Method and system for inhibiting thermal runaway of battery based on strong pulsed magnetic field

Abstract

The invention discloses a method and a system for suppressing thermal runaway of a battery based on a strong pulsed magnetic field. The method comprises the following steps: acquiring state parameters of a target battery module in real time; the current state parameter change rate of the target battery module is calculated according to the state parameter of the target battery module obtained in real time, and if the current state parameter change rate meets a preset condition, it is judged that the battery module has a thermal runaway risk; predicting the target magnetic field intensity and the target pulse width by using a pre-constructed neural network prediction model based on a radial basis function; issuing a command of applying a pulsed magnetic field to a magnetic field generation module, so that the magnetic field generation module applies the pulsed magnetic field with a target magnetic field intensity and a target pulse width to the target battery through a magnetic field coupling module; and evaluating the thermal runaway suppression effect of the target battery module until the thermal runaway suppression effect reaches the preset threshold. According to the invention, thermal runaway can be rapidly inhibited, and the battery is not damaged.

Description

Technical Field

[0001] This application relates to the field of thermal runaway suppression technology, and in particular to a method and system for suppressing battery thermal runaway based on a strong pulsed magnetic field. Background Technology

[0002] With the rapid development of high-energy-density electrochemical energy storage technology, thermal runaway safety has become a bottleneck restricting its large-scale application. Existing thermal runaway intervention technologies mainly follow two paths: "chemical inhibition" or "energy destruction," both of which have inherent limitations.

[0003] Chemical intervention: By adding flame retardants or pre-installing fire extinguishing agents in the electrolyte, the essence is to introduce foreign chemical substances, which permanently change the battery chemical system. This is often accompanied by side effects such as electrochemical performance degradation and increased internal resistance, and the intervention capability is limited.

[0004] Destructive intervention in the energy field: Technologies such as lasers and microwaves physically destroy the internal structure of the battery through instantaneous high-energy deposition (such as electrolyte decomposition and electrode melting). Although thermal runaway can be eliminated, it leads to irreversible and permanent damage to the battery.

[0005] Traditional physical methods, such as phase change material heat absorption and heat conduction path optimization, have a slow response and only work at the thermal management level, and cannot intervene in the violent chain reaction that has already been triggered. Summary of the Invention

[0006] Based on this, and in response to the aforementioned technical problems, a method and system for suppressing battery thermal runaway based on a strong pulsed magnetic field are provided to solve the problems of irreversible damage to the battery, slow intervention, and poor intervention effect caused by existing technologies when suppressing thermal runaway.

[0007] In a first aspect, a method for suppressing battery thermal runaway based on a strong pulsed magnetic field, the method comprising:

[0008] Step S1: Real-time acquisition of the status parameters of the target battery module; the status parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance;

[0009] Step S2: Calculate the rate of change of the current state parameters of the target battery module based on the real-time acquired state parameters of the target battery module. If the rate of change of the current state parameters meets the preset conditions, it is determined that the battery module has a risk of thermal runaway.

[0010] Step S3: Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the target magnetic field strength and target pulse width are predicted using a pre-built radial basis function neural network prediction model.

[0011] Step S4: Send a command to the magnetic field generating module to apply a pulsed magnetic field, so that the magnetic field generating module applies a pulsed magnetic field with a target magnetic field strength and a target pulse width to the target battery through the magnetic field coupling module;

[0012] Step S5: Evaluate the thermal runaway suppression effect of the target battery module based on the real-time acquired state parameters of the target battery module. If the thermal runaway suppression effect does not reach the preset threshold, repeat steps S3-S5 until the thermal runaway suppression effect reaches the preset threshold.

[0013] Optionally, in the above scheme, step S2 specifically includes:

[0014] The current voltage drop rate, temperature rise rate, internal resistance increase rate of the target battery module are calculated based on the real-time acquired state parameters of the target battery module, as well as whether an abnormal acoustic emission signal is detected.

[0015] If the voltage drop rate is greater than 10% / s of the initial voltage of the target battery module and the temperature rise rate exceeds 1.0°C / s, then it is determined that there is a risk of thermal runaway.

[0016] If the rate of increase in internal resistance is greater than 0.05 and abnormal acoustic emission signals are obtained, it is determined that there is a risk of thermal runaway.

[0017] Optionally, in the above scheme, the radial basis function-based neural network prediction model is constructed in the following manner:

[0018] Acquire historical data for different battery types; the historical data includes: SOC, SOH, and temperature when thermal runaway risk occurs, as well as battery state parameters after applying different pulse magnetic field strengths and pulse widths;

[0019] The historical data is input into a radial basis function neural network prediction model for training.

[0020] The theoretical range is used as a priori condition, so that the target magnetic field strength and target pulse width output by the radial basis function-based neural network prediction model during training and prediction are based on the theoretical range.

[0021] In the above scheme, optionally, the theoretical range is obtained by the following method:

[0022] Based on the ion mobility suppression model, the rate of decrease in the mobility of charged particles in the target battery type under different magnetic field intensities is calculated, and the initial theoretical range of the magnetic field intensity is determined based on the preset decrease rate threshold.

[0023] Based on the cyclotron radius and magnetic freezing model, the cyclotron radius of charged particles is calculated under the magnetic field strength within the initial theoretical range. The magnetic field strength corresponding to the cyclotron radius being smaller than the particle size of the active particles of the electrode material is determined as the final lower limit of the theoretical range of the magnetic field strength.

[0024] The pulse width range in the theoretical range was obtained through statistical analysis of thermal runaway suppression experimental data for the target battery type.

[0025] Optionally, in the above scheme, the magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system;

[0026] The energy storage unit is used to provide pulse energy to the pulse power system;

[0027] The pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current.

[0028] The coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulsed current.

[0029] Optionally, in the above scheme, the magnetic field generating module further includes: a thermal management unit;

[0030] Receive temperature data collected by a temperature sensor installed in the coil system;

[0031] When the temperature of the coil system exceeds a certain value, a cooling command is sent to the thermal management unit, which then initiates coolant circulation, allowing the coolant to flow through the microchannels inside the coil system and exchange heat with the flowing coolant.

[0032] In the above scheme, optionally, the magnetic field coupling module specifically includes:

[0033] Upper magnetic pole arm (1), lower magnetic pole arm (2), upper pole head (3), lower pole head (4), magnetic core (5), linear module (7), control motor (8), shielding shell (10), internal magnetic shielding cover (11);

[0034] The coil system (6) is respectively embedded in the upper magnetic pole arm (1) and the lower magnetic pole arm (2), the upper magnetic pole arm (1) and the lower magnetic pole arm (2) are arranged opposite to each other, and the tail ends are respectively fixed to the two ends of the C-type magnetic core (5); the upper pole head (3) and the lower pole head (4) are respectively set on the opposite end faces of the upper magnetic pole arm (1) and the lower magnetic pole arm (2), and an adjustable air gap (g) is formed between them; the battery module (9) is placed in the air gap;

[0035] The linear module (7) is connected to the control motor (8). The linear module (7) is used to move the upper magnetic pole arm (1) up and down along the air gap direction to adapt to batteries of different thicknesses.

[0036] The entire magnetic circuit assembly is housed within an internal magnetic shield (11), and the shielding shell (10) is coaxially fitted onto the outside of the internal magnetic shield (11) to form a double-layer electromagnetic shielding structure.

[0037] Secondly, a system for suppressing battery thermal runaway based on a strong pulsed magnetic field, the system comprising:

[0038] Control and Sensing Module: Used to acquire the state parameters of the target battery module in real time, calculate the rate of change of the current state parameters of the target battery module, and determine that the battery module has a risk of thermal runaway if the rate of change of the current state parameters meets the preset conditions. The state parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance. Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the module uses a pre-built radial basis function neural network prediction model to predict the target magnetic field strength and target pulse width. The module issues a command to apply a pulsed magnetic field to the magnetic field generation module, and evaluates the suppression effect in real time after intervention. If the threshold is not reached, the module automatically re-predicts and re-triggers.

[0039] The magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system; the energy storage unit is used to provide pulse energy to the pulse power supply system; the pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current; the coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulse current.

[0040] Magnetic field focusing and coupling module: used to guide the strong pulsed magnetic field generated by the coil system into the internal reaction region of the battery module.

[0041] Thirdly, a computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method for suppressing battery thermal runaway based on a strong pulsed magnetic field as described in the first aspect.

[0042] Fourthly, a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the method for suppressing battery thermal runaway based on a strong pulsed magnetic field as described in the first aspect.

[0043] This application has at least the following beneficial effects:

[0044] This application achieves efficient, rapid, and reversible suppression of battery thermal runaway by applying a magnetic field to the battery when the risk of thermal runaway is predicted. It can respond quickly in the early stages of thermal runaway, and by precisely controlling the magnetic field strength and pulse width, it significantly reduces the mobility of lithium ions and the electrochemical reaction rate, thereby effectively blocking the thermal runaway chain reaction and reducing heat generation. This technology is not only fast-responding but also reversible, enabling the battery to recover its function after intervention, extending battery life, and reducing maintenance costs. Furthermore, the magnetic field coupling module of this application has a compact design, integrating magnetic circuit focusing, an adapter structure, and electromagnetic shielding functions, making it easy to integrate with existing battery systems. Attached Figure Description

[0045] Figure 1 A flowchart illustrating a method for suppressing battery thermal runaway based on a strong pulsed magnetic field, as provided in one embodiment of this application;

[0046] Figure 2 A general framework diagram of a battery thermal runaway suppression system based on a strong pulsed magnetic field is provided as an embodiment of this application;

[0047] Figure 3 Another flowchart of a method for suppressing battery thermal runaway based on a strong pulsed magnetic field, provided in one embodiment of this application;

[0048] Figure 4 A schematic diagram of an in-vehicle embedded system integration for an embodiment of this application, illustrating a method for suppressing battery thermal runaway based on a strong pulsed magnetic field;

[0049] Figure 5 This is a structural diagram of an energy storage unit provided in one embodiment of this application;

[0050] Figure 6 A cross-sectional view of a coil system provided in one embodiment of this application;

[0051] Figure 7 A side view of a coil system provided according to an embodiment of this application;

[0052] Figure 8 This is a structural diagram of a thermal management unit provided in one embodiment of this application;

[0053] Figure 9 This is a structural diagram of a magnetic field coupling module provided in one embodiment of this application;

[0054] Wherein 1—upper magnetic pole arm, 2—lower magnetic pole arm, 3—upper pole head, 4—lower pole head, 5—magnetic core, 6—coil system, 7—linear module, 7—control motor, 10—shielding shell, 11—internal magnetic shielding cover. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] Existing technologies regarding the use of magnetic fields in batteries mainly include the following aspects:

[0057] (1) Injecting or encapsulating "magnetic liquid metal" into the battery interior / interface for thermal management is a material introduction scheme;

[0058] (2) Place the entire battery in a constant magnetic field of <2 T and expose it continuously for several hours or even longer. This improves the "performance indicators" such as cycle life, capacity retention, and polarization impedance, rather than providing millisecond-level rapid safety intervention. The physical mechanism is completely different from the instantaneous freezing effect of this invention.

[0059] (3) Electromagnetic induction heating technology: using an alternating magnetic field to generate eddy currents in a conductor to generate heat, the purpose and effect of which are completely opposite to the purpose of the present invention to suppress the reaction.

[0060] In the existing technology, there is no method or system that uses a short-duration, strong pulsed magnetic field to instantaneously freeze the migration of charged particles inside a battery to suppress thermal runaway. This invention fills a technological gap in the field of non-contact, reversible intervention.

[0061] This application constructs a closed-loop, non-contact physical field safety intervention system encompassing "perception-decision-generation-intervention-evaluation." The fundamental breakthrough lies in transforming the strong pulsed magnetic field technology from the field of high-energy physics into a reliable solution through interdisciplinary engineering innovation. This solution can be integrated into battery systems or used as independent equipment to provide millisecond-level, reversible (potential), and non-destructive intervention for battery thermal runaway under complex operating conditions.

[0062] This application aims to provide a method and system for suppressing battery thermal runaway based on freezing the migration of charged particles using a strong pulsed magnetic field, achieving a technological leap from "destructive eradication" to "physical suspension." The specific objectives are as follows:

[0063] (1) Achieve non-contact, non-destructive intervention: suppress thermal runaway through pure physical field action without damaging the battery structure or introducing foreign chemical substances.

[0064] (2) Achieve millisecond-level fast response: Establish a complete control chain from thermal runaway feature identification to strong magnetic field application, with a total response time of less than 1 millisecond.

[0065] (3) Targeting the potential of “reversible intervention”: instantaneously freezing the electrochemical reaction rather than permanently destroying the reaction medium, creating conditions for the battery to recover some or all of its functions after intervention.

[0066] (4) Construct a universal technology platform: energy storage devices applicable to various chemical systems (ternary lithium, lithium iron phosphate, solid-state batteries, etc.) and different scales (from single cell to vehicle battery pack).

[0067] (5) Achieve precise and controllable intervention effect: Precisely regulate the magnetic field strength, pulse width and spatiotemporal distribution according to the battery type, state (SOC, SOH) and thermal runaway stage.

[0068] This invention can provide a brand-new technical tool for the field of battery safety, change the safety design paradigm of battery systems, and lay the foundation for the development of "repairable" safe battery systems.

[0069] In one embodiment, such as Figure 1 , Figure 2 As shown, a method for suppressing battery thermal runaway based on a strong pulsed magnetic field is provided, the method comprising:

[0070] Step S1: Real-time acquisition of the status parameters of the target battery module; the status parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance;

[0071] Step S2: Calculate the rate of change of the current state parameters of the target battery module based on the real-time acquired state parameters of the target battery module. If the rate of change of the current state parameters meets the preset conditions, it is determined that the battery module has a risk of thermal runaway.

[0072] Step S3: Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the target magnetic field strength and target pulse width are predicted using a pre-built radial basis function neural network prediction model.

[0073] Step S4: Send a command to the magnetic field generating module to apply a pulsed magnetic field, so that the magnetic field generating module applies a pulsed magnetic field with a target magnetic field strength and a target pulse width to the target battery through the magnetic field coupling module;

[0074] Step S5: Evaluate the thermal runaway suppression effect of the target battery module based on the real-time acquired state parameters. If the thermal runaway suppression effect does not reach a preset threshold, repeat steps S3-S5 until the thermal runaway suppression effect reaches the preset threshold. The suppression effect is comprehensively judged by monitoring the battery's temperature change rate, voltage stability, and acoustic emission signal after magnetic field intervention; when the temperature rise rate is <0.1... When the voltage fluctuation is less than ±0.1V and the acoustic emission signal energy drops below the threshold, it is considered that the suppression is successful.

[0075] Thermal runaway chain reactions develop extremely rapidly (on the order of milliseconds to seconds), and intervention must be completed before the irreversible and violent stage. This invention uses a pulsed magnetic field instead of a steady-state magnetic field for the following reasons:

[0076] (1) Use instantaneous energy pulses (pulse width 0.1-5 ms) to match the rapid evolution of thermal runaway.

[0077] (2) Avoid system overheating, energy waste and long-term side effects on the battery caused by applying a magnetic field for a long time.

[0078] The aforementioned method for suppressing battery thermal runaway based on a strong pulsed magnetic field achieves efficient, rapid, and reversible suppression of thermal runaway by applying a magnetic field to the battery when the risk of thermal runaway is predicted. It can respond rapidly in the early stages of thermal runaway, and by precisely controlling the magnetic field strength and pulse width, it significantly reduces the lithium-ion mobility and electrochemical reaction rate, thereby effectively blocking the thermal runaway chain reaction and reducing heat generation. This technology not only has a fast response speed but also reversibility, enabling the battery to recover its function after intervention, extending battery life, and reducing maintenance costs. Furthermore, the magnetic field coupling module of this application has a compact design, integrating magnetic circuit focusing, adapter structure, and electromagnetic shielding functions, making it easy to integrate with existing battery systems.

[0079] In one embodiment, step S2 specifically includes:

[0080] The current voltage drop rate, temperature rise rate, internal resistance increase rate of the target battery module are calculated based on the real-time acquired state parameters of the target battery module, as well as whether an abnormal acoustic emission signal is detected.

[0081] If the voltage drop rate is greater than the initial voltage of the target battery module And the rate of temperature rise exceeds If so, it is determined that there is a risk of thermal runaway;

[0082] If the rate of increase in internal resistance is greater than 0.05 and abnormal acoustic emission signals are obtained, it is determined that there is a risk of thermal runaway.

[0083] In one embodiment, the radial basis function-based neural network prediction model is constructed in the following manner:

[0084] Acquire historical data for different battery types; the historical data includes: SOC, SOH, and temperature when thermal runaway risk occurs, as well as battery state parameters after applying different pulse magnetic field strengths and pulse widths;

[0085] The historical data is input into a radial basis function neural network prediction model for training.

[0086] The theoretical range is used as a priori condition, so that the target magnetic field strength and target pulse width output by the radial basis function-based neural network prediction model during training and prediction are based on the theoretical range.

[0087] In one embodiment, the theoretical range is obtained by the following method:

[0088] Based on the ion mobility suppression model, the rate of decrease in the mobility of charged particles in the target battery type under different magnetic field intensities is calculated, and the initial theoretical range of the magnetic field intensity is determined based on the preset decrease rate threshold.

[0089] Based on the cyclotron radius and magnetic freezing model, the cyclotron radius of charged particles is calculated under the magnetic field strength within the initial theoretical range. The magnetic field strength corresponding to the cyclotron radius being smaller than the particle size of the active particles of the electrode material is determined as the final lower limit of the theoretical range of the magnetic field strength.

[0090] The pulse width range in the theoretical range was obtained through statistical analysis of thermal runaway suppression experimental data for the target battery type.

[0091] The particle mobility suppression model:

[0092] ,

[0093] in, B represents the zero field mobility, and B represents the magnetic field. This represents particle mobility.

[0094] When B = 15 T, the apparent mobility of lithium ions in organic electrolytes can decrease to the level at zero field. .

[0095] The gyration radius and magnetic freezing criterion:

[0096]

[0097] Where v is the thermal velocity, q is the absolute value of the particle's charge, m is the particle's mass, and r is the radius of gyration;

[0098] Such as the speed of thermal motion The radius of gyration of lithium ions in a magnetic field of B=15 T is... Smaller than the particle size of the active particles in the electrode material ( "Magnetic freeze" occurs when ( ).

[0099] Reaction kinetics pause model: The magnetic field lowers the reactants ( The apparent diffusion coefficient Deff of ) makes the exchange current density The reaction rate decreases by an order of magnitude, thus "pausing" the electrochemical reaction.

[0100] In one embodiment, the magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system;

[0101] The energy storage unit is used to provide pulse energy to the pulse power system;

[0102] The pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current.

[0103] The coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulsed current.

[0104] In this embodiment, the selection of the energy storage unit includes:

[0105] (1) Capacitor selection: Metallized polypropylene film pulse capacitors (TDK B25620B series) are used, with a single capacitor capacity of 20 μF and a rated voltage of 30 kV.

[0106] (2) Combination method: 4 parallel and 12 series modular combination, total capacity 80 μF, total energy storage of 36 kJ at 30 kV, installed in a polycarbonate insulating box and filled with transformer oil. For example... Figure 5 As shown.

[0107] The selection of coil systems includes:

[0108] (1) Type and Material Selection: OFHC oxygen-free copper rectangular cross-section wire (5mm×10mm) is used for the solenoid coil. Water-cooled microchannel; C-type magnetic core coil with the core wound from iron-based nanocrystalline ribbon (1K107B), saturation magnetic induction intensity Bs=1.35 T. For example... Figure 6 and Figure 7 The diagram shows a cross-sectional view and a side view of the coil system.

[0109] (2) Mechanical and thermal management design: Under a current of 100 kA and a magnetic field of 15 T, the coil was optimized and reinforced through ANSYS simulation, with deformation < 0.1 mm; forced cooling with deionized water was adopted, with a flow rate ≥ The coil temperature rise after a single pulse is less than 15°C.

[0110] Pulse power supply system selection:

[0111] (1) Topology: The modular Marx generator topology is selected, with a 12-stage design. Each stage consists of a 1.2 μF, 40 kV pulse capacitor and a detonator-triggered vacuum switch (TTL).

[0112] (2) Key performance parameters are shown in Table 1:

[0113] Table 1

[0114]

[0115] (3) Engineering implementation details: The front stage of the switching device adopts SiC MOSFET pre-pulse shaping, and the main stage adopts field distortion type gas spark gap switch; the charging system adopts constant current resonant charging method with a charging current of 2A and high frequency inverter (20 kHz) to reduce the size.

[0116] In one embodiment, the magnetic field generating module further includes: a thermal management unit;

[0117] Receive temperature data collected by a temperature sensor installed in the coil system;

[0118] When the temperature of the coil system exceeds a certain value, a cooling command is sent to the thermal management unit, causing the thermal management unit to activate coolant circulation. This allows the coolant to flow through the microchannels inside the coil system, exchanging heat with the flowing coolant. The thermal management unit specifically includes: an outlet manifold, a return water pipe, a heat exchanger, a water storage tank, and a high-pressure pump inlet manifold for water exchange. Figure 8 As shown.

[0119] In one embodiment, the magnetic field coupling module comprises an upper magnetic pole arm 1, a lower magnetic pole arm 2, an upper pole head 3, a lower pole head 4, a magnetic core 5, a linear module 7, a control motor 8, a shielding shell 10, and an internal magnetic shielding cover 11.

[0120] The coil system 6 is respectively embedded in the upper magnetic pole arm 1 and the lower magnetic pole arm 2, with the upper magnetic pole arm 1 and the lower magnetic pole arm 2 arranged opposite to each other, and the tail ends are respectively fixed to the two ends of the C-shaped magnetic core 5; the upper pole head 3 and the lower pole head 4 are respectively set on the opposite end faces of the upper magnetic pole arm 1 and the lower magnetic pole arm 2, and an adjustable air gap is formed between them; the battery module 9 is placed in the air gap;

[0121] The linear module 7 is connected to the control motor 8. The linear module 7 is used to move the upper magnetic pole arm 1 up and down along the air gap direction to adapt to batteries of different thicknesses.

[0122] The selection process specifically includes:

[0123] 1) Magnetic circuit design: Finite element optimization: Using ANSYS Maxwell software, parameterized optimization was performed with "magnetic field uniformity in the internal reaction region of the battery" and "magnetic energy utilization rate" as dual objectives.

[0124] Final design parameters: The electrode head is a hyperbolic rotating surface, with an electrode diameter of 80 mm (for a 100 Ah square cell), and a working air gap of 3 mm; under a center field strength of 15 T, the internal structure of the battery... Volume magnetic field strength > 12 T, magnetic circuit efficiency .

[0125] 2) Adaptor structure and electromagnetic compatibility (EMC):

[0126] Mechanical structure: The magnetic pole arm is CNC machined from 7075 aluminum alloy and equipped with a ±150 mm stroke electric linear module to adjust the pole pitch.

[0127] Electromagnetic shielding: The magnetic circuit is wrapped with a 0.5 mm thick layer. The shielding cover and system enclosure are electrically shielded with 1.5 mm aluminum plate, and the radiated emissions below 30 MHz comply with CISPR 25 standards.

[0128] Controller: Hardware Architecture Core Processor: A Xilinx Kintex-7 series FPGA (XC7K325T) is responsible for real-time data acquisition at a 1MHz sampling rate and μs-level trigger control, paired with a TI Sitara AM5728 dual-core ARM Cortex-A15 as the application processor. Synchronization and Triggering: Based on the White Rabbit precision time protocol, time synchronization accuracy of <10 ns is achieved, and the trigger signal is transmitted through optical fiber to isolate interference.

[0129] In one embodiment, the key technological innovations are summarized as follows:

[0130] (1) Principle-level innovation: For the first time in the world, the physical principle of "strong pulse magnetic field freezing the migration of charged particles" is systematically applied to the suppression of battery thermal runaway, creating a new path for non-contact and reversible (potential) intervention.

[0131] (2) System architecture innovation: Through the collaborative design of low-inductance Marx generator topology, field distortion spark gap switch and microchannel cooling coil, a field strength of >15 T and millisecond-level response are achieved; hyperbolic pole head and nanocrystalline magnetic core design improve energy utilization. above.

[0132] (3) Intelligent and adaptive innovation: integrates electrical, thermal and acoustic multimodal signals to achieve early identification of ≤100 ms; based on the parameter adaptive technology of RBFNN model, solves the universality problem of different batteries and states.

[0133] (4) Reliability engineering innovation: Design a redundant protection mechanism for single-point faults; ensure the reliability of measurement and control under GW-level electromagnetic interference through measures such as fiber optic communication and synchronous triggering.

[0134] Example 1: Very early intervention in automotive embedded systems:

[0135] 100kWh high-nickel ternary lithium battery electric car fast charging up to After SOC (State of Charge), a single cell experiences an internal short circuit due to a manufacturing defect, causing the temperature to rise from [value missing] within 30 seconds. The voltage dropped slightly when the temperature rose to 65°C.

[0136] System configuration: Miniaturized C-type magnetic core pulse magnetic field coils are pre-installed between key modules in the battery pack. The weight of a single system is ≤1.5kg and the volume is ≤1.5L. It integrates a local intelligent control unit (ICU) and connects to the vehicle's main BMS.

[0137] Implementation process: The BMS detected abnormal signals (0.2V voltage fluctuation, temperature rise rate > 0.2V). Within 10ms, the risk is assessed and the ICU is instructed; ICU parameters are set (B_req=12 T, =0.8 ms) triggers magnetic field intervention; after intervention, the voltage stabilizes, and the temperature rise rate drops to within 5 seconds. .

[0138] Outcome of the response: Thermal runaway did not occur (temperature < The fault is limited to a single module, and the response time is < .

[0139] Example 2: Module-level interruption of stationary energy storage power station system:

[0140] Scenario: Inside a 100MWh lithium iron phosphate energy storage container, the internal resistance of a module in battery rack #5 increases. The temperature rose from 2 minutes Rise to There is a risk of thermal runaway spreading.

[0141] System configuration: A track-mounted mobile pulse magnetic field intervention robot is deployed above the battery rack channel, equipped with a solenoid coil magnetic field generation system (maximum field strength 20 T), with a positioning error of < 2 mm.

[0142] Implementation process: The monitoring platform issues an alert and locates the abnormal module; the robot moves to the target position and adjusts the coil axis to coincide with the module's central axis; parameters are set (B_req=10T, Intervention is triggered at 2 ms; after intervention, the module temperature stops rising and slowly decreases, and the voltage stabilizes.

[0143] Outcome: Successfully prevented potential thermal runaway and avoided damage to the battery rack and container; total time < 3 minutes.

[0144] Example 3: Emergency Response by a Mobile Emergency Rescue Platform

[0145] Scenario: The battery pack of the electric truck was severely deformed and smoking after the collision, and the scene was inaccessible.

[0146] System configuration: A mobile pulse magnetic field emergency rescue platform based on the Mengshi 4th generation off-road chassis, with a telescopic arm C-type magnetic pole and a maximum working radius of 6 meters and a peak energy storage of 50 kJ.

[0147] Implementation process: The platform was positioned 10 meters upwind, and two hot spots were located using an infrared thermal imager; after the hydraulic outriggers were leveled, the magnetic poles were used to sequentially locate the hot spots, and parameters were set (B_req=15 T). =1 ms) to implement intervention; after intervention, smoke decreased and hotspot temperature dropped.

[0148] Effectiveness: The battery pack was prevented from catching fire and exploding, buying time for subsequent handling; time taken was less than 5 minutes.

[0149] Table 2 shows a comparison between this application and the prior art:

[0150] Table 2

[0151]

[0152] Analysis of the mechanism of key technological advantages:

[0153] (1) "Physical freezing" and "chemical extinguishing": Traditional methods consume the three elements of combustion, while this invention directly acts on charged particles, "pausing" the reaction kinetics. In 150 experiments, 15T / 1ms magnetic field intervention SOC= Ternary lithium batteries, success rate .

[0154] (2) Step-by-step improvement in energy efficiency: Magnetic field energy penetrates the battery casing without loss, directly affecting microscopic particles. Only about 20 kJ is needed to suppress early thermal runaway in a 100Ah cell, while water-based fire suppression has insufficient effective energy utilization. The difference is three orders of magnitude.

[0155] (3) Scientific basis for reversible intervention potential: The obstruction effect disappears immediately after the magnetic field is removed. In 50 early internal short circuit intervention experiments, the open circuit voltage and internal resistance returned to normal after the cell was cooled in 41 of them.

[0156] In one embodiment, a system for suppressing battery thermal runaway based on a strong pulsed magnetic field is provided, the system comprising:

[0157] Control and Sensing Module: Used to acquire the state parameters of the target battery module in real time, calculate the rate of change of the current state parameters of the target battery module, and determine that the battery module has a risk of thermal runaway if the rate of change of the current state parameters meets the preset conditions. The state parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance. Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the module uses a pre-built radial basis function neural network prediction model to predict the target magnetic field strength and target pulse width. The module issues a command to apply a pulsed magnetic field to the magnetic field generation module, and evaluates the suppression effect in real time after intervention. If the threshold is not reached, the module automatically re-predicts and re-triggers.

[0158] The magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system; the energy storage unit is used to provide pulse energy to the pulse power supply system; the pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current; the coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulse current.

[0159] Magnetic field focusing and coupling module: used to guide the strong pulsed magnetic field generated by the coil system into the internal reaction region of the battery module.

[0160] In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the aforementioned method for suppressing battery thermal runaway based on a strong pulsed magnetic field.

[0161] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored relating to all or part of the processes in the methods of the above embodiments.

[0162] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0163] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for suppressing battery thermal runaway based on a strong pulsed magnetic field, characterized in that, The method includes: Step S1: Acquire the status parameters of the target battery module in real time; the status parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance; Step S2: Calculate the rate of change of the current state parameters of the target battery module based on the real-time acquired state parameters of the target battery module. If the rate of change of the current state parameters meets the preset conditions, it is determined that the battery module has a risk of thermal runaway. Step S3: Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the target magnetic field strength and target pulse width are predicted using a pre-built radial basis function neural network prediction model. Step S4: Send a command to the magnetic field generating module to apply a pulsed magnetic field, so that the magnetic field generating module applies a pulsed magnetic field with a target magnetic field strength and a target pulse width to the target battery through the magnetic field coupling module; Step S5: Evaluate the thermal runaway suppression effect of the target battery module based on the real-time acquired state parameters of the target battery module. If the thermal runaway suppression effect does not reach the preset threshold, repeat steps S3-S5 until the thermal runaway suppression effect reaches the preset threshold.

2. The method according to claim 1, characterized in that, Step S2 specifically includes: The current voltage drop rate, temperature rise rate, internal resistance increase rate of the target battery module are calculated based on the real-time acquired state parameters of the target battery module, as well as whether an abnormal acoustic emission signal is detected. If the voltage drop rate is greater than 10% / s of the initial voltage of the target battery module and the temperature rise rate exceeds 1.0°C / s, then it is determined that there is a risk of thermal runaway. If the rate of increase in internal resistance is greater than 0.05 and abnormal acoustic emission signals are obtained, it is determined that there is a risk of thermal runaway.

3. The method according to claim 1, characterized in that, The radial basis function-based neural network prediction model is constructed in the following way: Acquire historical data for different battery types; the historical data includes: SOC, SOH, and temperature when thermal runaway risk occurs, as well as battery state parameters after applying different pulse magnetic field strengths and pulse widths; The historical data is input into a radial basis function-based neural network prediction model for training. The theoretical range is used as a priori condition, so that the target magnetic field strength and target pulse width output by the radial basis function-based neural network prediction model during training and prediction are based on the theoretical range.

4. The method according to claim 3, characterized in that, The theoretical scope was obtained through the following methods: Based on the ion mobility suppression model, the rate of decrease in the mobility of charged particles in the target battery type under different magnetic field intensities is calculated, and the initial theoretical range of the magnetic field intensity is determined based on the preset decrease rate threshold. Based on the cyclotron radius and magnetic freezing model, the cyclotron radius of charged particles is calculated under the magnetic field strength within the initial theoretical range. The magnetic field strength corresponding to the cyclotron radius being smaller than the particle size of the active particles of the electrode material is determined as the final lower limit of the theoretical range of the magnetic field strength. The pulse width range in the theoretical range was obtained through statistical analysis of thermal runaway suppression experimental data for the target battery type.

5. The method according to claim 1, characterized in that, The magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system; The energy storage unit is used to provide pulse energy to the pulse power supply system; The pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current. The coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulse current.

6. The method according to claim 5, characterized in that, The magnetic field generating module also includes: a thermal management unit; Receive temperature data collected by a temperature sensor installed in the coil system; When the temperature of the coil system exceeds a certain value, a cooling command is sent to the thermal management unit, which then initiates coolant circulation, allowing the coolant to flow through the microchannels inside the coil system and exchange heat with the flowing coolant.

7. The method according to claim 5, characterized in that, The magnetic field coupling module specifically includes: Upper magnetic pole arm (1), lower magnetic pole arm (2), upper pole head (3), lower pole head (4), magnetic core (5), linear module (7), control motor (8), shielding shell (10), internal magnetic shielding cover (11); The coil system (6) is respectively embedded in the upper magnetic pole arm (1) and the lower magnetic pole arm (2). The upper magnetic pole arm (1) and the lower magnetic pole arm (2) are arranged opposite to each other, and their tail ends are respectively fixed to the two ends of the C-type magnetic core (5). The upper pole head (3) and the lower pole head (4) are respectively set on the opposite end faces of the upper magnetic pole arm (1) and the lower magnetic pole arm (2), and an adjustable air gap is formed between them. The battery module (9) is placed in the air gap. The linear module (7) is connected to the control motor (8). The linear module (7) is used to move the upper magnetic pole arm (1) up and down along the air gap direction to adapt to batteries of different thicknesses. The entire magnetic circuit assembly is housed within an internal magnetic shield (11), and the shielding shell (10) is coaxially fitted onto the outside of the internal magnetic shield (11) to form a double-layer electromagnetic shielding structure.

8. A system for suppressing battery thermal runaway based on a strong pulsed magnetic field, characterized in that, The system includes: Control and Sensing Module: Used to acquire the state parameters of the target battery module in real time, calculate the rate of change of the current state parameters of the target battery module, and determine that the battery module has a risk of thermal runaway if the rate of change of the current state parameters meets the preset conditions. The state parameters include: current, voltage, temperature, acoustic emission signal, and internal resistance. Based on the current SOC, current SOH, and current temperature of the target battery obtained through the BMS system, and combined with the battery type of the target battery module, the module uses a pre-built radial basis function neural network prediction model to predict the target magnetic field strength and target pulse width. The module issues a command to apply a pulsed magnetic field to the magnetic field generation module, and evaluates the suppression effect in real time after intervention. If the threshold is not reached, the module automatically re-predicts and re-triggers. The magnetic field generating module includes: an energy storage unit, a pulse power supply system, and a coil system; the energy storage unit is used to provide pulse energy to the pulse power supply system; the pulse power supply system is connected to the energy storage unit and is used to convert the stored energy into a high-voltage pulse current; the coil system is connected to the pulse power supply system and is used to generate a strong pulsed magnetic field with a target magnetic field strength and a target pulse width under the pulse current. Magnetic field focusing and coupling module: used to guide the strong pulsed magnetic field generated by the coil system into the internal reaction region of the battery module.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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