get the reference SEI film thickness Δδ SEI , formulated as follows:

[0013]

[0014] in, is the molar volume of the SEI film, is the reaction rate of the aging process, The formula is as follows:

[0015]

[0016] Among them, i 0，side represents the exchange current density during the aging process, α c，side represents the lithium ion transfer coefficient of the positive electrode, F is the Faraday constant, R represents the ideal gas constant, T represents the temperature, η side is the overpotential of the battery aging process, η side The formula is as follows:

[0017] η side =η n +U n -U ref，side ,

[0018]

[0019] where φ s is the electrode potential, φ e is the electrolyte liquid phase potential, U ref，side To balance the potential for the aging process, is the reference SEI film resistance.

[0020] According to the reference SEI film thickness Δδ SEI The reference SEI film resistance is obtained by formulating as follows:

[0021]

[0022] Among them, R SEI，0 is the initial value of SEI film resistance, k SEI is the electronic conductivity of the SEI film.

[0023] Optionally, performing parameter identification on an electrochemical performance model according to the output voltage and the measured voltage to obtain a true SEI film resistance includes:

[0024] The expression of the output voltage and the real SEI film resistance is obtained as follows:

[0025]

[0026] Where V is the output voltage, U p , U n are the positive and negative open circuit voltages, respectively, e (L),φ e (0) are the electrolyte potential at the positive and negative electrode current collector positions, I is the load current, and a is the s，n is the specific surface area of ​​the material, L n is the thickness of the electrode energy storage material, η p , η n are the positive and negative electrode overpotentials respectively.

[0027] The error function is obtained according to the measured voltage and the output voltage, and is formulated as follows:

[0028] e v =V m -V

[0029] Among them, e v is the voltage error used in the parameter identification algorithm, V m is the measured voltage, and V is the output voltage.

[0030] The real SEI film resistance is obtained according to the expression and the error function identification.

[0031] Optionally, the calculating the thermal runaway risk coefficient of the battery according to the reference SEI film resistance and the actual SEI film resistance includes:

[0032]

[0033] Among them, ΔR SEI is the change in the actual SEI film resistance obtained based on parameter identification, is the change in resistance of the reference SEI film obtained based on the electrochemical aging model.

[0034] Optionally, evaluating the battery safety risk level according to the thermal runaway risk coefficient includes:

[0035] If R TR If the value is less than the first threshold, the battery safety risk level is evaluated as a thermal runaway level 1 warning;

[0036] If R TR If the value is greater than or equal to the first threshold and less than the second threshold, the battery safety risk level is evaluated as a thermal runaway level 2 warning;

[0037] If R TR If the value is greater than or equal to the second threshold and less than the third threshold, the battery safety risk level is evaluated as a thermal runaway level 3 warning;

[0038] If R TR If the value is greater than or equal to the third threshold and less than or equal to the fourth threshold, the battery safety risk level is evaluated as a normal level;

[0039] If R TR If the value is greater than the third threshold, the battery safety risk level is evaluated as thermal runaway level 4 warning.

[0040] The second aspect of the present application provides a thermal runaway risk assessment device for a lithium-ion battery cell, which is characterized by comprising:

[0041] An acquisition module is used to acquire battery operating condition data within a preset time period, wherein the battery operating condition data includes a measured voltage and a load current, and obtain a reference solid electrolyte interface SEI film resistance and an output voltage according to the load current and based on an electrochemical aging model;

[0042] An identification module, used to perform parameter identification on an electrochemical performance model according to the output voltage and the measured voltage to obtain a true SEI film resistance;

[0043] A calculation module, used to calculate the thermal runaway risk coefficient of the battery according to the reference SEI film resistance and the actual SEI film resistance;

[0044] An evaluation module is used to evaluate the battery safety risk level according to the thermal runaway risk coefficient.

[0045] In a third aspect of the present application, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in any one of the first aspects above is implemented.

[0046] In a fourth aspect of the present application, a non-temporary computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in any one of the first aspects above is implemented.

[0047] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0048] Based on electrochemical principles, the reference SEI film resistance when the battery has no thermal runaway risk is calculated. Then, based on the working data, the actual SEI film resistance is obtained by parameter identification, and the battery thermal runaway risk coefficient is calculated to evaluate the battery safety status, which improves the accuracy and reliability of thermal runaway risk assessment and is easy to quantify.

[0049] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0051] Figure 1 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application;

[0052] Figure 2 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application;

[0053] Figure 3 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application;

[0054] Figure 4 is a block diagram of a thermal runaway risk assessment device for a lithium-ion battery cell according to an exemplary embodiment of the present application;

[0055] Figure 5 It is a block diagram of an electronic device. DETAILED DESCRIPTION

[0056] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0057] Figure 1 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application. Figure 1 Shown

[0058] Step 101, obtaining battery operating data within a preset time period, wherein the battery operating data includes measured voltage and load current, and obtaining a reference solid electrolyte interface SEI film resistance and output voltage according to the load current and based on an electrochemical aging model.

[0059] During the first charge and discharge process of liquid lithium-ion batteries, the electrode material and the electrolyte react at the solid-liquid interface to form a passivation layer covering the surface of the electrode material. This passivation layer is an interface layer with the characteristics of a solid electrolyte. It is an electronic insulator but an excellent conductor of Li+. Li+ can be freely embedded and removed through the passivation layer, so this passivation film is called a "solid electrolyte interface film."

[0060] In this embodiment, the electrochemical aging model can quantify the volume and resistance value of the SEI film, and the preset time period is based on the battery operation from the current moment to the previous reasonable time period.

[0061] In a possible embodiment, the battery operating condition data of 30 minutes before the current moment is obtained.

[0062] Step 102 : performing parameter identification on an electrochemical performance model according to the output voltage and the measured voltage to obtain a real SEI film resistance.

[0063] In this embodiment, the output voltage and the measured voltage are used as a model penalty function to identify and obtain the actual SEI resistance.

[0064] Step 103, calculating the thermal runaway risk coefficient of the battery according to the reference SEI film resistance and the actual SEI film resistance; the formula is as follows:

[0065]

[0066] Among them, ΔR SEI is the change in the actual SEI film resistance obtained based on parameter identification, is the change in resistance of the reference SEI film obtained based on the electrochemical aging model.

[0067] Step 104: Evaluate the battery safety risk level according to the thermal runaway risk coefficient.

[0068] In this embodiment, according to R TR The battery safety risk level is evaluated by comparing it with a pre-defined threshold.

[0069] If R TR If the value is less than the first threshold, the battery safety risk level is evaluated as a thermal runaway level 1 warning;

[0070] If R TR If the value is greater than or equal to the first threshold and less than the second threshold, the battery safety risk level is evaluated as a thermal runaway level 2 warning;

[0071] If R TR If the value is greater than or equal to the second threshold and less than the third threshold, the battery safety risk level is evaluated as a thermal runaway level 3 warning;

[0072] If R TR If the value is greater than or equal to the third threshold and less than or equal to the fourth threshold, the battery safety risk level is evaluated as a normal level;

[0073] If R TR If the value is greater than the third threshold, the battery safety risk level is evaluated as thermal runaway level 4 warning.

[0074] In a possible embodiment, the first threshold is -1, the second threshold is 0, the third threshold is 0.5, and the fourth threshold is 2.

[0075] In an embodiment of the present application, based on electrochemical principles, a reference SEI film resistance is calculated when the battery has no thermal runaway risk. Then, based on the working data, parameter identification is used to obtain the true SEI film resistance, and the battery thermal runaway risk coefficient is calculated to evaluate the battery safety status, thereby improving the accuracy and reliability of the thermal runaway risk assessment.

[0076] Figure 2 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application. Figure 2 As shown, step 101 also includes:

[0077] Step 201, obtaining a reference SEI film thickness Δδ SEI , formulated as follows:

[0078]

[0079] in, is the molar volume of the SEI film, is the reaction rate of the aging process, The formula is as follows:

[0080]

[0081] Among them, i 0，side represents the exchange current density during the aging process, α c，side represents the lithium ion transfer coefficient of the positive electrode, F is the Faraday constant, R represents the ideal gas constant, T represents the temperature, η side is the overpotential of the battery aging process, η side The formula is as follows:

[0082] η side =η n +U n -U ref，side ,

[0083]

[0084] where φ s is the electrode potential, φ e is the electrolyte liquid phase potential, U ref，side To balance the potential for the aging process, is the reference SEI film resistance.

[0085] Among them, α c，side The value of is 0.5, the value of F is 96487C / mol, and the value of R is 8.314J·mol-1·K-1.

[0086] Step 202: according to the reference SEI film thickness Δδ SEI The reference SEI film resistance is obtained by formulating as follows:

[0087]

[0088] Among them, R SEI，0 is the initial value of SEI film resistance, k SEI is the electronic conductivity of the SEI film.

[0089] In the embodiment of the present application, a reference SEI film thickness and a reference SEI film resistance are obtained according to an electrochemical aging model.

[0090] Figure 3 is a flow chart of a method for evaluating thermal runaway risk of a lithium-ion battery cell according to an exemplary embodiment of the present application. Figure 3 As shown, step 102 also includes:

[0091] Step 301, obtaining the expression of the output voltage and the real SEI film resistance, which is formulated as follows:

[0092]

[0093] Where V is the output voltage, U p , U n are the positive and negative open circuit voltages, respectively, e (L),φ e (0) are the electrolyte potential at the positive and negative electrode current collector positions, I is the load current, and a is the s，n is the specific surface area of ​​the material, L n is the thickness of the electrode energy storage material, η p , η n are the positive and negative electrode overpotentials respectively.

[0094] Step 302, obtaining an error function according to the measured voltage and the output voltage, which is formulated as follows:

[0095] e v =V m -V

[0096] Among them, e v is the voltage error used in the parameter identification algorithm, V m is the measured voltage, and V is the output voltage.

[0097] The real SEI film resistance is obtained according to the expression and the error function identification.

[0098] In this embodiment, the real SEI film resistance is identified in real time by genetic algorithm, and the parameters that can be obtained by identification are: positive and negative electrode open circuit voltage: "U p , U n ", electrolyte potential at the positive and negative electrode current collector positions φ e (L)-φ e (0), positive and negative electrode overpotential: “η p ,η n ”, and the real SEI film resistance R SEI .

[0099] In the embodiment of the present application, the real SEI film resistance is identified and obtained based on the electrochemical performance model and the measured voltage to obtain the real physical state inside the battery.

[0100] Figure 4 : is a block diagram of a lithium-ion battery monomer thermal runaway risk assessment device according to an exemplary embodiment of the present application, comprising:

[0101] An acquisition module 410 is used to acquire battery operating condition data within a preset time period, wherein the battery operating condition data includes a measured voltage and a load current, and obtain a reference solid electrolyte interface SEI film resistance and an output voltage according to the load current and based on an electrochemical aging model;

[0102] An identification module 420, configured to perform parameter identification on an electrochemical performance model according to the output voltage and the measured voltage to obtain a true SEI film resistance;

[0103] A calculation module 430, configured to calculate a thermal runaway risk coefficient of a battery according to the reference SEI film resistance and the actual SEI film resistance;

[0104] The evaluation module 440 is used to evaluate the battery safety risk level according to the thermal runaway risk coefficient.

[0105] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0106] Figure 5A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0107] like Figure 5 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0108] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0109] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as the voice instruction response method. For example, in some embodiments, the voice instruction response method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the voice instruction response method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the voice instruction response method in any other appropriate manner (e.g., by means of firmware).

[0110] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0112] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0113] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0114] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0115] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0116] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0117] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for assessing the thermal runaway risk of a lithium-ion battery cell, characterized in that: include: Acquire battery operating condition data within a preset time period, wherein the battery operating condition data includes measured voltage and load current, and acquire a solid electrolyte interface reference SEI film resistance and an output voltage according to the load current and based on an electrochemical aging model; Perform parameter identification on the electrochemical performance model according to the output voltage and the measured voltage to obtain the real SEI film resistance; Calculating a thermal runaway risk coefficient of a battery according to the solid electrolyte interface reference SEI film resistance and the actual SEI film resistance; Evaluate the battery safety risk level according to the thermal runaway risk coefficient; The obtaining of the reference SEI film resistance comprises: Obtain reference SEI film thickness , formulated as follows: ， in, is the molar volume of the SEI film, is the reaction rate of the aging process, The formula is as follows: ， in, represents the exchange current density during the aging process, represents the lithium ion transfer coefficient of the positive electrode, F is the Faraday constant, R represents the ideal gas constant, T represents the temperature, The overpotential of the battery aging process. The formula is as follows: ， ， in is the electrode potential, is the electrolyte liquid phase potential, To balance the potential for the aging process, is the reference SEI film resistance; According to the reference SEI film thickness The reference SEI film resistance is obtained by formulating as follows: in, is the initial value of SEI film resistance, is the electronic conductivity of the SEI film.

2. The method according to claim 1, characterized in that Performing parameter identification on the electrochemical performance model according to the output voltage and the measured voltage to obtain the real SEI film resistance includes: The expression of the output voltage and the real SEI film resistance is obtained as follows: ， Where V is the output voltage, , are the positive and negative open circuit voltages, respectively. , are the electrolyte potentials at the positive and negative electrode current collectors, is the load current, is the specific surface area of ​​the material, is the thickness of the electrode energy storage material, are the positive and negative electrode overpotentials respectively; The error function is obtained according to the measured voltage and the output voltage, and is formulated as follows: in, is the voltage error used in the parameter identification algorithm, is the measured voltage, is the output voltage; The real SEI film resistance is obtained according to the expression and the error function identification.

3. The method according to claim 1, characterized in that The calculating the thermal runaway risk coefficient of the battery according to the reference SEI film resistance and the real SEI film resistance includes: in, is the change in the actual SEI film resistance obtained based on parameter identification, is the change in resistance of the reference SEI film obtained based on the electrochemical aging model.

4. The method according to claim 3, characterized in that The evaluating the battery safety risk level according to the thermal runaway risk coefficient includes: like If the value is less than the first threshold, the battery safety risk level is evaluated as a thermal runaway level 1 warning; like If the value is greater than or equal to the first threshold and less than the second threshold, the battery safety risk level is evaluated as a thermal runaway level 2 warning; like If the value is greater than or equal to the second threshold and less than the third threshold, the battery safety risk level is evaluated as a thermal runaway level 3 warning; like If the value is greater than or equal to the third threshold and less than or equal to the fourth threshold, the battery safety risk level is evaluated as a normal level; like If the value is greater than the third threshold, the battery safety risk level is evaluated as thermal runaway level 4 warning.

5. A thermal runaway risk assessment device for a lithium-ion battery cell, characterized in that: include: An acquisition module is used to acquire battery operating condition data within a preset time period, wherein the battery operating condition data includes a measured voltage and a load current, and obtain a solid electrolyte interface reference SEI film resistance and an output voltage according to the load current and based on an electrochemical aging model; An identification module, used to perform parameter identification on an electrochemical performance model according to the output voltage and the measured voltage to obtain a true SEI film resistance; A calculation module, used to calculate the thermal runaway risk coefficient of the battery according to the solid electrolyte interface reference SEI film resistance and the actual SEI film resistance; An evaluation module, used to evaluate the battery safety risk level according to the thermal runaway risk coefficient; The obtaining of the reference SEI film resistance comprises: Obtain reference SEI film thickness , formulated as follows: ， in, is the molar volume of the SEI film, is the reaction rate of the aging process, The formula is as follows: ， in, represents the exchange current density during the aging process, represents the lithium ion transfer coefficient of the positive electrode, F is the Faraday constant, R represents the ideal gas constant, T represents the temperature, The overpotential of the battery aging process. The formula is as follows: ， ， in is the electrode potential, is the electrolyte liquid phase potential, To balance the potential for the aging process, is the reference SEI film resistance; According to the reference SEI film thickness The reference SEI film resistance is obtained by formulating as follows: in, is the initial value of SEI film resistance, is the electronic conductivity of the SEI film.

6. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 4 is implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images