Energy storage battery safety assessment method, system, device and program

Abstract

The invention discloses an energy storage battery safety assessment method, system, device and program. The method comprises the steps that a dielectric constant imaginary part of an energy storage battery in the charging and discharging process is collected; modulating a dielectric constant imaginary part based on the surface state of the topological insulator; performing quantum de-coherence detection on the surface state of the topological insulator; when a quantum de-coherence signal is detected, constructing a relaxation time distribution function based on the modulated dielectric constant imaginary part; judging whether an abnormal peak exists in the relaxation time distribution function or not; wherein when an abnormal peak exists in the relaxation time distribution function, it is judged that potential safety hazards exist in the energy storage battery. Through the processing scheme disclosed by the invention, the energy storage battery can be evaluated at a nanosecond level, and magnetic pulse blocking can be carried out on potential safety hazards.

Description

Technical Field

[0001] The present invention relates to the technical field of battery safety assessment, and particularly to a method, system, device and program for evaluating the safety of energy storage batteries. Background Art

[0002] The safety assessment of energy storage batteries is of great significance for ensuring the safety of personnel's lives and property.

[0003] Existing assessment methods include electrochemical model simulation and real-time monitoring systems, etc.; among them, electrochemical model simulation is based on battery equivalent circuit models (such as Thevenin model) or electrochemical P2D models to simulate the changes in voltage, temperature, and SOC (state of charge) during the charging and discharging process of the battery, and predict the risks of overcharging, over-discharging, and thermal runaway. The real-time monitoring system collects data in real time through voltage, current, and temperature sensors, and combines threshold alarms (such as an alarm is triggered when the temperature > 60°C).

[0004] Moreover, existing other assessment methods mostly rely on single-sensor data such as voltage and temperature, and cannot capture hidden faults such as mechanical deformation and internal lithium plating; traditional machine learning models cannot adapt to the parameter drift caused by battery aging; existing methods mostly alarm after an abnormality occurs and lack the ability to predict risks.

[0005] Although the above methods can evaluate energy storage batteries to a certain extent, it is found that there are still several disadvantages in their structures / methods during actual use. Since the best use effect has not been achieved, the disadvantages can be summarized as follows: 1) Limitations of the electrochemical model: The P2D model requires a large amount of computing resources and is difficult to be embedded in a real-time control system; 2) Lag of real-time monitoring: The temperature sensor has a slow response; the false alarm rate is high (such as normal lithium plating at low temperature is misjudged as a fault); 3) Unable to detect intrinsic defects such as lattice distortion of electrode materials and rupture of the solid electrolyte interface (SEI); 4) Lack of risk prediction ability.

[0006] Therefore, it can be seen that the above existing energy storage battery assessment methods are obviously still inconvenient and defective in use and urgently need to be further improved. How to create a new energy storage battery safety assessment method has become an urgent goal to be improved in the current industry. Summary of the Invention

[0007] In view of this, embodiments of the present disclosure provide a method for evaluating the safety of energy storage batteries, which at least partially solves the problems existing in the prior art.

[0008] In a first aspect, embodiments of the present disclosure provide a method for evaluating the safety of energy storage batteries, and the method includes the following steps: Collect the imaginary part of the dielectric constant of the energy storage battery during charge and discharge; Modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator; Perform quantum decoherence detection on the surface state of the topological insulator; When a quantum decoherence signal is detected, construct a relaxation time distribution function based on the modulated imaginary part of the dielectric constant; Determine whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is determined that the energy storage battery has a safety hazard.

[0009] According to a specific implementation manner of the embodiments of the present disclosure, the modulating the imaginary part of the dielectric constant based on the surface state of the topological insulator includes: ; wherein, is the imaginary part of the modulated dielectric constant; is the surface state carrier concentration; is the surface state conductivity; is the electronic charge; is the Planck constant; is the vacuum permittivity; is the angular frequency of the alternating electric field.

[0010] According to a specific implementation manner of the embodiments of the present disclosure, the performing quantum decoherence detection on the surface state of the topological insulator includes: Obtain the fractional derivative of the surface state conductivity based on Caputo; Determine whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity.

[0011] According to a specific implementation manner of the embodiments of the present disclosure, obtaining the fractional derivative of the surface state conductivity based on Caputo includes: ; wherein, is the fractional differential order, ∈(0,1); is the gamma function; is the time variable; is the surface state conductivity; is the derivative of the conductivity function; is the historical time variable; The determining whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity includes: When the fractional derivative of the surface state conductivity is greater than three times the standard deviation of the conductivity baseline noise and the surface state conductivity decreases by more than 30%, it is determined that quantum decoherence occurs.

[0012] According to a specific implementation manner of an embodiment of the present disclosure, the method further includes: when the surface state conductivity decreases by 30%, increasing the frequency of collecting the imaginary part of the dielectric constant of the energy storage battery during charge and discharge by 10 times.

[0013] According to a specific implementation manner of an embodiment of the present disclosure, the constructing the relaxation time distribution function based on the modulated imaginary part of the dielectric constant includes: ; wherein, is the relaxation time distribution function, satisfying ; is the imaginary part of the modulated dielectric constant; is the angular frequency of the alternating electric field; is the relaxation time; is the pi.

[0014] According to a specific implementation manner of an embodiment of the present disclosure, the method further includes: When there is a safety hazard in the energy storage battery, obtaining the position of the abnormal peak and blocking the abnormality through a magnetic pulse; Calculating the magnetic pulse intensity required to block the abnormality based on the following formula: ; wherein, is the magnetic pulse intensity for blocking the abnormality; is the critical relaxation time of the relaxation time distribution function; is the position of the abnormal peak of the relaxation time distribution function; is the reference magnetic field intensity, and when , ; In a second aspect, an embodiment of the present disclosure provides a safety evaluation system for an energy storage battery, the system includes: A collection module configured to collect the imaginary part of the dielectric constant of the energy storage battery during charge and discharge; A modulation module configured to modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator; A detection module configured to perform quantum decoherence detection on the surface state of the topological insulator; A function construction module configured to construct a relaxation time distribution function based on the modulated imaginary part of the dielectric constant when a quantum decoherence signal is detected; An evaluation module configured to determine whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is determined that there is a safety hazard in the energy storage battery.

[0015] In a third aspect, an embodiment of the present disclosure further provides an electronic device, which includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor performs the energy storage battery safety evaluation method according to any one of the preceding first aspect or any implementation manner of the first aspect.

[0016] In a fourth aspect, an embodiment of the present disclosure further provides a non-transitory computer-readable storage medium storing computer instructions, and when the computer instructions are executed by at least one processor, the at least one processor performs the energy storage battery safety evaluation method according to any one of the preceding first aspect or any implementation manner of the first aspect.

[0017] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which includes a computing program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer performs the energy storage battery safety evaluation method according to any one of the preceding first aspect or any implementation manner of the first aspect.

[0018] The energy storage battery safety evaluation method in the embodiments of the present disclosure utilizes the ultrafast response characteristics of topological insulator boundary states and the analysis of the dielectric spectrum relaxation peak shape to achieve nanosecond-level quantitative diagnosis of SEI film microcracks and dendrites, and blocks anomalies through precise strong magnetic field non-contact magnetic pulses. The blocking efficiency is 6 times higher than that of traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic flow chart of an energy storage battery safety evaluation method provided by an embodiment of the present disclosure; Figure 2 It is a block diagram of an energy storage battery safety evaluation method provided by an embodiment of the present disclosure; Figure 3 It is a schematic structural diagram of an energy storage battery safety evaluation system provided by an embodiment of the present disclosure; Figure 4 It is a schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0021] The following describes the embodiments of the present disclosure through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts belong to the scope of protection of the present disclosure.

[0022] It should be noted that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. In addition, this device and / or method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0023] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0024] The embodiment of the present invention provides a method for evaluating the safety of an energy storage battery. By utilizing the ultrafast response characteristics of the boundary states of topological insulators and the analysis of the dielectric spectrum relaxation peak shape, quantitative diagnosis of microcracks and dendrites in the SEI film (Solid Electrolyte Interphase) can be achieved at the nanosecond level, and magnetic pulse blocking of potential safety hazards can be performed, with the blocking efficiency being 6 times higher than that of traditional methods.

[0025] Figure 1 It is a schematic diagram of the process of the method for evaluating the safety of an energy storage battery provided by the embodiment of the present disclosure.

[0026] Figure 2 For Figure 1 The corresponding block diagram of the process of the method for evaluating the safety of an energy storage battery.

[0027] As Figure 1 shown, at step S110, the imaginary part of the dielectric constant of the energy storage battery during charge and discharge is collected.

[0028] More specifically, during the charge and discharge of the energy storage battery, 10 -3 ~10 2Hz alternating electric field to measure the imaginary part of the dielectric constant.

[0029] The imaginary part of the dielectric constant (loss factor) can reflect the energy dissipation characteristics of the material in the alternating electric field. By scanning the angular frequency of the alternating electric field, a curve of the imaginary part of the dielectric constant can be obtained.

[0030] More specifically, next, turn to step S120.

[0031] At step S120, modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator.

[0032] More specifically, deposit a bismuth selenide (Bi2Se3) topological insulator thin film (thickness 50 - 200 nm) on the surface of the electrode current collector, and detect the sudden change in the surface state electron mobility in real time.

[0033] In the embodiment of the present invention, the modulation of the imaginary part of the dielectric constant based on the surface state of the topological insulator includes: ; Wherein, is the imaginary part of the modulated dielectric constant; is the surface state carrier concentration; is the surface state conductivity; is the electron charge amount; is the Planck constant; is the vacuum permittivity; is the angular frequency of the alternating electric field, used to control the speed of the electric field change (10 -3 ~10 2 Hz corresponds to =6.28×10 -3 ~6.28×10 2 rad / s).

[0034] Next, turn to step S130.

[0035] At step S130, perform quantum decoherence detection on the surface state of the topological insulator.

[0036] More specifically, when dendritic growth or SEI film rupture occurs inside the energy storage battery, quantum decoherence will occur in the topological surface state, specifically manifested as: a decrease in the surface state conductivity (enhanced surface state electron scattering) and an increase in the spatial distribution inhomogeneity of the surface state carrier concentration.

[0037] When local overheating (greater than 120 °C) occurs inside the energy storage battery, the topologically protected surface states of the Bi2Se3 thin film will decohere due to lattice expansion, resulting in a sudden drop in the surface state conductivity within 0.1 ms. That is, when decoherence is detected, it indicates that the internal temperature of the battery exceeds 120 °C. Fractional differentiation can sensitively capture this non-stationary mutation, with the signal-to-noise ratio increased by 4.2 times compared to conventional differentiation.

[0038] In an embodiment of the present invention, the quantum decoherence detection of the surface states of the topological insulator includes: obtaining the fractional derivative of the surface state conductivity based on Caputo; and determining whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity.

[0039] In an embodiment of the present invention, obtaining the fractional derivative of the surface state conductivity based on Caputo includes: ; where is the fractional differentiation order, ∈(0, 1); is the gamma function; is the time variable; is the surface state conductivity; is the derivative of the conductivity function; is the historical time variable; Determining whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity includes: when the fractional derivative of the surface state conductivity is greater than three times the standard deviation of the conductivity baseline noise and the surface state conductivity decreases by more than 30%, it is determined that quantum decoherence occurs.

[0040] More specifically, the traditional integer-order derivative ( = 1) only reflects the instantaneous change rate at the current moment and ignores historical information.

[0041] The fractional derivative of the present invention ( < 1) introduces a time integral kernel and endows the evaluation system with a memory effect. For example, when = 0.7, the system retains approximately 30% of the memory weight for the conductivity change within the past 1 second; when the conductivity mutates due to dendrite growth, the fractional derivative can more sensitively capture its non-stationarity.

[0042] In an embodiment of the present invention, the method further includes: when the surface state conductivity decreases by 30%, increasing the frequency of collecting the imaginary part of the dielectric constant of the energy storage battery during charge and discharge by 10 times and pre-starting the magnetic pulse system.

[0043] Next, go to step S140.

[0044] At step S140, when a quantum decoherence signal is detected, a relaxation time distribution function is constructed based on the imaginary part of the modulated dielectric constant.

[0045] In an embodiment of the present invention, constructing the relaxation time distribution function based on the imaginary part of the modulated dielectric constant includes: ; wherein, is the relaxation time distribution function, satisfying , characterizing the ionic kinetic processes at different time scales; is the imaginary part of the modulated dielectric constant; is the angular frequency of the alternating electric field; is the relaxation time, ; is the pi.

[0046] More specifically, when the relaxation time distribution function is in the normal state, the main peak of = 10 -2 ~10 -1 s (corresponding to the conventional insertion and extraction of lithium ions); when there appears < 10 -3 s sub-peak (indicating rapid dendrite growth), the relaxation time distribution function is in the abnormal state.

[0047] Furthermore, when the full width at half maximum of the main peak of < 10 -2 s), it indicates that the dispersion of the lithium ion migration energy barrier increases, and it is determined that the SEI film has mechanical failure; when the peak position shifts to the left ( < 10 -2 s), it indicates that the proportion of low energy barrier paths increases, predicting the risk of dendrite growth; that is, microcracks occur at the electrode / electrolyte interface.

[0048] Next, go to step S150.

[0049] At step S150, determine whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is determined that the energy storage battery has a safety hazard.

[0050] In an embodiment of the present invention, the method further includes: when the energy storage battery has a safety hazard, obtain the position of the abnormal peak and block the abnormality through a magnetic pulse; Calculate the magnetic pulse intensity required to block the abnormality based on the following formula: ; wherein, is the magnetic pulse intensity for blocking the abnormality; is the critical relaxation time of the relaxation time distribution function; is the abnormal peak position of the relaxation time distribution function; is the reference magnetic field strength, and when = at this time, , at this time the magnetic field can just inhibit the critical growth of dendrites. is when the abnormal relaxation time is equal to the critical relaxation time at this time, the magnetic pulse intensity to be applied. It represents the minimum magnetic field strength required in the critical state (that is, when the dendrite growth rate reaches the dangerous threshold), and is the design reference for blocking the system. When < (dendrite growth accelerates), it is necessary to increase the magnetic field to to enhance the blocking effect.

[0051] Furthermore, when = 0.1 ms (at the initial stage of dendrite formation), = 5 T; when = 0.01 ms (dendrite penetrates the diaphragm), it needs to be increased to 15 T (superconducting coil intervenes).

[0052] More specifically, the position of the abnormal peak can be obtained through statistical tests, joint time-frequency domain analysis, or machine learning models. The following takes statistical tests as an example for illustration: Statistical test method: Point-by-point test whether it conforms to the normal distribution hypothesis to identify outliers; if at a certain point exceeds the threshold, it is marked as a potential abnormal peak.

[0053] Through moving window variance analysis, the local variance is calculated using a sliding window. When at this time, it is determined as an abnormal area, where is the local variance, is the global variance.

[0054] In the embodiments of the present invention, when the fractional derivative of the surface state conductivity is greater than five times the standard deviation of the conductivity baseline noise, the abnormality is blocked by a magnetic pulse.

[0055] Figure 3 FIG. shows the energy storage battery safety evaluation system 300 provided by the present invention, including an acquisition module 310, a modulation module 320, a detection module 330, a function construction module 340, and an evaluation module 350.

[0056] The acquisition module 310 is used to acquire the imaginary part of the dielectric constant of the energy storage battery during the charging and discharging process; The modulation module 320 is configured to modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator; The detection module 330 is configured to perform quantum decoherence detection on the surface state of the topological insulator; The function construction module 340 is configured to construct a relaxation time distribution function based on the modulated imaginary part of the dielectric constant when a quantum decoherence signal is detected; The evaluation module 350 is configured to determine whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is determined that there is a safety hazard in the energy storage battery.

[0057] See Figure 4 , this embodiment of the present disclosure also provides an electronic device 40, which includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the energy storage battery safety evaluation method in the foregoing method embodiments.

[0058] This embodiment of the present disclosure also provides a non-transitory computer-readable storage medium, which stores computer instructions for causing the computer to execute the energy storage battery safety evaluation method in the foregoing method embodiments.

[0059] This embodiment of the present disclosure also provides a computer program product, which includes a computing program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer is caused to execute the energy storage battery safety evaluation method in the foregoing method embodiments.

[0060] Next, refer to Figure 4 , which shows a schematic structural diagram of an electronic device 40 suitable for implementing this embodiment of the present disclosure. The electronic device in this embodiment of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The illustrated electronic device is only an example and should not impose any limitation on the functions and usage scope of this embodiment of the present disclosure.

[0061] As Figure 4As shown, the electronic device 40 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 401, which may perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage device 408 into the random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 40 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0062] Generally, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 40 to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows an electronic device 40 having various devices, it should be understood that it is not required to implement or include all the shown devices. More or fewer devices may be implemented or included alternatively.

[0063] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart may be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above functions defined in the method of the embodiment of the present disclosure are executed.

[0064] It should be noted that the above-mentioned computer-readable medium in the present disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, 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 above. In the present disclosure, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0065] The above-mentioned computer-readable medium can be included in the above-mentioned electronic device; it can also exist separately and not be assembled into the electronic device.

[0066] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device is caused to: obtain at least two Internet protocol addresses; send a node evaluation request including the at least two Internet protocol addresses to a node evaluation device, where the node evaluation device selects an Internet protocol address from the at least two Internet protocol addresses and returns it; receive the Internet protocol address returned by the node evaluation device; where the obtained Internet protocol addresses indicate edge nodes in a content distribution network.

[0067] Alternatively, the above computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: receive a node evaluation request including at least two Internet Protocol addresses; select an Internet Protocol address from the at least two Internet Protocol addresses; return the selected Internet Protocol address; wherein the received Internet Protocol addresses indicate edge nodes in a content delivery network.

[0068] Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0070] The units described in the embodiments of the present disclosure may be implemented in software or in hardware. Wherein, the name of the unit does not constitute a limitation on the unit itself in some cases. For example, the first acquisition unit may also be described as "the unit for acquiring at least two Internet Protocol addresses".

[0071] It should be understood that the various parts of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.

[0072] As described above, it is only the specific implementation manner of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present disclosure should be covered within the protection scope of the present disclosure.

Claims

1. A method for evaluating the safety of an energy storage battery, characterized in that, The method includes the following steps: Collect the imaginary part of the dielectric constant of the energy storage battery during charge and discharge; Modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator; Perform quantum decoherence detection on the surface state of the topological insulator; When a quantum decoherence signal is detected, construct a relaxation time distribution function based on the modulated imaginary part of the dielectric constant; Judge whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is judged that the energy storage battery has a safety hazard.

2. The safety evaluation method of the energy storage battery according to claim 1, wherein The modulating the imaginary part of the dielectric constant based on the surface state of the topological insulator includes: ； Among them, is the imaginary part of the modulated dielectric constant; is the surface state carrier concentration; is the surface state conductivity; is the electron charge; is the Planck constant; is the vacuum permittivity; is the angular frequency of the alternating electric field.

3. The energy storage battery safety assessment method according to claim 1, wherein The performing quantum decoherence detection on the surface state of the topological insulator includes: Obtain the fractional derivative of the surface state conductivity based on Caputo; Judge whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity.

4. The energy storage battery safety assessment method according to claim 3, wherein Obtaining the fractional derivative of the surface state conductivity based on Caputo includes: ； Among them, is the fractional differential order, ∈(0, 1); is the gamma function; is the time variable; is the surface state conductivity; is the derivative of the conductivity function; is the historical time variable; The judging whether quantum decoherence occurs based on the fractional derivative of the surface state conductivity includes: When the fractional derivative of the surface state conductivity is greater than three times the standard deviation of the conductivity baseline noise and the surface state conductivity decreases by more than 30%, it is judged that quantum decoherence occurs.

5. The safety evaluation method of the energy storage battery according to claim 4, wherein The method further includes: when the surface state conductivity decreases by 30%, increase the frequency of collecting the imaginary part of the dielectric constant of the energy storage battery during charge and discharge by 10 times.

6. The safety evaluation method of the energy storage battery according to claim 1, characterized in that, The constructing the relaxation time distribution function based on the modulated imaginary part of the dielectric constant includes: ； Among them, is the relaxation time distribution function, satisfying ; is the imaginary part of the modulated dielectric constant; is the angular frequency of the alternating electric field; is the relaxation time; is the pi.

7. The safety evaluation method of the energy storage battery according to claim 1, wherein, The method further includes: When the energy storage battery has a safety hazard, obtain the position of the abnormal peak and block the abnormality through a magnetic pulse; Calculate the magnetic pulse intensity required to block the abnormality based on the following formula: ； Among them, is to block the abnormal magnetic pulse intensity; is the critical relaxation time of the relaxation time distribution function; is the abnormal peak position of the relaxation time distribution function; is the reference magnetic field intensity, and when = at this time, .

8. A safety evaluation system for energy storage batteries, characterized in that, The system includes: A collection module configured to collect the imaginary part of the dielectric constant of the energy storage battery during charge and discharge; A modulation module configured to modulate the imaginary part of the dielectric constant based on the surface state of the topological insulator; A detection module configured to perform quantum decoherence detection on the surface state of the topological insulator; A function construction module configured to construct a relaxation time distribution function based on the modulated imaginary part of the dielectric constant when a quantum decoherence signal is detected; An evaluation module configured to judge whether there is an abnormal peak in the relaxation time distribution function; wherein, when there is an abnormal peak in the relaxation time distribution function, it is judged that the energy storage battery has a safety hazard.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor executes the energy storage battery safety evaluation method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes a computing program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the energy storage battery safety evaluation method according to any one of claims 1 to 7.

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